Wearable Technology to Characterize and Treat mTBI Subtypes: Biofeedback-Based Precision Rehabilitation
Phase: NA
Conditions: Mild Traumatic Brain Injury, Concussion, Rehabilitation, Balance Impairment
Sponsor: Oregon Health and Science University

 
Version Date: 1/14/2025 
 
 
 
 
 
 
 
 
 
 
 
 
Wearable Technology to Characterize and Treat mTBI Subtypes: Biofeedback-Based Precision 
Rehabilitation (SuBTyPE) 
 
NCT06381674 
Unique Protocol ID: OHSU IRB #25890 
Secondary IDs: HT9425-23-1-0845 
Date: 1/23/2025 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
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Minimal Risk Protocol Template 
 
1. Protocol Title 
Wearable Technology to Characterize and Treat mTBI Subtypes: Biofeedback-Based Precision Rehabilitation 
 
2. Objectives  
Current clinical assessment tools are not sensitive enough to detect and treat some subtle (yet troubling) 
problems after mild traumatic brain injury (mTBI). In this study we will test a new treatment approach using 
wearable sensors for feedback during physical therapy that focuses on sensory and motor dysfunction after 
mTBI. The goal of Aim I is to see if multidimensional real-time biofeedback using novel wearable technology 
improves outcomes after rehabilitation compared to standard care. The goal of Aim II is to explore the 
relationship between responsiveness to rehabilitation and subtype classification. The goal of Aim III is to 
determine if daily life mobility (quality of gait and turning) is impacted differently in people with high V/O deficits 
 
3. Background 
Every year 3-4 million people sustain a traumatic brain injury (TBI) in the United States and, of these, 
up to 90% are considered mild TBI (mTBI) 1, 2. According to data from the Traumatic Brain Injury Center of 
Excellence, 13,778 service members sustained a mTBI in 2020. The estimated annual cost to society from 
TBI, including lost productivity, was $60.4 billion 3, 4. Balance impairments are a common complaint after mTBI 
5, 6. Ongoing balance problems are significant contributors to anxiety, difficulty with return to work, and may 
even underlie the observation that people with a recent history of mTBI are at a threefold greater risk of 
sustaining a second mTBI and increased risk for musculoskeletal injury 7-11. 
 
Even with rehabilitation, recovery of balance in people with mTBI is challenging and rates of 
responsiveness to rehabilitation are suboptimal. In fact, there have been several studies examining the 
effects of rehabilitation after an mTBI. Two relevant systematic reviews concluded that most of these studies 
were small and not standardized but that there was weak but promising evidence for vestibular rehabilitation 
after mTBI 12, 13. The authors state that there is a need for larger, high-quality studies to determine efficacy of 
such rehabilitation for mTBI. Another more recent systematic review that included 12 studies on physical 
therapy interventions reported that symptom subthreshold exercise may improve symptoms but did not reduce 
days to recovery and that standalone therapies such as vestibular and ocular-motor exercises had limited 
evidence for improvements 14. 
 
One reason for suboptimal outcomes in rehabilitation may be due to poor performance of the 
rehabilitation exercises. People with vestibular pathology have impaired perception of head position and 
movement and may limit their head velocity to minimize symptoms 15, 16. We recently published a paper 
showing that people with mTBI do not move their head as fast or as far when asked to perform walking with 
head turns, a common task required in daily life 17. Vestibular and balance rehabilitation relies on progressively 
increasing head movement amplitude and velocity during static and dynamic balance tasks while maintaining a 
stable trunk 18, 19. While gait speed is often normal after mTBI, our work showing that head movements during 
walking with head turns are abnormal, has practical implications for a successful return-to-duty 17. A person may 
compensate for subtle deficits by limiting head movement; this tradeoff should be an important consideration 
with return to duty, sport, and everyday activities that require both balance and stable gaze. Exercise dosing 
factors, such as speed and range of head movements, are important and may impact outcomes, but little is 
known. A clinical practice guideline for vestibular hypofunction reported that there is very little evidence 
available for exercise dosing recommendations and that researchers should ‘examine the impact of frequency, 
intensity, time and type of exercises on rehabilitation outcomes’20. Although this is a major gap in our clinical 

 
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care and the intensity (e.g., velocity of head movement) dose factor is likely a critical aspect of vestibular 
rehabilitation, exercise intensity is not well defined, nor easily measured. Our group is one of the first to 
examine the use of wearable sensors to quantify dosing factors during vestibular rehabilitation exercises 21, 22. 
 
Adhering to motor learning principles is essential for successful rehabilitation 23-25. One important 
principle of motor learning is feedback of performance, yet this important feature is hard to implement 
objectively in balance rehabilitation. For example, orthopedic physical therapy uses objective measures of joint 
angles, peak torques and gait speed during task acquisition. To maximize the effects, biofeedback should be 
immediate and constant at the early stages with progression to slightly delayed and intermittent feedback as 
the skill improves 25. Rehabilitation of balance deficits is more difficult to quantify and to provide feedback while 
performing a training task. Subtle movements, such as postural sway, head and trunk synchronicity, and head 
velocity are often not detected visually and therefore not assessed or fed back to patients. Biofeedback has 
been used for over two decades to improve outcomes of rehabilitation 26, 27 but the current approach cannot 
provide feedback on multidimensional complex movements. For example, biofeedback for balance training 
typically provides real-time visual or auditory feedback to practice stability during quiet standing, using a force 
plate to visualize center of pressure movement 27. To date, most balance feedback simply tries to decrease 
postural sway in static conditions or to improve gait joint motion, without measuring multidimensional 
movements, like walking with head turns 28. 
There are no commercially available biofeedback systems that simultaneously measure 
multisegmental performance such as head movement amplitude/velocity while concurrently providing 
objective measures of gait and balance. Despite evidence that people with mTBI may have both impaired 
perception of head movement and impaired balance 6, 17, 29, we currently have no easy way to quantify 
impairments nor to provide concurrent feedback during therapy. Computerized dynamic visual acuity testing is 
available to measure: 1) changes in visual acuity at head velocities associated with the vestibulo-ocular reflex 
(VOR) and 2) the maximum head velocity the patient can achieve while maintaining accurate vision during a 
gaze stabilization test 30. There are a handful of other clinical systems that can be used to provide feedback on 
head movement but training is performed in static seated or quiet standing positions in clinical settings only 31. 
Our group has developed the first wearable and portable system that combines biofeedback on head 
and trunk movement while monitoring patients’ dynamic stability during functional tasks 
(Figure 1) (W81XWH-17-1-0424). The system provides the physical therapist and/or patient objective 
information on the quality of head and trunk movements during training of rehabilitation tasks that can progress 
from sitting to standing to walking. This system enables physical therapists to evaluate the tradeoff between 
balance and increasingly complex movements, as well as to teach 
patients to perform the exercises correctly during increasingly difficult 
and dynamic conditions. Because of the portability of wearable 
sensors, the system is intended to be used in any environment where 
rehabilitation and movement monitoring is needed, including 
clinical facilities, laboratories, hospitals, outdoors, at-home, or in 
the field. The system allows the physical therapist to select among a 
variety of exercises that target balance and vestibular function and 
has the capability to incorporate motor learning principles such as 
changing the timing and frequency of feedback, as well as changing 
rehabilitation goals. 
 
 
 
Figure 1. Current APDM feedback 
prototype using a laptop real-time 
analysis with auditory feedback 

 
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Another reason for suboptimal rates of responsiveness to rehabilitation 
after mTBI may be the lack of targeted and precision rehabilitation. 
Recent work has identified several mTBI subtypes based on common clinical 
presentation as cognitive, ocular-motor, headache/migraine, vestibular, and 
anxiety/mood with cervical strain and sleep disturbance as associated 
conditions (Figure 2). Sleep and cervical strain are common with mTBI but 
do not appear in isolation, therefore are not considered a stand-alone 
subtype. The concept of mTBI subtypes has been discussed and identified in 
the literature including an expert panel (Dr. Chesnutt; Co-I on this project), 
and supported by a systematic review 32-35. Correctly identifying the 
prominent subtypes may be a critical step in determining the most appropriate 
referral and rehabilitation intervention. However, current subtype 
classification is primarily based on subjective rating scales 36. 
Characterization of published subtypes was based on acute mTBI patients 34 
but people with ongoing symptoms may have a more complex profile, with 
overlapping and equally prominent subtypes. We examined 22 patients from our outpatient OHSU Concussion 
Clinic using the Concussion Symptom Subtype Inventory (CSSI) 37 profile screen. We found that only 12% of 
the patients seen in our clinic over the past month with moderate symptoms had one clear primary subtype. 
Twenty-four percent had 2 subtypes of equal severity and 65% had greater than 3 subtypes. These people 
were, on average, 11.2  20.1 months from injury with an average age of 38 16 years. It is currently unclear 
how to use the available scales to characterize subtypes on more complex patients who may have high 
symptom burden across subtype domains. This project will explore how best to characterize subtypes using 
multiple outcome measures to help direct patient care. The most appropriate mTBI subtypes to benefit from 
physical therapy are sensorimotor subtypes including vestibular and/or ocular-motor but these measures are 
under-represented in subjective rating scales 38. A recent study that examined the 8 most commonly used 
questionnaires found that vestibular and ocular-motor (V/O) subtypes were minimally represented in the 
questions presented on the questionnaires. Specifically, ocular-motor was 11% and vestibular was 19% of the 
questions in the scales 38. Therefore, using a subjective approach to determine primary subtypes may lead to 
missed opportunity for rehabilitation. Alternatively, many people may be inappropriately referred to physical 
therapy (i.e., cognitive subtype) who would benefit more from a referral to neuropsychology or speech and 
language therapy. Anecdotally and based on our pilot data (see below), referrals to physical therapy that may be 
inappropriate can lead to low responder rates. This proposal will attempt to better define the subtypes of 
vestibular and ocular-motor (V/O) to improve identification leading to improved rehabilitation outcomes. 
 
Measures of sensorimotor impairment are often subjective and easily overlooked as a treatable deficit. 
For example, the most frequently administered clinical balance test after mTBI is the Balance Error Scoring 
System (BESS) in which people are asked to stand in varying conditions (i.e., eyes closed on a firm or foam 
surface) to challenge postural stability 39. Errors, such as loss of balance, are counted subjectively by the 
clinician. However, studies have reported that the BESS has a high degree of subjectivity and provides only 
limited, low-resolution information about the balance control system and does not provide a sensitive scale on 
which to judge progress or deficits 40, 41. Sub-optimal psychometric properties (sensitivity 34%–64% to detect 
mTBI) have also been reported for the BESS and are likely due to the subjectivity of the measurement 40, 41. 
Clinical balance tests with limited clinimetric properties may lead to lower detection rates and make it difficult to 
identify those who might benefit from physical therapy. More objective measures of balance may help identify 
people with impaired balance due to sensorimotor deficits (i.e., vestibular and/or ocular-motor) in which a 
targeted physical therapy intervention would help recovery.  
 
 
Figure 2. Five subtypes 
of mTBI (solid lines). 
Dashed lines are 
associated conditions. 

 
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Recent evidence suggests that objective measures of function are a critical part of assessment after 
mTBI. In the subtype classification, gait and balance deficits fall under the vestibular subtype. Such deficits are 
often subtle, yet very troubling, and can often only be detected objectively using instrumented measures such 
as force plates and wearable sensors to measure postural sway, central sensorimotor integration, and gait 
parameters 39-42. Our laboratory has been on the forefront of developing objective measures to improve 
detection of deficits to facilitate targeted and precision rehabilitation. Our work has provided evidence that 
instrumenting common balance tests with body-worn inertial sensors can better differentiate people after mTBI 
compared to subjective measures of balance 42-44. While objective measures have been deemed essential for 
assessing deficits after mTBI, routine clinical care typically does not include such objective measures. 
Wearable sensors have the potential to change health care outcomes due to their objectivity, increasing utility, 
accessibility and affordability.  
 
Body-worn technology, which can now 
automatically quantify hundreds of gait 
and balance measures in supervised and 
un-supervised settings, may facilitate 
mTBI subtype classification. Most body-
worn sensors measure quantity of activity, 
such as number of steps or activity levels. 
However, in partnership with APDM 
Wearable Technologies, our group has 
developed a novel, body-worn inertial 
system to characterize quality, such as 
abnormal turning patterns 45-47. Our novel 
instrumented socks (Figure 3) can be worn 
during daily life for continuous monitoring. 
We recently demonstrated that quality, but 
not quantity, of daily life activity at home is impaired in people with 
mTBI compared to healthy control participants 48, and 
particularly turning mobility (Figure 4). Therefore, we are 
uniquely positioned to assess daily functional mobility 
impairments in people with mTBI with the goal of improving subtype classification. Functioning optimally at 
home and in everyday life is the goal of recovery after mTBI. Our goal is to optimize assessment across 
subtype classification and generate evidence for novel outcome measures that predict real-world function and 
facilitate recovery. 
There has been little to no work in determining the strength of the relationship between clinical 
subtypes and objective measures, an area of known importance in mTBI. In this proposal, we will use 
objective measures to address potential obstacles for successful rehabilitation after mTBI. We will use 
multidimensional, real-time biofeedback to improve quality of performance during rehabilitation and use state-
of-the-art wearable technology to identify V/O subtypes that may be more responsive to rehabilitation. 
 
Rigor of previously related funded work. This proposal is a natural continuation of our previous funding 
that used objective measures to improve assessment and precision rehabilitation after mTBI. In 2012 we 
were awarded a pilot grant (NIH; Center for Translation of Rehabilitation Engineering Advances and 
Technology; King PI) to develop a protocol for instrumented balance testing for people with chronic post-
concussion syndrome 42. From there, we moved the instrumented balance testing to on-site assessments at 
6 local universities to explore the usefulness of wearable sensors in acutely-injured athletes and to measure 
the trajectory of balance recovery after mTBI (NIH; Oregon Clinical Translational Research Center (OCTRI) 
KL2 Award and National Institute of Health KL2TR000152; R21 NIH R21HD080398; King PI). We received 
several Department of Defense (DoD) grants to 1) investigate central sensorimotor integration and vestibular 
deficits in people with mTBI (King PI-W81XWH-15-1-0620), 2) investigate optimal timing of rehabilitation and 
to develop a system using wearable sensors to facilitate vestibular rehabilitation after mTBI (King PI- 
W81XWH-17-1-0424), and 3) to develop and test ecologically valid assessments of dual-task testing (with 2 
 
Figure 3. 
Instrumented socks 
with inertial sensors 
on top of foot (A) and 
battery on the side (B). 
 
Figure 4. Control and mTBI subjects had 
similar daily step counts over 7 days (A) 
but mTBI subjects had slower peak 
turning velocities (B), more variable 
peak turning velocities (C), and larger 
average turning angles (D). 
 

 
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other academic and 3 military sites) (King PI-W81XWH-18-2-0049).  
 
We have had several SBIR/STTR grants in collaboration with APDM Wearable Technologies producing 
wearable sensors for documenting physical movements including: a Phase 1 DOD contract 
(W81XWH19C0125) to develop a ruggedized wearable sensor system to assess movement dysfunction in a 
field environment and to guide clinical and return-to-duty decision-making, a Phase II SBIR (R44AG055388; 
NIA) to assess continuous monitoring of mobility in daily lives of people with neurological disease, a Phase I-
II SBIR (AG044863; NIA) to continuously measure functional mobility in older people with fall risk, a Phase I-
II SBIR (AG056012; NIA) to develop and commercialize a gait biofeedback system for physical therapists to 
provide biofeedback for gait training in people with gait impairments, and a Phase II SBIR 
(HHSN261201600067C; NCI) to develop a portable clinical system to quickly and automatically obtain 
objective measures of balance and gait impairments. APDM and OHSU completed a Phase I-II STTR (R42 
HD071760; NCMRR) that enabled APDM to develop and commercialize its Mobility Lab system with 
protocols and reports for the Short-Instrumented Test of Mobility to provide a validated, objective fall risk 
evaluation. Simultaneously, our team has been involved in exploring the clinical profiles of people after mTBI 
and Dr. Chesnutt (Co-I) has been selected as a member of the concussion subtype national expert panel 
that delineated concussion subtypes supported by a systematic literature review 34, 35. The proposed project 
uses the technical advances and scientific understandings made in these projects for this Level 2 Clinical 
Trial Award. 
PRELIMINARY STUDIES 
Aim I. Multidimensional, real-time biofeedback for rehabilitation. The goal of Aim I is to determine if 
multidimensional real-time biofeedback using novel wearable technology improves outcomes after 
rehabilitation compared to standard care. With previous funding from the Department of Defense (W81XWH-
17-1-0424), we have developed a novel, wearable sensor-based system that can deliver multidimensional 
real-time biofeedback during complex activities and exercises that require precise head/trunk movement 
while maintaining balance during standing and walking with a user-friendly interface (Figure 5). It is common 
to decrease head motion to minimize exacerbation of symptoms but this compensatory strategy will not be 
optimal when a person returns to duty or to sport. The feedback delivered by the system is instantaneous, 
adaptable by the physical therapist, and provides multiple objective measures concurrently during 
ecologically-relevant, functional tasks. 
 
Figure 5. Screenshot of a participant performing walking with head turns; demonstrating that A) cervical range of motion (ROM) and B) 
velocity are reduced compared to the normal, target zone (horizontal grey line). Panel C shows that despite slowed head movements, the 
person’s gait is stable and within the mediolateral target zones determined by healthy control data. 

 
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This novel system can detect the tradeoff between speed/amplitude of head movement and stability, 
a critical consideration in the readiness for return to duty. The screenshot in Figure 6 shows that a 
person may have very slow and small head movements yet be quite stable in quiet stance (red in 
stabilogram; panel C). However, when the patient is provided feedback (see dashed line at 12 seconds) to 
increase head speed or amplitude, they show quantifiable signs of imbalance (black stabilogram; panel C). 
The gray horizontal shaded areas in A and B show healthy normative ranges and the end-goal for people 
with mTBI. Most available biofeedback systems measure either head motion or postural sway, but not both 
simultaneously; this system concurrently measures multiple domains which means individuals can train using 
functional tasks more reflective of the concurrent demands of daily life. 
 
 
This feedback system provides 
immediate feedback on correct task 
performance. Figure 7 shows the capability 
of this system to detect poor performance on a 
rehabilitation task. In this example, the person 
is instructed to maintain a stable gaze, while 
turning the head (gaze stabilization exercise). 
In standing gaze stabilization, there should be 
a dissociation between the head and the trunk. 
But, in order to minimize symptoms associated 
with increased stimulation to the vestibular system (i.e., head movement), a person often moves the trunk 
together with the head as a compensatory strategy. The screenshot in Figure 7 shows that this person 
initially had excessive trunk motion but with feedback (dashed lines at 15 s) could alter this movement pattern 
to isolate head movement. 
 
 
Figure 7. Screenshot demonstrating that initially this person had excessive 
trunk motion, but after feedback was able to move the head while keeping 
trunk still during a gaze stabilization exercise. 
 
Figure 6. Gaze stabilization task requiring head movement at a specified speed and amplitude. This screenshot shows performance tradeoff of 
a person standing while performing head turns. (A) Cervical range of motion (ROM) was normal but speed (B) was at suboptimal levels prior 
to biofeedback, although postural sway (C) was stable (red line). Once feedback to improve head speed and maintain amplitude was initiated 
(after dashed line), postural sway increased (C-black line) to outside of the target goal zone of healthy normative values (grey ellipse panel C). 

 
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This multidimensional real-time biofeedback is feasible in the clinic. We have preliminary data showing 
that this system is feasible and that physical therapists think it would be useful in the clinic. Using the System 
Usability Scale 49, which asks about perceived usability and usefulness, we found that 3 different physical 
therapists who treat people 
with mTBI had favorable 
opinions of the system. After 
using the system with 
several different patients 
with mTBI during their 
clinical visit, the average 
System Usability Scale 
score was 80 
 3.5, a 
calculated score that falls 
between ‘good’ and ‘best 
imaginable’ 49, 50. See Table 
1 for specific item questions. 
 
 
Aim II. Responsiveness to rehabilitation; objective measures to identify vestibular and/or ocular-
motor subtypes. The goal of Aim II is to explore the relationship between responsiveness to rehabilitation 
and subtype classification. We have pilot data showing that mTBI subtyping is not routinely used in clinical 
practice for referrals and this could result in inappropriate referrals to physical therapy, as well as 
unproductive use of time and money on a treatment that may not help. Further, the time spent in the wrong 
type of rehabilitation is wasting a critical window of recovery where the correct, targeted treatment could 
help. We will explore how best to classify V/O subtypes using objective measures with the goal of improving 
responsiveness to rehabilitation. 
Current practice does not consistently use subtype classification for referrals - better classification 
with objective measures may change this pattern. We retrospectively examined 22 patients from the 
OHSU Concussion Clinic to determine if mTBI subtype related to referral patterns for physical rehabilitation. 
Ideally, we would expect to see the patients with high V/O deficits consistently being referred to physical 
therapy, rather than the other subtypes (i.e., anxiety/mood and cognitive). We found that 15 people reported 
symptoms of vestibular or ocular-motor complaints on the CSSI V/O categories; of these, only 8 were 
referred to physical therapy. Of the 7 who had no V/O symptoms, 3 were referred for physical therapy. Of these 
3, none were classified with cervical signs/symptoms that could explain the referral. This potentially 
inappropriate pattern of referral could result in poor outcomes and low responder rates after rehabilitation. 
Responsiveness to rehabilitation increases when only people 
with objective measures of V/O deficits are included. In people 
with subacute mTBI who went through a 6-week, multimodal physical 
therapy program, we calculated responsiveness to intervention using 
the top 2 levels of the Patient Global Impression of Change (PGIC) 
(defined as a ‘definite’ improvement and ‘made a world of difference’ 
on a 7-point scale) 51, 52. We found that when considering the group 
as a whole (n=72), regardless of subtype, 74% were considered 
‘responders’ to rehabilitation; leaving a sizable number of people 
(26%) who did not improve. This poor responder rate is not 
uncommon for physical therapy interventions 14. However, when we 
considered only those with objective V / O  laboratory measures 
(n=14), the responder rate went up to 93% (Figure 8). Of note, this 
classification was based solely on laboratory (not self-report) measures of V/O function.  
Questions rated from 1 (strongly disagree) to 5 strongly (agree) 
Mean  SD 
I think that I would like to use this system frequently 
4.7  0.6 
I would imagine that most people would learn to use this system very quickly 
4.3  1.2 
I found the various functions in this system were well integrated 
4.3  0.6 
I thought this system was easy to use 
4.0  0.0 
I felt very confident using this system 
3.3  0.6 
I think that I would need assistance to be able to use this system 
2.3  1.5 
I needed to learn a lot of things before I could get going with this system. 
2.3  0.6 
I found this system unnecessarily complex 
1.7  0.6 
I thought there was too much inconsistency in this system. 
1.7  0.6 
I found this system very cumbersome/awkward to use. 
1.0  0.0 
Table 1 Results from the System Usability Scale for trial of our novel multidimensional real-time 
biofeedback system in our outpatient concussion clinic. 
 
 
Figure 8. Responder rate after 6-weeks of 
rehabilitation after mTBI (King, pilot data). 
Left graph includes all subtypes and right 
graph only the subtypes with abnormal 
vestibular and/or oculomotor function. 

 
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Patient-reported measures of V/O symptoms may not 
relate to Clinical or Instrumented Assessment so 
both subjective and objective measures may be 
critical in classifying mTBI subtypes. We analyzed 
preliminary data on 12 people who completed the CSSI 37 
as well as other V/O measures that fall under Patient 
reported, Clinical and Instrumented. Figure 9 shows the 
highest correlations were between CSSI V/O subscores 
and other Patient-reported measures. There were very 
few to no significant correlations between CSSI V/O 
subscores and Clinical or Instrumented V/O 
Assessments. The lack of relationship between Patient-
reported V/O outcomes and Clinical and Instrumented 
V/O measures highlight the importance of including both 
subjective and objective measures in our assessment 
after mTBI. 
Aim III. Daily life mobility in people with V/O subtype. 
The goal of Aim III is to determine if daily life mobility (quality of gait and turning) is impacted differently in 
people with high V/O deficits. We have compelling preliminary data suggesting that people with high V/O deficits 
have more impaired quality of daily life mobility compared to people with low V/O deficits. We have already 
published that people with mTBI (without considering subtype) have different quality of movement compared to 
healthy control participants during daily life 48, 53. We will explore if daily life mobility is different in people with 
high V/O deficits compared to low V/O deficits. 
People with impaired vestibular and ocular-motor function had impaired quality of turning during daily 
life compared to people without deficits in these areas. Figure 10A shows that the measures of quantity, 
such as steps per day and activity rate, 
are similar in people with and without 
V/O deficits, whereas Figure 10B shows 
clear differences in daily turning in 
people with versus without V/O deficits. 
Vestibular and ocular-motor function 
was measured using objective 
laboratory testing. People with 
documented V/O deficits demonstrate 
smaller turn angles, less variability in 
turns and lower peak velocity of turns in 
7 days of daily life. 
 
 
 
Objectives & Specific Aims: 
Our long-term goal is to improve the assessment and rehabilitative treatment of patients with mTBI 
with a focus on integrating objective measures for identifying and treating V/O subtypes. Our central 
premise is that objective measures are a critical, yet missing, component of a comprehensive assessment and 
treatment plan after mTBI. We believe that rehabilitation, commonly prescribed after mTBI, will benefit from 
integrating immediate and objective information on complex sensorimotor task performance using a novel, 
wearable, sensor-based system recently developed by this team. Further, we believe that integrating objective 
measures of function, including daily life mobility, will provide an important aspect of subtype identification after 
mTBI and will ultimately facilitate precision rehabilitation. While it is well accepted that objective measures are 
essential in identifying deficits after mTBI, subtype identification is currently based solely on symptom reporting 
36, 37. Within this clinical trial, we will explore whether using novel, wearable technology can improve 
rehabilitation by integrating multidimensional, real-time biofeedback during rehabilitation and by using objective 
 
Figure 9. Radar plot showing poor correlations between 
CSSI V/O subscores and Clinical and Instrumented 
Assessments in the vestibular (Orange) and ocular-
motor (Pink). The dashed line represents significance at 
0.05. 
 
Figure 10. Continuous home monitoring over 7 days in 8 people with mTBI showing A) 
people with mTBI who had abnormal vestibular and/or ocular-motor function had 
similar activity rates (quantity) including total daily steps and daily activity rate as those 
without abnormalities in those domains while B) people with vestibular and/or ocular-
motor abnormalities had different quality of movement including daily turn angles, turn 
angle variability and peak turn velocity compared to those without abnormalities in 
those domains. 

 
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measures to better identify people with sensorimotor deficits (as associated with V/O subtypes). These 
sensorimotor subtypes are more likely to have higher response rates to physical rehabilitation, compared to 
those with non-sensorimotor deficits, such as anxiety/mood and cognitive subtypes. Further, we will explore 
whether quality of daily mobility (i.e., continuous monitoring of gait and turning), differs in people with high V/O 
deficits. We will focus on whether objective measures of V/O function provide insight into responsiveness to 
rehabilitation and explore the relationship between subjective and objective measures of V/O function to 
improve subtype classification. 
Aim I. Multidimensional, real-time biofeedback for rehabilitation: To determine if multidimensional real-
time biofeedback using novel wearable technology that measures head/trunk and balance/gait improves 
outcomes after rehabilitation compared to standard care. We hypothesize that augmenting rehabilitation with 
wearable sensors to simultaneously measure and provide feedback on head, trunk and balance/gait will improve 
outcomes. For Aim I, 100 people with mTBI from 2 sites (Oregon Health & Science University (OHSU) and 
University of Utah (UU)) will be randomized into either standard care or standard care augmented feedback 
using wearable sensors. People will be tested before and after a 6-week (2x/week) rehabilitation program. Our 
primary outcome will be the Patient Global Impression of Change (PGIC) Scale 52. Secondary outcomes will be 
structured according to Subjective Patient-reported (including qualitative measures), Clinical Assessment, and 
Instrumented Assessment measures (Table 4). We will measure covariates to help interpret rehabilitation 
efficacy. We will: 1) determine if multidimensional real-time biofeedback improves efficacy of rehabilitation after 
mTBI and 2) summarize perceptions from the treating physical therapists to help inform next steps for clinical 
implementation of head/trunk/balance biofeedback. 
Aim II. Responsiveness to rehabilitation; objective measures to identify V/O subtype: Aim II is a separate 
analysis based on the data collected in Aim I. Here, we will explore: a) the responsiveness to rehabilitation by 
level of V/O deficit and b) the strength of the relationship between Patient-reported and Clinical and Instrumented 
Assessments of V/O measures. To focus on people with prominent V/O deficits, we will group people 
according to severity of V/O symptoms; moderate to severe (V/O HI) and minimal (V/O LO). Groups (V/O HI 
and LO) will be based on a several measures including the Concussion Clinical Profiles Screening (CP 
Screening), VOMS total score, and the Dizziness Handicap Index (DHI). The CP Screen is a subtyping tool 
has been validated and includes both vestibular and ocular-motor domains 36 and the other measures are 
common clinical scales that measure symptoms and performance around vestibular and ocular domains. In 
this way of categorizing our groups, we will have more severely impacted people from V/O deficits to compare 
with less V/O deficits that would include people from cognitive, headache/migraine, and anxiety/mood cognitive 
subtypes. We hypothesize that a) people with V/O HI will demonstrate a higher rate of responsiveness 
compared to those people with V/O LO and b) there will be only a small to moderate relationship between 
Patient-reported and Clinical and Instrumented Assessments that relate to V/O measures. For Aim II, we will 
use the data collected at baseline from Aim I, prior to rehabilitation, and a “responder” to rehabilitation will be 
defined using the highest 2 categories of the PGIC 51 (Figure 15). To explore the relationship between Patient-
reported and Clinical and Instrumented Assessments, we will examine the strength of correlations across all 
V/O measures. 
Aim III. Daily life mobility in people with V/O subtype: To: a) determine if daily life mobility (quality of gait 
and turning) is impacted differently in people with high V/O deficits and b) calculate healthy normative data for 
daily life mobility measures in active duty military service members. We hypothesize that gait and turning quality, 
measured during 7 days of daily life, will be worse in people with high V/O deficits. We hypothesize that people 
with V/O HI will have worse quality of mobility during daily life (turn angles, variability and velocity) than those 
with V/O LO. For Aim III, 50 people from Aim I, divided equally with V/O HI and V/O LO, will wear instrumented 
socks (APDM Wearable Technologies) (Figure 3) over a 7-day period. Since the instrumented socks are 
currently a prototype provided by APDM Wearable Technologies, our supply will allow only for this subset of 50 
participants. Daily life mobility (quantity and quality) will also be collected on 40 healthy active-duty service 
members for approximately 7 days at Fort Sam Houston (FSH) to facilitate next steps in using continuous 
monitoring as an outcome measure after mTBI in the military.  

 
Version Date: 1/14/2025 
 
 
 
 
 
 
 
 
 
 
 
4. Study Design/Statistical Plan/Data Analysis 
a. Study Design. This is a single-blinded, randomized controlled trial to determine if multidimensional real-
time biofeedback improves outcomes after rehabilitation. Participants with mTBI will be randomized into 
6 weeks of multimodal rehabilitation consisting of either 1) standard care or 2) standard care plus 
biofeedback (Figure 11). 
b. Participants. Participants will include 100 civilians with persistent symptoms from mTBI and 40 active 
duty, service members as healthy controls. Two civilian/academic sites (OHSU and UU) will test 
civilians while one military site (FSH) will test military service members for daily life home monitoring 
(Aim III FSH).  
c. Recruitment. Our primary sources for recruitment of civilians with mTBI will be the OHSU Concussion 
Clinic (see Letter of Support; Dr. Chesnutt), and the University of Utah Outpatient Rehabilitation 
Services Orthopedic Center and the Balance and Mobility Clinic (See Letters of Support; Drs. Ballard, 
Ward, and Cohee). Active-duty military control participants will be recruited at Fort Sam Houston from 
personnel assigned or attached to the U.S. Army Medical Center of Excellence (MEDCoE) and the 
Military Education Training Campus (See Letter of Support; Dr. Douglas). Recruitment will occur by 
word of mouth, flyers and posters distributed around these facilities and briefings to assigned 
personnel.  
d. Inclusion criteria. For all Aims, participants may be either civilians, active duty military, or Veterans, 
and must:1) have a diagnosis of mTBI based upon VA/DoD criteria 54, 55, 2) be between 18-60 years 
old, 3) be able to stand unassisted for 10 minutes at a time, 4) be outside of the acute stage (> 2 weeks 
post-concussion) but within 6 months of their most recent mTBI and still reporting symptoms, 5) have 
at least some measurable deficit in V/O categories based on CP Screen (See justification below), 6) 
have sufficient vision (corrected or uncorrected) for unassisted reading and performance of everyday 
personal tasks and independent community ambulation, and 7) have adequate hearing (without 
amplification) adequate for engaging in close-range personal or telephone conversation. 
 
Table 2 Overview of Study Aims and Milestones 
Aim Focus 
Protocol 
Participants 
Milestones 
I 
Multidimensional 
real-time 
biofeedback 
using wearable 
sensors during 
rehabilitation 
Aim 1: Randomized to 
biofeedback or standard 
care 
100 people with mTBI: 
OHSU (n=50) 
UU (n=50) 
 
a. Determine if multidimensional real-
time biofeedback improves efficacy 
of rehabilitation 
Summarize qualitative assessments from 
he treating physical therapists to help 
nform next steps for clinical 
mplementation  
II 
Responsiveness 
to rehabilitation 
and V/O subtype 
classification 
Aim II: Calculate 
percentage of responders to 
rehabilitation across V/O 
subtypes; explore 
correlations between types 
of measures used for V/O 
subtype classification 
All 100 mTBI subjects 
from Aim I 
c. Calculate responsiveness to 
rehabilitation across severity of 
V/O deficitsExplore the strength of 
correlations between subjective and 
objective measures of V/O function 
 
 
 
III 
Continuous 
monitoring of 
daily life function 
with wearable 
sensors 
Aim III: A subset from Aim 
I will wear instrumented 
socks for approximately 7 
days  
Healthy military normative 
data
50 people with mTBI: 
OHSU (n=25)  
UU (n=25) 
40 healthy control active 
duty military FSH (n=40) 
d. Characterize daily life mobility 
based on V/O subtypes Calculate 
healthy normative daily life data for 
active-duty military service 
members 

 
Version Date: 1/14/2025 
 
e. Aim III healthy controls: Participants must be active duty military service members with no recent (< 3 
years) history of mTBI and no residual symptoms from any remote mTBIs.  
f. 
Exclusion criteria for all Aims: Participants must not: 1) have had or currently have any other injury, 
medical, or neurological illness that could potentially explain balance or vision deficits (e.g., CNS 
disease, stroke, epilepsy, greater than mild TBI, Meniere’s, bilateral vestibular loss, recent lower 
extremity or spine orthopedic injury requiring a profile)  2) meet criteria for moderate to severe 
substance-use disorder within the past month, as defined by DSM-V, 3) display behavior that would 
significantly interfere with validity of data collection or safety during study, 4) be in significant pain 
during the evaluation (> 7/10 by patient subjective report), 5) be a pregnant female (balance 
considerations), 6) been hospitalized for any brain injuries (separate from emergency department), 7) 
have significant joint pain or recent musculoskeletal injury that limits walking or mobility, 8) have had 
any major surgeries in the past year or amputation, 9) use an assistive device  or 10) unable to stand 
barefoot, 11) currently receiving rehabilitation services for their mTBI or injuries related to their 
concussion (if rehabilitation has been completed more than 1 month ago participants may still be 
included). 
Justification for CP Screen V/O cut-offs: The concept of individuals with mTBI having one primary 
subtype was developed on people seen in the acute stage of mTBI. People who do not recover quickly 
and have a longer time frame since diagnosis and often develop a more heterogeneous profile. These 
are typically the people we see in our rehabilitation clinic and therefore, it was not feasible to use a 
primary subtype as a grouping variable. This project proposes an alternative method of categorizing 
individuals with vestibular and/or ocular clinical subtypes based on their CP Screen vestibular and 
ocular score, VOMS total score, or Dizziness Handicap Index (DHI). People will be categorized as no 
V/O deficits (excluded from study), low V/O deficits (V/O LO) and high V/O (V/O HI) deficits. To be 
included in the study, people will be required to have some level of V/O deficits to justify rehabilitation. 
Our expectation that individuals with high V/O scores would be expected to have stronger response to 
physical rehabilitation. The chosen cut-offs were based on a pilot study we conducted of 12 healthy 
individuals with no recent (< 3 years) history of mTBI and no residual symptoms from any remote 
mTBIs (the same inclusion criteria for Aim III healthy controls). Additionally, the chosen cut-offs of the 
VOMS total score, and DHI were added after 9 people were enrolled in the study. The qualitative 
reports of the patients will be considered with the CP Screen, and cut-offs will be adjusted to ensure 
that the intent of our inclusion criteria is met. 
Groups – Based on Vestibular or Ocular scores: exclude 0.0 to 0.6 (total 3 or less out of max of 5) 
 
VO High 
Cut off 
VO Low 
Cut off 
Rationale 
CP 
Screening 
1.6 or 
greater of 
vestibular or 
ocular sub 
score 
CP 
Screening 
1.5-.61 or 
vestibular or 
ocular subs 
core 
In a recent study (Thirunagari et al., 2022) a sub score of 1.5 points was 
successfully used with other ocular measures to classify a high grade or low-
grade ocular subtype of mTBI. The 1.5 cut-off score was significantly correlated 
with other eye movement function tests. Therefore, in this study we will include 
the cut-off of 1.5 for ocular and vestibular sub scores to designate individuals 
with high and low vestibular-ocular symptoms. 
VOMS total 
score greater 
or equal to 
50 
VOMS total 
score less 
than or equal 
to 49 
Upon review of our current data (W81XWH-18-2-0049 &  
W81XWH-17-1-0424) and data from previous mTBI studies versus healthy 
controls, the cut-off of 50 points on the VOMS has been consistent in our 
research and in other publications. In a study conducted by Kontos et al. (2021) 
average VOMS total score for people with mTBI was found to be 54.6 points. In 
consideration with our current VOMS scores in the vestibular-ocular subtype, a 
VOMS total score of 50 or greater will designate people as having high 
symptoms.  

 
Version Date: 1/14/2025 
 
DHI total 
score greater 
or equal to 
54 points 
DHI total 
score less 
than or equal 
to 53 points 
To classify those with vestibular symptoms, a DHI score of 54 or above will be 
used to determine if people have VO high. This is consistent with our current DHI 
scores and the original cut-off scores in the DHI (Jacobson et al., 1990). A score 
of 53 or lower will be considered as having low VO symptoms.  
 
Aim I: Multidimensional, real-time biofeedback for rehabilitation. To determine if multidimensional 
biofeedback using novel, wearable technology that combines head and trunk movement with dynamic 
balance improves outcomes after rehabilitation compared to standard care. 
g. Rationale. Rehabilitation therapies have produced disappointing results in many patients with 
prolonged symptoms after mTBI 56. Our underlying premise is that objective measures are a critical, 
yet missing, component of a comprehensive assessment and treatment plan after mTBI. We believe 
that rehabilitation, commonly prescribed after mTBI, will benefit from integrating immediate and 
objective information on complex task performance using a novel wearable sensor-based protocol 
recently developed by our team. Current limitations in mTBI rehabilitation include administering 
specific rehabilitation exercises without knowing appropriate dosing metrics (i.e. velocity and 
amplitude of head movement) and lack of objective measures of performance. This approach does 
not follow motor learning principles and may not maximize neuroplasticity. Aim I will determine if 
using objective measures of head/trunk/balance exercise performance with immediate feedback on 
complex movements will improve rehabilitation after mTBI. 
h. Blinding and Randomization. After baseline testing, each participant will learn their group assignment 
by opening a sealed, sequentially numbered 
envelope that contains the randomly determined 
group assignment. Because sensorimotor deficit 
(V/O) is central to several of our hypotheses, we will 
use a stratified block randomization scheme. This 
approach will be stratified using V/O HI and V/O LO 
so that both rehabilitation interventions will get 
approximately equal number of participants with the 
same severity of V/O deficits. Block randomization 
will help ensure equal numbers in the two arms, and 
we will vary block sizes (2, 4, 6 or 8) to help avoid 
selection bias. The participants will not be told 
which intervention is favored, the groups will be 
trained at separate times, and the researchers 
administering the pre and posttests and analyzing 
the data will be blinded to group assignment.  
 
i. 
Power and sample size considerations. To power this Aim, we used pilot data on participants with 
mTBI who received physical rehabilitation for balance deficits. This data, obtained during the 
development phase of the biofeedback system (W81XWH-17-1-0424), was based on using wearable 
sensors to measure multidimensional movement but the feedback was not real-time. Rather, it was 
delivered at the next physical therapy session. This step was critical to development of the current 
real-time system. In a group of 43 participants with mTBI, half of the participants received standard 
care physical therapy and the other half used wearable sensors during exercise at home and were 
provided feedback at the subsequent session. At the conclusion of rehabilitation, participants rated 
their perception of change using the PGIC after intervention. We found that the participants who 
provided sensor data to the physical therapist on objective measures of performance had a mean 
PGIC score 0.5 points (SD=1.3) higher than the standard care group. In the proposed study, we 
anticipate we will observe a larger mean difference (0.75) because the sensor group will receive 
immediate feedback. Also, we anticipate a smaller standard deviation because of more consistent 
 
Figure 11 Study design 

 
Version Date: 1/14/2025 
 
therapeutic results (SD=1). Using a Mann-Whitney U test, we estimate that we will have 90% power 
to detect a mean difference of 0.75 (SD=1) using a two-sided test, alpha at 0.05, and with 40 
participants per group. This sample size takes into account an anticipated dropout rate of 25%. 
Calculations were computed using PASS 2019 57. 
j. 
Study Intervention. We designed a vestibular rehabilitation program based on the current 
recommendation from the concussion clinical practice guideline (CPG) that includes a standardized 
approach to target the common dysfunctional areas after mTBI; cervical, vestibular/ocular-motor and 
motor function 58-61. We will individualize the protocol based on the impairments each participant 
demonstrates during the physical therapy assessment. Each domain will have several areas of focus 
that will be targeted and advanced based on participant tolerance. The physical therapist can 
determine where to focus each treatment based on participant performance and symptoms. If there 
are no impairments or functional limitations present, the physical therapist can minimize time spent in 
that domain. We will document the components of each treatment session for all participants so that 
we can summarize the components and progressions of each of the intervention groups. Both groups 
will use the same rehabilitation interventions (Table 3) with the exception of real-time biofeedback 
used during rehabilitation for, vestibular, ocular-motor, and motor function impairments. Each 
participant will come to physical therapy two times per week for one-hour sessions for six weeks. The 
rehabilitation will consist of exercise ‘domains’ (Table 3) with several areas of progression built in per  
task. Each exercise will be challenged with increasing speed/amplitude, surface changes (i.e., foam or 
rocker board), visual changes (i.e. eyes closed, moving background) and/or cognitive (dual task training) 
additions. All participants will be provided home exercises to be performed on days when they are not 
receiving physical therapy. In addition, participants that report high level of cervical pain or if cervical pain 
limits their ability to perform the vestibular rehabilitation program, the study physical therapists will prescribe 
appropriate cervical exercises to address either range of motion or strength impairments. Additionally, if 
participants test positive for either posterior or horizontal benign paroxysmal positional vertigo (BPPV), the 
Table 3: Summary of V/O domains, areas of focus, use of multi-modal feedback, progressions and exercise goals 
 

 
Version Date: 1/14/2025 
 
physical therapist will perform either Epley maneuver or Barbeque Roll until the canal is clear. 
 
k. Mobility Lab for multidimensional real-time biofeedback: The system we will use for the intervention 
was developed with previous Department of Defense funding (W81XWH-17-1-0424) by several of 
the team members in this current proposal. The system uses synchronized inertial sensors (Opals by 
APDM). The Opals have 3D accelerometers, gyroscopes, and magnetometers. The Opal 
sensors will be worn on the head, lumbar, sternum, and feet using elastic Velcro bands during the 
rehabilitation sessions for common cervical, vestibular/ocular-motor and motor function exercises. 
The inertial data on head ROM/velocity, trunk ROM/velocity and stability will be collected, 
synchronized, and wirelessly transferred to a nearby laptop computer for analysis and feedback 
visualization. The physical therapist can use this instrumented data to provide either immediate or 
delayed feedback to improve both the quality of movement and stability based on motor learning 
principles. The physical therapist will be able to select among a variety of exercises, advance level of 
difficulty, progress target zones and change the timing and type of feedback (visual vs auditory) based 
on patient performance and symptoms (Figure 12). 
l. 
Outcomes. The primary outcome measure for Aim I is the PGIC. Secondary outcome measures will 
satisfy the Common Data Elements (CDE) as provided by the National Institute of Neurological 
Disorders and Stroke (NINDS) CDE TBI Project 62 and will be categorized according to patient Patient-
reported, Clinical Assessment, and Instrumented Assessment. In accordance with CDE 
recommendations, several measures fall under the core, highly recommended or recommended 
measures 63-65. The forms selected for use in this study are also common data elements in Federal 
Interagency Traumatic Brain Injury Research (FITBIR) and will allow for easy data management. For 
measures that are instrumented with wearable sensors, Opal sensors 
(APDM) will be used to calculate objective measures of mobility (balance, 
gait and turning) and will provide both commercially available metrics from 
the software (Mobility Lab) as well as novel metrics based on our own 
algorithms 66, 67. Wireless synchronization, unique to the APDM Opal 
sensors, allows precise temporal binding of data across sensors. The 
outcome measures are summarized in Table 4.  
 
Patient-reported Assessment: The Patient Global Impression of Change (PGIC) 
is a one-question measure on a seven-point Likert scale, in which the external 
judgment of meaningful change is made by the patient 52. In 2014, the PGIC was 
chosen, by DoD stakeholders of the Office of Outcomes and Assessment at the 
Defense and Veterans Brain Injury Center, as one of the two core measure for 
mTBI health care outcomes, in regards to benefit from treatment 68. This is the 
primary outcome measure. The Dizziness Handicap Inventory (DHI) is a 25-item 
self-assessment inventory that evaluates the self-perceived handicapping effects 
due to a vestibular disorders 69. Criterion validity of this questionnaire has been 
confirmed within the TBI population, showing excellent correlation between the DHI and objective visual and 
balance measures 70, 71. The DHI has been reported to have content validity among TBI patients 72, 73. The 
Neurobehavioral Symptom Inventory (NSI) is a 22-item self-report questionnaire recommended for 
standardization by the Office of Outcomes and Assessments and the Defense and Veterans Brain Injury 
Center 74. The NSI was developed to assess a wide range of symptoms in patients presenting with post 
concussive syndrome” 74. Widely used by the DoD, the validity of the NSI has been confirmed through 
studies demonstrating internal consistency and scores correlating with clinician-confirmed TBI 75. The Quality 
of Life after Brain Injury scale (QOLIBRI) is a questionnaire with 37 items addressing 6 dimensions of quality 
of life; cognition, self, daily life and autonomy, social relationships, physical problems and feeling bothered 
by emotions 76. The QOLIBRI has established test-retest reliability and internal consistency in assessing 
quality of life across cultures in patients with TBI 76. The Concussion Clinical Profile Screen (CP Screen) 36 is 
a 29-item scale that is organized around concussion clinical profiles: 1) anxiety/mood (5 items), 2) 
cognitive/fatigue (3 items), 3) migraine (5 items), 4) ocular (5 items), and 5) vestibular (5 items); and 2 
Figure 12 Participant and 
physical therapist with 
multidimensional real-time 
biofeedback 

 
Version Date: 1/14/2025 
 
modifiers: 1) sleep (4 items), and 2) neck (cervical) (2 items). Participants respond to each item on a 0 
(none) to 3 (severe) Likert-type scale. The CP Screen provides a total symptom score ranging from 0 to 87 
and individual subscale scores 36. 
Qualitative questions: We will incorporate qualitative feedback from the physical therapist’s impression of using 
the biofeedback system with the participants. We held a focus group with several stakeholders to solicit a 
concise set of questions to include. Stakeholders included mTBI research experts, research and clinical 
physical therapists, a consultant with lived experience, and a psychometrician/methodologist. While we plan to 
use the PGIC as an outcome measure, we will also ask the participants with mTBI to rate themselves on the 
following: activity, symptoms, emotions and overall function and how that factored into their rating on the PGIC 
scale. The International Physical Activity Questionnaire (IPAQ) is a valid and reliable self-report on activity 
level. The PROMIS Item Bank v1.0 (Satisfaction with Participation in Social Roles – Short Form 4a) is a 
questionnaire that asks four questions related to how satisfied they are with social roles in the past 7 days.  It 
takes approximately 2 minutes. The Hospital Anxiety and Depression Scale (HADS) is a questionnaire with 13 
questions on a four-point responses (0-3) per question. The HADS delineates potential anxiety or depression 
dominance where possible scores could range 0-21 for anxiety and 0 to 21 for depression. The Headache 
Impact Test (HIT-6) is a questionnaire with six questions that assess the impact of headache severity of daily 
life activities. Responses to the six questions range from never (6 points), rarely (8 points), sometimes (10 
points), very often (11 points), and always (13 points), with a total score range of 36-78 points. The Insomnia 
Severity Index (ISI) is a 7-question survey that assesses sleep problems on a 0-4 scale, with a maximum 
severity score of 28. The Neck Disability Index (NDI) is a reliable and valid patient report outcome that has 10 
questions regarding neck pain during daily activities that have a response range 0-5 and the maximum severity 
score would be a 100%. The Convergence Insufficiency Symptom Survey (CISS) has 15 questions related to 
problems with convergence in everyday activities that range from 0-5, giving a maximum severity score of 60 
points. The Vertigo Symptom Scale (VSS) is a questionnaire with 15 questions that have responses that range 
from never to very often (0-4) in relation to how effected a participant is by vestibular and autonomic-anxiety 
symptoms. This questionnaire includes subcores for vestibular and autonomic-anxiety symptoms severity. The 
The Automated Neuropsychological Assessment Metric (ANAM) test is a computerized neurocognitive test and 
takes about 40 minutes to complete. 
Table 4. Outcome measures  
Patient-reported (subjective) 
Clinical Assessment 
Instrumented Assessment 
Patient Global Impression of Change 
(PGIC-Primary) 
Dizziness Handicap Inventory (DHI) 
Neurobehavioral Symptoms Inventory 
(NSI) 
Quality of Life after Brain Injury (QOLIBRI) 
Patient-Reported Outcomes 
Measurement Information System 
(PROMIS Short Form 4a) 
International Physical Activity 
Questionnaire (IPAQ) 
Vertigo Symptom Scale (VSS) 
Convergence Insufficiency Symptom 
Survey (CISS) 
Headache Impact Test (HIT-6) 
Hospital Anxiety & Depression Scale 
(HADS) 
Automated Neuropsychological 
Assessment Metrics (ANAM) 
Concussion Clinical Profile Screen (CP 
Screen)  
Neck Disability Index (NDI) 
Insomnia Severity Index (ISI) 
Balance: 
Modified Balance Error Scoring System (mBESS) 
Modified Central Test of Sensory Integration on 
Balance (mCTSIB) 
Gait: 
Functional Gait Assessment (FGA) 
1-min walk (single and dual task) 
Tandem Gait  
Hybrid Assessment of Mobility (HAM-4) 
Turns: 
Custom Turning Course (CTC) 
Vestibular/ocular-motor: 
Vestibular/Ocular Motor Screening (VOMS) 
Clinical Dynamic Visual Acuity 
Clinical Ocular Assessment  
 
Balance: 
Instrumented BESS 
Instrumented mCTSIB 
Central Sensorimotor Integration (CSMI) 
Gait: 
Instrumented FGA 
Instrumented 1-min walk 
Turns: 
Instrumented CTC 
Vestibular/ocular-motor: 
Laboratory measures including: smooth 
pursuit, saccades, vHIT 
 

 
Version Date: 1/14/2025 
 
 
We will ask the participant to discuss their return to work/study and their return to activity. For return to 
work/study, we will use a scale adapted from Moore et al. and van der Naalt et al; (0=previous work/study 
resumed or full return to duty, 1= resumed with lower demands or part time or on limited duty/profile, 2= not 
resumed or different work on a significantly lower level or reassignment, 3=unemployed/not studying or 
recommended for medical board) 77, 78. The participant will then be asked to elaborate on facilitators and 
barriers in achieving this level of return to work/study. For return to activity, we will ask about the level of 
intensity and types of activities they are currently participating in compared to previous (prior to the mTBI) 
using a scale adapted from Moore et al; (0 = participation in previous physical/recreational activities 
resumed, 1 = previous physical/recreational activities resumes with lower demands, 2 = not resumed or 
different activities on a significantly lower level, 3 = inactive/no participation in physical/recreational activities) 
77. The participant will then be asked to elaborate on facilitators and barriers in achieving this level of return 
to activity. We will ask the physical therapist at each site one open-ended question: “Would you continue to 
use this feedback system after the study is over. Please discuss why or why not.” 
Clinical Assessment: The modified Balance Error Scoring System (BESS) assesses balance by asking 
participants to stand in progressively challenging conditions (feet together, single limb stance and tandem) 
both on firm and foam surfaces 39. All items are performed with eyes closed. A rater evaluates the number of 
errors committed by the participant, such as opening their eyes or removing their hands from their hips 
during the first 20 seconds of the trial. The modified Clinical Test for Sensory Integration on Balance 
(mCTSIB) 79 assesses the sensory contributions to balance. In this test, participants stand with feet together 
in 4 conditions; 1) eyes open on a firm surface, 2) eyes closed on a firm surface, 3) eyes open on foam 
surface, and 4) eyes closed on a foam surface. Participants are clinician-rated on stability based on the 
ability to maintain balance for 30 seconds in each condition. The Functional Gait Assessment (FGA) 
evaluates a patient’s ability to adapt their balance while walking and undertaking a series of additional tasks 
such as turning their head, changing speeds, and stepping over an obstacle. The FGA is a tool that can 
differentiate gait differences between healthy people and those with mTBI (AUC = 0.78) 80. The patient’s 
performance on the test is rated by a clinician on a scale of 0 to 30 with higher scores indicating better 
performance. One-minute walk 81 is a measurement of endurance that measures walking distance over 1 
minutes. The Complex Turning Course (CTC) is a test of mobility that evaluates a person’s ability to walk a 
prescribed path involving multiple turns of various angles 82. Individuals walk around the course at their 
preferred normal walking speed. The course is marked with arrows taped on the ground indicating turns of 
45°, 90°, and 135°. Participants complete a minimum of 6 laps, and the time is recorded via a stopwatch. The 
average time to complete each lap is recorded, with faster lap times indicating better performance. The Hybrid 
Assessment of Mobility (HAM-4) includes two components of the FGA (horizontal head turns and gait with 
pivot turn), as well as a fast walk forward and backward; the total score possible is 14 points. The Vestibular 
Ocular Motor Screening (VOMS) was designed to examine how extra-ocular and head movements (e.g., 
saccades, smooth pursuits) provoke symptoms in individuals post-mTBI 83. Each eye or head movement task 
on the VOMS is scored from 0-10 with higher scores indicating more provocation of symptoms. The VOMS 
assessment examines how smooth pursuit, horizontal saccades, vertical saccades, convergence, horizontal 
VOR, vertical VOR, and visual motion sensitivity, affect headache, dizziness, nausea, and fogginess 
symptoms. At baseline and after each condition, the symptoms are scored from 0-10, with higher scores 
indicating more provocation of symptoms. Cervical Assessment will assess the participants range of motion 
and symptoms during neck movements.  Dynamic Visual Acuity (DVA) 84 assesses gaze stability during yaw 
plane head rotations relative to head-stationary visual acuity. First, static visual acuity is assessed with the 
head stationary and the patient looking straight ahead while seated 4 meters from an Early Treatment of 
Diabetic Retinopathy Study (ETDRS) visual acuity chart. The patient reads the lowest line recognizable and 
keeps reading until they can no longer identify all the letters on a given line. The examiner notes the last line 
where all letters were correctly identified and the total number of letters correctly identified. For the dynamic 
portion of the test, the examiner stands behind the research participant and holds their head with both hands. 
Starting at least 5 lines above the last line read during the static acuity testing, the examiner rotates the 
participants head in an arc of 20 degrees on either side of midline in time with a metronome set to 240 beats 
per minute, to ensure that the VOR is prioritized to stabilize vision. Again, the participant reads the letters on 

 
Version Date: 1/14/2025 
 
the lowest line of the eye chart possible and the examiner notes the last line where all letters were correctly 
identified. The number of line difference between static and dynamic acuity tests will 
be compared and a loss of three or more lines of visual acuity relative to one’s static 
visual acuity will be regarded as clinically meaningful and suggestive of gaze 
stabilization difficulty85.  
Instrumented Assessment: Instrumented assessments of balance and gait will use 
synchronized inertial sensors (Opals by APDM; Figure 13). The Opals have 3D 
accelerometers (range ±6 g), gyroscopes (range ± 2000°/s), and magnetometers 
(range ±6 gauss). Opal sensors will be applied to the head, sternum, lumbar 
spine and feet with elastic Velcro bands. Inertial data collected at 128 Hz will be 
synchronized and wirelessly transferred to a laptop for automatic generation of 
metrics with raw data stored for further analysis. The Opals are designed for easy use; they require no 
switches or configuration by the user. The instrumented system uses Mobility Lab software to enable sensor 
configuration, recording, real-time visualization, and data management. Mobility Lab provides sensitive, 
valid, and reliable outcome measures of gait and balance 46, 67, 86. Study data is exported from the Mobility Lab 
desktop software to the Mobility Exchange server, using an HTTPS channel employing a 2048-bit RSA 
encryption. Data integrity checks happen up-front, during the data collection and analysis process. When 
using the in-clinic data collection mode, users are alerted about integrity issues immediately and provided 
the opportunity to re-record the test. The instrumented mBESS 87, mCTSIB 43, FGA, HAM-4, 1 minute walk 
and CTC 88 will occur simultaneously with the clinical test (see above). 
Instrumented BESS – Postural sway measured by an Opal sensor on the waist will be evaluated 
simultaneously with the BESS described above 42, 87. Postural sway will be automatically quantified in the ML 
direction using APDM software during each stance condition by calculating the root-mean-square (RMS) 
around the mean acceleration, a metric representing sway dispersion. Our primary measure for this test will 
be the averaged ML RMS. Our previous research identified this stance condition and metric as the best for 
identifying individuals with mTBI 87. Other temporal and spatial metrics such as sway area, velocity, 
frequency and jerkiness will be simultaneously collected for secondary analysis. Instrumented mCTSIB – 
Postural sway will also be quantified using an Opal sensor during the clinical mCTSIB. The same outcomes 
of sway will be obtained for the Instrumented mCTSIB as for the Instrumented BESS above. Instrumented 
FGA - Participants will complete all of the walking tasks that are components of the FGA. Based on our 
previous research, we are particularly interested in 4 items: Gait Level Surface (FGA-1); Gait with Horizontal 
Head Turns (FGA-3); Gait with Vertical Head Turns (FGA-4); and Gait with Eyes Closed (FGA-8). 
Additionally, the head turn kinematics will be quantified during FGA-3 and FGA-4) 89. Peak angular 
displacements and velocities of the head and trunk will be extracted from the angular velocity data. Head 
movement variability (e.g., RMS of head acceleration) during the FGA-1 and FGA-8 will also be calculated 
using custom MATLAB algorithms. Instrumented Gait – Participants will walk at their self-selected pace for 2 
minutes between two lines. Spatiotemporal gait metrics will be obtained from the APDM Mobility Lab software 
67 Measures will be used to identify gait domains associated with mTBI, including Variability, Rhythm, Pace, 
and Turning 90. 
 
Figure 13. Watch 
size Opal sensor  

 
Version Date: 1/14/2025 
 
Instrumented CTC – Turning velocity and 
segmental coordination will be quantified 
using Opal inertial sensors located on the 
head, sternum, and lumbar regions as 
participants complete the CTC described 
above (Figure 14). The peak axial rotation 
(i.e., yaw) angular velocity and segmental 
coordination are extracted for each turn 
(45°, 90°, 135°) using custom MATLAB 
algorithms developed by our research 
team. Using these methods, our previous 
studies have shown that the peak angular 
velocity is sensitive to mTBI 91 and can be 
equivalently collected across multiple sites 
88. Slower turning velocities indicate more 
impaired function 88. 
Instrumented Vestibular and Ocular-motor 
measures – Commercial (Interacoustics VisualEyes 525, Neurolign I-Portal NOTC and VEST, Natus 
Otometrics ICS Chartr 200, and Natus Otometrics ICS Impulse) systems will be used to assess vestibular 
and ocular-motor function based on quantitative analysis of infrared video eye movement recordings. 
Vestibular function evaluation will include video head impulse tests (vHIT) for the detection of reduced or 
asymmetric vestibular function, and measurement of spontaneous and positional nystagmus in the dark. 
Ocular-motor function assessments will include horizontal (0.3 and 0.75 Hz) and vertical (0.3 Hz) smooth 
pursuit eye tracking of sinusoidally moving targets, and horizontal and vertical saccades to visual targets 
appearing in random locations. These commercial systems analyze recorded eye movements that provide 
quantitative measures of performance (examples: vHIT gain, comparing the ratio of evoked eye velocity to 
head velocity and vHIT asymmetry, comparing gains for head movements to the right versus the left; smooth 
pursuit eye velocity gains and asymmetry; saccade onset latency and accuracy). Established clinical norms 
for these tests will be used to classify participants into normal versus abnormal vestibular and ocular-motor 
function categories. 
 
o Central Sensorimotor Integration (CSMI) Testing: Participants will be tested on a modified Research 
NeuroCom platform where they will stand on a force plate to record postural sway. The surface and / or 
visual surround will move while the participant is instructed to maintain their balance. Participants will 
wear a safety harness attached above to prevent a fall in case a loss of balance occurs. Participants 
will complete several trials of different perturbations (e.g., visual surround moving, platform moving, 
both moving). This test will take approximately 20 minutes to complete.  
m. Potential covariates and confounders, in agreement with the CDE recommendations, will be 
measured. These measures are CDE’s for both the NINDS and the Federal Interagency Traumatic 
Brain Injury Research (FITBIR):1) Age, gender, significant medical history including previous mTBI 
history (prior mTBIs, loss or alteration of consciousness, length of post-traumatic amnesia, time since 
injury), 2) Post- traumatic stress disorders (PTSD) using the PTSD Checklist for Civilians or PTSD 
Checklist for Veterans 92, 93 
n. Statistical Analysis Plan. The primary outcome for Aim 1 is the Patient Global Impression of Change 
(PGIC). It is an ordinal variable where participants rate their global assessment of change on a scale 
from 1 to 7. To test whether the group with multidimensional real-time biofeedback has larger 
improvements in the PGIC than the group with standard care physical therapy, we will first conduct a 
Mann-Whitney U test to assess group differences and a Chi-square test to compare responders vs. 
non-responders in PGIC scores between groups. Responsiveness to rehabilitation will be determined 
by the participants' score on the PGIC after rehabilitation. PGIC score will be dichotomized by 
“responder” or “non-responder”. We will classify participants who score 6 or above on the PGIC as 
“responders” and those who score 5 or below as “non-responders”. Then we will perform subsequent 
 
Figure 14. Custom Clinical Turning Course (top left) shown with angular 
velocity timeseries data (bottom). The timeseries depicts 9 laps, and data from 
one lap is enlarged (top right) to illustrate the turns at each angle. Different 
angles of turns are shaded with different colored bands. Turns of 45 degrees 
are shaded green, turns of 90 degrees are shaded red, and turns of 135 
degrees are shaded yellow 

 
Version Date: 1/14/2025 
 
analyses using ordinal logistic regression to examine group differences accounting for covariate effects 
(e.g., age, gender, PTSD, etc.). Additionally, we will also conduct a logistic regression on responder 
vs. non-responder as the binary outcome to assess differences between groups accounting for 
covariates. 
Secondary outcomes (e.g., patient-reported symptoms, clinical and instrumented objective assessments) will 
be measured at baseline and post-rehabilitation. All secondary outcomes will be assessed for normality and 
we will perform a data transformation (e.g., log transformation) when appropriate. We will calculate the pre-
post change in each secondary outcome for each participant. To test the difference in pre-post change 
between the multidimensional real-time biofeedback group and the standard care group, we will conduct a 
two-sample t-test or a Mann-Whitney U test for each secondary outcome. We will also employ mixed effects 
models to assess the differences in change in secondary outcomes between the real-time biofeedback and 
standard care group. Two fixed effects will be included in the model: 1) group effect (real-time biofeedback vs. 
standard care) and 2) time effect (baseline and post-rehabilitation). The interaction between group and time 
(group x time) will also be included. We will include covariates in the fully adjusted model. Random intercepts 
will be included to account for the clustering effect within subjects over time. We will use an inverse probability 
weighting (IPW) approach to account for participant attrition in the study and perform sensitivity analyses for 
IPW. We will also compare the descriptive information on demographic and clinical variables between those 
who drop out of the study and those who complete the study. 
o.  
 
p. Qualitative Outcomes. Participant responses will help contextualize the quantitative measures and 
provide a more nuanced understanding of how patients regard their response to therapy. To minimize 
bias, participant will be sent qualitative questions via electronic survey. This information will be 
summarized at the completion of the study. Participants will also be contacted via phone call or email 
3 months after their last testing session to assess if they have had any injuries since completing the 
study. On a yearly basis our research physical therapists with answer qualitative questions regarding 
the real time biofeedback. 
q. Potential Problems. Recruitment – We may have difficulty recruiting enough people but this is unlikely 
given our previous success with similar recruitment criteria at all sites. All sites have established 
recruitment methods already in place. It is also possible we will enroll a subject that does not have 
either a vestibular and/or ocular-motor deficit, but we think this will be unlikely as we will only enroll 
people who have some symptoms of V/O complaints (See Justification above for V/O cut-off scores). 
Further, we will prescreen participants using several V/O scales to make sure we have equal number of 
people with more severe V/O subtype compared to minimal V/O deficits. Attrition – We may have high 
numbers of people who drop out of the study but we factored in an estimated 25% drop-out rate so we 
don’t anticipate this to be a problem. Technical – We may experience technical difficulties with wearable 
sensor-based feedback system. All proposed sites have some experience using wearable technology 
and have had minimal technical issues with previous studies. With our expertise in embedded system 
technology, we will be able to handle technical issues as they arise. We have already solved many 
problems in the development phase such as minimizing the delay and providing a system with low 
latency and optimized energy usage. The sensing/controlling unit was designed to have the speed 
needed to detect and communicate objective measures in the shortest possible time. 
Aim II. Responsiveness to rehabilitation; objective measures to identify V/O subtype. To explore a) 
rehabilitation efficacy across severity of V/O deficits, using multiple measures of V/O function and b) the 
strength of the relationship between subjective and objective measures of V/O function.  
Rationale. While objective measures have been recently highlighted as a critical component of assessment 
after mTBI, self-reported measures continue to drive medical referrals, clinical subtyping and plan of care. It 
is documented that V/O subtypes are common with approximately 35% of patients categorized with V/O as 
the primary subtype in a retrospective chart review 94. We believe that using both subjective and objective 
measures of V/O function will result in a more accurate classification of subtypes, leading to the better 

 
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identification of V/O subtypes, creating more appropriate referrals and precision medicine. 
a. Design and Participants. This is an observational study where we will explore responsiveness to 
rehabilitation and relationships across multiple measures of V/O function including Patient-reported, 
Clinical Assessment and Instrumented Assessment. We will use the data acquired from participants 
in Aim I to explore responsiveness to rehabilitation and to explore the relationship among measures 
of V/O function. 
b. Power and sample size considerations for Aim II. Because this is an exploratory Aim, we will use 
estimates from the data to inform power and sample size calculations for future studies. Therefore, 
we will use data from all participants from Aim I. 
Statistical analysis plan.  In this exploratory aim, we will: 1) assess high vestibular/ocular (V/O HI) versus low 
vestibular/ocular (V/O LO) participants’ responsiveness to rehabilitation and 2) explore the relationship 
between subjective and objective measures of V/O domains. First, we will examine the distribution of PGIC 
scores and conduct a Mann Whitney U test of PGIC scores between V/O high and V/O low groups. Then we 
will perform a Chi-square test to compare responders vs. non-responders (based on PGIC scores) between 
Hi V/O and LO V/O groups regardless of 
randomization group assignment. Then we 
will 
assess the PGIC as an ordinal outcome variable and 
test group differences (V/O HI vs. V/O LO) in 
responsiveness using ordinal logistic regression. 
Additionally, we will conduct a logistic regression on 
responder vs. non-responder as the binary outcome 
to assess differences between V/O HI group and V/O 
LO group. Both regression models will allow us to 
control for covariates (e.g., age, gender, days since 
injury, intervention arm) in the models. We will use the 
data to obtain estimates to inform future studies and 
power calculations. Finally, to explore the strength of 
associations between the Patient-reported, Clinical, 
and Instrumented V/O measures, we will measure the 
associations using Pearson correlation coefficients for continuous variables and Spearman correlation 
coefficients for ordinal variables. 
c. Outcomes. The outcomes for Aim II are the same outcomes measured for Aim I (see Table 4). 
d. Interpretation. If we find that the people with high V/O deficits are more responsive to an evidence-
based, multimodal, 6-week physical therapy intervention for people with mTBI compared to those with 
milder V/O deficits (that may include other subtypes such as cognitive, headache/migraine or 
anxiety/mood), we will conclude that it is essential that subtype classification occur routinely, prior to 
initiating physical therapy. If we find that there are only small or moderate associations between 
subjective and objective measures of V/O function, we will conclude that mTBI subtyping should 
include more than just subjective symptom reporting and that objective measures are essential for 
routine clinical assessment prior to referrals and targeted treatments. 
e. Potential problems. We anticipate varied responses for the PGIC. In the event that responses are 
homogeneous, this will limit conclusions that we can draw on responders versus non-responders. 
However, we also have numerous secondary measures across levels including subjective, clinical, 
and instrumented measures that will inform and motivate future studies. 
Aim III: Daily life mobility in people with V/O subtype. To: a) determine if daily life mobility (quality of gait 
and turning) is impacted differently in people with high versus low V/O deficits, b) calculate healthy normative 
data for daily life mobility measures in active duty military service members. 
a. Rationale. We recently published a study demonstrating that quality (but not quantity) of daily life 
mobility is different in people with chronic mTBI 48 (Figure 4) and the proposed study will now explore 
 
Figure 15. Binary cut off scores to define responsiveness to 
rehabilitation on the PGIC.  

 
Version Date: 1/14/2025 
 
whether people with more severe V/O symptoms have worse quality of daily mobility. We are 
particularly interested in continuous monitoring as an outcome measure since there are very few 
participation level outcomes used according to the International Classification of Function, Disability 
and Health (ICF) model, a model that provides a standard framework for assessing a person’s health 
and health-related state 95. Several reports identify the concern that studies use minimal participation 
level assessments and currently the majority of participation level outcomes are self-reported 
measures. Understanding changes at the participation level is vital to know if and how injury and/or 
rehabilitation effects daily life 95-97. 
We will also obtain healthy normative values for military active duty service members since this 
population may have higher and more variable activity levels than civilians. Specifically, physical fitness 
and exercise training are emphasized in the armed forces to meet the physical demands of the job, while 
such demands are not as widely expected within the careers of the civilian population 98. Further, 
military personnel are reported to have more regimented engagement in physical activity, excel in 
meeting weight standards and have access to more formalized exercise training which many civilians 
are not offered in places of employment 99-101. The 40 healthy control military service members will 
provide daily life mobility control data that will be useful in assessing global function of service members 
post-mTBI and ultimately could be useful for return to duty decisions. 
b. Participants. For Aim III, we will enroll the first 25 people who classify as V/O HI and the first 25 
people who rate as V/O LO(See justification above for cut-off scores). For the 40 healthy active duty 
military personnel, service members working at FSH will be recruited primarily from the U.S. Army 
Medical Center of Excellence. Participants must be active duty military service members with no 
recent (<3 year) history of mTBI and no residual symptoms from any other previous mTBIs to be 
enrolled. 
c. Power and sample size consideration. Preliminary pilot data were collected from eight participants on 
objective daily life mobility metrics. In the pilot study, the participants were categorized as having 
either moderate to severe V/O deficits (n=3) or minimal V/O deficits (n=5) based on the Concussion 
Symptom Subtype Inventory (CSSI)37. For the purpose of power analysis for Aim III, three quality 
metrics including turn angle (deg), turn angle variability (CV), and turn peak velocity (deg/s) were 
assessed between two groups to obtain the parameters. From our preliminary data, the estimated 
mean difference between two groups and common standard deviation (SD) of turn angle, turn angle 
variability and turn peak velocity are 4.48(±4.14), 0.018(±0.016), and 7.95(±4.47), respectively, which 
yielded very strong effect sizes (1.1, 1.1 and 1.8). Therefore, we conservatively determine sample 
size calculation with the effect size of 0.90 when comparing two groups. To gain at least 80% power 
to detect the difference, we need at least 21 subjects for each group, at a level of significance alpha = 
0.05. Therefore, we aim for collecting measurements from at least 21 subjects per group (N=42). 
Given an estimated completion rate larger than 85%, we plan to enroll 25 subjects per each group 
(N=50).  
 
d. Procedure. Participants will wear 3 sensors, one on each foot (embedded in neoprene instrumented 
socks, Figure 3) and one on the waist (on elastic belt) to passively quantify gait and turning during 
approximately 7 days of daily life. The 50 participants (25 from OHSU and 25 from UU) will undergo 
approximately 7 days of continuous, passive monitoring and the 40 active-duty military service 
members will also undergo 1 week of continuous monitoring. In the morning, participants will don the 
instrumented socks (Figure 3) and the belt-worn sensor. The sensors will be worn all day and then 
inserted into a docking station to charge each night. The cutting-edge technological approach will 
allow us to develop sensitive, functional test batteries for assessing and treating mobility disorders for 
use in future clinical trials and practice. 
 
e. Daily life mobility measures; The measures of mobility during daily life will be calculated with either 
proprietary algorithms from APDM Wearable Technologies or our Balance Disorders Laboratory 
algorithms, all of which have been validated 45-47, 67. Measures are calculated by combining the 3 axes 
of linear acceleration with 3 axes of angular velocity and the magnetometer, all sampled at 128 Hz to 

 
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obtain motion and orientation of the feet and body in space. The APDM wearable sensors have a 
unique, patent-protected, wireless synchronization of the sensors that allows precise temporal 
binding of data across sensors. Our partnership with APDM Wearable Technologies resulted in a 
series of NIH-SBIR grants focused on developing and testing these novel instrumented socks, 
consisting of inertial sensors on top of the feet connected to a long-lasting battery on the lower leg 47. 
Data are automatically stored in the internal memory of the sensors and automatically uploaded to a 
secure data server (using HIPAA compliant AWS services) when docked to charge at night. 
Incremental backups of the data on all Mobility Exchange instances are performed daily. Redundant 
copies of these backups are transferred daily to a separate AWS region, managed by AWS services. 
In parallel to this innovative hardware, we have also developed and validated algorithms to analyze 
turning and straight-ahead gait during daily life 45, 67. Specifically, for turning we validated inertial 
sensor algorithms to measure turning quality for 45-360 degree angles performed at normal, fast and 
slow gait speeds during continuous walking tasks compared to gold-standard, motion analysis and for 
daily living compared to video-data from a waist-mounted, GoPro mini-camera aimed at participants’ 
feet during normal activities in the home 45. The algorithms showed a sensitivity of 0.90 and a 
specificity of 0.75 for detecting the start and end of each spontaneous turn compared to motion 
analysis. Sensitivity and specificity of the algorithm compared to video-raters for home measurement 
was 0.75 and 0.7745. Our studies not only demonstrated the feasibility of the method for continuous 
monitoring of mobility up to 14 hours per day, but also validated the ability to use the same gait and 
turning algorithms during daily life as used in the laboratory, after identifying walking bouts and 
standing and turning periods 47. Further details on metrics extractions are described in previous 
publications 45, 46, 67. 
 
f. 
Outcomes. We will focus on a subset of daily life passive monitoring measures (Table 5), based on our 
published results and pilot data 48. Out of 43 different measures of gait and turning (plus their variability 
as SD) obtained from approximately 7 days 
of daily life passive monitoring, several 
turning measures and their variability were 
consistently different between people with 
mTBI and healthy control participants 48,53. 
Specifically, people with mTBI avoided 
large turn angles, turned slower and had 
less variability throughout their daily 
mobility. Our pilot data suggested that 
similar measures were different in people 
with objective deficits in V/O domains, 
compared to those without (Figure 10). We 
will use the same measures outlined in 
Table 5 to test our hypothesis that quality of 
daily life mobility is worse in people with 
V/O HI deficits. Additionally, as the mobility 
measures listed in Table 5 are those that differ the most between controls and people with mTBI, we 
expect that rehabilitation-related changes will be revealed by these measures.  
Covariates are described under Aim I outcomes and for Aim III we will add activity measures including 
the International Physical Activity Questionnaire (IPAQ), a valid and reliable self-report on activity level 
102 . 
g. Statistical Analysis Plan. Participants will be grouped according to their level of severity of V/O deficits 
(HI or LO V/O deficits), regardless of intervention group. Prior to detailed statistical modeling, we will 
compute quality metrics of daily life mobility quantified from instrumented socks summarized over the 
duration the devices were worn by each participant (for those that wore the devices for approximately 
7 days and approximately 10 hours/day). Specifically, we will provide both statistical and graphical 
evaluation for the distributions of turn quality metrics: (Turn ngle and its variability (primary), Turn 
duration and its variability, , and Turn peak velocity and its variability), and then transform the values if 
Table 5: Outcome measures from continuous monitoring  
Quality Turning Measures 
Quantity Activity Measures 
Turn Angle (°) and variability 
(Primary) 
Activity Rate 
Turn Duration (seconds) and 
its variability 
Number of steps per day 
Peak turn velocity (°/second) 
and its variability 
Number of turns per hour 
Covariates for Aim III: 
Age, gender, previous mTBI history 
Post-Traumatic Stress Disorder (PTSD Checklist 
The International Physical Activity Questionnaire 
(IPAQ) 

 
Version Date: 1/14/2025 
 
necessary to better meet model assumptions. We will also examine quantitative activity measures 
including Activity rate, Number of steps per day and Number of turns per hour). We will examine the 
distribution of the metrics in each group. The descriptive statistics of metrics for each group will be 
reported as mean (SD). To test whether daily life mobility measures differ between V/O HI and V/O LO 
groups, we will test the metrics for group differences using a two sample t-test. In addition, we will 
conduct subsequent analyses to compare metrics between two groups accounting for covariates using 
the multivariate generalized linear modeling (GLM) approach. The model will be constructed for each 
metric (outcome) separately. The group estimates will be assessed with and without the co-existing 
covariates to explore potential confounding factors, which allows us to test for group differences while 
controlling for the possible effects of other covariates. In addition, we will explore other quality and 
quantity metrics and and will also examine the distributions using the same method and conduct two 
independent sample t-test between two groups for the completeness of the analysis. 
h. To summarize the healthy military normative group, we will similarly collect data from 
instrumented socks worn over an approximate 7-day period. We will examine the distribution 
of the metrics and provide descriptive statistics including means, standard deviations, 
median and 25th, 75th percentiles. Additionally, we will check the normality of the data. This 
will provide preliminary data for our next studies exploring daily life mobility in those cleared 
to return to duty after mTBI. 
i. 
Interpretation. If we find that turning quality, measured during daily life, looks different in people with 
high versus low V/O symptoms, this would support adding this as an outcome measure to help direct 
rehabilitation and track recovery. A future study should explore if service members cleared to return 
to duty post-mTBI have the same level of daily life mobility as healthy service members (a value 
established in Aim III). If they do not, perhaps return to duty decisions were made too soon or 
rehabilitation was incomplete. 
j. 
Potential problems. Technical: It is possible that the Opal sensors will fail to synchronize after 
charging or that subjects will wear them inappropriately. However, our experience with over 300 older 
people with multiple diagnoses (some with mild cognitive impairment) wearing Opals for 
approximately 7 days tells us these types of technical issues will be quite limited. Nevertheless, the 
research assistant will call participants the day after issuing the system to mitigate technical issues. 
Compliance: We may find that people do not wear the instrumented socks for enough hours/day or 
days/week. It is unlikely, but possible that the participants may be unable to complete the 7 days of 
recording. If this occurs, only the completed period will be used in the performance assessment. 
Compliance data from our previous studies showed that people rated wearing our instrumented 
socks comfortable for seven days during daily activities. Subtype categorization: In the event that we 
don’t have enough representation of participants with mild V/O deficits, we will revisit categorization 
criteria or recruit more mild V/O patients. 
      
5. Screening Procedures: The research assistant will ask participants prescreening questions over the phone 
to determine eligibility for the study. If they appear to meet all inclusion and exclusion criteria, as listed above, 
the research assistant will schedule an initial appointment. During this session, the research assistant will 
ask additional screening questions, including pertinent medical history, after consent is obtained.   
 
6. Risks/Benefits Assessment: These are safety measures to minimize and/or eliminate risks to human 
subjects and personnel.  
• 
Falls: The proposed team of researchers has tested over 500 participants using similar tests of postural 
control in various projects at OHSU without significant injury to any participant. A trained and experienced 
assistant will ‘spot’ participants during all balance testing to be ready to catch participants if needed. In 
addition, if the participants have especially poor balance, a safety belt can be placed on participants before 
balance testing to make it easier to spot during clinical testing. It is therefore highly unlikely that participants 
will experience a loss of balance or be injured during testing.  

 
Version Date: 1/14/2025 
 
• 
Exacerbation of symptoms: If symptoms of dizziness, headache or nausea are exacerbated, the session 
will not proceed until participants symptoms have decreased. Additionally, we will have designated rest 
periods during the protocol for safety.     
• 
Loss of confidentiality: The computer that will store the project database will be protected by current 
network security. An institutional computer account and password will be required to access the computer 
storing the recruitment database and the images. Data will be maintained on secure, encrypted servers 
maintained by OHSU.  
• 
Emotional anxiety: Should emotional anxiety result from testing or questionnaires, we will inform 
participants that the testing does not reveal information about the severity of problems, as this is not the 
purpose of the study. We will encourage participants to discuss any balance problems with participants 
treating physician and physical therapists.  
• 
Physical injury: There is a low risk of injury during or after a testing session. The risk is reduced by use 
of well-trained assistants and by the mild nature of the gait, balance and vestibular testing.   
• 
Loss of privacy: Participants will be assigned a coded identification number and this number will be used 
to keep track of data. Only individuals who are specifically authorized to view private health information by 
the principal investigator will have access to information that could be used to identify participants. Thus, the 
risk to participants in this research is in the categories of unlikely physical risks and potential loss of 
information privacy.  
• 
Wearable sensor system: The wearable sensors worn on the body are commonly use in other laboratory 
studies assessing balance and gait. There is no identifiable information stored on these sensors. These 
sensors are non-invasive but may cause minimal discomfort similar to wearing a headband, wristwatch or 
belt.   
• 
Biofeedback sensor system: These sensors used for biofeedback are the same as the sensors in the 
wearable sensor system. There is no identifiable information stored on theses sensors. These sensors are 
non-invasive and may cause minimal discomfort similar to wearing a headband, wristwatch or belt.   
  
7. Risk Management and emergency response:  
Procedures in this study were specifically designed to minimize risks to the participants. However, Dr. King 
(overseeing principal investigator) or her designee will review data checks monthly to ensure routine evaluation 
of events, to determine any potential unanticipated problems that may involve risks to subjects or others, and 
the appropriate action as a result of such events. Study personnel will be responsible for reporting adverse 
events as they occur to Dr. King, who will notify the OHSU IRB of the occurrence within 5 days of the event. 
Serious adverse events (life-threatening or disabling and requiring medical attention) that may occur during this 
study, such as death and cardiovascular events, Dr. King, and all other investigators, will be notified immediately 
and will submit a full written report to the IRB within 24 hours. While these events are extremely rare in persons 
engaging in low or moderate activity, it is possible that a person with previously undisclosed cardiovascular 
disease may experience a cardiovascular event or death during activity. In the event this occurs, study personnel 
will take the appropriate, necessary measures. However, this federally funded study will not have the ability to 
provide compensation for research-related injury. Emergency treatment may be available but subjects and/or 
their insurance company will be charged for this treatment.  Events such as dropouts and protocol deviations will 
be reported to Dr. King and they will be reported to the IRB during annual continuing reviews.   
  
8. Potential benefits: Participants may or may not personally benefit from being in this study. Participants will 
receive $75 for the first testing session and $100 for post intervention assessment. If participants are asked 
to wear the sensors at home for approximately 7 days, participants will receive an additional $10/day totaling 
$70.    
  
9. Data Management 
  
a. Identifiers: Participants will be assigned a coded study identification (ID) number generated after written 
informed consent has been obtained.  The participant’s name and unique ID number will be recorded in 
an electronic file, stored on a password-protected secure drive. Research records will be stored in a 

 
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confidential manner so as to protect the confidentiality of subject information. Data collection forms will 
be labeled using unique study ID numbers and will not have personal identifiers.  
  
b. Confidentiality: To ensure and protect participants privacy and to maintain confidentiality of the data, 
the following activities for data and safety monitoring will be in place for the study: 1) A detailed plan will 
be approved through a multi-level Institutional Review Board (IRB) approval process (see Study 
Personnel and Organization: Study Management Plan) before recruitment begins, 2) Data will be coded 
upon collection with the key to the code held separately from the data and accessible only to IRB 
approved study personnel who need to know. Subject information and study data will be stored in locked 
cabinets (if paper) at each site and behind a secure Oregon Health & Science University (OHSU) firewall 
on network drives requiring password authentication. The representatives of the US Army Medical 
Research and Material Command (USAMRMC) are eligible to review study records. The persons who 
are authorized to use and disclose the data from this study are the approved investigators, other research 
professionals at each site who are participating in the conduct of this research protocol, and the OHSU 
IRB. The IRB at each site is authorized to use and disclose data relating to participants tested that that 
site. All data will be safeguarded in accordance with Health Insurance Portability and Accountability Act 
(HIPAA). The knowledge of any pending compliance inspection/visit by the USAMRMC, or other 
government agency concerning clinical investigation or research, the issuance of Inspection Reports, 
warning letters, or actions taken by any Regulatory Agencies, including legal or medical actions, and any 
instances of serious or continuing noncompliance with the regulations or requirements will be reported 
immediately to the site-specific IRB, to OHSU, and to the Department of Defense and/or USAMRMC. 
Representatives from USAMRMC are eligible to review study records upon request. Data collected in 
this study do not include any sensitive information, such as history of communicable diseases that are 
required to be reported to state or local authorities.  
  
c. Sharing study results: The results generated in this study are experimental in nature and will not be 
shared with study subjects.   
  
d. Laboratory Evaluations: Not applicable; no specimens will be collected for study purposes.   
  
e. Data capture, verification and disposition: The multicenter protocol will rely on a web-based 
system  of data input into a central Research Electronic Data Capture system (REDCap). REDCap is a 
secure electronic database administered by OHSU and maintained on secure servers with limited 
access. The system will feature multi-tiered security-protected access and will conform to HIPAA 
security policies. Stored data will be backed up daily. The de-identified Mobility Lab data will be 
collected on a password-protected and data-encrypted laptop computer and uploaded after each test 
session to an OHSU secure server. Authenticated investigators will have access to the dataset from 
any secure Internet access point. Computers that will store the project database will be protected by 
current network security behind an OHSU firewall. All investigators and key study personnel will be 
provided with an institutional OHSU account to access REDCap. An institutional computer account and 
password will be required to access the computer storing the recruitment database and the images. In 
addition, the REDCap database is password protected, and only project personnel approved by Dr. 
King will be given access.   
   
Data will be gathered from questionnaires and instrumented assessments, and entered into the 
REDCap web-based data entry portal by research assistants at each site. The investigator or 
coordinator at each site will subsequently confirm the accuracy of data entry for every third participant 
by comparing electronic data with the original hard copy data. Once sites have completed their data 
checks then OHSU’s study coordinator will investigate any discrepancies or incomplete data entries. All 
forms will be locked by OHSU’s study coordinator once data verification is complete.    
   
The feedback system utilizes wearable inertial sensors (Opals) for precise quantification of motion. The 
Opals log kinematic data to on-board memory, which can be transmitted to a PC either wirelessly or via 

 
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a USB adapter. When used in the clinic, the system uses a Docking Station to recharge the Opal's 
battery and transfer the raw sensor data logged to a computer and an Access Point to enable wireless 
streaming to a computer. The system also includes a cloud-based Clinical Data Management System 
called Mobility Exchange, which is designed to help execute multi-site clinical trials employing the 
software for data collection. The primary functionality of the Mobility Exchange server is to support the 
aggregation of data collected from multiple systems, support the centralized administration of a clinical 
study, and to implement technical controls to satisfy regulatory requirements and guidance.   
   
Mobility Exchange uses HIPAA-compliant Amazon Web Services (AWS) services, and it manages user 
access, tracks changes in an audit log, ensures valid data uploads, and stores each site’s data (raw 
and analyzed) in a central repository. Incremental backups of the data on all Mobility Exchange 
instances will be performed daily. Redundant copies of these backups are transferred daily to a 
separate AWS region. These are managed by AWS services.   
   
Hard-copy research records and consent forms will be stored in a locked file cabinet within a locked, 
secure office. Hard-copy and electronic research records will be kept for seven years, in compliance 
with HIPAA, or one year after publication, whichever is longer. All identifiers will be removed at the 
completion of the study and it will not be possible to link the data to individuals after that time.   
 
f. Access to test results: The results of research tests will not be made available to participants because 
the research is still in an early phase and the reliability of the results is unknown.  We are asking 
participants to provide their information for a data bank, also called a repository.  These samples will be 
stored indefinitely and may be used and disclosed in the future for research. 
 
 
Pre-
Rehab 
Testing 
7 Days 
Home 
Monitoring 
with 
SmartSox  
Intervention 
(with or 
without 
biofeedback) 
Post-
Rehab 
Testing 
Screening 
X 
 
 
 
Consent and 
Enrollment 
X 
 
 
 
Questionnaires 
X 
 
 
 
X 
 
Balance Assessment 
(Static and Dynamic) 
X 
 
 
X 
Clinical Ocular 
Assessment 
X 
 
 
X 
Laboratory 
Vestibular-Ocular 
Assessment 
X 
 
 
X 
6-Week 
Rehabilitation 
 
 
X 
 
7-Days Home 
Monitoring 
 
X 
 
 
Patient Global 
Impression of 
Change (PGIC) 
 
 
 
X 
Total Time 
6-8 hours 
(over two 
days) 
57-70 hours 
720 minutes 
6-8 hours 
(over two 
days) 

 
Version Date: 1/14/2025 
 
 
 
 
10. RISKS AND DISCOMFORTS:   
Loss of confidentiality: The computer that will store the project database will be protected by current network 
security. An institutional computer account and password will be required to access the computer storing the 
recruitment database and the images. Data will be maintained on secure, encrypted servers maintained by 
OHSU.  
 
Loss of privacy: Participants will be assigned a coded identification number and this number will be used to keep 
track of participant data. Only individuals who are specifically authorized to view private health information by 
the principal investigator will have access to information that could be used to identify participants. Thus, the risk 
to participants in this research is in the categories of unlikely physical risks and potential loss of information 
privacy.  
  
Musculoskeletal injury: There is a low risk of joint, tendon, or muscle pain, inflammation, or swelling during or 
after the gait and balance testing session. This risk is reduced by the mild nature of the gait and balance testing 
administered by well-trained research assistants.   
 
Exacerbation of symptoms: There is a low risk that symptoms such as dizziness, headache or nausea will 
become worse by performing the tests and by doing physical therapy. We will try to monitor symptoms and 
provide breaks.   
 
Emotional Distress: Some of the questions asked may be personal or embarrassing. Participants have the right 
to refuse to answer any of the questions if they do not want to. Additionally, they may learn information about 
balance and walking and that could be upsetting to participants.   
 
Falls: The balance and walking tasks may cause participants to lose their balance or fall. However, our trained 
research assistants will walk alongside participants at all times; if they happen to lose balance, our research 
assistant will be there to assist and prevent a fall. All safety measures will be taken to ensure a secure and 
comfortable environment. Participants will be allowed to take breaks during the balance and walking tasks 
whenever necessary. It is unlikely that participants will fall.   
 
Wearable sensor system: The wearable sensors worn on the body are commonly use in other laboratory studies 
assessing balance and gait. There is no identifiable information stored on these sensors. These sensors are 
non-invasive but may cause minimal discomfort similar to wearing a headband, wristwatch or belt.   
 
Biofeedback sensor system: These sensors used for biofeedback are the same as the sensors in the wearable 
sensor system. There is no identifiable information stored on theses sensors. These sensors are non-invasive 
and may cause minimal discomfort similar to wearing a headband, wristwatch or belt.  
  
11. BENEFITS: Participants may or may not personally benefit from being in this study. However, by serving as 
a subject, they may help us learn how to benefit patients in the future.  
  
12. ALTERNATIVES: Participants may choose not to participate in this study.  
 
13. CONFIDENTIALITY AND PRIVACY OF PROTECTED HEALTH INFORMATION:  
We will not use the participant’s name or identity for publication or publicity purposes.  
The specific health information that we collect may include:  
1. Health information about the participants mTBI  
2. Body motion  
3. Responses to questionnaires  
4. Video recordings of the balance and gait tests  

 
Version Date: 1/14/2025 
 
  
The purpose of this information is:  
1. To learn more about the condition being studied  
2. To improve health care for persons with the condition being studied  
3. To analyze research results  
4. To complete research obligations in this study  
5. For teaching purposes  
  
The persons who are authorized to use and disclose this information are: all investigators and co-investigators 
who are participating in the conduct of this research protocol, the Regional Health Command Central, Institutional 
Review Boards, and the Army Human Research Protection Office. The Department of Defense is authorized to 
access research records as part of its human subject’s protection oversight activities. Data will be shared for 
research purposes through the Federal Interagency Traumatic Brain Injury Research Informatics System 
(FITBIR). All links with participant identity will be removed from the data before they are shared. Only de-identified 
data, which does not include anything that might directly identify participants, will be shared with FITBIR users 
and the general scientific community for research purposes.   
 
The persons who are authorized to receive this information are: the sponsors of the study and the Office for 
Human Research Protections.   
 
We may continue to use and disclose protected health information that we collect from participants in this study 
indefinitely.  
 
While this study is still in progress, participants may not be given access to medical information about them that 
is related to the study. After the study is completed and the results have been analyzed, they will be permitted 
access to any medical information collected about them in the study.    
 
Participants have the right to revoke this authorization and can withdraw their permission for us to use their 
information for this research by sending a written request to the principal investigator listed on page one of the 
consent and authorization form. If they do send a letter to the principal investigator, the use and disclosure of 
protected health information will stop as of the date she receives the request. However, the principal investigator 
is allowed to use information collected before the date of the letter or collected in good faith before their letter 
arrives. Revoking this authorization will not affect their health care or their relationship with OHSU. The 
information about them that is used or disclosed in this study may be re-disclosed and no longer protected under 
federal law.   
 
14. COSTS: There is no cost to the participant to be in this study.  
 
They will receive $75 for the first testing session and $100 for post intervention assessment. If participants are 
asked to wear the sensors at home for approximately 7 days, they will receive an additional $10/day totaling 
$70.   
 
 
15. LIABILITY: If participants believe they have been injured or harmed while participating in this research and 
require immediate treatment, contact Laurie King, Ph.D., P.T., MCR (503) 418-2602. Participants have not 
waived their legal rights by signing this form. If they are harmed by the study procedures, they will be treated. 
OHSU does not offer to pay for the cost of the treatment. Any claim the participant make against OHSU may 
be limited by Oregon Tort Claims Act (ORS 30.260 through 30.300). If participants have questions on this 
subject, please call the OHSU Research Integrity Office at (503) 494-7887.  
 
This federally funded study does not have the ability to provide compensation for research-related injury. If 
participants are injured or become ill from taking part in this study, it is important to tell their study doctor. 

 
Version Date: 1/14/2025 
 
Emergency treatment may be available but the participant or their insurance company will be charged for this 
treatment.  
 
16. PARTICIPATION: If participants have any questions regarding their rights as a research subject, they may 
contact the OHSU Research Integrity Office at (503) 494-7887. They do not have to join this or any research 
study. If participants do join, and later change their mind, they may quit at any time. If they refuse to join or 
withdraw early from the study, there will be no penalty or loss of any benefits to which they are otherwise 
entitled.  
 
Participants health care provider may be one of the investigators of this research study, and as an investigator 
is interested in both their clinical welfare and in the conduct of this study. Before entering this study or at any 
time during the research, participants may ask for a second opinion about their care from another doctor who is 
in no way involved in this project. Participants do not have to be in any research study offered by participants 
physician.  
 

 
Version Date: 1/14/2025