User-Independent Intent Recognition on a Powered Transfemoral Prosthesis
Phase: NA
Conditions: Amputation
Sponsor: Georgia Institute of Technology

Title: User‐Independent Intent Recognition on a Powered Transfemoral Prosthesis   
 
NCT #: NCT05537792 
 
Document Date: 08/06/2024 
 
 
 
Protocol and Statistical Analysis Plan 

1. 
Study Aim, Background and Design 
The primary scientific challenge that this research aims to address is to accurately 
decode user intent and apply this information to improve control of powered prostheses. 
The fundamental challenge is to allow users to intuitively control a robotic assistive device 
by applying wearable sensing technology either in the device or on the user.  This is an 
especially significant research challenge now that advanced mechatronic prosthetic devices 
have come onto the clinical market and are actively being developed by different research 
and industry groups. These devices have vast potential to help improve the lives of 
individuals with a major lower limb amputation, but control systems for such devices need 
significant improvement [1], [2]. A smart and reliable control interface greatly enhances the 
user experience in any enterprise and is especially important for controlling complicated 
mechatronic assistive devices. Users may abandon or under-utilize the technology if the 
interface between the user and the device—the control system—does not function in an 
intuitive manner that is safe and convenient for them to use. This proposed research focuses 
on bridging this important gap. 
It is important to further develop prosthetic control technology because of the large 
impact new technology can have on health outcomes for their potential users. Prosthetic 
technology is useful to individuals who have suffered from a major lower limb amputation 
which affects over 650,000 people in the United States [3]. These amputations cause 
significant disability and decreased quality of life [4]. It results in asymmetric gait that is 
energetically unfavorable [5] and slower self-selected walking speeds [6] compared to non-
amputees.  These impairments are due to a variety of reasons such as trauma, disease 
condition (such as diabetes), congenital limb deficiency, and cancer. There is a critical need 
for improving the walking capabilities of individuals who have suffered a lower limb 
amputation to increase their community mobility, independence and ultimately their quality 
of life.  
New and exciting advances have been made on integrating microcomputers, 
sensors and actuators in mechanical devices to augment lower limb prosthetic technology 
to solve this need [7], [8]. These devices can help patients reduce their metabolic energy 
expenditure [9] and traverse more difficult terrain that is often encountered in community 
ambulation such as slopes, curbs, uneven ground, and stairs. A gap of commercial systems 
is a lack of sophisticated and robust intent recognition. They instead often rely on the user 
either using a key fob or performing a set of unintuitive movements unrelated to the 
movement itself (such as rocking back and forth on the prosthesis) to transition between 
different modes of operation. Powered prostheses would benefit greatly from an enhanced 
intent recognition system that seamlessly, automatically, and naturally transitions the device 
between different modes based on the user’s desired activity. Our goal is to develop and 
evaluate such an intent recognition system that is ready to be deployed in the field on state-
of-the-art powered prostheses. These systems can help improve clinically meaningful 
outcomes in amputee patients including reducing their metabolic cost of walking and 
increasing their preferred ambulation speed. Additionally, the ability to traverse different 
terrains more effectively will help improve their community ambulation capability and overall 
independence as these are commonly encountered outside the home.  

One solution that we have previously used to perform intent recognition is to use 
advanced pattern recognition technology from the machine learning community. Pattern 
recognition techniques are advantageous because they allow users to be able to seamlessly 
and automatically shift between modes without having to stop and press buttons on a key 
fob or perform an unintuitive movement. Instead, we can design a system that recognizes 
the patterns of sensor information that are generated when humans move and predict a 
person’s movement flow to optimally control both the timing and magnitude of power 
generation or absorption during movement. One of our previous accomplishments – 
published in IEEE Transactions on Neural Systems and Rehabilitation – demonstrated that 
by training pattern recognition systems with transitions between different modes improved 
the accuracy compared to previous studies from 84.5% to 93.9% [10] . 
Several leading edge laboratories have studied pattern recognition techniques to 
improve intent recognition [10]–[13] – including our own previous work – but a significant 
drawback to these systems are that they are highly user-specific and rely on acquiring large 
amounts of training data from each subject. Part of this project will focus on developing a 
user interface that does not need user dependent training data. Voice recognition software 
previously required users to train the system with their own voice commands and only a 
relatively small number of people used it. In contrast, state-of-the-art voice recognition 
software used in cell phones today does not require any user dependent training and is 
widely adopted. Similarly, intent recognition systems for prostheses must innovate and 
provide intent recognition systems that require minimal user specific training so that patients 
will be willing to use them. We propose to do this through novel sensing technology, smarter 
algorithms, and adapting to each individual user’s patterns. We need an innovative 
approach to achieve an intent recognition system that can be quickly applied to different 
users without hours of training time or the need for user specific recalibration. A broad goal 
of this project is to develop signal processing techniques and novel pattern recognition 
algorithms to enable user-independent intent recognition for powered lower limb 
prostheses. We will implement a novel adaptation algorithm that will adapt our intention 
recognition system to new individuals and provide speed-variable prosthetic assistance – 
eliminating the need to for any user dependent training. These algorithms will be 
implemented on the Open Source Leg (OSL) powered prosthesis, which was designed by 
collaborator Dr. Elliott Rouse [14]. A minimum group of ten individuals who use a prosthetic 
knee and foot in their clinically prescribed prosthesis will be trained on the powered leg and 
will complete the experiment. We will compare the accuracy of the intent recognition 
systems in walking speed estimation and also measure other clinically meaningful 
parameters including self-selected walking speed and relevant biomechanics. We expect 
adapted systems to exhibit advantages in walking speed estimation error compared to non-
adapted systems and provide appropriate powered response for each walking speed during 
treadmill and overground walking. 
 
2. Participant population 
Subjects must fit into one of two categories stated in the study design section: able 
bodied individuals, and disabled individuals/amputees. Disabled individuals are considered 

part of a vulnerable population. This group will be protected through the use of safety 
equipment such as hand rails and a safety harness for the case of stumbles and falls. The 
goal is to collect data from at least 10-15 participants from the amputee population.  
Participants will be between 18-75 years old. Inclusion criteria includes subjects 
must be between 18-75 years of age, use a prosthetic knee and foot in their clinically 
prescribed prosthesis (except for the able bodied subjects). Subjects must be at K3 or K4 
ambulatory level according to the Medicare/Medicaid designation as the study requires 
subjects to walk, ascend/descent stairs and ascend/descend ramps. Subjects will be 
excluded if they have any history of a neurological injury, gait pathology, or a cardiovascular 
condition that would limit their ability to ambulate for multiple hours during the experimental 
sessions. Pregnant subjects will also be excluded to the risk of a fall during the experiment. 
All participants that meet the appropriate criteria will be recruited through official 
flyers and verbal scripts, even if they are already known to the researchers. Flyers will be 
posted around the campus of Georgia Institute of Technology, in designated advertising 
areas. Additionally, word of mouth recruiting will use a script with similar language as the 
flyers. Recruiting materials are attached as separate documents including a flyer and e-mail 
script. Permission will be obtained from participants before using any information for 
research purposes that has individual identifiers attached. 
 
3. Study Procedures 
This will be a single-visit study. If participants are not able to complete the study 
during their first visit, they will be asked to return. All testing will take place at the Georgia 
Tech Manufacturing Institute (GTMI) at the Georgia Institute of Technology. Testing will last 
between 2-3 hours with no more than 30 minutes of continuous movement and visits will be 
scheduled at the convenience of the participants. 
Able bodied individuals may be fitted with a commercialized assistive walking 
device, iWALK (user manual attached as separate document), that has been adapted in 
order to be used with the prosthetic device. This is to ensure controllers are functioning 
before a subject comes in and walks on the prosthetic device. During all testing participants 
are instructed to vocalize any concerns or discomfort to researchers. At any time if 
participants are uncomfortable, they have the right to quit the study with no penalty. The 
first visit will last no longer than 4 hours. If the participant obliges, they will be asked to return 
for additional visits, scheduled at their convenience. During additional visits, human 
participants will be asked to perform typical tasks such as standing, sitting, or walking, in a 
safe and monitored environment. Tests will begin on a treadmill with a security harness and 
or gait belt, based on the level of comfort of the participant. If the participant feels 
comfortable, testing will be moved from the treadmill to the floor for supported and then 
freestanding walking. Another type of treadmill is a force-instrumented treadmill 
incorporated into the Computer Assisted Rehabilitation Environment (CAREN).  This 
treadmill is embedded in a large platform that is able to move in six degrees of freedom, 
allowing the application of disturbances during standing or walking by moving the platform.  
During all types of testing in which subjects are asked to respond to environmental 
disturbances, they will be required to wear a safety harness. During tests, verbal feedback 

from the participants will be used to improve the comfort of the devices. Participants are 
instructed to notify researchers if they feel unsafe, and may quit the study at any time without 
penalty. Testing will first be conducted on able-bodied individuals until the PI feels that it is 
safe to transition to disabled individuals/amputees. Testing with disabled individuals will only 
occur after initial tests can be run without functional errors involving either hardware or 
software. Once the software and control system of the devices are thoroughly tested on 
able bodied users the optimized device be used for testing with disabled individuals. 
Additionally, participants may be asked to wear EMG sensors, markers for measuring 
biomechanics, other mechanical sensors (such as IMUs) and a metabolic mask. One of the 
metabolic masks and heart rate monitor comprise an FDA approved metabolic system 
called the COSMED Fitmate Pro. Another type of a metabolic measurement system may be 
used such as the ParvoMedics TrueOne 2400 metabolic cart. The Fitmate Pro or ParvoMedics 
system will be demonstrated to the participant, after which they will choose whether or not 
they are willing to use this system. All participants will be guided through the following 
general procedure during their visits, requiring action on their part: 
● Participants will be briefed about the details of and their rights during the study. 
● The prosthetic and attachment interface will be fit to the participant, along with any 
additional data collection equipment. 
● Participants will be guided through the specific activities of the study, detailed 
already. 
● Participants will receive assistance removing any hardware used during the study. 
 
Other equipment may be utilized to measure biomechanics of the user during ambulation. 
Specifically, we will be using a VICON motion capture analysis system. This will also us to 
measure biomechanical similarities and differences while using the powered prosthesis 
compared to the sound side limb. Also, some protocols will require the use of an EMG 
(electromyography) system to measure muscle activity across different ambulation tasks. 
Three systems may be used which includes the Delsys Trigno Wireless EMG system, 
Biometrics Ltd. EMG system, and COAPT EMG system. All of these systems will use 
electromyography sensors that will be placed on the surface of the user’s skin. 
In order to also measure functional clinical measures, a Protokinetics gait mat will 
be utilized to measure common measures such as step length, step time, and symmetry. 
This system is just a mat that users will need to walk on top similar to walking overground. 
Users will be in a harness and have the options for handrails or gait belt if needed.  
Throughout the tests there will be a camera recording the session. The purpose of 
the camera is to record performance for future analysis. The participant will always have the 
right to stop the test and/or take a break. The participant may also choose to discontinue 
participation at any time. 
This study will ask participants to walk on treadmill and overground settings to adapt 
pre-trained (baseline) walking speed estimation machine learning (ML) models to user-
specific data. The adaptation pipeline self-labels and updates models with user data in real-
time. We explore two methods of self-labeling referred to as Direct Integration (DI) and 
Ground Truth (GT). DI computes walking speed labels using heel-to-heel foot 

displacements measured by a foot inertial measurement unit (IMU). GT provides labels that 
are the true treadmill speed (for treadmill trials) or center-of-mass speed (for overground 
trials). Treadmill speed profiles follow either a staircase profile (P1) or a triangular profile 
(P2). Overground walking is constrained to a 5-meter straight path between two cones. 
Adapted models are renamed based on the environment (P1, P2, or OVG) and labeling 
method (DI or GT) used. Models are evaluated on how well they can estimate the current 
speed (forward estimation). Additionally, we provide biomimetic assistance that scales with 
estimated walking speed. 
 
4. Statistical Analysis Plan 
A repeated measures ANOVA will be conducted to examine the impact of different 
forward estimators on the real-time forward estimation error, which served as the dependent 
variable. In this analysis, the forward estimator functioned as the intra-subject factor, with 
multiple measurements taken for each subject across different conditions. Instances of 
significant differences were further explored using Tukey's Honesty Significant Difference 
test to conduct detailed comparisons between specific groups. Paired t-tests were used to 
compare the offline forward estimation error of each adapted forward estimator with the 
baseline during overground walking. The error served as the dependent variable in these 
analyses. 
 
5. Research Risks 
The main risk of the study is a possible fall. Each participant will be given ample time 
to get accustomed to using the devices. This adjustment period will involve getting used to 
balancing with the given device or control method. In this adjustment period, participants 
run the highest risk of falling. However, to manage this risk, there will be rails around the 
treadmill at all times, which the user may hold to prevent falls. Based on the participant's 
comfort, there are varying levels of additional treadmill support or padding. After the 
adjustment period, if the participant is comfortable enough for freestanding walking there 
will be spotters next to them at all times. When testing the prosthetic, there is an additional 
risk of irritation caused by the method of attachment. The level of risk varies depending on 
the walking style and skin sensitivity of the participant. To reduce the likelihood of irritation, 
amputees will use their own prosthetic socket and non-amputees will use a commercial 
assistive walking device. The instruction manual for the commercialized assistive walking 
device (iWALK) is attached as a separate document.  
Participants are strongly encouraged to vocalize any discomfort to try and prevent 
irritation from occurring. If irritation does occur, brief medical care in the form of disinfectant 
wipes and/or a Band-Aid will be provided. In the unlikely event of an irritation too severe for 
a Band-Aid, the participant will be referred to a physician. Any adverse events will be 
reported to ORIA within the regulated time frame. If the metabolic system is used by the 
participant, there are slight risks associated with the system. They include transmission of 
communicable 
diseases, 
aspiration 
of 
contaminants, 
irritation 
from 
wear, 
choking/strangulation, and discomfort. To protect against infection, the mask and monitor 
will be properly disinfected between uses, and will always be handled with disposable 

sanitary gloves. Also, antibacterial filters will always be used with the metabolic mask to 
prevent aspiration of contaminants.  
To prevent irritation subjects are strongly encouraged to notify a researcher if they 
feel pain or discomfort. Careful attention will be paid to the position of the chords, to avoid 
entanglement and possible choking or strangulation. Verbal communication is strongly 
encouraged throughout testing to act as a preventative measure for discomfort. General 
risks associated with testing any electrical device include fire and electrical shock. These 
risks will be avoided by keeping the device away from water or open flame sources. 
Researchers will always be vigilant about the conditions of the testing environment. 
General risks associated with testing any electrical device include fire and electrical 
shock. These risks will be avoided by keeping the device away from water or open flame 
sources. Researchers will always be vigilant about the conditions of the testing environment. 
No undue psychological risks are anticipated during this study, and volunteers retain the 
ability to stop testing at any point. Privacy will be maintained during testing via an enclosed 
indoor testing environment by monitoring the perimeter for unauthorized personal; no 
significant privacy risks are anticipated. 
 
6. Confidentiality 
Participants will sign a consent form before participating which explains that no 
identifiers linking them to this study will be included in any sort of report that might be 
published except for the video taken. Participant faces will be blocked out upon request. 
They will be given a pseudonym different from their own name that will be referred to in 
studies published, if at all. Participants will be assured in the informed consent that the data 
will be used only for studies that are consistent with the original research purpose. 
This consent form will be filed securely in an official area. People who have access 
to information include the Principal Investigators and research study personnel. 
Representatives of regulatory agencies such as the Office of Human Research Protections 
(OHRP), the Food and Drug Administration, the DoD, and entities such as the Georgia Tech 
Office of Research Integrity Assurance may access participant records to make sure the 
study is being run correctly and that information is collected properly. 
Information about participants related to this study will be kept confidential to the 
extent permitted or required by law. 
When the data is stored, it will no longer be linked to the subject's personal 
information. There will be a master list stored separately that connects the subject identifiers 
with their personal information, for when they need to be contacted. The data will be kept 
on the computers of the research personnel only. These computers will all be password 
protected to prevent nonauthorized access to the data. Data will be transmitted 
electronically between researchers. The master list of subjects and their personal 
information will not be transmitted in any form between researchers. This master list will 
only be in the possession of the PI and researcher responsible for recruiting. It will not be 
shared with anyone else in any way. 
 
7. Benefits 

The goal of this research is to improve upon the existing design processes of 
prostheses and exoskeletons for the future, and there are no foreseen direct benefits from 
this study. Participation in these tests may help any person that may someday need or want 
one of these devices. These tests will not benefit participants personally unless they intend 
to use these types of devices in the future. 
 
8. Compensation 
We will compensate amputees at a rate of $25/hour (rounded to the next full hour). 
Subjects will be given the choice of compensation via check which will be issued through 
USPS mail to a home (or a provided) mailing address or a gift card which will provided at 
the end of each visit to the lab. 
9. Costs 
There are no direct costs to study participants. The costs to participants for this study 
will most likely be only their time and energy. Participants will be responsible for covering 
any unforeseen costs including, but not limited to, transportation to the research location, 
parking expenses, food, or child care. 
 
10. Alternatives 
Participants are informed that participation in this study is voluntary. It is made clear 
that they have the right to change their mind and leave the study at any time without giving 
any reason and without penalty. Any new information that may make participants change 
their minds about being in this study will be given to them. 
 
11. Consent/Assent Process and Documentation of Consent/Assent 
After being informed about the study through recruitment by way of flyers, e-mail or 
word of mouth, participants will be given a consent form outlining details about the study. 
The consent form provides detailed information about the study procedures. When reading 
through the consent form potential participants are encouraged to vocalize any questions 
they have including, but not limited to, inquiries about testing procedure, risks of the study 
and participant rights. Questions will be answered by the researcher personnel conducting 
the study. Participants will be given as much time as they need to make a decision about 
whether or not to participate. During this process, as well as throughout testing it will be 
made clear that participants may chooses to end the study at any time, no questions asked, 
and will not face any negative repercussions. Signing of the consent form will take place in 
person where researchers present will answer any questions then obtain their signatures. 
This consent form will be filed securely in an official area that can only be accessed by 
Principal Investigators of this study and research study personnel. Participants will be given 
a copy of this consent form and do not waive any legal rights by signing it. 
The only personal information we will collect is the participant's name, telephone, 
email, and contact information. This information will not be published in the research results, 
nor will it be used to perform data analysis. This information will also not influence the results 
of the research. We only collect this information so we can contact the participants and refer 
to them by their names during conversation. 

 
12. Investigator’s Qualifications 
The PI, Dr. Aaron Young, has conducted a number of experiments similar to this one 
with amputees. The devices will be designed using the same process that has proven 
successful for a wide variety of robotic and robotic assistive devices built by collaborator-PI 
Rouse’s Neurobionics Lab. The OSL device was manufactured in house at the Montgomery 
Machining Mall at Georgia Tech, The testing of this device was IRB approved previously at 
Georgia Tech with a similar protocol (H16351). A recent paper has been published on the 
design of the OSL device [14]. Additionally, all students listed on the IRB are members of 
the EPIC lab and are very familiar with the devices. All members listed on this IRB protocol 
have CITI training. 
 
13. Funding Sources 
This work is funded by the Department of Defense through the Congressional 
Directed Medical Research Program (CDMRP). The grant title is User-independent Intent 
Recognition on a Powered Transfemoral Prosthesis. None of the researchers involved in 
this study have conflict of interest. 
 

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