Clinical trial NCT06602544: Robotic Apparel to Prevent Freezing of Gait in Parkinson Disease
Official title: Preventing Freezing of Gait in Parkinson's Disease Using Soft Robotic Apparel
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Parkinson Disease (PD)
Keywords: Parkinson Disease
Freezing-of-gait
Wearable Robot
Soft Robotics
Gait
Rehabilitation
Lead sponsor: Harvard Medical School (HMS and HSDM)
Sponsor class: OTHER
Collaborators: name: Michael J Fox Foundation for Parkinson Research
name: Boston University
First posted: 2024-09-19
Enrollment: 20
Sex: ALL
Minimum age (years): 18
Maximum age (years): 90
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Primary purpose: TREATMENT

Brief summary: Freezing-of-gait (FoG) in Parkinson Disease (PD) is one of the most vivid and disturbing gait phenomena in neurology. Often described by patients as a feeling of "feet getting glued to the floor," FoG is formally defined as a "brief, episodic absence or marked reduction of forward progression of the feet despite the intention to walk." This debilitating gait phenomena is very common in PD, occurring in up to 80% of individuals with severe PD. When FoG arrests walking, serious consequences can occur such as loss of balance, falls, injurious events, consequent fear of falling, and increased hospitalization. Wearable robots are capable of augmenting spatiotemporal gait mechanics and are emerging as viable solutions for locomotor assistance in various neurological populations. For the proposed study, our goal is to understand how low force mechanical assistance from soft robotic apparel can best mitigate gait decline preceding a freezing episode and subsequent onset of FoG by improving spatial (e.g. stride length) and temporal features (e.g. stride time variability) of walking. We hypothesize that the ongoing gait-preserving effects can essentially minimize the accumulation of motor errors that lead to FoG. Importantly, the autonomous assistance provided by the wearable robot circumvents the need for cognitive or attentional resources, thereby minimizing risks for overloading the cognitive systems -- a known trigger for FoG, thus enhancing the repeatability and robustness of FoG-preventing effects.

Detailed description: Wearable robots are capable of augmenting spatiotemporal gait mechanics and are emerging as viable solutions for locomotor assistance in various neurological populations. Given the breakdown of spatiotemporal gait parameters prior to onset of FoG, we aim to understand how the use of mechanical assistance from a soft robotic apparel can best mitigate gait decline preceding a freezing episode, and subsequent onset of FoG through a multi-day proof-of-concept study. In Aim 1, we will determine the biomechanical mechanisms underpinning the effects of robotic apparel on FoG. We posit that robotic apparel will prevent FoG by supporting natural gait biomechanics and reducing motor errors and gait degradation (i.e., increase stride length, decrease stride variability) known to precede freezing. In Aim 2, we will quantify the impact of robotic apparel in preventing FoG in PD under a variety of walking conditions in a series of controlled laboratory-based experiments. We hypothesize that robotic apparel will be effective in preventing FoG as evidenced by lower percent time spent freezing and lower FoG severity ratio scores (IMU data, video annotation) during walking and turning, resulting in farther walking distances (2-Minute Walk Test) compared to unassisted walking, repeatable across days of testing. Additionally, we hypothesize that robotic apparel will be effective in preventing FoG across various walking contexts (i.e., walking in open spaces, turning, dual-tasking and medication on/off). In Aim 3, we will examine proof-of-concept of robotic apparel to prevent FoG in the home/community during walking, under FoG provoking conditions. We hypothesize that robotic apparel will be effective in preventing FoG, compared to unassisted walking, as evidenced by lower percent time spent freezing and lower FoG severity ratio scores (IMU data, video annotation) during walking in the home/community, including conditions that trigger FoG (e.g., personalized FoG "hotspots).

The study will utilize a soft robotic apparel that has previously shown to demonstrate robust, gait-preserving benefits and FoG prevention in a single-subject repeated measures case study. To examine the effectiveness of the intervention using our robotic apparel, this 8-visit study will collect data on amount of time spent freezing, spatiotemporal gait measures, clinical measures, and patient perspectives on the device during different standardized assessments and freeze-provoking activities across multiple environments (i.e. home, lab) and medication states (on, relative off) with and without the robotic apparel assistance.

Eligibility criteria: Inclusion Criteria:

* 18-90 years old
* Self-reported Freezing of Gait due to PD
* Score of 21 or higher on the cognitive screening test (Montreal Cognitive Assessment Score (MoCA))
* Independent ambulation (with or without an assistive device, no physical assistance) for at least 20 meters
* Able to understand, communicate, and be understood by study staff
* Provide HIPAA Authorization to allow communication with the participant's treating physician/provider for medical clearance (if deemed necessary by study clinical team) to verify self-reported medical history (if deemed necessary by study clinical team)
* Provide informed consent
* Ability to participate in 8 research study visits

Exclusion Criteria:

* More than 2 falls in the previous month, as a result of gait impairment (may enroll under clinician discretion)
* Major surgery in the last 6 months that interferes with walking (may enroll under clinician discretion)
* Gait deficits due to missing limbs
* Experience chronic pain that interferes with walking ability (may enroll under clinician discretion)
* Serious co-morbidities (unrelated to gait impairment) that may interfere with ability to participate in research (e.g. cardiovascular, neurological, skin, and vascular conditions such as acute, ongoing/unmanaged deep vein thrombosis)
* No observable freezing-of-gait

Primary outcomes:
measure: Change in percent time spent freezing
timeFrame: Visit 4 (within 6 months after enrollment)
measure: Change in percent time spent freezing
timeFrame: Visit 5 (within 6 months after enrollment)
measure: Change in percent time spent freezing
timeFrame: Visit 6 (within 6 months after enrollment)
measure: Change in percent time spent freezing
timeFrame: Visit 7 (within 6 months after enrollment)
measure: Change in percent time spent freezing
timeFrame: Visit 8 (within 6 months after enrollment)
measure: Change in stride length
timeFrame: Visit 4 (within 6 months after enrollment)
measure: Change in stride length
timeFrame: Visit 5 (within 6 months after enrollment)
measure: Change in stride length
timeFrame: Visit 6 (within 6 months after enrollment)
measure: Change in stride length
timeFrame: Visit 7 (within 6 months after enrollment)
measure: Change in stride length
timeFrame: Visit 8 (within 6 months after enrollment)
Secondary outcomes:
measure: Change in freezing-of-gait ratio
timeFrame: Visit 4 (within 6 months after enrollment)
measure: Change in freezing-of-gait ratio
timeFrame: Visit 5 (within 6 months after enrollment)
measure: Change in freezing-of-gait ratio
timeFrame: Visit 6 (within 6 months after enrollment)
measure: Change in freezing-of-gait ratio
timeFrame: Visit 7 (within 6 months after enrollment)
measure: Change in freezing-of-gait ratio
timeFrame: Visit 8 (within 6 months after enrollment)
measure: Change in 2-Minute Walk Test Distance
timeFrame: Visit 5 (within 6 months after enrollment)
measure: Change in 2-Minute Walk Test Distance
timeFrame: Visit 6 (within 6 months after enrollment)
measure: Change in 2-Minute Walk Test Distance
timeFrame: Visit 7 (within 6 months after enrollment)
measure: Change in 2-Minute Walk Test Distance
timeFrame: Visit 8 (within 6 months after enrollment)
measure: Change in range of motion
timeFrame: Visit 4 (within 6 months after enrollment)
measure: Change in cadence
timeFrame: Visit 4 (within 6 months after enrollment)
measure: Change in cadence
timeFrame: Visit 5 (within 6 months after enrollment)
measure: Change in cadence
timeFrame: Visit 6 (within 6 months after enrollment)
measure: Change in cadence
timeFrame: Visit 7 (within 6 months after enrollment)
measure: Change in cadence
timeFrame: Visit 8 (within 6 months after enrollment)
measure: Change in stride time variability
timeFrame: Visit 4 (within 6 months after enrollment)
measure: Change in stride time variability
timeFrame: Visit 5 (within 6 months after enrollment)
measure: Change in stride time variability
timeFrame: Visit 6 (within 6 months after enrollment)
measure: Change in stride time variability
timeFrame: Visit 7 (within 6 months after enrollment)
measure: Change in stride time variability
timeFrame: Visit 8 (within 6 months after enrollment)
measure: Change in peak foot-to-floor angle
timeFrame: Visit 4 (within 6 months after enrollment)
Other outcomes:
Locations:
city: Allston
country: United States
facility: Harvard Science and Engineering Complex
state: Massachusetts
city: Boston
country: United States
facility: Boston University Sargent College of Health and Rehabilitation Sciences
state: Massachusetts
Study officials:
affiliation: Boston University
name: Terry Ellis, PT, PhD
role: PRINCIPAL_INVESTIGATOR
affiliation: Harvard University
name: Conor J Walsh, PhD
role: PRINCIPAL_INVESTIGATOR
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