Purpose

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.

Condition

Eligibility

Eligible Ages
Between 18 Years and 90 Years
Eligible Genders
All
Accepts Healthy Volunteers
No

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

Study Design

Phase
N/A
Study Type
Interventional
Allocation
N/A
Intervention Model
Single Group Assignment
Primary Purpose
Treatment
Masking
None (Open Label)

Arm Groups

ArmDescriptionAssigned Intervention
Experimental
Multi-visit ambulatory activities with soft robotic apparel
Participants will engage in ambulatory activities (i.e. straight-line walking, turning) with and without the assistance of robotic apparel, performed across multiple visits under various freezing-of-gait (FoG) provoking scenarios
  • Device: Robotic Apparel
    A robotic apparel system is a portable, lightweight textile-based wearable robot that is worn around the waist and thighs. The apparel provides assistive flexion moment about the hip joint during the swing phase of gait by spooling in a cable that connects the thigh wraps to the front of the waist belt. Inertial measurement units embedded in the thigh wraps are used to control the timing of the robotic apparel assistance. Robotic apparel assistance magnitude is delivered as a small percentage of the bodyweight of the wearer.

Recruiting Locations

Boston University Sargent College of Health and Rehabilitation Sciences
Boston, Massachusetts 02215
Contact:
Terry Ellis, PhD, PT, FAPTA
617-353-7525
tellis@bu.edu

More Details

Status
Recruiting
Sponsor
Harvard Medical School (HMS and HSDM)

Study Contact

Franchino Porciuncula, EdD, PT, DScPT
617-353-7525
fporciun@bu.edu

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.

Notice

Study information shown on this site is derived from ClinicalTrials.gov (a public registry operated by the National Institutes of Health). The listing of studies provided is not certain to be all studies for which you might be eligible. Furthermore, study eligibility requirements can be difficult to understand and may change over time, so it is wise to speak with your medical care provider and individual research study teams when making decisions related to participation.