Robotic Apparel to Prevent Freezing of Gait in Parkinson Disease

NCT ID: NCT06602544

Last Updated: 2025-07-18

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Clinical Phase

NA

Total Enrollment

20 participants

Study Classification

INTERVENTIONAL

Study Start Date

2024-09-03

Study Completion Date

2027-09-30

Brief Summary

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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

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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 9-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.

Conditions

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Parkinson Disease (PD)

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Primary Study Purpose

TREATMENT

Blinding Strategy

NONE

Study Groups

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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

Group Type EXPERIMENTAL

Robotic Apparel

Intervention Type DEVICE

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.

Interventions

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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.

Intervention Type DEVICE

Eligibility Criteria

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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
Minimum Eligible Age

18 Years

Maximum Eligible Age

90 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Michael J Fox Foundation for Parkinson Research

UNKNOWN

Sponsor Role collaborator

Boston University

OTHER

Sponsor Role collaborator

Harvard Medical School (HMS and HSDM)

OTHER

Sponsor Role lead

Responsible Party

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Conor Walsh

Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Terry Ellis, PT, PhD

Role: PRINCIPAL_INVESTIGATOR

Boston University

Conor J Walsh, PhD

Role: PRINCIPAL_INVESTIGATOR

Harvard University

Locations

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Harvard Science and Engineering Complex

Allston, Massachusetts, United States

Site Status RECRUITING

Boston University Sargent College of Health and Rehabilitation Sciences

Boston, Massachusetts, United States

Site Status RECRUITING

Countries

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United States

Central Contacts

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Franchino Porciuncula, EdD, PT, DScPT

Role: CONTACT

617-353-7525

Teresa Baker, DPT

Role: CONTACT

617-353-7525

Facility Contacts

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Conor J Walsh, PhD

Role: primary

617-496-4269

Christina Lee, PhD

Role: backup

617-353-7525

Terry Ellis, PhD, PT, FAPTA

Role: primary

617-353-7525

Franchino Porciuncula, EdD, PT, DScPT

Role: backup

617-353-7525

References

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Ziegler K, Schroeteler F, Ceballos-Baumann AO, Fietzek UM. A new rating instrument to assess festination and freezing gait in Parkinsonian patients. Mov Disord. 2010 Jun 15;25(8):1012-8. doi: 10.1002/mds.22993.

Reference Type BACKGROUND
PMID: 20310009 (View on PubMed)

Ehgoetz Martens KA, Shine JM, Walton CC, Georgiades MJ, Gilat M, Hall JM, Muller AJ, Szeto JYY, Lewis SJG. Evidence for subtypes of freezing of gait in Parkinson's disease. Mov Disord. 2018 Jul;33(7):1174-1178. doi: 10.1002/mds.27417.

Reference Type BACKGROUND
PMID: 30153383 (View on PubMed)

Plotnik M, Giladi N, Hausdorff JM. Is freezing of gait in Parkinson's disease a result of multiple gait impairments? Implications for treatment. Parkinsons Dis. 2012;2012:459321. doi: 10.1155/2012/459321. Epub 2012 Jan 12.

Reference Type BACKGROUND
PMID: 22288021 (View on PubMed)

Nieuwboer A, Giladi N. Characterizing freezing of gait in Parkinson's disease: models of an episodic phenomenon. Mov Disord. 2013 Sep 15;28(11):1509-19. doi: 10.1002/mds.25683.

Reference Type BACKGROUND
PMID: 24132839 (View on PubMed)

Alice N, Fabienne C, Anne-Marie W, Kaat D. Does freezing in Parkinson's disease change limb coordination? A kinematic analysis. J Neurol. 2007 Sep;254(9):1268-77. doi: 10.1007/s00415-006-0514-3. Epub 2007 Apr 2.

Reference Type BACKGROUND
PMID: 17401738 (View on PubMed)

Nieuwboer A, Dom R, De Weerdt W, Desloovere K, Fieuws S, Broens-Kaucsik E. Abnormalities of the spatiotemporal characteristics of gait at the onset of freezing in Parkinson's disease. Mov Disord. 2001 Nov;16(6):1066-75. doi: 10.1002/mds.1206.

Reference Type BACKGROUND
PMID: 11748737 (View on PubMed)

Hausdorff JM, Schaafsma JD, Balash Y, Bartels AL, Gurevich T, Giladi N. Impaired regulation of stride variability in Parkinson's disease subjects with freezing of gait. Exp Brain Res. 2003 Mar;149(2):187-94. doi: 10.1007/s00221-002-1354-8. Epub 2003 Jan 22.

Reference Type BACKGROUND
PMID: 12610686 (View on PubMed)

Siviy C, Baker LM, Quinlivan BT, Porciuncula F, Swaminathan K, Awad LN, Walsh CJ. Opportunities and challenges in the development of exoskeletons for locomotor assistance. Nat Biomed Eng. 2023 Apr;7(4):456-472. doi: 10.1038/s41551-022-00984-1. Epub 2022 Dec 22.

Reference Type BACKGROUND
PMID: 36550303 (View on PubMed)

Macht M, Kaussner Y, Moller JC, Stiasny-Kolster K, Eggert KM, Kruger HP, Ellgring H. Predictors of freezing in Parkinson's disease: a survey of 6,620 patients. Mov Disord. 2007 May 15;22(7):953-6. doi: 10.1002/mds.21458.

Reference Type BACKGROUND
PMID: 17377927 (View on PubMed)

Nutt JG, Bloem BR, Giladi N, Hallett M, Horak FB, Nieuwboer A. Freezing of gait: moving forward on a mysterious clinical phenomenon. Lancet Neurol. 2011 Aug;10(8):734-44. doi: 10.1016/S1474-4422(11)70143-0.

Reference Type BACKGROUND
PMID: 21777828 (View on PubMed)

Jacobs JV, Nutt JG, Carlson-Kuhta P, Stephens M, Horak FB. Knee trembling during freezing of gait represents multiple anticipatory postural adjustments. Exp Neurol. 2009 Feb;215(2):334-41. doi: 10.1016/j.expneurol.2008.10.019. Epub 2008 Nov 12.

Reference Type BACKGROUND
PMID: 19061889 (View on PubMed)

Mancini M, Shah VV, Stuart S, Curtze C, Horak FB, Safarpour D, Nutt JG. Measuring freezing of gait during daily-life: an open-source, wearable sensors approach. J Neuroeng Rehabil. 2021 Jan 4;18(1):1. doi: 10.1186/s12984-020-00774-3.

Reference Type BACKGROUND
PMID: 33397401 (View on PubMed)

Other Identifiers

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024589

Identifier Type: OTHER_GRANT

Identifier Source: secondary_id

IRB#24-0986

Identifier Type: -

Identifier Source: org_study_id

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