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.
Parkinson Disease (PD)
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.
Robotic Apparel to Prevent Freezing of Gait in Parkinson Disease
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Harvard Science and Engineering Complex, Allston, Massachusetts, United States, 02134
Boston University Sargent College of Health and Rehabilitation Sciences, Boston, Massachusetts, United States, 02215
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18 Years to 90 Years
ALL
No
Harvard Medical School (HMS and HSDM),
Terry Ellis, PT, PhD, PRINCIPAL_INVESTIGATOR, Boston University
Conor J Walsh, PhD, PRINCIPAL_INVESTIGATOR, Harvard University
2027-09