SCH: A personalized wearable rehabilitation sensing system for stroke survivors

In the United States, there are about 800,000 people per year suffering a cerebral stroke, and the associated
cost is about $33 billion per year. Stroke is also a leading cause of disability, and most stroke survivors exhibit
persistent motor impairments despite extensive rehabilitation after the stroke. As a result, independent living
and return to the work force is limited in a majority of stroke survivors. A majority of stroke survivors exhibit
upper and lower limb motor impairments, ranging from incapability of reaching and grasping objects to limited
ambulation. Despite extensive rehabilitation therapy in the clinic, these persistent impairments still severely
limit independent living, partly because the training effect in the clinical setting is not effectively transferred
to activities of daily living (ADL). Furthermore, the inability to perform essential daily functions at the chronic
stage can further exacerbate the impairment, due to limb disuse and/or maladaptation of the neuromuscular
system. We hypothesize that a continuous rehabilitation training that is integrated into community living (e.g.,
at home, in the shopping mall, or at the park) can capitalize the clinic rehabilitation effect and enhance daily
functions of stroke survivors.
The goal of this project is to develop a personalized community-based rehabilitation sensing system to
improve daily functions of these individuals. Thus, our proposal directly addresses the NICHD scientific
research theme 5: Advancing Safe and Effective Therapeutics and Devices for People with Disabilities. We
seek a truly wearable system that is comfortable to wear, low power in operation, and friendly to use (e.g.,
via smartphones). The system will include three essential components: a nanomaterial-enabled multimodal
wearable sensor network to monitor arm and leg functional activities; a low-power data acquisition,
processing, and transmission protocol; and a smart phone APP to communicate training outcomes to the
users and clinicians via internet and receive feedback from them. Specifically, we propose the following aims.
Aim 1: To develop truly wearable sensor network that can monitor the physical activities involving the affected
and contralateral limbs of stroke survivors. Aim 2: To integrate the multi-modality sensing network into a
coherent system and efficiently communicate the sensor data. Aim 3: To extract prominent features from the
acquired motor activity information and provide personalized community rehabilitation guidance. Aim 4: To
evaluate the system performance and clinical feasibility.
RELEVANCE (See instructions):
The outcome of the proposed research could transform personalized rehabilitation of stroke survivors with a
truly wearable system for continuous rehabilitation at various community settings, which could enable tele-
rehabilitation, and maximize functional recovery of stroke survivors. Wearable physical activity tracking
promises a paradigm shift for healthcare and wellbeing. The user-friendly nature of our system can also
facilitate wide applications in other clinical populations with motor impairment.