Research Project
10437974
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.
