We aim to develop a smart system, which will monitor and evaluate motor control, fall risk, and gait speed of patients post stroke using wearable Bluetooth Low-Energy (BLE) devices. Stroke, the leading cause of disability for adults, has a high cost in inpatient care and rehabilitation ($54 billion in 2010). To reduce the cost and ultimately improve stroke-care outcomes, follow-up data is required to correlate successful versus unsuccessful recovery and determine optimal interventions. However, this data is not currently available due to difficulties involved in data acquisition and lack of centralized databanks once patients are released from acute care hospitals. Our proposed system will evaluate recovery of post-stroke patients after they leave the hospital, and will provide trustworthy customized activity analysis and statistical interpretation to support health care providers in delivering improved health services beyond usual stroke care. Our research is focused on developing a smart system that is practical, accurate, secure, and effective. Thus, we anticipate that this system will have a significant impact on stroke rehabilitation (intervention and research) and patients'long-term recovery. Significance of Our Proposed System: Post stroke functional recovery is enhanced by movement and activity practice. Providing health care professionals with patient-specific post stroke movement and activity reports, beyond those directly observed, will facilitate prescription of specific interventions and, over the long term, optimize patient recovery. In summary, the benefits of our smart system have three folds: 1) Enhancing Acute Management: Immediately post stroke (e.g., 2-4 days), when physicians are actively engaged in achieving patients'medical stability and beginning physical rehabilitation, our smart system may be used to provide movement and activity information beyond that which is typically available in usual care. This will enhance health providers'understanding of the magnitude of movement dysfunction and support prescription of the optimal acute stroke rehabilitation setting. 2) Enhancing Acute Rehabilitation: Once patients are discharged from the acute or rehabilitation hospital to home or assisted living environments, our smart system will provide objective movement and activity health information. This phase of post stroke recovery is typically managed by patients and their caregivers with occasional professional guidance (e.g., home health or outpatient visits). Physicians and therapists will have access to previously unavailable real-time data, supporting efficient and effective management strategies when patients are seen in regularly scheduled appointments. 3) Extending Care: At the end of rehab, when therapy is discontinued and physician appointments are less frequent, our smart system will provide physicians with previously unavailable real-time data, whereby medical and/or rehabilitation intervention may be triggered to support patients'optimal long-term recovery.
The specific aims of this project are:
Aim 1 : Efficient Data Acquisition and Reliable Data Transmission Aim 2: Automated Motor Control Scoring, Fall Risk Assessment, and Gait Speed Measurements Aim 3: Health Data Security Aim 4: Demonstration of Patient Usability and Efficacy of mStroke Student Involvement: Our proposed smart system provides a dynamic learning environment for both undergraduate and graduate students. Under the supervision of PD/PIs, the students will contribute to implement the proposed algorithms and integrate them to develop the proposed automated post-stroke assessment tool. Then, students will help to collect the testing data and validate the system. This will introduce both undergraduate and graduate students to real-world challenges and excite them with the opportunity to do research, especially in fields of smart health, physical therapy, data analysis, security, and data compression.
The proposed research is relevant to public health because it is very promising to solve the major challenges and bottlenecks in effectively and securely track and evaluate activities of post-stroke patients in a remote and automatic way. Stroke is the leading cause of serious and long-term disability for adults in the United States. There is a distinct need to track the motor ability and activity of patients post stroke beyond the acute hospital setting. Our proposed research will lay a solid foundation for building a real-world high-impact application of managing stroke care. Hence, our research has great potential to contribute to the mission of NIBIB, which is to improve health by leading the development and accelerating the application of biomedical technologies.
| Cho, Jin S; Hu, Zhen; Fell, Nancy et al. (2017) Hospital Discharge Disposition of Stroke Patients in Tennessee. South Med J 110:594-600 |
| Williams, Brian; Allen, Brandon; Hu, Zhen et al. (2017) Real-Time Fall Risk Assessment Using Functional Reach Test. Int J Telemed Appl 2017:2042974 |
