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mStroke: Mobile Technology for Post-Stroke Recurrence Prevention and Recovery

mStroke：用于中风后复发预防和恢复的移动技术

基本信息

批准号：
8626740
负责人：
Nancy Lynn Tripp Fell
金额：
$ 38.47万
依托单位：
UNIVERSITY OF TENNESSEE CHATTANOOGA
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-05-01 至 2019-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8626740
关键词：
Acute Adult Algorithms Appointment Appointments and Schedules Assisted Living Facilities Biomedical Technology Caregivers Caring Clinical Clinical Trials Code Cognitive Collaborations Communication Communication impairment Computer software Data Data Analyses Data Compression Data Security Databases Development Devices Ensure Environment Equilibrium Foundations Functional disorder Gait Goals Health Health Insurance Portability and Accountability Act Health Personnel Health Professional Health Services Home environment Hospitals Immune Impairment Individual Inpatients Institution Instruction Intervention Knowledge Learning Left Leg Length of Stay Long-Term Care Measurement Measures Medical Mission Monitor Motion Motor Movement National Institute of Biomedical Imaging and Bioengineering Outcome Outpatients Patient Discharge Patient Monitoring Patients Phase Physical Rehabilitation Physical therapy Physicians Principal Investigator Process Public Health Recovery Recovery of Function Recurrence Registries Rehabilitation therapy Reporting Research Risk Assessment Secure Security Solid Speed Stream Stroke Stroke prevention Students Supervision Survivors System Techniques Technology Testing Time Training United States United States National Institutes of Health Visit Wireless Technology Yang acute stroke arm base cost data acquisition data exchange disability disorder later incidence prevention encryption fall risk follow-up graduate student improved motor control multidisciplinary outcome forecast post stroke public health relevance rehabilitation management sensor stroke recovery stroke rehabilitation tool transmission process treatment as usual undergraduate student usability

项目摘要

Research Summary 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.

研究综述我们的目标是开发一个智能系统，该系统将监测和评估运动控制，跌倒风险和步态速度中风后患者使用可穿戴蓝牙低功耗（BLE）设备。中风是导致成年人的残疾，住院护理和康复费用很高（2010年为540亿美元）。减少成本并最终改善卒中护理结果，需要随访数据将成功的与不成功的恢复，并确定最佳干预措施。然而，这一数据目前并不由于数据采集困难和缺乏集中式数据库，从急症护理医院出院我们提出的系统将评估中风后的恢复情况。患者离开医院后，将提供值得信赖的定制活动分析，统计解释，以支持卫生保健提供者提供更好的卫生服务，常规中风护理。我们的研究重点是开发一种实用、准确、安全有效因此，我们预计该系统将对中风产生重大影响康复（干预和研究）和患者的长期康复。我们建议的系统的意义：中风后的功能恢复通过运动和活动练习来增强。提供保健专业人士与患者特定的中风后运动和活动报告，除了那些直接观察，将促进处方的具体干预措施，并在长期内，优化患者复苏总之，我们的智能系统的好处有三个方面： 1)加强急性管理：中风后立即（例如，2-4日），当医生积极致力于实现患者的医疗稳定和开始身体康复，我们的智能系统可用于提供运动和活动信息，常规护理这将增强健康提供者对运动功能障碍程度的理解和支持处方的最佳急性中风康复设置。 2)加强急性康复：一旦患者从急性或康复医院出院，到家庭或辅助生活环境，我们的智能系统将提供客观的运动和活动健康信息中风后恢复的这一阶段通常由患者及其家属管理。护理人员偶尔进行专业指导（例如，家庭健康或门诊访问）。医生和治疗师将能够访问以前无法获得的实时数据，管理策略时，病人看到定期预约。 3)延长护理：在康复结束时，当治疗停止，医生预约，我们的智能系统将为医生提供以前无法获得的实时数据，由此可以触发医疗和/或康复干预以支持患者的最佳长期复苏该项目的具体目标是：目标1：高效的数据采集和可靠的数据传输目标2：自动运动控制评分、跌倒风险评估和步态速度测量目标3：健康数据安全目的4：证明mStroke的患者可用性和有效性学生参与：我们提出的智能系统提供了一个动态的学习环境，研究生。在PD/PI的监督下，学生将为实施提出的算法，并整合它们，以开发拟议的自动中风后评估工具。然后，学生将帮助收集测试数据和验证系统。这将同时介绍本科生和研究生的现实世界的挑战，并激发他们的机会，做研究，特别是在智能健康，物理治疗，数据分析，安全和数据领域压缩。