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

研究总结 我们的目标是开发一个智能系统，它将监测和评估运动控制、摔倒风险和步态速度 中风后使用可穿戴蓝牙低能量(BLE)设备的患者。中风，中风的主要原因 针对成年人的残疾，住院护理和康复费用很高(2010年为540亿美元)。以减少 成本和最终改善中风护理结果，需要随访数据来关联成功 与不成功恢复的对比，并确定最佳干预措施。但是，此数据当前不是 由于患者一旦遇到数据采集困难且缺乏集中数据库而可用 已从急救医院出院。我们建议的系统将评估中风后的恢复情况 患者出院后，并将提供值得信赖的定制活动分析和 统计解释，以支持医疗保健提供者提供更好的医疗服务 常规的中风护理。我们的研究重点是开发一种实用、准确、 安全、有效。因此，我们预计这一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： 通过运动和活动练习促进中风后的功能恢复。提供医疗保健 具有特定于患者的中风后运动和活动报告的专业人员，而不是直接 观察，将促进特定干预措施的处方，并从长远来看，优化患者 恢复。总而言之，我们的智能系统的好处有三个方面： 1)加强急诊处理：中风后立即(如2-4天)，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 可以用来提供运动和活动信息，而不是 照常照看。这将加强卫生保健提供者对运动障碍的严重程度的了解 支持处方的最佳急性卒中康复设置。 2)加强急性康复：一旦患者从急诊或康复医院出院 对于居家或辅助生活环境，我们的智能系统将提供客观的运动和活动 健康信息。中风后康复的这一阶段通常由患者和他们的 偶尔接受专业指导的照顾者(例如，家庭健康或门诊)。医生和 治疗师将可以访问以前无法获得的实时数据，从而支持高效和有效 定期预约看病时的管理策略。 3)延长护理：在康复结束时，停止治疗，预约医生 不那么频繁的是，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 恢复。 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：医疗数据安全 目标4：演示mStroke的患者可用性和有效性 学生参与： 我们建议的智能系统为本科生和学生提供一个动态的学习环境 研究生。在PD/PIS的监督下，学生将为实施 提出的算法，并将它们集成起来，开发出所提出的中风后自动评估工具。 然后，学生将帮助收集测试数据并验证系统。这将引入两个 本科生和研究生面对现实世界的挑战，并用机会激发他们做 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。

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.