I-Corps: Mobile, Smart Gait Assessment System

这个i-Corps项目的更广泛的影响/商业潜力是一个移动的智能步态评估系统的产品，该系统允许在临床环境之外连续监测步态，该系统可用于包括帕金森病(PD)在内的步态障碍患者的在线远程临床管理。仅帕金森病就影响了美国100多万人，这个数字每年增加6万人。这项技术将通过跌倒跟踪和预防来支持预防再次入院，通过允许在家中监控疾病进展来减少住院次数和住院时间，实施受监控的健康计划，通过模式识别区分疾病类型，并通过跟踪介入结果提供及时和高效的临床管理。耐心的客户将受益于收到关于步态和姿势习惯的建议，从而减少摔倒的发生。此外，他们还将从活动监测中受益，因为他们会收到关于锻炼常规的建议，这已被证明可以增进健康和健身。另一方面，诊所和医院将受益于减少其设施中的病人数量，保险机构将受益于减少病人的住院时间。I-Corps项目提出了一种能够检测运动学和运动学步态参数之间不对称性的系统，该系统由嵌入式惯性测量单元和带有压阻式压力传感器阵列的鞋垫组成。利用机器学习算法，该系统可以检测和分类疾病进展，这将支持治疗修改以及正常的病程和症状变化。这种用于疾病预后的智能、非侵入性、非药物方法也可能导致更多的人参与临床试验，因为所需的低风险参与可能会鼓励患有和没有帕金森病的人参与。这项开发的技术允许在临床环境之外连续记录步态。这种智能的无线步态监测系统有可能减轻与众多诊所就诊相关的负担。智能的优点在于使用新兴技术，包括云计算和人工智能，用于特征提取、分类和罕见事件检测。这些功能将支持医疗专业人员从早期阶段就治疗过程做出决策，而不必为他们本已繁忙的日程增加更多努力。此外，设计的物联网(IoT)架构将允许移动健康监测，包括治疗依从性和治疗改善分类。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project is the product of a mobile, smart gait assessment system allowing for continuous gait monitoring outside the clinical settings, which can be used for online, remote clinical management for patients with gait disorders including patients with Parkinson Disease (PD). PD alone affects over one million people in the United States, a number that increases by 60,000 each year. This technology will support the prevention of re-admission by fall tracking and prevention, lower hospital visits and length of stay by allowing at-home monitoring of disease progression, implement monitored wellness programs, differentiate disease types by pattern recognition, and provide timely and efficient clinical management by tracking interventional outcomes. The patient customers will benefit by receiving recommendations on gait and posture habits, leading to a decrease in fall occurrences. Moreover, they will benefit from activity monitoring by receiving suggestions on exercise routines, which have been shown to increase health and fitness. On the other hand, clinics and hospitals will benefit from reducing the volume of patients at their facilities, and insurance agencies will benefit by decreasing patients' length of stay. This I-Corps project proposes a system capable of detecting asymmetry between kinetic and kinematic gait parameters, which consists of embedded inertial measurement units and insoles with piezoresistive pressure sensor arrays. With machine learning algorithms, the system can detect and classify the disease progression, which will support treatment modification along with normal disease course and symptomatic changes. This smart, non-invasive, non-pharmaceutical approach for disease prognosis could also lead to an increase in participation in clinical trials, as the low-risk involvement required could encourage persons with and without PD to participate. The developed technology allows for continuous gait recordings outside the clinical setting. This smart, wireless gait monitoring system has the potential of decreasing the burden associated with the numerous clinic visits. The intellectual merits lie in the use of emerging technologies, including cloud computing and artificial intelligence for feature extraction, classification, and rare-event detection. These features will support medical professionals' decision-making regarding the course of treatments from its early stages without having to add more effort to their already busy schedules. In addition, the designed Internet-of-Things (IoT) architecture will allow mobile health monitoring, including treatment compliance and categorization for treatment improvement.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.