I-Corps: Mobile, Smart Gait Assessment System

该I-Corps项目更广泛的影响/商业潜力是一种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进行连续步态监测，可用于步态障碍患者（包括帕金森病（PD）患者）的在线远程临床管理。仅PD就影响了美国100多万人，这个数字每年增加60，000人。该技术将通过跌倒跟踪和预防来支持预防再次入院，通过允许在家监测疾病进展来减少医院就诊和住院时间，实施监测健康计划，通过模式识别来区分疾病类型，并通过跟踪干预结果来提供及时有效的临床管理。患者客户将受益于接收步态和姿势习惯的建议，从而减少跌倒发生率。此外，他们将受益于活动监测，通过接收有关锻炼程序的建议，这已被证明可以增加健康和健身。另一方面，诊所和医院将从减少其设施的病人数量中受益，保险机构将从减少病人住院时间中受益。 该I-Corps项目提出了一种能够检测动力学和运动学步态参数之间的不对称性的系统，该系统由嵌入式惯性测量单元和具有压阻式压力传感器阵列的鞋垫组成。通过机器学习算法，系统可以检测和分类疾病进展，这将支持治疗修改沿着正常病程和症状变化。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临床试验参与率的增加，因为所需的低风险参与可以鼓励患有和没有PD的人参与。所开发的技术允许在临床环境之外进行连续步态记录。这种智能无线步态监测系统有可能减少与大量诊所就诊相关的负担。其智力优势在于使用新兴技术，包括云计算和人工智能进行特征提取、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做出关于治疗过程的决策，而不必在他们已经忙碌的日程安排中增加更多的工作。此外，设计的物联网（IoT）架构将允许移动的健康监测，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知识价值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.