I-Corps: HealthSmart Technical Development Plan

拟议的i-Corps活动汇集了来自工程学、健康科学和人文科学的跨学科研究团队，以探索将PI产生的HealthSmart技术商业化的途径？正在进行的研究。7年多来，该团队一直在合作和从事创新的生物医学研究活动。建议技术的核心是一个多传感器平台，它是从以前的NSF Tie CMMI拨款演变而来的，用于以允许先进的临床诊断和预后程序的采样率连续和同步地收集、高速无线传输和可视化多种不同的生理信号。该团队计划同时追求两个主要目标，(A)开发用于连续、同步采集血流动力学信号的可穿戴多传感器服装，以及(B)实施该团队先前开发的个性化预测和预测方法。可穿戴传感器的开发将是独一无二的，因为：(A)将根据行为研究和客户/用户反馈获取和评估服装在目标人群中的穿着性能(从患者-S的角度)，以及(B)将同步获取多个微电子机械系统(MEMS)传感器，以跟踪生理过程之间的动态耦合。预测学方法结合了非线性/非平稳动力系统理论中的关键思想和生理动力学治疗，以识别短期健康变化(如睡眠呼吸暂停)和慢性疾病之间的长期过渡(如心血管疾病)。如果成功，拟议的项目有可能吸引更多对HealthSmart服装感兴趣的客户，这些服装用于家庭或医院内的心血管(CV)疾病监测和事件预测。这项技术的潜在首批采用者将是睡眠呼吸暂停诊断提供商，他们对使用拟议的HealthSmart服装进行阻塞性睡眠呼吸暂停(OSA)家庭诊断测试的成本节约感兴趣。

The proposed I-Corps activity brings together an interdisciplinary team of investigators from engineering, health sciences, and human sciences, to explore pathways to commercialize HealthSmart technology resulting from PIs? ongoing research. The team has been collaborating and pursuing innovative biomedical research activities for over 7 years. Central to the proposed technology is a multi-sensor platform that has evolved from prior NSF TiE CMMI grants for the collection, high-speed wireless transmission, and visualization of multiple heterogeneous physiological signals continuously and synchronously at sampling rates that permit advanced clinical diagnostics and prognostic procedures. The team plans to concurrently pursue two major objectives, (a) development of wearable multi-sensor garments for continuous, synchronous acquisition of hemodynamic signals, and (b) implementation of personalized prediction and prognostic approaches previously developed by the team. The wearable sensor development will be unique in that (a) the wearability (from a patient?s perspective) of the garment among the targeted population would be acquired and assessed based on behavioral studies and customer/user feedback, and (b) multiple microelectromechanical system (MEMS) sensors will be synchronously acquired to track dynamic couplings among physiological processes. The prognostics approach combines key ideas in nonlinear/nonstationary dynamic systems theory with physiological dynamics treated to discern both the short-term health variations (i.e. sleep apnea) and long-term transitions between chronic conditions (i.e. cardiovascular disease). If successful, the proposed project has the potential to attract a breadth of customers who are interested in a HealthSmart garment for at-home or in-hospital cardiovascular (CV) disease monitoring and event prediction. A potential first adopter of this technology would be sleep-apnea diagnostic providers who are interested in the cost savings of at-home diagnostic testing of Obstructive Sleep Apnea (OSA) using the proposed HealthSmart garment.