SCH:INT: Self-powered Smart Ring for Always-On Health Interventions

持续监测在支持及时干预的预防性、个性化护理中变得越来越重要。新的传感器和通信技术为更积极主动的护理模式提供了机会，这些模式可以在家庭和日常生活中接触到人们，以改善健康行为。尽管可穿戴传感器在技术促进的健康干预中发挥了重要作用，但事实证明，对于大多数人来说，维持使用超过几周是困难的。 延长使用的一个重大障碍是需要对设备进行充电，通常是每天进行充电，以便进行量身定制的即时信息传递和有效干预。用于生理传感器的实时评估和解释的当前技术需要耗电的数据收集、传输和解释，以提供定制的和及时的反馈。 每次可穿戴设备需要充电时，都需要新的动力来充电，并需要额外的动力将其重新安装。该项目的目标是创建一个多传感器舒适的自供电环，永远不需要充电。 该团队将压力监测和管理作为一项重要的临床挑战，需要多个传感器和即时交互作为一个例子来测试多传感器智能戒指的贡献，以及智能采样推断和传输，以提供量身定制的压力辅导建议，而无需电池充电或设备移除。压力是对国民健康和生产力的主要威胁之一。 作为一种健康危害，它影响所有主要器官，并与许多疾病和预期寿命缩短有关。 通常，监测压力数据并提供实时干预需要每6小时为可穿戴设备充电一次。为了解决这个问题，研究团队计划开发一种芯片上的能量收集系统（SoC），其算法可以最大限度地降低功耗。该系统将嵌入一个舒适的防水环内，用户永远不必移除或充电。 这项新功能将使需要持续参与和反馈的有效健康教练干预成为可能。在这个为期一年的项目中，该团队计划开发一个原型自供电环，该环具有监测压力管理干预中重要的健康和活动变量的能力。 这些变量包括心率、心率变异性和皮肤电活动（皮肤电导的指标）。 该研究小组还计划使用加速度传感器测量运动，以提供区分身体压力和情绪压力目标分类的信息。 该项目将涉及两项主要活动。 首先，该项目将开发算法，以最大限度地减少功耗，使传感器能够永久运行，以进行压力监测。为了实现这一目标，项目团队将首先指定监测和反馈方案的临床要求。 然后，该规范将告知信号采样和滤波要求、数据融合规范以及最小化数据存储和传输的方法指南。 决策理论算法将用于优化来自环的多个传感器数据的采样和传输。 现有的算法将通过整合心率、心率变异性、皮肤电活动和加速度计来优化压力监测和传感器融合，以真实的时间准确分类压力水平。第二个主要活动将是开发一个具有动态性能扩展和制造协议的能量收集SoC，用于智能环系统集成和防水封装。该项目将开发一个高精度的片上时钟源和先进的电源管理电路，以实现动态决策算法和从外部室内太阳能电池收集的能量利用。然后，该团队将高效GaAs太阳能电池、动态采样/传输SoC、传感器组件（光电体积描记传感器、皮肤电活动电极）和具有先进灵活封装方案的无线模块集成到一个始终在线的智能健康监测环中。预计该项目的成功将推广到显著改善健康行为干预，并将通过始终连接的数据，人员和系统改变下一代健康和医学研究。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。

Continuous monitoring is becoming increasingly more important in preventive, personalized care supporting just-in-time interventions. New sensor and communications technologies offer opportunities for more proactive models of care that reach people in their homes and everyday lives to improve health behaviors. Although wearable sensors have played an important role in technology-facilitated health interventions, maintaining use for longer than a few weeks has proven difficult for much of the population. One substantial barrier to extended use is the need to recharge the devices, usually on a daily basis for tailored just-in-time messaging and effective interventions. Current techniques for real-time assessment and interpretation of physiological sensors require power hungry data collection, transfer, and interpretation to deliver tailored and timely feedback. Each time a wearable device requires charging, it takes renewed motivation to charge it and additional motivation to put it back on. The goal of this project is to create a multi-sensor comfortable self-powered ring that never needs charging. The team will use stress monitoring and management as an important clinical challenge requiring multiple sensors and just-in-time interactions as an example to test the contributions of a multi-sensor smart ring, as well as intelligent sampling inference and transmission, to provide tailored stress coaching advice without the need for battery charging or device removal. Stress is one of the key threats to the health and productivity of the nation. As a health hazard, it affects all major organs and is associated with many diseases and a reduction in life expectancy. Normally, monitoring stress data and providing real-time intervention would require recharging a wearable device every 6 hours. To address this issue, the research team plans to develop an energy harvesting system on a chip (SoC) with algorithms that minimize power consumption. This system will be embedded within a comfortable waterproof ring that users never have to remove or charge. This novel capability will enable effective health coaching interventions that require continuous engagement and feedback.In this one-year project, the team plans to develop a prototype self-powered ring with the capability to monitor health and activity variables important in stress management interventions. These variables include heart rate, heart rate variability, and electrodermal activity (an indicator of skin conductance). This research group also plans to measure motion using an accelerometry sensor to provide information in distinguishing physical stress from the target classification of emotional stress. The project will involve two main activities. Firstly, the project will develop algorithms to minimize power consumption to enable perpetually operating sensors for stress monitoring. To accomplish this goal, the project team will first specify the clinical requirements for the monitoring and feedback protocols. This specification will then inform signal sampling and filtering requirements, data fusion specifications, as well as guidelines for approaches to minimizing data storage and transfer. Decision-theoretic algorithms will be used to optimize the sampling and transmission of multiple sensor data from the ring. Existing algorithms will be optimized for stress monitoring and sensor fusion by integrating heart rate, heart rate variability, electrodermal activity and accelerometry to accurately classify stress levels in real time. The second main activity will be to develop an energy harvesting SoC with dynamic performance scaling and fabrication protocols for smart ring system integration and waterproof packaging. The project will develop a high-precision on-chip clock source and advanced power management circuitry to enable implementation of the dynamic decision algorithms and energy utilization harvested from external indoor solar cells. The team will then integrate high efficiency GaAs solar cells, dynamic sampling/transmission SoC, sensor components (photoplethysmography sensors, electrodermal activity electrodes), and wireless modules with advanced flexible encapsulation scheme into an always-on smart health monitoring ring. It is anticipated that the success of this project will generalize to markedly improve health behavior interventions and will transform the next-generation health and medical research through always-connected data, people, and systems.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.