SCH: Wireless battery-less smart sensing and analytic with application to wound assessment

拟议项目的目标是开发智能和互联的健康传感器，使用软件和 适用于通过汗液和其他生物流体进行持续监测的可整合材料。整合成绷带， 敷料、尿布或衣服，并使用WiFi无线供电，这些将使连续 对健康人和高血压患者的多种生命体征、生物标记物和代谢物的测量 急性病或慢性病。体现这种传感器的关键需求的一个应用是监控 以及伤口的护理，特别是慢性伤口和手术部位感染。临床上的伤口监测 这种情况很少见，患者经常必须在家中自我监测和护理自己的伤口。 为了满足这一需求，本建议书描述了SMART 伤口监测器将通过多个传感器评估伤口状态，包括温度、湿度、 PH值和靶向生物标志物。以有用的方式获取这些连续信号需要传感器 可以廉价地集成到绷带或敷料中，包括无线数据读出和无电池 手术。提取预测预测需要从时变和 温度变化的传感器数据，在存在伪影和环境噪声的情况下，需要连接 和实时智能分析。拟开展的研究包括共形的发展 测量柔软织物上生物标志物的电化学传感器.集成 扩展射频供电传感器工作范围的电路；传感器和 使用自适应多传感器读出接口电路将电子设备转化为一次性、无电池设备 能量最小化；以及先进的概率分类方法在多传感器中的应用 用于新的预后预测和健康状态建模的时间序列数据。 拟议的方法将为患者和护理提供者提供多种好处，包括(I) 自动反馈给临床医生关于伤口进展的信息，(Ii)反馈给患者以减少发病率 (3)早期发现感染，减少与感染相关的感染 发病率和死亡率。该项目还包括使用人工伤口床的验证计划， 接下来是动物模型试验，以及训练病人的材料的开发， 护理人员和临床医生正确使用智能伤口监测器。

The goal of the proposed project is to develop smart and connected health sensors using soft and conformable materials for continuous monitoring via sweat and other biofluids. Integrated into bandages, dressings, diapers, or clothing, and powered wirelessly using WiFi, these would enable continuous measurement of multiple vitals, biomarkers, and metabolites for both healthy individuals and those with acute or chronic illness. An application that embodies the critical need for such sensors is the monitoring and care of wounds, especially chronic wounds and surgical site infections. Wound monitoring in the clinic is infrequent, and patients often must self-monitor and care for their wounds at home. To address this need, this proposal describes the design, implementation, and validation of a smart wound monitor that will assess wound status through multiple sensors, including temperature, moisture, pH, and targeted biomarkers. Acquiring these continuous signals in a useful manner requires sensors that can be integrated cheaply into a bandage or dressing, including wireless data readout and battery-less operation. Extracting prognosis prediction requires robust inference from time-varying and temperature-varying sensor data, in the presence of artifacts and environmental noise, requiring connected and intelligent analytics in real time. The proposed research includes the development of conformal electrochemical sensors for measurement of biological markers on soft fabrics; development of integrated circuits that extend the range of operation of RF-powered sensors; co-integration of sensors and electronics into a disposable, battery-less device using adaptive multi-sensor readout interface circuits for energy minimization; and, the application of advanced probabilistic classification methods to multi-sensor time-series data for novel prognosis prediction and health status modeling. The proposed approach would provide multiple benefits for the patient and care provider, including (i) automated feedback to the clinician on wound progression, (ii) feedback to the patient to reduce incidence of common wound-care mistakes, and (iii) early detection of infection, reducing infection-associated morbidity and mortality. The project additionally includes a validation plan using an artificial wound bed, followed by testing in animal model, as well as the development of materials for training patients, caregivers, and clinicians in the proper use of the smart wound monitor.