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连接的健康传感器， 可通过汗液和其他生物流体进行连续监测的贴合材料。与绷带结合， 敷料，尿布或衣服，并使用WiFi无线供电，这些将使连续 测量健康个体和患有糖尿病的个体的多个生命体征、生物标志物和代谢物， 急性或慢性疾病。体现对这种传感器的关键需求的应用是监测 和伤口护理，特别是慢性伤口和手术部位感染。临床伤口监测 很少发生，患者通常必须在家中自我监测和护理伤口。 为了满足这一需求，本提案描述了智能 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， 可以便宜地集成到绷带或敷料中，包括无线数据读出和无电池 操作提取预后预测需要从随时间变化的、 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 和真实的智能分析。建议的研究包括共形的发展 测量柔软织物上生物标记物的电化学传感器.集成 扩展射频供电传感器工作范围的电路;传感器和 将电子器件集成到一次性的无电池设备中， 能量最小化;以及，应用先进的概率分类方法，多传感器 时间序列数据用于新的预后预测和健康状态建模。 所提出的方法将为患者和护理提供者提供多种益处，包括（i） 向临床医生提供关于伤口进展的自动反馈，（ii）向患者提供反馈以降低发生率 常见的伤口护理错误，和（iii）早期发现感染，减少感染相关的 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， 随后进行动物模型测试，以及开发培训患者的材料， 护理人员和临床医生正确使用智能伤口监测仪。

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.