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

SCH：无线无电池智能传感和分析，应用于伤口评估

• 批准号: 10238028
• 负责人: Matthew L Johnston
• 金额: $ 23.43万
• 依托单位: OREGON STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-22 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10238028
• 关键词: Acute; Address; Animal Model; Bandage; Biological Markers; Caregivers; Caring; Chronic Disease; Classification; Clinic; Clothing; Computer software; Data; Development; Devices; Disease; Early Diagnosis; Electronics; Feedback; Goals; Health; Health Status; Home; Incidence; Individual; Infection; Intelligence; Measurement; Methods; Mission; Modeling; Monitor; Morbidity - disease rate; Morphologic artifacts; National Institute of Biomedical Imaging and Bioengineering; Noise; Patient Care; Patient Education; Patients; Prognosis; Research; SMART health; Series; Signal Transduction; Sterile coverings; Surgical Wound Infection; Technology; Temperature; Testing; Textiles; Time; Validation; Wireless Technology; care providers; chronic wound; connected health; design; improved; innovation; mortality; novel; operation; sensor; sensor technology; targeted biomarker; wound; wound bed; wound care

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.

拟议项目的目标是使用软硬件开发智能互联健康传感器 通过汗液和其他生物流体进行连续监测的舒适材料。融入绷带， 敷料、尿布或衣服，并使用 WiFi 无线供电，这些将能够连续 测量健康人和患有疾病的人的多种生命体征、生物标志物和代谢物 急性或慢性疾病。体现对此类传感器的关键需求的一个应用是监控 以及伤口护理，尤其是慢性伤口和手术部位感染。诊所的伤口监测 这种情况并不常见，患者通常必须在家自我监测和护理伤口。 为了满足这一需求，本提案描述了智能系统的设计、实现和验证。 伤口监视器将通过多个传感器评估伤口状态，包括温度、湿度、 pH 值和目标生物标志物。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。提取预后预测需要从时变和 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。拟议的研究包括保形的开发 用于测量柔软织物上生物标记的电化学传感器；综合开发 扩展射频供电传感器工作范围的电路；传感器和的协同集成 使用自适应多传感器读出接口电路将电子器件集成到一次性无电池设备中 能源最小化；并且，先进的概率分类方法在多传感器中的应用 用于新型预后预测和健康状况建模的时间序列数据。 拟议的方法将为患者和护理人员提供多种好处，包括（i） 自动向临床医生反馈伤口进展情况，(ii) 向患者反馈以减少发生率 常见的伤口护理错误，以及 (iii) 及早发现感染，减少与感染相关的 发病率和死亡率。该项目还包括使用人造伤口床的验证计划， 随后进行动物模型测试，以及开发用于培训患者的材料， 护理人员和临床医生正确使用智能伤口监测仪。