用热响应和相分离的水凝用于用深度学习算法诊断心律失常
Hui Chen1, Jian Zhou1, Huan Cao2
1College of Mechanical and Vehicle Engineering, Hunan University, Changsha, 410082, China.
Biosensors & bioelectronics
|February 18, 2025
概括
新的水凝电极提供可编程的附着性,可用于可靠的心律失常诊断. 这个可穿戴系统捕获心电图 (ECG) 信号,使远程监测和深度学习的准确检测成为可能.
科学领域:
- 生物材料科学 生物材料科学
- 可穿戴技术可穿戴技术
- 医疗器械 医疗器械
背景情况:
- 常规的电心电图 (ECG) 监测的粘合液电极缺乏可编程的粘合力,可能会损伤皮肤和信号损失.
- 目前的方法难以实现可靠的,长期的粘附和脱落,而不会损害皮肤的微妙组织.
研究的目的:
- 开发先进的水凝电极,可根据需求进行可编程的粘附和脱离,以改进ECG信号采集.
- 通过可穿戴传感平台,实现心律失常的准确远程诊断.
主要方法:
- 在相隔智能水凝中集成动态多尺度接触和温度介导的可切换键.
- 微尺度调节粘合物分子和中尺度模块调节可调节粘合 (1.3 N/m至110 N/m).
- 开发一个实时云平台,用于远程ECG监测和深度学习算法用于心律失常诊断.
主要成果:
- 实现了84.5倍的开启/关闭粘合能,在低温下降低了98%的皮肤粘合力.
- 成功捕获了八种常见心律失常的患者的高保真性心电图信号.
- 展示了一个可穿戴的心律失常智能诊断系统,识别准确率为98.5%.
结论:
- 开发的水凝电极提供可编程的粘附性,增强了用于心脏监测的皮肤接口能力.
- 可穿戴式传感平台可实现远程,实时的心电图监测和准确的心律失常诊断.
- 这项技术代表了心血管健康可穿戴诊断技术的重大进步.
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