使用可穿戴传感器进行压力监测:医疗领域的物联网技术
Fatma M Talaat1, Rana Mohamed El-Balka2
1Faculty of Artificial Intelligence, Kafrelsheikh University, Kafrelsheikh, Egypt.
Neural computing & applications
|June 26, 2023
概括
物联网 (IoT) 能够实现远程电子健康监控系统. 这项研究提出了一个使用可穿戴传感器和机器学习的压力监测算法,确定随机森林是最有效的疾病预测.
科学领域:
- 生物医学工程 生物医学工程
- 计算机科学 计算机科学
- 数字健康数字健康
背景情况:
- 物联网 (IoT) 正在通过实现先进的电子健康监控系统来彻底改变医疗保健.
- 可穿戴技术和远程传感器对于收集患者数据以评估身体和心理健康至关重要.
- 目前的电子健康系统旨在自动提供处方,并允许远程观察患者.
研究的目的:
- 检查物联网技术在医疗行业中的应用及其对医疗保健质量的影响.
- 通过物联网集成来评估传统医疗实践的提升.
- 调查物联网在提高医疗保健服务标准方面的潜力.
主要方法:
- 从可穿戴设备导入和处理信号,包括峰值增强.
- 开发和实施一种使用可穿戴传感器的新型压力监测算法 (SMA).
- 比较各种机器学习 (ML) 算法,包括随机森林,决策树和XGBoost,用于信号分析和预测.
主要成果:
- 拟议的SMA由四个阶段组成:数据采集,信号处理,预测和性能评估.
- 使用网格搜索来优化支持向量机 (SVM) 模型的超参数.
- 随机森林在分类任务中表现出卓越的表现,紧随其后的是决策树和XGBoost.
结论:
- 物联网的整合显著提高了远程患者监测和医疗保健的提供.
- 开发的压力监测算法有效地处理可穿戴传感器数据以进行健康评估.
- 机器学习算法,特别是随机森林,对于分析电子健康数据和预测患者状态非常有效.
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