拒绝生理信号:评估,技术和可穿戴的实施
概括
这项研究检查了无声化的生理信号,发现皮肤温度是强大的运动工件,而EEG和ECG需要工件移除用于体力活动期间的可穿戴监控.
科学领域:
- 生物医学工程 生物医学工程
- 信号处理 信号处理
- 可穿戴技术可穿戴技术
背景情况:
- 运动工件在体力活动期间显著污染生理信号,特别影响残疾人.
- 有效的消毒对于可穿戴系统中可靠的生理监测至关重要.
- 评估计算成本和消除噪音技术的必要性对于实际实施至关重要.
研究的目的:
- 为了评估运动器件在运动期间对各种生理信号的影响.
- 分析不同无色化方法的计算成本和功耗.
- 为了确定低功耗可穿戴设备的高效消噪策略.
主要方法:
- 收集了各种体力活动期间的生理信号 (EEG,ECG,皮肤温度) 的数据库.
- 审查和分析各种信号消音技术的计算成本.
- 不同复杂度级别和采样速率的无噪声算法的测试功耗.
主要成果:
- 皮肤温度信号显示了对运动工件的高免疫力.
- 脑电图 (EEG) 和心电图 (ECG) 信号受到运动的显著影响,跳跃造成了最多的污染.
- 电力消耗因消噪技术的复杂性和采样率而异.
结论:
- 并非所有生理信号都需要去除噪音;皮肤温度在很大程度上是人工物免疫.
- 在体力活动期间对EEG和ECG进行监测,特别是用于可穿戴应用时,需要有效的消噪方法.
- 选择消噪技术时,应考虑低功耗可穿戴系统的计算效率和功耗.
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