基于Soli的非接触式心率检测用于睡眠和冥想跟踪
Luzhou Xu1, Jaime Lien2, Haiguang Li2
1Google LLC, 6420 Sequence Drive, San Diego, CA, 92121, USA. lzxu@google.com.
Scientific reports
|October 21, 2023
概括
这项研究引入了一种新的非接触式心率 (HR) 检测方法,使用紧的雷达芯片,非常适合睡眠和冥想跟踪. 它为传统的可穿戴设备提供了一种方便的替代方案.
科学领域:
- 生物医学工程 生物医学工程
- 信号处理 信号处理
- 机器学习 机器学习
背景情况:
- 心率 (HR) 监测对健康和健身至关重要,但传统的可穿戴设备在睡眠和冥想期间可能会侵入.
- 现有的非接触式雷达HR检测方法通常需要重的设备和特定的传感器放置,限制了便携性和应用.
研究的目的:
- 开发和验证一种新的非接触式心率检测方法,使用小型雷达芯片来改善睡眠和冥想期间的HR监测.
- 评估将基于雷达的HR检测集成到便携式设备中的可行性,以进行不引人注目的健康跟踪.
主要方法:
- 使用一个小型的Soli雷达芯片,集成到一个便携式设备中,用于非接触式HR信号采集.
- 采用先进的信号处理和机器学习算法来从雷达数据中提取HR.
- 验证了广泛睡眠 (62名用户,498小时) 和冥想 (114名用户,1131分钟) 数据集的方法.
主要成果:
- 在睡眠数据集上实现了1.69bpm的平均绝对误差 (MAE) 和[公式:见文本]的平均绝对百分比误差 (MAPE).
- 在冥想数据集上获得了1.05bpm的MAE和[公式:参见文本]的MAPE.
- 证明了睡眠和冥想的高回忆率[公式:见文本].
结论:
- 建议使用小型雷达芯片的非接触式HR检测方法对于睡眠和冥想跟踪是有效的.
- 这项技术提供了一个有希望的,方便的替代品可穿戴式传感器,用于日常生活中持续的HR监控.
- 代表了这种非接触式HR检测技术的首次应用,专门用于睡眠和冥想监测.
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