使用手腕穿戴的IMU传感器对自由生活环境进行饮食速度测量
IEEE journal of biomedical and health informatics
|July 3, 2024
概括
本研究引入了一种自动化方法,用于使用IMU数据测量进食速度,克服自我报告的主观性. 该方法在现实环境中客观地量化了进食速度.
科学领域:
- 营养科学 营养科学
- 生物医学工程 生物医学工程
- 可穿戴技术可穿戴技术
背景情况:
- 吃得快与肥胖和糖尿病等健康问题有关.
- 目前的方法依赖于主观的自我报告问卷.
- 需要对进食速度进行客观和自动测量.
研究的目的:
- 开发一种自动化和客观的方法来测量进食速度.
- 为了整合咬伤和吃食事件检测,以进行准确的测量.
- 为了验证近乎自由生活环境中的方法.
主要方法:
- 利用时间卷积网络与多头注意力 (TCN-MHA) 来从IMU数据中检测咬伤.
- 集群检测到的咬伤进入进食的情节.
- 通过将咬伤数与插曲持续时间划分来计算进食速度.
主要成果:
- 在FD-I数据集上达到0.110的平均绝对百分比误差 (MAPE),在FD-II数据集上达到0.146.
- 在两个公开可用的数据集 (FD-I和FD-II) 上验证了方法,其中有61名参与者和513小时的数据.
- 证明了自动食用速度测量的可行性.
结论:
- 拟议的基于TCN-MHA的方法提供了一个客观而准确的方法来测量进食速度.
- 自动食用速度测量可以在几乎自由的生活条件下有效实施.
- 这项技术在营养监测和健康研究中具有潜在的应用.
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