一个现实世界的数据集,用于检测日常生活中的洗手,使用可穿戴设备的手腕运动数据
Robin Burchard1, Kristina Kirsten2, Marcel Miché3
1University of Siegen, Siegen, Germany. robin.burchard@uni-siegen.de.
Scientific data
|February 5, 2026
概括
这项研究介绍了OCDetect,这是第一个使用惯性传感器进行无脚本强迫洗手的数据集. 本资源有助于开发自动化系统来检测强迫性洗手症 (OCD) 患者的强迫性洗手症.
科学领域:
- 活动认可 活动认可
- 穿戴式传感器数据分析数据分析
- 心理健康技术 心理健康技术
背景情况:
- 洗手检测对于卫生和医疗保健至关重要.
- 强迫性洗手显著影响有强迫性障碍 (OCD) 的个体.
- 现有的数据集缺乏现实世界,无脚本的强迫洗手数据.
研究的目的:
- 引入OCDetect数据集,这是首个针对强迫洗手的数据集.
- 为了实现自动化系统的发展,实时检测强迫性洗手.
- 支持强迫症患者的治疗干预措施.
主要方法:
- 在28天内使用惯性测量单位 (IMU) 从22名参与者收集数据.
- 记录了大约3000起洗手的案例,标注为强迫或例行.
- 开发和评估了一种系统,用于从未见过的参与者的背景活动中发现洗手行为.
主要成果:
- 在从背景活动中检测洗手时获得了0.77的最大F1得分.
- 平均F1得分为0.33,明显高于0.03.的机会水平.
- OCDetect数据集为活动识别研究提供了宝贵的资源.
结论:
- 强迫症检测数据集是第一个捕捉无脚本的,在野外的强迫洗手.
- 这一数据集有助于创建用于强迫症管理的辅助技术.
- 公共可用的数据集和代码促进了对活动识别和心理健康支持的进一步研究.
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