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用动态时间扭曲步数算法对应个人特有的模板,用于多个步行活动
Valeria Filippou1, Michael R Backhouse2, Anthony C Redmond3
1Institute of Medical and Biological Engineering, University of Leeds, Leeds LS2 9JT, UK.
Sensors (Basel, Switzerland)
|November 25, 2023
概括
一个新的算法,StepMatchDTWBA,使用可穿戴加速度计准确计算步骤. 它改善了健康个体和患有病态步行的身体活动测量.
科学领域:
- 生物医学工程 生物医学工程
- 可穿戴技术可穿戴技术
- 人类运动分析 人类运动分析
背景情况:
- 准确的身体活动监测对于健康和健康至关重要.
- 现有的步数算法与个体步态变化作斗争,特别是在病态群体中.
- 可穿戴式加速度计为持续活动跟踪提供了一个有前途的平台.
研究的目的:
- 开发和评估StepMatchDTWBA算法,用于精确的步数计数.
- 在健康和模拟的病态步行群体中评估算法性能.
- 通过可穿戴设备增强个性化的体育活动测量.
主要方法:
- 开发了StepMatchDTWBA算法,利用动态时间扭曲 (DTW) 质量中心平均值来创建个性化的步骤模板.
- 使用DTW将步骤模板与加速度计数据时代进行比较.
- 用30名健康志愿者验证了算法,使用手腕加速度计和GAITRite步道测量距离和楼梯.
主要成果:
- StepMatchDTWBA实现了健康步行的平均平方根平均误差为2步,模拟病态步行的平均误差为12步.
- 该算法在病态步行群体中的基准算法相比,表现优越.
- 个性化的模板有效地解释了个人的步行变化.
结论:
- 对于不同的群体,StepMatchDTWBA在准确的步数计数方面取得了重大进展.
- 该算法显示了高度个性化和精确的身体活动监测的潜力.
- 这项技术可以使各种健康,健康和康复应用受益.
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