在智能手表上实现的使用Kurtosis的上肢运动多样性的实时感应
Guillem Cornella-Barba1, Shusuke Okita2, Zheng Li3
1Department of Mechanical and Aerospace Engineering, University of California Irvine, Irvine, CA 92697, USA.
Sensors (Basel, Switzerland)
|August 29, 2024
概括
这项研究表明,不同的活动产生了不同的运动多样性,通过kurtosis来衡量. 一个新的算法可以在智能手表上实时计算kurtosis,以获得康复反.
科学领域:
- 生物医学工程 生物医学工程
- 康复科学 康复科学 康复科学
- 可穿戴技术可穿戴技术
背景情况:
- 传统的可穿戴传感器测量运动量 (例如,步骤).
- 量化运动质量,如多样性和复杂性,对于神经系统康复至关重要.
- 库尔托斯是分布峰值的统计测量,可以量化前臂姿势多样性在上肢损伤的个体.
研究的目的:
- 为了确定不同的运动活动是否会产生不同的皮质变化值.
- 开发一个计算效率高的算法,用于实时kurtosis计算.
- 为了验证商用智能手表上的实时kurtosis算法,用于可穿戴的康复应用.
主要方法:
- 评估了前臂姿势多样性在7个未受损害个体的12项活动中的kurtosis.
- 开发并实施了一种用于实时kurtosis计算的新型递归算法.
- 使用机器人模拟器在智能手表上验证了算法的准确性.
主要成果:
- 不同的活动导致了各种各样的质值,表明了不同的运动多样性.
- 这种新的算法将库尔托斯计算时间减少了200的因素.
- 基于智能手表的算法在模拟活动中准确计算了kurtosis.
结论:
- 运动的多样性,量化通过kurtosis,在不同的活动有很大的差异.
- 一个计算效率高的算法使可穿戴设备上的实时kurtosis计算成为可能.
- 这项工作是开发可穿戴系统的关键一步,用于实时反康复中的运动质量.
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