在日常生活中基于持续加速计的震动检测.
Luis Martinez1, Orlando Martinez1, Stephen L Schmidt2
1Department of Electrical and Computer Engineering, California State University, Los Angeles, Los Angeles, CA 90032, USA.
Sensors (Basel, Switzerland)
|March 14, 2026
概括
我们开发了一个自动化算法,使用手腕穿戴的加速度计来持续检测帕金森症震. 这种算法将与日常活动区分开来,帮助自适应性深度脑刺激 (DBS) 控制.
科学领域:
- 生物医学工程 生物医学工程
- 神经科学是一个神经科学.
- 可穿戴技术可穿戴技术
背景情况:
- 帕金森病 (PD) 的管理需要先进的适应性深度大脑刺激 (DBS) 控制.
- 连续的实时震检测对于优化DBS治疗至关重要.
- 现有的震评估方法在日常生活场景中可能受到限制.
研究的目的:
- 开发和验证用于连续检测帕金森发的自动化算法.
- 评估使用可穿戴加速度计用于震动监测的可行性.
- 为了区分帕金森发与日常生活活动中的自愿运动.
主要方法:
- 开发了一种自动化算法,利用商用手腕加速度计 (Apple Watch) 和植入的DBS设备的三轴加速度数据.
- 算法识别了自愿活动,然后检测到4-7赫兹帕金森震频段的峰值.
- 采用连续波束变换来增强峰值和波检测,与短时间里埃变换相比.
主要成果:
- 开发的算法在日常活动中准确地检测了帕金森的震.
- 使用果手表的震动检测准确度高于植入的DBS设备 (IPG).
- 该算法与DBS强度 (r = -0.93至 -0.97) 和行业标准度量 (r = 0.57) 显示出强烈的相关性.
结论:
- 该自动化算法提供了一种临床相关的方法,用于使用可穿戴加速度计连续检测帕金森症.
- 这项技术通过在日常生活中将震与自愿运动区分开来,促进了自适应的DBS控制.
- 这些发现支持使用方便的商业手腕设备来监测PD震.
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