在行走过程中自动识别下肢神经肌肉激活模式,使用织可穿戴多传感器系统
Federica Amitrano1, Armando Coccia1, Federico Colelli Riano1
1Movement Analysis and Robotics Laboratory (MARLab), Istituti Clinici Scientifici Maugeri IRCCS, Telese Terme Institute, 82037 Benevento, Italy.
Sensors (Basel, Switzerland)
|February 13, 2026
概括
这项研究开发了一种舒适的可穿戴系统,使用表面肌电图 (sEMG) 和压力内来监测步行期间的肌肉激活. 该系统有效地捕获了健康成年人的前和胃后活动模式.
科学领域:
- 生物医学工程 生物医学工程
- 运动学 运动学
- 可穿戴技术可穿戴技术
背景情况:
- 穿戴式传感器对于评估日常活动中的神经肌肉功能至关重要.
- 在临床评估中,准确监测步行过程中的肌肉激活是非常重要的.
研究的目的:
- 介绍和评估一款多传感器可穿戴系统,用于在走路时监测前 (TA) 和胃半后 (GL) 肌肉激活.
- 评估整合表面肌电图 (sEMG) 和足部压力传感的可行性和有效性.
主要方法:
- 开发了一个系统,结合了基于织品的sEMG袖子和压力传感内底.
- 收集了11名健康成年人在地面上行走时的同步sEMG和脚部压力数据.
- 利用专门的算法来检测跨行走周期的肌肉激活间隔.
主要成果:
- 可穿戴系统舒适,并提供稳定的录音.
- 每个步行周期检测到1-4个肌肉激活爆发,在终端摆动中具有一致的TA活动,在中至终端姿势中具有GL活动.
- 观察到肌肉激活模式的个体间和个体内变化,与生理步态调节保持一致.
结论:
- 多传感器可穿戴系统可用于描述行走期间的肌肉激活.
- 该系统的舒适性,信号质量和易于集成支持其用于临床步态分析和远程监控.
- 未来的研究将专注于系统优化和在不同人群中的验证.
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