Beck Rebecca B J, Houtman Caroline J, O'Malley Mark J, Lowery Madeleine M, Stegeman Dick F
Department of Electronic and Electrical Engineering, University College Dublin, Dublin 4, Ireland.
IEEE Trans Biomed Eng. 2005 Apr;52(4):622-9. doi: 10.1109/TBME.2005.844027.
The speed of propagation of an action potential along a muscle fiber, its conduction velocity (CV), can be used as an indication of the physiological or pathological state of the muscle fiber membrane. The motor unit action potential (MUAP), the waveform resulting from the spatial and temporal summation of the individual muscle fiber action potentials of that motor unit (MU), propagates with a speed referred to as the motor unit conduction velocity (MUCV). This paper introduces a new algorithm, the MU tracking algorithm, which estimates MUCVs and MUAP amplitudes for individual MUs in a localized MU population using SEMG signals. By tracking these values across time, the electrical activity of the localized MU pool can be monitored. An assessment of the performance of the algorithm has been achieved using simulated SEMG signals. It is concluded that this analysis technique enhances the suitability of SEMG for clinical applications and points toward a future of noninvasive diagnosis and assessment of neuromuscular disorders.
动作电位沿肌纤维的传播速度,即其传导速度(CV),可用于指示肌纤维膜的生理或病理状态。运动单位动作电位(MUAP)是该运动单位(MU)单个肌纤维动作电位时空总和产生的波形,以称为运动单位传导速度(MUCV)的速度传播。本文介绍了一种新算法——MU跟踪算法,该算法使用表面肌电信号估计局部MU群体中单个MU的MUCV和MUAP幅度。通过随时间跟踪这些值,可以监测局部MU池的电活动。使用模拟表面肌电信号对该算法的性能进行了评估。得出的结论是,这种分析技术提高了表面肌电在临床应用中的适用性,并指向了神经肌肉疾病无创诊断和评估的未来。