Abstract
We describe the method for identification of motor unit (MU) firings from high-density surface electromyograms (hdEMG), recorded during repeated dynamic muscle contractions. A new convolutive data model for dynamic hdEMG is presented, along with the pulse-to-noise ratio (PNR) metric for assessment of MU identification accuracy and analysis of the impact of MU action potential (MUAP) changes in dynamic muscle contractions on MU identification. We tested the presented methodology on signals from biceps brachii, vastus lateralis, and rectus famoris muscles, all during different speeds of dynamic contractions. In synthetic signals with excitation levels of 10%, 30% and 50%, and MUAPs experimentally recorded from biceps brachii muscle, the presented method identified 15 ± 1, 18 ± 1, and 20 ± 1 MUs per contraction, respectively, all with average sensitivity and precision >90% and PNR >30dB. In experimental signals acquired during low force contractions of vastus lateralis and rectus femoris muscle, the method identified 9.4±1.9 and 7.8±1.4 MUs with PNR values of 35.4±3.6 and 34.1±2.7 dB. In comparison with the previously introduced Convolution Kernel Compensation method, the capability of the new method to follow dynamic MUAP changes is confirmed, also in relatively fast muscle contractions.
Highlights
S KELETAL muscles spatially spread and amplify the neural codes that control human movements [5], [6], [17]and have been under intense investigation in the fields of neurophysiology, neurology, rehabilitation, prosthetics, ergonomics and many others [22]
We introduced the new methodology for identification of motor unit (MU) spike trains in dynamic muscle contractions
We extended previously introduced pulse-tonoise ratio (PNR) metric to dynamic conditions and showed that we can use it for assessing the impact of MU action potential (MUAP) changes on MU spike trains identified by cyclostationary Convolution Kernel Compensation (CKC)
Summary
S KELETAL muscles spatially spread and amplify the neural codes that control human movements [5], [6], [17]and have been under intense investigation in the fields of neurophysiology, neurology, rehabilitation, prosthetics, ergonomics and many others [22]. Due to the complexity of the EMG mixing process, which is typically modelled by convolutive multiple-input-multiple-output system [12]–[15], identification of individual MU firing pattern has been largely limited to isometric muscle contractions, in which the geometry of the muscle and surrounding tissue does not change considerably. In such conditions, the MU action potentials (MUAPs), acquired by the uptake electrodes are relatively stationary and the main EMG nonstationarity comes from the MU recruitment and firing rates modulation. Whether or not the population coding of MUs in isometric conditions is representative for the dynamic conditions remains an open research question
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