IEEE J Biomed Health Inform - Surface EMG decomposition based on K-means clustering and convolution kernel compensation.

Tópicos

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Resumo

A new approach has been developed by combining the K-mean clustering (KMC) method and a modified convolution kernel compensation (CKC) method for multichannel surface electromyogram (EMG) decomposition. The KMC method was first utilized to cluster vectors of observations at different time instants and then estimate the initial innervation pulse train (IPT). The CKC method, modified with a novel multistep iterative process, was conducted to update the estimated IPT. The performance of the proposed K-means clustering-Modified CKC (KmCKC) approach was evaluated by reconstructing IPTs from both simulated and experimental surface EMG signals. The KmCKC approach successfully reconstructed all 10 IPTs from the simulated surface EMG signals with true positive rates (TPR) of over 90% with a low signal-to-noise ratio (SNR) of -10 dB. More than 10 motor units were also successfully extracted from the 64-channel experimental surface EMG signals of the first dorsal interosseous (FDI) muscles when a contraction force was held at 8 N by using the KmCKC approach. A "two-source" test was further conducted with 64-channel surface EMG signals. The high percentage of common MUs and common pulses (over 92% at all force levels) between the IPTs reconstructed from the two independent groups of surface EMG signals demonstrates the reliability and capability of the proposed KmCKC approach in multichannel surface EMG decomposition. Results from both simulated and experimental data are consistent and confirm that the proposed KmCKC approach can successfully reconstruct IPTs with high accuracy at different levels of contraction.

Resumo Limpo

new approach develop combin kmean cluster kmc method modifi convolut kernel compens ckc method multichannel surfac electromyogram emg decomposit kmc method first util cluster vector observ differ time instant estim initi innerv puls train ipt ckc method modifi novel multistep iter process conduct updat estim ipt perform propos kmean clusteringmodifi ckc kmckc approach evalu reconstruct ipt simul experiment surfac emg signal kmckc approach success reconstruct ipt simul surfac emg signal true posit rate tpr low signaltonois ratio snr db motor unit also success extract channel experiment surfac emg signal first dorsal inteross fdi muscl contract forc held n use kmckc approach twosourc test conduct channel surfac emg signal high percentag common mus common puls forc level ipt reconstruct two independ group surfac emg signal demonstr reliabl capabl propos kmckc approach multichannel surfac emg decomposit result simul experiment data consist confirm propos kmckc approach can success reconstruct ipt high accuraci differ level contract

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