20.500.12556/DKUM-88846 Identifikacija gruč neločljivih motoričnih enot iz večkanalnih površinskih elektromiogramov dvoglave nadlahtne mišice Identification of clusters of inseparable motor units from high-density electromyograms of biceps brachii muscle We analyzed the capability of previously introduced Convolution Kernel Compensation (CKC) method to identify clusters of motor units (MUs) that share similar motor unit action potentials (MUAPs) and, therefore, cannot be mutually discriminated by the decomposition of high-density surface electromyograms (hdEMG). The tests were performed on biceps brachii muscle because hdEMG decomposition yields relatively small number of individual MUs in this muscle. In this study, we analyzed how many MUs of biceps brachii get merged into the same spike train by the CKC method due to MUAP similarity and what are the sensitivity and precision of MU discharge identification in merged spike trains. We compared these metrics with the identification of individual MUs in both synthetic and experimental hdEMG. In synthetic hdEMG with 20 dB noise, the number of identified MUs increased from 5.2 ± 2.8 (individual MUs) to 16.4±8.4 MUs when merged MU spike trains were taken into consideration, in addition to individual MUs. Discharges of individual MUs were identified with sensitivity of 77.0±15.8 % and precision of 86.1±25.4 %, whereas the merg ed MUs were identified with sensitivity of 79.6±15.7 % and precision of 97.4±11.8 %. Similar results were observed also for noiseless hdEMG. In experimental hdEMG signals from biceps brachii muscle of two young healthy individuals, the number of identified MUs increased from 7.5±2.4 (individual MUs) to 21.9±17.6 MUs (merged MU spike trains). Individual MUs were identified with sensitivity of 83.3±15.9 % and precision of 80.0±19.0 %, whereas when considering also merged MUs, the sensitivity and precision of MU discharge identification increased to 82.3±22.4 % and 94.9±11.4 %, respectively. In conclusion, the merged MU spike trains obtained by hdEMG decompositions carry important information about the activity of skeletal muscles and can be used to increase the number of MUs identified from hdEMG. We analyzed the capability of previously introduced Convolution Kernel Compensation (CKC) method to identify clusters of motor units (MUs) that share similar motor unit action potentials (MUAPs) and, therefore, cannot be mutually discriminated by the decomposition of high-density surface electromyograms (hdEMG). The tests were performed on biceps brachii muscle because hdEMG decomposition yields relatively small number of individual MUs in this muscle. In this study, we analyzed how many MUs of biceps brachii get merged into the same spike train by the CKC method due to MUAP similarity and what are the sensitivity and precision of MU discharge identification in merged spike trains. We compared these metrics with the identification of individual MUs in both synthetic and experimental hdEMG. In synthetic hdEMG with 20 dB noise, the number of identified MUs increased from 5.2 ± 2.8 (individual MUs) to 16.4±8.4 MUs when merged MU spike trains were taken into consideration, in addition to individual MUs. Discharges of individual MUs were identified with sensitivity of 77.0±15.8 % and precision of 86.1±25.4 %, whereas the merg ed MUs were identified with sensitivity of 79.6±15.7 % and precision of 97.4±11.8 %. Similar results were observed also for noiseless hdEMG. In experimental hdEMG signals from biceps brachii muscle of two young healthy individuals, the number of identified MUs increased from 7.5±2.4 (individual MUs) to 21.9±17.6 MUs (merged MU spike trains). Individual MUs were identified with sensitivity of 83.3±15.9 % and precision of 80.0±19.0 %, whereas when considering also merged MUs, the sensitivity and precision of MU discharge identification increased to 82.3±22.4 % and 94.9±11.4 %, respectively. In conclusion, the merged MU spike trains obtained by hdEMG decompositions carry important information about the activity of skeletal muscles and can be used to increase the number of MUs identified from hdEMG. površinski elektromiogram (EMG) motorična enota vlak impulzov zlivanje motoričnih enot biceps brachii surface high density electromyogram (HDEMG) motor unit spike train motor unit merging biceps brachii true true false Slovenski jezik Angleški jezik Neznano 2024-05-29 23:22:11 2024-05-30 22:34:57 2024-12-09 09:58:02 0000-00-00 00:00:00 2023 0 0 4 0000-00-00 Zaloznikova NiDoloceno NiDoloceno 0000-00-00 0000-00-00 2023-09-28 004.9 166001667 167880451 2591-0442 Identifikacija_gruc_nelocljivih_motoricnih_enot_iz_veckanalnih_povrsinskih_elektromiogramov_dvoglavne_nadlahtne_misice_-_Kutos_et_al.pdf Identifikacija_gruc_nelocljivih_motoricnih_enot_iz_veckanalnih_povrsinskih_elektromiogramov_dvoglavne_nadlahtne_misice_-_Kutos_et_al.pdf 1 45D88D3F5C890A4ACC833F0EB8C5FFF3 671d0d28c0a138390296ffab3f6a7afe463de1843cddd25bac1f5f70fa3515bd a8c27591-1e01-11ef-8334-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=179904 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0