title: Trunk muscle onset detection technique for EMG signals with ECG artefact.
abstract: The timing of trunk muscle activation has become an important element in the understanding of human movement in normal and chronic low back pain populations. The detection of anticipatory postural adjustment via trunk muscle onsets from electromyographic (EMG) signals can be problematic due to baseline noise or electro-cardiac (ECG) artefact. Shewhart protocols or whole signal analyses may show different degrees of sensitivity under different conditions. Muscle activity onsets were determined from surface EMG of seven muscles for five trials before and after fatigue were examined in four subjects (n=280). The objective of this study was to examine two detection methods (Shewhart and integrated protocol (IP)) in determining the onsets of trunk muscles. The variability of the baseline amplitude and the impact of added Gaussian noise on the detected onsets were used to test for robustness. The results of this study demonstrate that before and after fatigue there is a large degree of baseline variance in the trunk muscles (coefficients of variation between 40-65%) between trials. This could be normal response to body sway. The IP method was less susceptible to false onsets (detecting onsets in the baseline window) 3 vs. 51%. The findings suggest the IP method is robust with large variance in the baseline if the signal to noise ratio is greater than six. In spite of the robustness of the algorithm, the findings would suggest that statistical assessments should be used to target trials for selective visual inspection for subtle trunk muscle onsets.
authors.affiliation: The Centre for Musculoskeletal Studies, School of Surgery and Pathology, The University of Western Australia, Level 2 Medical Research Foundation Building, Rear 50 Murray Street, Perth 6000, Australia. gta@cms.uwa.edu.au
authors.forename: G T
authors.initials: GT
authors.lastname: Allison
mesh_terms: D000009:Abdominal Muscles / Q000502:physiology; D000465:Algorithms; D016477:Artifacts; D001415:Back; D004562:Electrocardiography; D004576:Electromyography; D006801:Humans; D018763:Muscle Fatigue; D018482:Muscle, Skeletal / Q000502:physiology*; D011187:Posture; D012815:Signal Processing, Computer-Assisted