Carmeli's S index assesses motion and muscle artefact reduction in rowers' electrocardiograms.
Electrocardiograms (ECG) suffer high perturbations from motion and muscle activities when measured on the chest of rowers. However, for cardiac assessment and sport performance measures, ECG complexes and their time occurrences contain information of great value. We thus propose to use electromyogram (EMG) sensors placed on the distal pectoral muscle to provide a reference signal for motion and muscle activity cancellation. The low frequencies of the EMG signal are conserved for motion cancellation. A combination of band-pass and adaptive filters allows us to recover ECG complexes. This specific scheme is intended to be used for advanced ECG sensors with on-board digital signal processing which requires low-power electronics. A validation of the method is performed based on a nonlinear dynamic model of the ECG and linear frequency modulated rowing movement for various input and output signal-to-noise ratios and adaptive filter gain parameters. Results show a good motion tracking cancellation of the adaptive filter. Finally, assessments of the method on the real recorded data from five subjects are presented. To this end, we have first computed estimates of the signal-to-noise ratio gain between the original and noise-reduced signals. Second, we have developed a modified synchronization index first proposed by Carmeli et al between a QRS template and the original and noise-reduced signals. Both assessment measures are complementary to each other.
Celka
Patrick
P
School of Engineering, Griffith University, Gold Coast Campus, Southport 4215 Queensland, Australia. p.celka@griffith.edu.au
Kilner
Brett
B
D016477:Artifacts; D004562:Electrocardiography / Q000592:standards*; D004576:Electromyography; D006801:Humans; D009038:Motion; D010369:Pectoralis Muscles / Q000502:physiology*; D013177:Sports / Q000502:physiology*