Comparative Analysis Of Electromyographic Signals Using Bursts And Epochs: Optimizing Measurement Accuracy In Signal Processing

Electromyography (EMG) is widely used to assess muscle activity; however, optimal methods for signal selection during dynamic muscle contractions remain unclear. PURPOSE: To compare EMG signals in single contraction BURSTS versus multi-contraction time EPOCHs during non-fatiguing cycle ergometry. METHODS: Nineteen recreationally trained, college-aged cyclists visited the lab twice. The first visit included informed consent, familiarization, and a graded exercise test to determine VO2max, gas exchange threshold (GET), Rating of Perceived Exertion (RPE) at GET, and power output associated with GET and VO2max. Participants returned to the lab 48 hours later for a 60-minute cycle ergometry test at the power output and RPE corresponding to their GET, with power adjusted to maintain RPE at GET level. Participants wore bi-polar surface EMG electrodes on the vastus lateralis to measure muscle activation, EMG root mean square (RMS), and mean power frequency (MPF). Signals were selected in two formats: 10 BURSTS from each muscle contraction at minutes 3, 5, 7, 9, 11, 13, 15, 17, 19, and 21 to avoid interference from potential fatigue. EPOCHs around the same time points included both muscle contraction and relaxation periods. Mean BURST and EPOCH RMS and MPF values were calculated at each time point. Bland-Altman analysis determined mean bias and 95% confidence intervals between these methods. RESULTS: Analysis for EMG RMS from minutes 3 to 21 revealed a substantial negative bias, with the EPOCH method consistently underestimating RMS compared to BURST, showing a mean difference of approximately -50 units. Despite most differences falling within the 95% limits of agreement, the narrow confidence interval indicates persistent systematic error. Conversely, analysis for EMG MPF showed a small, consistent bias, with a mean difference near zero. CONCLUSION: These results indicate that while both methods effectively assess muscle activation in dynamic cycling, the EPOCH method significantly underestimates RMS, suggesting it may be less suitable for evaluating non-static muscle activity. The data support using BURST over EPOCH analysis for dynamic muscle contractions when RMS is the variable of interest. Supported by: Point Loma Nazarene University