Comparative Analysis of Electromyographic Signals Using Bursts and EPOCHs: Optimizing Measurement Accuracy and Reliability in Signal Processing

Electromyography (EMG) is a tool for assessing muscle activity, yet methods for signal selection during dynamic muscle contractions remains unclear. PURPOSE: To compare dynamic EMG signals in single contraction BURSTS vs. multi-contraction time EPOCHs during non-fatiguing cycle ergometry. METHODS: 19 recreationally trained college-aged cyclists visited the lab on two separate occasions. The first visit included informed consent, familiarization, and the completion of a graded exercise test to determine VO2max, the 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 hr later to perform a 60 minute cycle ergometry test at the power output and RPE associated with their GET where power ouput was adjusted to maintain RPE associated with GET. Participants wore bi-polar surface EMG electrodes on their vastus lateralis for the measure overall muscle activation, EMG root mean square (RMS) and mean power frequency (MPF). Upon completion of the clamped RPE ride, signals were selected in two forms: 10 BURSTS were selected from each muscle contraction at min 3,5,7,9,11,13,15,17,19, and 21 of the exercise test. Data was selected from this period to avoid interference of potential muscular fatigue later in the ride. EPOCHs of signals around the same time points were selected in which the muscle contraction and relaxation period were included for processing. Following selection, signals were processed to calculate mean BURST and EPOCH RMS and MPF around each cycling time point. Bland-Altman analysis was applied to determine mean bias as well as 95% confidence intervals between these two methods. RESULTS: Bland-Altman analysis for EMG RMS from minutes 3 to 21 displayed a substantial negative bias, with the EPOCH method consistently underestimating RMS values compared to the BURST method, showing a mean difference of approximately -50 units. Although most differences were within the 95% limits of agreement, the narrow confidence interval for the bias indicates a persistent systematic error. In contrast, the Bland-Altman analysis for EMG MPF from minutes 3 to 21 showed a small, consistent bias, with a mean difference close to zero. CONCLUSION: These findings suggest that while both methods are effective for assessing muscle activation in dynamic cycling, the EPOCH method may significantly underestimate RMS, making it less suitable for evaluating non-static muscle activity. Therefore, the data supports the use of BURST over EPOCH analysis for dynamic muscle contractions when RMS is a variable to interest.