How Stable Are Temporal EMG Parameters in Rowing? A Seven-Day Test–Retest Reliability Study Using Wearable sEMG

Surface electromyography (sEMG), increasingly delivered through wireless wearable systems, is a key non-invasive tool for the objective monitoring of muscle activation during repetitive motor tasks. The clinical and longitudinal usefulness of wearable sEMG during rowing depends on the test–retest reliability of the parameters extracted from the signal during high-intensity, multi-muscle cyclic locomotor tasks. This study aimed to use advanced sEMG processing to quantify the between-session reliability of EMG-derived parameters (onset, offset, active duration, and peak position) across seven major muscles, to characterize the between-session similarity of ensemble-averaged activation waveforms, and to describe within-trial activation dynamics. Fifteen competitive rowers (10 males, five females; aged 14–22 years) performed two identical 2000 m all-out trials seven days apart, with sEMG recorded by a wireless wearable system. Reliability was assessed by ICC(A,1) with 95% CIs, SEM, MDC95, CV%, and Bland–Altman analysis. The waveform similarity of the session ensemble cycles was quantified by Pearson correlation, cosine similarity, normalized cross-correlation maximum, and normalized dynamic time warping (DTW). Within-trial dynamics were assessed across ten consecutive stroke-count windows. Onset showed excellent reliability across all seven muscles (ICC = 0.943–0.995); offset, moderate-to-excellent (0.524–0.907); peak position, poor-to-excellent (0.114–0.948); active duration, poor-to-good (0.077–0.814). Ensemble-waveform similarity between sessions was high for each athlete across all muscles (Pearson r = 0.832–0.972; cosine similarity = 0.924–0.983), confirming that the individual activation fingerprint of the mean stroke cycle is stable over a 7-day interval. Both amplitude (FMPR) and active duration revealed a reproducible U-shaped within-trial pattern. These findings highlight the potential of wearable sEMG to provide reliable, personalized insights into rowing-specific muscle activation patterns, supporting more individualized monitoring and training optimization in rowers.