Counting twitches: automated mechanomyography of muscle fatigue in healthy adults

Abstract Background Assessing skeletal muscle fatigue is essential for diagnosing neuromuscular impairment, but conventional methods rely on maximal or tetanic contractions that can be impractical or uncomfortable in clinical populations. Surface mechanomyography (MMG) provides a non-invasive alternative; however, current MMG-based fatigue protocols require time-consuming manual peak-to-peak analysis. This study evaluated an automated algorithm for extracting MMG-derived fatigue metrics from electrically evoked muscle twitches. Methods Eighteen healthy adults completed a standardized fatigue protocol on the wrist extensors and ankle dorsiflexors using electrical stimulation at 2, 4, and 6 Hz over 9 min. A triaxial accelerometer captured MMG signals from > 2,100 contractions per muscle (approximately 4,320 per participant across the two muscles). A custom algorithm automatically extracted peak-to-peak values and computed the endurance index; the mean contraction amplitude was derived from peak and trough points identified manually by the research team. Repeated-measures ANOVAs assessed differences across stimulation frequencies and muscle groups. Results Endurance index declined significantly across the fixed ascending 2-, 4-, and 6-Hz stimulation sequence ( p < 0.001) and was lower in ankle dorsiflexors than wrist extensors ( p = 0.010), averaging approximately 6% points lower across frequencies. Mean contraction amplitude was significantly lower in the dorsiflexors ( p < 0.001) and greater at 6 Hz than at 2–4 Hz ( p < 0.001). Conclusion This study demonstrates the feasibility of an automated peak-to-peak extraction algorithm for deriving the MMG-based endurance index, enabling rapid processing of > 2,100 contractions per muscle. The mean contraction amplitude reported here was measured manually, and extending automated extraction to that measure remains to be implemented. The combination of the endurance index and the mean contraction amplitude provides a dual-metric approach to characterizing muscle performance. As a feasibility study in healthy adults, it does not establish clinical validity. Future work should validate the algorithm against manual methods and test it in clinical populations, including patients with ICU-acquired weakness.