Multimuscle Surface-EMG Characterization of Upper-Limb Fatigue During Repetitive Haptic Interaction for Health 5.0 Applications

Vollständiger Abstract

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Health 5.0 increasingly involves medical robots and haptic systems that sustain physical interaction with patients and clinicians. This proof-of-concept study examined fatigue-related surface electromyography (sEMG) spectral changes during a 400 s repetitive haptic-writing task in 20 adults. Five upper-limb muscles were monitored at 1000 Hz, and mean frequency (MNF) and median frequency (MDF) trajectories were summarized by fitted start-to-end spectral decline and combined into arm-level indices. MDF had the higher association with the archived participant-level fatigue-analysis score (r=0.954 versus r=0.783; Δr=0.171; Holm-adjusted p=0.0035). Small-sample influence analysis supported the stability of this within-sample ordering: after omitting each participant in turn, Δr remained positive in 20/20 analyses (range 0.125–0.218), although the exact paired label-swap sensitivity test remained inconclusive (p=0.082). Exploratory leave-one-participant-out calibration produced lower held-out error for MDF (MAE 4.38, RMSE 5.87 percentage points) than for MNF (MAE 9.24, RMSE 12.02 percentage points). The raw seven-category Q2 responses and the archived 0–100 analysis score are reported as separate data products because they are not numerically equivalent under direct linear rescaling. Accordingly, the results identify MDF as the more promising spectral summary for prospective validation in this task, rather than establishing universal superiority or numerical replacement of subjective fatigue. The experiment was a laboratory haptic-writing study and did not test a surgical robot, rehabilitation robot, patient population, or clinical controller; Health 5.0 is therefore presented as a translational motivation rather than a demonstrated application.