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The increased popularization of cycling has brought an increase in cycling-related injuries, which has been suggested to be associated with muscle fatigue. However, it still remains unclear on the utility of different EMG indices in muscle fatigue evaluation induced by cycling exercise. In this study, ten cyclist volunteers performed a 30-second all-out cycling exercise after a warm-up period. Surface electromyography (sEMG) from vastus lateralis muscle (VL) and power output and cadence were recorded and EMG RMS, MF and MPF based on Fourier Transform, MDF and MNF based on wavelet packet transformation, and C(n) based on Lempel–Ziv complexity algorithm were calculated. Utility of the indices was compared based on the grey rational grade of sEMG indices and power output and cadence. The results suggested that MNF derived from wavelet packet transformation was significantly higher than other EMG indices, indicating the potential application for fatigue evaluation induced by all-out cycling exercise.

Herein, we demonstrate that iron oxide modified MnO2 (FeOx-MnO2) catalyzed micromotors can be fabricated via electrochemical co-reduction and exhibit exceptional high performance at an extremely low hydrogen peroxide (H2O2) fuel concentration. We observed that graphene/FeOx-MnO2 microtubes could show motion behaviors at fuel concentration as low as 0.03% H2O2, which is nearly one order of magnitude lower than Pt-based micromotors (normally at above 0.2% H2O2). Moreover, the micromotors exhibit higher speeds than any other reported catalytic micro/nanomotors (MNMs) at low peroxide levels. The FeOx-MnO2 systems are better catalytic MNMs, due to their excellent catalytic activity, easy fabrication, robust structure and movement, as well as low-cost, biocompatible and abundance nature, showing great potential for future applications.

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