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In this study, a new way to predict the muscle fatigue and force from Electromyography (EMG) signal for repeated isokinetic exercise is demonstrated. The relationship between cumulative biceps fatigue and EMG signal during repetitive dumbbell curl tasks with constant velocity was investigated with respect to Maximum voluntary contraction (MVC) levels (20 %, 35 %, 50 % and 75 % MVC). The mean integrated EMG and mean frequency per cycle were obtained from the time domain and frequency domain, respectively. The mean IEMG value and mean frequency values were co-plotted in the global EMG index map. Finally, we developed a new algorithm to predict muscle fatigue and force based on a global EMG index map employing mean IEMG and MNF values. The proposed algorithm based on a global EMG index map can be used to simultaneously predict muscle fatigue and force from real-time EMG signals with arbitrary MVC levels. [ABSTRACT FROM AUTHOR]

Cadavers are often used to measure the material properties of muscle via the static tensile loading test. However, the mechanical properties of the cadaver are different from that of in vivo muscle. In this work, a new way to measure the stiffness of in vivo muscle was proposed based on a vibration test combined with measured electromyography (EMG) signals. The stiffness of the biceps brachii muscle during isometric contractions with various weights (0 - 11 kg) was measured from the vibration test utilizing support properties of a spring attached to a mass. The relationship between the load level, the EMG signal, and the muscle stiffness was investigated and a multiple- spring model for biceps brachii muscle was newly suggested. Also, simulation using a commercial bio-mechanics simulation software (LifeMOD) was conducted to verify the developed muscle spring model and the measured stiffness of the in vivo muscle. The in vivo stiffness of the biceps brachii measured experimentally agreed well with the simulation result. [ABSTRACT FROM AUTHOR]