| Sumario: | Purpose Muscle strength plays a key role in mobility and independent living in human aging processes. An effective evaluation method of muscle activation is important to estimate muscle strength and the effects of resistance exercise. However, there is a lack of reliable evaluation methods for muscle activation due to measurement errors from frequent muscle movements and variations of sensor positions on the body. The present study aims to propose two reliable indicators for evaluating muscle activation; one is by using surface electromyography (sEMG) signals (Heinonen et al., 2012), and the other is by utilizing Detection of Muscle Activation (DOMA; Son et al., 2018). Method There were two types of experiments. The first experiment was to examine upper limbic muscle activation based on the hand resistance exercise. Participants (N=3; 29-31 aged) did hand exercises using a hand gripper with three levels of strength (easy, moderate, hard) for 60s at each level. The second experiment was about thigh muscle activation to measure lower leg muscle activation based on the resistance walking exercise. The other participants (N=1; 31 aged) walked on the treadmill after wearing a wearable robot (GEMS-H; Lee et al., 2020) with resistance walking mode at the maximum resistance level for 30s. We got signals on muscle activation from sEMG and DoMA at the same time during experimental period. Results and Discussion There are commonalities and differences between signals from sEMG and signals from DoMA in the two experiments. The sEMG seems to measure whether muscle becomes activated or not, and DoMA seems to detect how many the muscle moved. Although there are variations depending on the location of the measured muscles, the results of sEMG and DoMA analyses suggest reliable indicators that can evaluate the activation of the closest muscles of each sensor.
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