Many researchers have used machine learning models to control artificial hands, walking
aids, assistance suits, etc., using the biological signal of electromyography (EMG). The use …

Electromyographic (EMG) signals sensed at the skin surface on the forearm can be used to
accurately infer wrist-hand poses. However this is only possible when the EMG sensors are …

Exoskeleton robot is a typical application to assist the motion of lower limbs. To make the
lower extremity exoskeleton more flexible, it is necessary to identify various motion …

This paper presents a way of acquiring a sparse signal by taking only a limited number of
samples; sampling and compression are performed in one step by the analog to information …

In this work, we introduce two novel methodologies to compute the envelope of superficial
electromyography signals. Our methods are based on the detection of activation and …

Surface electromyography (EMG) serves as a pivotal tool in hand gesture recognition and
human-computer interaction, offering a non-invasive means of signal acquisition. This study …

Electromyographic (EMG) signals provide information about muscle activity. In hand
movements, each gesture's execution involves the activation of different combinations of the …

Electromyographic (EMG) signals provide information about a person's muscle activity. For
hand movements, in particular, the execution of each gesture involves the activation of …

In order to solve the inaccuracy of age estimation dataset and the imbalance of age
distribution, this paper proposes an age estimation model based on the structured sparse …

Electromyographic (EMG) signals provide information about muscle activity. In hand
movements, each gesture's execution involves the activation of different combinations of the …