Mobile and wearable devices have enabled numerous applications, including activity
tracking, wellness monitoring, and human–computer interaction, that measure and improve …

Background: Thanks to the rapid development of computer-based systems and deep-
learning-based algorithms, artificial intelligence (AI) has long been integrated into the …

Human activity recognition is essential in many domains, including the medical and smart
home sectors. Using deep learning, we conduct a comprehensive survey of current state …

Amputation of the upper limb brings heavy burden to amputees, reduces their quality of life,
and limits their performance in activities of daily life. The realization of natural control for …

The journey of a prosthetic user is characterized by the opportunities and the limitations of a
device that should enable activities of daily living (ADL). In particular, experiencing a bionic …

Electromyogram (EMG) signals have been increasingly used for hand and finger gesture
recognition. However, most studies have focused on the wrist and whole-hand gestures and …

Designing efficient and labor-saving prosthetic hands requires powerful hand gesture
recognition algorithms that can achieve high accuracy with limited complexity and latency. In …

Surface electromyography (EMG) is one of the promising signals for the recognition of the
intended hand movement of an amputee. Nevertheless, there are several barriers to its …

Human activity recognition (HAR) has become increasingly popular in recent years due to its
potential to meet the growing needs of various industries. Electromyography (EMG) is …

Wearables developed for human body signal detection receive increasing attention in the
current decade. Compared to implantable sensors, wearables are more focused on body …