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 …

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 …

Objective. This study aims to design and implement the first deep learning (DL) model to
classify subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state …

Thanks to the powerful capability of the feature extraction, deep learning has become a
promising technology for an increasing number of researchers to decode movements from …

Recently, human–machine interfaces (HMI) that make life convenient have been studied in
many fields. In particular, a hand gesture recognition (HGR) system, which can be …

Deep learning (DL) has made significant progress in hyperspectral target detection (HTD) in
recent years. However, the existing DL-based HTD methods generally generate numerous …

Transformer architectures have become increasingly popular in healthcare applications.
Through outstanding performance in natural language processing and superior capability to …

Currently, gesture recognition primarily utilizes Convolutional Neural Networks (CNNs) and
Recurrent Neural Networks (RNNs) among deep learning methods. However, the unique …

Physiological signals serve as indispensable clues for understanding various physiological
states of human bodies. Most existing works have focused on a single type of physiological …

With the development of signal analysis technology and artificial intelligence, surface
electromyography (sEMG) signal gesture recognition is widely used in rehabilitation therapy …