In domains such as medical and healthcare, the interpretability and explainability of
machine learning and artificial intelligence systems are crucial for building trust in their …

The integration of machine/deep learning and sensing technologies is transforming
healthcare and medical practice. However, inherent limitations in healthcare data, namely …

Recently proposed legal frameworks for Artificial Intelligence (AI) depart from some
frameworks of concepts regarding ethical and trustworthy AI that provide the technical …

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 …

Over the past decade, the utilization of machine learning (ML) models for recognizing hand
gestures from surface electromyography (sEMG) signals has been in demand for the control …

Inadequate training poses a significant risk of injury among young firefighters. Although
Human Activity Recognition (HAR) algorithms have shown potential in monitoring and …

Recently, lower limb activity recognition (LLAR) based on surface electromyography (sEMG)
signal has attracted increasing attention, mainly due to its applications in the control of …

Lower limb activity recognition utilizing body sensor data has attracted researchers due to its
practical applications, such as neuromuscular disease detection and kinesiological …

This article develops a novel distributed framework based on physics-informed deep
learning for robust and efficient musculoskeletal modeling in nonstationary scenarios, which …

This systematic literature review employs the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses (PRISMA) methodology to investigate recent applications of …