This reprint focuses on recent advances in the processing of surface electromyography (EMG) signals acquired during human movement, as well as on innovative approaches to sense muscle activity. A wide range of methods is examined, including machine learning techniques to detect the onset/offset timing of muscle activity and approaches to evaluate muscle fatigue and analyze muscle synergies and co-contractions. Applications of these techniques are explored in different medical scenarios, e.g., for the benefit of patients suffering from low back pain, stroke survivors, and patients requiring polysomnography.