The field of surface electromyography (sEMG) has undergone a profound transformation over recent decades, evolving from a specialized laboratory tool to a versatile instrument widely utilized in rehabilitation, sports science, and occupational health. Initially confined to academic research for analyzing superficial muscle electrical activity, sEMG has benefited from technological advancements that extend its clinical applications, enabling non-invasive assessments of voluntary muscle contractions in dynamic settings. These innovations include high-density wearable sensors, improved signal processing algorithms to handle inter-subject variability, and integration with real-time biofeedback systems, making it accessible beyond research labs [1,2,3,4]. Recent studies have highlighted sEMG`s critical role in continuous monitoring for rehabilitation, such as post-surgical recovery and neurodegenerative disease management, where it enhances diagnostic precision and personalized therapy. In sports, sEMG supports biomechanical analysis and injury prevention by evaluating muscle activation patterns during complex movements like running or skating. Similarly, in occupational health, it detects ergonomic risks from load handling, identifying muscle fatigue and abnormal co-activations to prevent musculoskeletal disorders [5,6,7,8]. This transformation addresses longstanding challenges, including signal artifacts from motion and the need for robust normalization methods like MVC or submaximal contractions, ensuring reliability in daily practice. Wearable sEMG systems now facilitate ecological validity, bridging the gap between controlled experiments and real-world applications in diverse fields [9,10]. This Special Issue, entitled "EMG Signal Acquisition, Processing and Analysis: From Research to Daily Practice in the Rehabilitation, Sports, and Occupational Fields," was conceived to explore the delicate balance between high-quality data acquisition and practical usability for non-researcher professionals.
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