Electrical properties of muscles have been under intense scientific and clinical investigation for decades. From the neurophysiologic point of view, it is essential to achieve a deeper understanding of neuromuscular alterations and of their relation to work condition, immobilization, overtraining and microgravity. Measurable indicators of incipient degeneration, effectiveness of treatment, and preventive actions are required to practice evidence based medicine, rehabilitation and training of athletes. Technical difficulties associated with recording and analysis of electromyograms have limited the accuracy with which the characteristics of individual motor units can be established during movements. The existing information extraction techniques have mainly been applied to the isometric muscle contractions, with the muscle geometry kept constant during the measurement session. On the other hand, the contractions of human muscles are almost always dynamic, with the muscle moving with respect to the skin. The main objective of the iMOVE project is to design and implement automated signal processing techniques capable of extracting the information about the individual motor units from the dynamic surface electromyograms recorded during controlled dynamic contractions of skeletal muscles, to study the feasibility, efficiency and repeatability of information extraction during movements, and to define the recommendations for sensors, sensor placement and signal processing in dynamic conditions. Possible collateral applications of the proposed project include objective assessment of effectiveness of rehabilitation and training of athletes, prevention of work-related neuromuscular disorders and diseases, and monitoring of the musculoskeletal deterioration in the microgravity environment.