# Research on Biomechanics, Motor Control and Learning of Human Movements
###### Abstract  
The discipline of biomechanics, devoted to understanding human movement, has ancient roots reaching back over 2300 years to the ancient Greek civilization [1; 2; 3]. However, its rapid development began between the mid-1960s and the 1970s [4; 5; 6]. During this period, researchers established biomechanics as the study of the structure and function of biological systems through mechanical principles [7]. From this pivotal era onward, biomechanics research into human movement has concentrated on two primary objectives: enhancing human performance and mitigating the injury risk associated with physical activities [8; 9; 10; 11; 12].  
Embedded within the broader domain of human movement science, biomechanics intersects significantly with two closely related fields: motor control [13; 14; 11] and motor learning [15; 16]. Motor control addresses the organization of major human systems--particularly the brain, muscles, and limbs, and sometimes external objects--in the execution of physical tasks to enable the precision required for motor skills, while motor learning concerns the acquisition of these skills over time, with a relatively permanent capacity for efficient performance established through repeated practice or training [17; 18; 19]. Together with biomechanics, these three areas converge to examine not only the structural mechanics of movement but also the neurological, muscular, and experiential factors that contribute to skilled motion.  
The convergence of biomechanics, motor control, and motor learning represents a rapidly advancing frontier in human movement science [20; 21; 22; 23]. This interdisciplinary intersection seeks to illuminate the fundamental mechanisms of human motion by exploring the biomechanical properties, control strategies, and adaptive learning processes that underpin the acquisition and refinement of skills. Through the integration of emerging methodologies and analytical tools, researchers are increasingly able to decode complex movement patterns and previously understudied motor skills--often intricate or acrobatic [24; 25; 26]--that were previously inaccessible but are essential for both athletic and functional performance. Furthermore, this approach reveals movement control patterns [27; 28; 26] that enhance performance by allowing us to improve training methods and develop injury prevention strategies for safer training [30; 31]. Understanding these elements promotes evidence-based learning and contributes to safer, more efficient physical training environments.  
This Special Issue presents recent advancements in cross-disciplinary research into biomechanics, motor control, and motor learning, highlighting the depth and diversity of contemporary work in this interdisciplinary field. The twelve articles included showcase a range of innovations, from novel analytical methodologies and artificial intelligence (AI) applications to biomechanics-based learning and training strategies, along with new perspectives on the application of biomechanical feedback. By focusing on biomechanically decoding motor control processes and enhancing motor learning and training methods, this collection sheds light on practical applications aimed at improving physical performance and reducing injury risk. The topics of this Special Issue span biomechanical analyses of complex skill acquisition to innovative AI approaches that support the use of personalized,data-driven feedback in practice. Additionally, this Issue underscores the value of biomechanics beyond sports, providing insights into occupational contexts and rehabilitation practices, where movement efficiency and injury resilience are essential. In summary, this collection offers a comprehensive exploration of human movement science, demonstrating how a multidisciplinary approach can drive significant advancements in human performance, safety, and well-being.