Understanding neural control of movement necessitates a collaborative approach between
many disciplines, including biomechanics, neuroscience, and motor control. Biomechanics …

Learning effective continuous control policies in high-dimensional systems, including
musculoskeletal agents, remains a significant challenge. Over the course of biological …

Neuromechanical studies investigate how the nervous system interacts with the
musculoskeletal (MSK) system to generate volitional movements. Such studies have been …

Objective: Surface electromyography (sEMG) driven musculoskeletal models are promising
to be applied in the field of human-computer interaction. However, due to the individual …

Objective. Developing neural decoders robust to non-stationary conditions is essential to
ensure their long-term accuracy and stability. This is particularly important when decoding …

Manual dexterity has been considered one of the critical components for human evolution.
The ability to perform movements as simple as holding and rotating an object in the hand …

Computational models of musculoskeletal systems are essential tools for understanding
how muscles, tendons, bones, and actuation signals generate motion. In particular, the …

Markerless motion capture using computer vision and human pose estimation (HPE) has the
potential to expand access to precise movement analysis. This could greatly benefit …

Uphill movement is considered an important rehabilitation training activity, with the
estimation of its motion intentions based on human surface electromyography (sEMG) …

Objective. Intracortical brain–computer interfaces (iBCIs) aim to enable individuals with
paralysis to control the movement of virtual limbs and robotic arms. Because patients' …