Postural Adjustment

Postural adjustment research focuses on understanding and improving how humans and robots maintain and correct their posture, aiming to enhance stability, efficiency, and ergonomics. Current research employs diverse approaches, including transformer networks for human pose analysis and correction, convolutional and graph convolutional networks for image-based posture adjustments, and bio-inspired designs for robotic systems. These advancements have implications for various fields, such as improving human-robot interaction, preventing work-related musculoskeletal disorders, and developing assistive technologies for individuals with mobility impairments. The development of accurate and computationally efficient ergonomic assessment models is also a key area of focus.