Data acquisition of hand and hand in an exoskeleton movements with artificial intelligence elements

Abstract

The study of hand movement properties is crucial in developing human-computer interfaces and robotic arms, especially within the context of Industry 4.0 and exoskeletons that support human movement. Despite advancements, there are research gaps regarding people with disabilities and children. Key challenges include maintaining hand and upper limb position, image quality in image analysis techniques, and protecting equipment from sudden movements in individuals with disabilities. To acquire hand motion data, sensor-based technologies are utilized, with Python and the OpenCV library commonly used for image analysis. Current research focuses on integrating XR technologies (VR, AR, MR) with environmental data acquisition, enabling the analysis of hand manipulation in interaction with surrounding objects.