Spatial muscle synergy-based network modeling and analysis of sit-to-stand transition with and without robot assistance

Abstract

The sit-to-stand (STS) transition is crucial for daily activities, and it is particularly challenging for those with physical disabilities. This paper investigates the dynamics of muscle synergy networks during the STS transition, comparing self-executed STS with robotic assistance. Six subjects participated in the study, performing STS with and without robotic assistance. Muscle coordination was assessed using electromyography data from the trunk, thigh, and shank muscles. Non-negative matrix factorization (NMF) was employed to extract muscle coordination patterns, revealing distinctions in the number of synergies between self- and robot-STS. Spatial muscle synergy analysis indicated significant differences between self- and robot-STS, emphasizing alterations in muscle activation patterns due to robotic assistance. Detailed muscle-level analysis highlighted specific muscles' modulation, particularly in the shank, thigh, and trunk regions. Network analysis demonstrated variations in coordination network connectivity and stability between self- and robot-assisted STS. Centrality measures identified specific muscles, such as vastus lateralis, playing a crucial role in dynamic correlations within the muscle synergy network during STS. The findings suggest adaptability in human motor system responses to external assistance, with implications for refining robotic assistance strategies to align with natural movement patterns. Future research could involve a more diverse participant pool and explore upper-limb support.