Decomposition and Reconstruction of Human Palm Movements

• Published in: IEEE transactions on biomedical engineering 2023-11, Vol.PP (11), p.1-12
• Main Authors: Chu, Dai, Xiong, Caihua, Cai, Junjie, Zhang, Jiarui, Ma, Jiaji, Sun, Baiyang
• Format: Article
• Language: English
• Subjects: Decomposition; Eigen-movements; Hand (anatomy); human palm; Joints (anatomy); Kinematics; movement constitution; musculoskeletal structures; Palm; palm coordination characteristics
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/TBME.2023.3276079

Objective: The human hand is known to have excellent manipulation ability compared to other primate hands. Without the palm movements, the human hand would lose more than 40% of its functions. However, uncovering the constitution of palm movements is still a challenging problem involving kinesiology, physiology, and engineering science. Methods: By recording the palm joint angles during common grasping, gesturing, and manipulation tasks, we built a palm kinematic dataset. Then, a method for extracting the eigen-movements to characterize the common motion correlation relationships of palm joints was proposed to explore the palm movement constitution. Results: This study revealed a palm kinematic characteristic that we named the joint motion grouping coupling characteristic. During natural palm movements, there are several joint groups with a high degree of motor independence, while the movements of joints within each joint group are interdependent. Based on these characteristics, the palm movements can be decomposed into seven eigen-movements. The linear combinations of these eigen-movements can reconstruct more than 90% of palm movement ability. Moreover, combined with the palm musculoskeletal structures, we found that the revealed eigen-movements are associated with joint groups that are defined by muscular functions, which provided a meaningful context for palm movement decomposition. Conclusion: This paper suggests that some invariable characteristics underlie the variable palm motor behaviors and can be used to simplify palm movement generation. Significance: This paper provides important insights into palm kinematics, and helps facilitate motor function assessment and the development of better artificial hands.