Decomposition and Reconstruction of Human Palm Movements
- Citation Author(s):
- Submitted by:
- chu dai
- Last updated:
- Fri, 05/12/2023 - 01:46
- Data Format:
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.
The dataset contains two different data, which are placed in two different data folders. One of the folders, called "preliminary_experiment_data", contains angle data of 18 hand joints of 4 subjects performing 28 daily tasks. The other folder, called "formal_experiment_data", contains angle data of 9 palm joints of 15 subjects performing 63 daily tasks. Detailed explanations about each data can be found inside each data folder.