Analysis and Clustering of Upper Limb Motion during the Hand Dexterity Pegboard Test using Inertial Sensor Systems

Area of Science:

• Biomechanics
• Human Motor Control
• Robotics

Background:

• Maintaining hand and upper limb mobility is vital for daily life and work performance.
• Limited research has detailed hand and finger movements during complex tasks.
• Understanding upper limb motion is key to assessing and enhancing dexterity.

Purpose of the Study:

• To analyze upper limb and hand motion during a pegboard dexterity test.
• To identify distinct movement characteristics in different phases of the peg-in-hole task.
• To clarify joint coordination patterns for improved dexterity.

Main Methods:

• Utilized inertial sensor systems to measure upper limb motion during a pegboard test.
• Segmented peg-in-hole motion into pinch, and carry-insert sections.
• Applied singular value decomposition (SVD) to joint angle data, grouped by arm and finger segments.
• Clustered SVD results across multiple trials and subjects to identify common movement patterns.

Main Results:

• Singular value decomposition revealed distinct joint coordination patterns in the pinch and carry-insert sections.
• Clustering and averaging of SVD results clarified joint distributions and combinations.
• Recalculated joint angles and animation highlighted key characteristics for enhanced dexterity.
• High dexterity motion characteristics were identified in specific phases of the pegboard test.

Conclusions:

• The study successfully characterized upper limb motion during a pegboard test, differentiating movement strategies.
• Distinct joint coordination patterns in the pinch and carry-insert sections are indicative of high dexterity.
• The findings provide insights for developing interventions or technologies to improve hand and upper limb function.