Analysis of dexterous finger movements for writing using a Hand Motion Capture system

Abstract

Motion capture (MoCap) technique that can digitize a position and a posture as a function of time is widely used in order to create animation and CG. It is very difficult to measure all hand movements because one hand has twenty-seven bones and nineteen joints. Therefore, it has been impossible to record the finger movements of a sports player that are high in speed and in accuracy. In this study, we developed a high accuracy ‘Hand MoCap system’ by using the electromagnetic tracker that used small and light receivers. The cables of the receivers were replaced with special thin cables so as not to block the movements of the fingers. In this paper, we have measured dexterous finger movements for writing of six skilled calligraphy teachers and six inexperience students. In order to analyze the finger movements, we have to know the relative positions between the receivers and the nib of a pen. We also developed a calibration method to make a transformation matrix by using the motion capture data. From the comparison of the motion capture data of the skilled teachers and the inexperience students, it made clear that the movement of thumb is a key for writing neatly.