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Learning Process of Bimanual Coordination
Yukihito Suzuki,Hiroki Takase,Yaodong Pan,Jun Ishikawa,Katsuhisa Furuta 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
There are many systems that need sophisticated skills for operation. Operators must practice very well before actually operating systems, such as cranes, helicopters, and so on. We focus on two hand (bimanual) operation of human in this research. In the bimanual operation, motion of one hand of a low-skilled operator tends to suffer interfering in motion of the other hand. We have already identified human bimanual dynamic characteristics based on experimental results. However, learning process during bimanual operation was not clarified in the previous research. Therefore, in this research, we clarified the learning process by a simple task, i.e., bimanually moving grips on XY-stages back and forth only. In the experiment, subjects simultaneously moved one hand back and forth at 0:3[Hz] and the other at 0:5[Hz]. We divided subjects into two groups: Learning process A (LP A) and Learning process B (LP B). Subjects in LP A group conducts only manual operation without mechanical assistance, and those in LP B group conduct manual operation after a training guided by the XY-stages. It has been confirmed that subjects in LP B needed less number of trials than those in LP A to achieve the same performance trajectory.
Emotional Level of Sadness for Normal and Dementia Subjects by NIRS
Shinichi Yoshino,Katsuhisa Furuta,Tetsuo Shiotsuki,Yukihito Suzuki,Hideto Shimizu,Hiroki Takase 동국대학교 정보융합기술원 2010 International Journal of Assistive Robotics and Sy Vol.11 No.1
This paper proposes a method to measure the level of sadness by the 52 channels signals of near infrared spectroscopy (NIRS). Normal and dementia subjects are measured while they watch the sad video story. The analysis has been done by using the first principal component of 52 measured signals, and the paper proposes to classify sadness into two classes; sequence of emotional reactions defining ‘dynamic sadness’ and accumulation of sadness defining ‘static sadness’. Both represent the feeling of sadness. They are measured quantitatively by the power over the certain frequencies and the time average of principal components of the measured NIRS signals. The measured signals of the normal subjects show that weight distribution parameters are rather large in the prefrontal cortex area corresponding from 32 to 52 channels, which indicates the subjects understanding the story. This paper shows that the difference of the sad emotion between the normal and dementia subjects is found by using both time average and power of the first principal component of NIRS signals over the whole measurement time. These informations may be used to test brain activities of both normal and dementia subjects. The proposed approach can be used to measure other brain activities using NIRS signals.