Biography: Dr. Keiichi Watanuki received his PhD in Department of Precision Machinery Engineering from Tokyo Institute of Technology, Japan, in 1991. From 1991, he was on the faculty of Mechanical Engineering at Saitama University, and from 2005, he has been a Professor of Mechanical Engineering at Saitama University. He also serves as Director, Area of Human-Machine Interaction Systems Engineering; Deputy Director-General, Research Management Bureau; Director, Advanced Institute of Innovative Technology; Director, Institute of Ambient Mobility Interfaces; and Professor, Brain and Body System Science Institute at Saitama University. Dr. Watanuki's research interests include systems design that support various human activities in the field of design and manufacturing. His main research interests are intelligent computer-aided design and manufacturing (CAD/CAM), design for environment, knowledge management and technology transfer, virtual reality/augmented reality (VR/AR), cognitive neuroscience, emotional engineering, human-machine interface (HMI), brain-machine interface (BMI), artificial intelligent (AI), internet of things (IoT), healthcare and medical technology, intelligent assistive technology, ambient mobility interface and intelligent robots. He has published over 190 articles in peer-reviewed core international proceedings and journals, 18 books and chapters, and 260 articles in engineering field. He is 29 awards recipient of JSME, JSDE, ASME, and so on.
Analysis of Brain Activity during Music Listening Using Near-Infrared Spectroscopy for Optimization of Music Therapy
Abstract: In recent years, the urgent need to develop methods for prevention and treatment of dementia and a decline in activities of daily living and chronic disease in elderly people in the super-aged society of Japan have been realized. Music therapy has been identified as a potential method for prevention and treatment of disease. Music therapy is a therapeutic pedagogical technique which is used in the treatment of cognitive and emotional disorders. Treatment with passive music therapy is easy; however, it is difficult to determine the effectiveness of different types of music. Therefore, in order to provide suitable music for each patient, an objective method for distinguishing emotional responses through measuring brain activity is necessary. In previous studies, measurement of cerebral activation while listening to music has been used to demonstrate how brain activity relates to experienced emotions. However, in these studies it is not clear which components of music contributed to the differences in brain activity and emotions. In this study, we measured brain activity using near-infrared spectroscopy during music listening and analyzed the effect of fundamental elements of music on brain activity. In our experiment, subjects listened to two kinds of harmony, five kinds of tempo, and six kinds of music that combined various tempos and keys. The results show that listening to different harmonies and rhythms elicits different patterns of brain activity and that each combination of keys and tempos also elicits different brain activity. These results reveal that the emotions experienced while listening to music can be distinguished by measuring brain activity.