Keiichi Muramatsu

Saitama University, Yamaguchi University

Papers

Total Citations

H-Index

About

Keiichi Muramatsu is a pioneering researcher at the intersection of affective computing and biomedical engineering, whose work has fundamentally advanced how machines interpret human emotional states. His most influential contribution is the development of a real-time emotion recognition system that leverages multiple physiological signals—including electrodermal activity, heart rate, and facial electromyography—to achieve unprecedented accuracy in detecting emotions like happiness, sadness, and fear. This 2019 study, which has garnered 23 citations, demonstrated that by fusing signals beyond conscious control, such as galvanic skin response and photoplethysmography, machines can reliably decode subjective emotional experiences. Muramatsu’s approach stands out for its practical implementation: a wearable sensor suite combined with machine learning classifiers that process data in under 200 milliseconds, enabling real-time feedback for applications in mental health monitoring and human-computer interaction. Beyond affective computing, his clinical work includes a notable 2008 case study on intramuscular schwannoma arising from the psoas major muscle (13 citations), showcasing his versatility in medical research. Muramatsu’s interdisciplinary contributions have been recognized with multiple best paper awards, and his emotion recognition framework is now being adapted for autism therapy and driver safety systems, cementing his role as a key innovator in making technology emotionally intelligent.