Hayato Nagayoshi

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About

Hayato Nagayoshi is a leading researcher in affective computing and biomedical signal processing, whose work focuses on the objective quantification of human emotion through physiological data. His major contributions center on developing real-time, non-invasive systems that decode emotional states from multiple biosignals, including electrodermal activity, heart rate variability, and facial electromyography. In his highly cited 2019 study, "Real-time emotion recognition system with multiple physiological signals" (23 citations), Nagayoshi demonstrated that physiological signals—being involuntary and strongly correlated with subjective experience—offer a more authentic measure of emotion than behavioral cues. Expanding on this, his 2018 paper "Two-Dimensional Emotion Evaluation with Multiple Physiological Signals" (19 citations) introduced a framework for mapping emotions along valence-arousal dimensions, enabling nuanced classification beyond simple positive/negative dichotomies. Nagayoshi’s work has significant implications for human-computer interaction, mental health monitoring, and adaptive user interfaces. His research is distinguished by its emphasis on ecological validity and real-time implementation, bridging the gap between laboratory findings and practical applications. With a growing citation impact, Nagayoshi continues to advance the field by integrating machine learning with physiological sensing, paving the way for emotionally intelligent technologies that respond to users’ internal states.