Abstract
As people’s lives become easier because of conveniences and richer in material assets, they may tend to worsen in terms of mental stress, resulting in physical conditions such as insomnia and related sleep disorders. Prior literature has advocated music as an efficacious way to reduce stress; however, only a few studies have connected music features with a combination of personal cognition factors and physiological signals. Kansei engineering considered personal cognition factors and physiological signals in user-oriented design. Based on this, this study aims to investigate and identify the music characteristics which can relax people and which comprise the most soothing music for therapeutic application. Our research used fuzzy c-means (FCM) clustering during analysis and conducted experiments to classify music accordingly. Results show that music with a low amplitude variability (in the range of 96-to-128 beats per minute (BPM)) generates the optimal positive feelings that can soothe the body and mind. With an eye toward developing this methodology as a promising new service for therapeutic music design, this study employed questionnaires and heart rate variability (HRV) signals to examine user experience (UX) at the products/service design stages. Our findings align with HRV data to confirm the consistency in psychology and physiology. A majority of study participants indicated they were drawn to the pragmatic elements of the endeavor. This study provides suggestions for the development of this service in relation to music therapy design, based on the analysis of music elements that indicate a strong positive direction for selecting music appropriate for therapeutic applications.