TY - GEN
T1 - Mid-Distance Running Exercise Assistance System via IoT and Exercise-oriented Music
AU - Chen, Yi
AU - Chen, Chung Chiang
AU - Tang, Li Chuan
AU - Chieng, Wei Hua
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This study explores the effectiveness of a music-assisted IoT exercise system specifically designed for mid-distance running. The primary objectives are to augment the sports experience, facilitate recovery, and surpass the benefits provided by existing solutions. This system ensures a personalized experience through real-time music tempo adaptation according to the heart rate (HR), exercise tracking, customizable music selection, adjustable parameters, and voice recognition technology for effortless completion of questionnaires. In our findings, we observed a significant interaction (p <0.05) in terms of Condition × Exercise Stage for HR, Rating of Perceived Exertion (RPE), Feeling Scale (FS), and Felt Arousal Scale (FAS). It suggests that exercise-oriented music considerably impacts physiological (HR), perceptual (RPE), and affective (FS, FAS) responses. Furthermore, tailored and enjoyable exercise experiences lead to an increase in positive arousal and a decrease in fatigue. The music-assisted IoT exercise system demonstrates potential as an efficacious instrument for promoting physical activity and enhancing health outcomes. Future work will concentrate on further exploring the impact of music on exercise performance and recovery, investigating other musical parameters, integrating sensors for capturing behavioral responses, and enhancing data privacy and security through blockchain technology.
AB - This study explores the effectiveness of a music-assisted IoT exercise system specifically designed for mid-distance running. The primary objectives are to augment the sports experience, facilitate recovery, and surpass the benefits provided by existing solutions. This system ensures a personalized experience through real-time music tempo adaptation according to the heart rate (HR), exercise tracking, customizable music selection, adjustable parameters, and voice recognition technology for effortless completion of questionnaires. In our findings, we observed a significant interaction (p <0.05) in terms of Condition × Exercise Stage for HR, Rating of Perceived Exertion (RPE), Feeling Scale (FS), and Felt Arousal Scale (FAS). It suggests that exercise-oriented music considerably impacts physiological (HR), perceptual (RPE), and affective (FS, FAS) responses. Furthermore, tailored and enjoyable exercise experiences lead to an increase in positive arousal and a decrease in fatigue. The music-assisted IoT exercise system demonstrates potential as an efficacious instrument for promoting physical activity and enhancing health outcomes. Future work will concentrate on further exploring the impact of music on exercise performance and recovery, investigating other musical parameters, integrating sensors for capturing behavioral responses, and enhancing data privacy and security through blockchain technology.
KW - exercise-oriented music
KW - Feeling Scale
KW - Felt Arousal Scale
KW - IoT exercise system
KW - rating of perceived exertion
UR - http://www.scopus.com/inward/record.url?scp=85166619831&partnerID=8YFLogxK
U2 - 10.1109/AIIoT58121.2023.10174324
DO - 10.1109/AIIoT58121.2023.10174324
M3 - Conference contribution
AN - SCOPUS:85166619831
T3 - 2023 IEEE World AI IoT Congress, AIIoT 2023
SP - 264
EP - 272
BT - 2023 IEEE World AI IoT Congress, AIIoT 2023
A2 - Chakrabarti, Satyajit
A2 - Paul, Rajashree
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE World AI IoT Congress, AIIoT 2023
Y2 - 7 June 2023 through 10 June 2023
ER -