Enhancing Running Exercise With IoT, Blockchain, and Heart Rate Adaptive Running Music

Yi Chen, Chung Chiang Chen, Li Chuan Tang, Wei Hua Chieng*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


This research proposes a music-adaptive IoT exercise system integrating edge computing and blockchain technology to enhance middle-distance running exercise. The system personalizes music tempo based on real-time biosignals to provide a tailored experience. Experiments demonstrate that adaptive music significantly augments users' physiological, psychological, and behavioral responses compared to no music, improving engagement and effectiveness. The system overcomes limitations in existing solutions regarding personalization, real-time adaptation, and data privacy. Edge computing enables on-device processing, and blockchain encryption guarantees security. Results highlight the benefits of HR adaptive running music for arousal, pleasure, and performance. This study offers insights into designing personalized, rewarding exercise systems using emerging technologies. It has promising implications for exercise, rehabilitation, and recreational fitness. Further work should investigate specific mechanisms and long-term impacts, integrate additional signals and music parameters, and enhance security. In conclusion, this innovative system combines IoT, adaptive music, edge computing, and blockchain to unlock new possibilities in exercise experiences.

Original languageEnglish
Pages (from-to)14168-14181
Number of pages14
JournalIEEE Access
StatePublished - 2024


  • IoT exercise system
  • adaptive music
  • blockchain
  • data privacy
  • secret sharing


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