AI-Enabled Muscle Oxygen Sensors for Personalized Exercise Intensity Monitoring and Recovery Analysis
Through the integration of artificial intelligence (AI) with muscle oxygen sensors, this work presents a unique way to exercise intensity monitoring and recovery analysis. Subjective assessments or heavy equipment are the backbone of the traditional approaches to evaluating exercise intensity and recovery. Using the latest developments in AI and wearable sensor technology, our system offers real-time personalized feedback to athletes and fitness enthusiasts. Our Muscle oxygen sensors were vigorously tested to ensure their precision and performance. Wearing the sensors, participants varied their workout regimen while the sensors sent data on the participants' muscle oxygen levels to an AI program. According to the results, the algorithm could correctly determine workout intensity levels and establish individual recuperation timeframes. Moreover, the AI system learns the user's physiological traits and can personalize recommendations and training programs for everyone. Our approach may help improve athletic performance, avoid overtraining injuries, and maximize fitness results by giving practical advice on recovering from exercises at the right intensity.
Authors
- Sree Southry S
- K. Balasubadra
- Balachander Kannan (ORCID: https://orcid.org/0000-0002-9630-7001)
- S. Sakthivel Murugan (ORCID: https://orcid.org/0000-0002-3777-8807)
- B. Meenakshi
- Bharat Tidke
Institutions
- Sri Ramachandra Institute of Higher Education and Research (IN)
- Symbiosis International University (IN)
- R.M.D. Engineering College
- Saveetha University (IN)
Publication Details
- Published
- 2025-01-09
- DOI
- https://doi.org/10.1109/icaect63952.2025.10958953
- Citations
- 6
- Primary Topic
- Cardiovascular and exercise physiology
- Type
- article
- Field-Weighted Citation Impact
- 14.29