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Smart Electrically Assisted Bicycles as Health Monitoring Systems: A Review
Eli Gabriel Avina-Bravo1, Johan Cassirame2,3,4, Christophe Escriba1
1Laboratory for Analysis and Architecture of Systems (LAAS), University of Toulouse, F-31077 Toulouse, France.
Sensors (Basel, Switzerland)
|January 22, 2022
Summary
This review explores how electrically assisted bicycles (e-bikes) can monitor rider health and adjust assistance. E-bikes offer a low-impact way to exercise, improving health and reducing emissions.
Area of Science:
- Sports Science
- Biomedical Engineering
- Public Health
Background:
- Electrically assisted bicycles (e-bikes) are increasingly used for commuting and physical activity.
- E-bikes offer a low-impact exercise option, beneficial for sedentary individuals and overall health.
- Monitoring rider physiological data can personalize e-bike assistance for health and rehabilitation.
Purpose of the Study:
- To review the application of e-bikes for collecting rider physical and physiological data.
- To explore the potential of e-bikes in health monitoring and personalized medical assistance.
- To discuss the integration of artificial intelligence (AI) in e-bikes for data processing and adaptive support.
Main Methods:
- Systematic review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.
- Comprehensive literature search for papers on e-bikes, health monitoring, and physiological data recovery.
- Analysis of existing research on e-bike functionalities and their health-related applications.
Main Results:
- E-bikes facilitate physical activity, contributing to improved user health and reduced environmental pollution.
- Data recovery and processing capabilities in e-bikes are crucial for personalized health monitoring.
- The integration of AI in e-bikes is essential for advanced data analysis and adaptive assistance.
Conclusions:
- E-bikes represent a promising tool for promoting physical activity and monitoring health.
- Future e-bike development should focus on AI integration for sophisticated data analysis and personalized user support.
- Further research is needed to fully realize the potential of AI-powered e-bikes in health and rehabilitation.
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