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Smart Electrically Assisted Bicycles as Health Monitoring Systems: A Review.
Avina-Bravo, Eli Gabriel; Cassirame, Johan; Escriba, Christophe; Acco, Pascal; Fourniols, Jean-Yves; Soto-Romero, Georges.
  • Avina-Bravo EG; Laboratory for Analysis and Architecture of Systems (LAAS), University of Toulouse, F-31077 Toulouse, France.
  • Cassirame J; EA4660, Culture, Sport, Health and Society Department and Exercise Performance, University of Bourgogne-France Comté, 25000 Besançon, France.
  • Escriba C; EA7507, Laboratoire Performance Santé Métrologie Société, 51100 Reims, France.
  • Acco P; Société Mtraining, R&D Division, 25480 Ecole Valentin, France.
  • Fourniols JY; Laboratory for Analysis and Architecture of Systems (LAAS), University of Toulouse, F-31077 Toulouse, France.
  • Soto-Romero G; Laboratory for Analysis and Architecture of Systems (LAAS), University of Toulouse, F-31077 Toulouse, France.
Sensors (Basel) ; 22(2)2022 Jan 08.
Article in English | MEDLINE | ID: covidwho-1630027
ABSTRACT
This paper aims to provide a review of the electrically assisted bicycles (also known as e-bikes) used for recovery of the rider's physical and physiological information, monitoring of their health state, and adjusting the "medical" assistance accordingly. E-bikes have proven to be an excellent way to do physical activity while commuting, thus improving the user's health and reducing air pollutant emissions. Such devices can also be seen as the first step to help unhealthy sedentary people to start exercising with reduced strain. Based on this analysis, the need to have e-bikes with artificial intelligence (AI) systems that recover and processe a large amount of data is discussed in depth. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were used to complete the relevant papers' search and selection in this systematic review.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Bicycling / Artificial Intelligence Type of study: Reviews / Systematic review/Meta Analysis Limits: Humans Language: English Year: 2022 Document Type: Article Affiliation country: S22020468

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Bicycling / Artificial Intelligence Type of study: Reviews / Systematic review/Meta Analysis Limits: Humans Language: English Year: 2022 Document Type: Article Affiliation country: S22020468