| Title: |
Smart Electrically Assisted Bicycles as Health Monitoring Systems: A Review |
| Authors: |
Aviña Bravo, Eli Gabriel; Cassirame, Johan; Escriba, Christophe; Acco, Pascal; Fourniols, Jean-Yves; Soto-Romero, Georges |
| Contributors: |
Équipe Instrumentation embarquée et systèmes de surveillance intelligents (LAAS-S4M); Laboratoire d'analyse et d'architecture des systèmes (LAAS); Université Toulouse Capitole (UT Capitole); Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse); Institut National des Sciences Appliquées (INSA)-Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Institut National des Sciences Appliquées (INSA)-Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Université Toulouse - Jean Jaurès (UT2J); Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Université Toulouse III - Paul Sabatier (UT3); Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP); Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Université Toulouse Capitole (UT Capitole); Communauté d'universités et établissements de Toulouse (Comue de Toulouse); Laboratoire Culture, sport, santé, société - UFC (UR 4660) (C3S); Université de Franche-Comté (UFC); Université Bourgogne Franche-Comté COMUE (UBFC)-Université Bourgogne Franche-Comté COMUE (UBFC) |
| Source: |
ISSN: 1424-8220 ; Sensors ; https://laas.hal.science/hal-03546127 ; Sensors, 2022, 22 (2), pp.468. ⟨10.3390/s22020468⟩ ; https://www.mdpi.com/1424-8220/22/2/468. |
| Publisher Information: |
CCSD; MDPI |
| Publication Year: |
2022 |
| Collection: |
Université Toulouse III - Paul Sabatier: HAL-UPS |
| Subject Terms: |
health; e-bike; physical activity; physiology; monitoring systems; intelligent sensors; [INFO.INFO-ES]Computer Science [cs]/Embedded Systems; [SPI.TRON]Engineering Sciences [physics]/Electronics; [SDV.IB]Life Sciences [q-bio]/Bioengineering |
| Description: |
International audience ; 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. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| Relation: |
PUBMEDCENTRAL: PMC8780236 |
| DOI: |
10.3390/s22020468 |
| Availability: |
https://laas.hal.science/hal-03546127; https://laas.hal.science/hal-03546127v1/document; https://laas.hal.science/hal-03546127v1/file/sensors-22-00468.pdf; https://doi.org/10.3390/s22020468 |
| Rights: |
info:eu-repo/semantics/OpenAccess |
| Accession Number: |
edsbas.335C4804 |
| Database: |
BASE |