Evidence map›Paper›PMID 35062429›Full record

SynthesisSensors (Basel, Switzerland)2022

Smart Electrically Assisted Bicycles as Health Monitoring Systems: A Review.

Eli Gabriel Avina-Bravo, Johan Cassirame, Christophe Escriba, Pascal Acco, Jean-Yves Fourniols, Georges Soto-Romero

Abstract readSystematic Review
In one paragraph

Synthesis in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Eli Gabriel Avina-BravoLaboratory for Analysis and Architecture of Systems (LAAS), University of Toulouse, F-31077 Toulouse, France.ORCID 0000-0002-5900-3973
Johan CassirameEA4660, Culture, Sport, Health and Society Department and Exercise Performance, University of Bourgogne-France Comté, 25000 Besançon, France.ORCID 0000-0002-6116-5795
Christophe EscribaLaboratory for Analysis and Architecture of Systems (LAAS), University of Toulouse, F-31077 Toulouse, France.ORCID 0000-0002-8054-714X
Pascal AccoLaboratory for Analysis and Architecture of Systems (LAAS), University of Toulouse, F-31077 Toulouse, France.ORCID 0000-0002-6563-0842
Jean-Yves FourniolsLaboratory for Analysis and Architecture of Systems (LAAS), University of Toulouse, F-31077 Toulouse, France.
Georges Soto-RomeroLaboratory for Analysis and Architecture of Systems (LAAS), University of Toulouse, F-31077 Toulouse, France.ORCID 0000-0002-3823-1635

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Artificial IntelligenceBicyclingAccidents, TrafficElectricityHumansTransportatione-bikehealthintelligent sensorsmonitoring systemsphysical activityphysiology

Identifiers

PMID35062429
PMCPMC8780236

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.