Evidence map›Paper›PMID 22163600›Full record

ArticleSensors (Basel, Switzerland)2010

Correlating multimodal physical sensor information with biological analysis in ultra endurance cycling.

Gregory C May, Aiden R Doherty, Alan F Smeaton, Giles D Warrington

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 31% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. 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

4 authors at 2 institutions in 1 country.

Gregory C MayCentre for Sensor Web Technologies Dublin City University, Glasnevin, Dublin 9, Ireland. gregory.c.may@gmail.com
Aiden R Doherty
Alan F Smeaton
Giles D Warrington
Dublin City University · IEClarity Centre for Sensor Web Technologies · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The sporting domain has traditionally been used as a testing ground for new technologies which subsequently make their way into the public domain. This includes sensors. In this article a range of physical and biological sensors deployed in a 64 hour ultra-endurance non-stop cycling race are described. A novel algorithm to estimate the energy expenditure while cycling and resting during the event are outlined. Initial analysis in this noisy domain of "sensors in the field" are very encouraging and represent a first with respect to cycling.

Indexed as

AlgorithmsAthletesBicyclingBiosensing TechniquesBlood Cell CountEnergy MetabolismHumansPhysical EnduranceReproducibility of ResultsStatistics as Topicbody sensorscycling event detectionestimating energy expenditureultra-endurance cycling

Identifiers

PMID22163600
PMCPMC3231179
OpenAlexW2052567164

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.