Evidence map›Paper›PMID 31883068›Full record

ReviewSports medicine - open2019

A survey of mathematical models of human performance using power and energy.

Vijay Sarthy M Sreedhara, Gregory M Mocko, Randolph E Hutchison

Abstract readReview
In one paragraph

Review in Sports medicine - open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
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  4. Review
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  6. Review
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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

3 authors.

Vijay Sarthy M SreedharaDepartment of Mechanical Engineering, Clemson University, 243 Fluor Daniel EIB, Clemson, SC, 29634-0921, USA.ORCID http://orcid.org/0000-0002-8443-0854
Gregory M MockoDepartment of Mechanical Engineering, Clemson University, 243 Fluor Daniel EIB, Clemson, SC, 29634-0921, USA. gmocko@clemson.edu.ORCID http://orcid.org/0000-0001-8845-4581
Randolph E HutchisonDepartment of Health Sciences, Furman University, Greenville, SC, 29613, USA.ORCID http://orcid.org/0000-0002-2700-9254

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ability to predict the systematic decrease of power during physical exertion gives valuable insights into health, performance, and injury. This review surveys the research of power-based models of fatigue and recovery within the area of human performance. Upon a thorough review of available literature, it is observed that the two-parameter critical power model is most popular due to its simplicity. This two-parameter model is a hyperbolic relationship between power and time with critical power as the power-asymptote and the curvature constant denoted by W'. Critical power (CP) is a theoretical power output that can be sustained indefinitely by an individual, and the curvature constant (W') represents the amount of work that can be done above CP. Different methods and models have been validated to determine CP and W', most of which are algebraic manipulations of the two-parameter model. The models yield different CP and W' estimates for the same data depending on the regression fit and rounding off approximations. These estimates, at the subject level, have an inherent day-to-day variability called intra-individual variability (IIV) associated with them, which is not captured by any of the existing methods. This calls for a need for new methods to arrive at the IIV associated with CP and W'. Furthermore, existing models focus on the expenditure of W' for efforts above CP and do not model its recovery in the sub-CP domain. Thus, there is a need for methods and models that account for (i) the IIV to measure the effectiveness of individual training prescriptions and (ii) the recovery of W' to aid human performance optimization.

Indexed as

Critical powerEnergy expenditureFatigueHuman performance modelingRecoveryTime to exhaustion

Identifiers

PMID31883068
PMCPMC6934642

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Registered trials

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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.