Literature DB >> 22436093

A new metric for quantifying performance impairment on the psychomotor vigilance test.

Srinivasan Rajaraman1, Sridhar Ramakrishnan, David Thorsley, Nancy J Wesensten, Thomas J Balkin, Jaques Reifman.   

Abstract

We have developed a new psychomotor vigilance test (PVT) metric for quantifying the effects of sleep loss on performance impairment. The new metric quantifies performance impairment by estimating the probability density of response times (RTs) in a PVT session, and then considering deviations of the density relative to that of a baseline-session density. Results from a controlled laboratory study involving 12 healthy adults subjected to 85 h of extended wakefulness, followed by 12 h of recovery sleep, revealed that the group performance variability based on the new metric remained relatively uniform throughout wakefulness. In contrast, the variability of PVT lapses, mean RT, median RT and (to a lesser extent) mean speed showed strong time-of-day effects, with the PVT lapse variability changing with time of day depending on the selected threshold. Our analysis suggests that the new metric captures more effectively the homeostatic and circadian process underlying sleep regulation than the other metrics, both directly in terms of larger effect sizes (4-61% larger) and indirectly through improved fits to the two-process model (9-67% larger coefficient of determination). Although the trend of the mean speed results followed those of the new metric, we found that mean speed yields significantly smaller (∼50%) intersubject performance variance than the other metrics. Based on these findings, and that the new metric considers performance changes based on the entire set of responses relative to a baseline, we conclude that it provides a number of potential advantages over the traditional PVT metrics.
© 2012 European Sleep Research Society.

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Year:  2012        PMID: 22436093     DOI: 10.1111/j.1365-2869.2012.01008.x

Source DB:  PubMed          Journal:  J Sleep Res        ISSN: 0962-1105            Impact factor:   3.981


  6 in total

1.  A Unified Model of Performance for Predicting the Effects of Sleep and Caffeine.

Authors:  Sridhar Ramakrishnan; Nancy J Wesensten; Gary H Kamimori; James E Moon; Thomas J Balkin; Jaques Reifman
Journal:  Sleep       Date:  2016-10-01       Impact factor: 5.849

2.  Improved Mental Acuity Forecasting with an Individualized Quantitative Sleep Model.

Authors:  Brent D Winslow; Nam Nguyen; Kimberly E Venta
Journal:  Front Neurol       Date:  2017-04-25       Impact factor: 4.003

3.  Classifying attentional vulnerability to total sleep deprivation using baseline features of Psychomotor Vigilance Test performance.

Authors:  Eric Chern-Pin Chua; Jason P Sullivan; Jeanne F Duffy; Elizabeth B Klerman; Steven W Lockley; Bruce S Kristal; Charles A Czeisler; Joshua J Gooley
Journal:  Sci Rep       Date:  2019-08-20       Impact factor: 4.379

4.  Effect of moderate and Severe Hypoxic exposure coupled with fatigue on psychomotor vigilance testing, muscle tissue oxygenation, and muscular performance.

Authors:  Cory M Smith; Owen F Salmon; Jasmin R Jenkins
Journal:  Curr Res Physiol       Date:  2021-11-04

5.  PC-PVT: a platform for psychomotor vigilance task testing, analysis, and prediction.

Authors:  Maxim Y Khitrov; Srinivas Laxminarayan; David Thorsley; Sridhar Ramakrishnan; Srinivasan Rajaraman; Nancy J Wesensten; Jaques Reifman
Journal:  Behav Res Methods       Date:  2014-03

6.  The influence of vibration on seated human drowsiness.

Authors:  Amzar Azizan; Mohammad Fard; Michael F Azari; Bryndís Benediktsdóttir; Erna Sif Arnardóttir; Reza Jazar; Setsuo Maeda
Journal:  Ind Health       Date:  2016-01-30       Impact factor: 2.179

  6 in total

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