Literature DB >> 28189461

Software thresholds alter the bias of actigraphy for monitoring sleep in team-sport athletes.

Kate L Fuller1, Laura Juliff2, Christopher J Gore3, Jeremiah J Peiffer2, Shona L Halson3.   

Abstract

OBJECTIVES: Actical® actigraphy is commonly used to monitor athlete sleep. The proprietary software, called Actiware®, processes data with three different sleep-wake thresholds (Low, Medium or High), but there is no standardisation regarding their use. The purpose of this study was to examine validity and bias of the sleep-wake thresholds for processing Actical® sleep data in team sport athletes.
DESIGN: Validation study comparing actigraph against accepted gold standard polysomnography (PSG).
METHODS: Sixty seven nights of sleep were recorded simultaneously with polysomnography and Actical® devices. Individual night data was compared across five sleep measures for each sleep-wake threshold using Actiware® software. Accuracy of each sleep-wake threshold compared with PSG was evaluated from mean bias with 95% confidence limits, Pearson moment-product correlation and associated standard error of estimate.
RESULTS: The Medium threshold generated the smallest mean bias compared with polysomnography for total sleep time (8.5min), sleep efficiency (1.8%) and wake after sleep onset (-4.1min); whereas the Low threshold had the smallest bias (7.5min) for wake bouts. Bias in sleep onset latency was the same across thresholds (-9.5min). The standard error of the estimate was similar across all thresholds; total sleep time ∼25min, sleep efficiency ∼4.5%, wake after sleep onset ∼21min, and wake bouts ∼8 counts.
CONCLUSIONS: Sleep parameters measured by the Actical® device are greatly influenced by the sleep-wake threshold applied. In the present study the Medium threshold produced the smallest bias for most parameters compared with PSG. Given the magnitude of measurement variability, confidence limits should be employed when interpreting changes in sleep parameters.
Copyright © 2017 Sports Medicine Australia. All rights reserved.

Entities:  

Keywords:  Accelerometry; Actical(®); Polysomnography; Validity

Mesh:

Year:  2017        PMID: 28189461     DOI: 10.1016/j.jsams.2016.11.021

Source DB:  PubMed          Journal:  J Sci Med Sport        ISSN: 1878-1861            Impact factor:   4.319


  14 in total

1.  Agreement between actigraphic and polysomnographic measures of sleep in adults with and without chronic conditions: A systematic review and meta-analysis.

Authors:  Samantha Conley; Andrea Knies; Janene Batten; Garrett Ash; Brienne Miner; Youri Hwang; Sangchoon Jeon; Nancy S Redeker
Journal:  Sleep Med Rev       Date:  2019-05-13       Impact factor: 11.609

Review 2.  Sleep Monitoring in Athletes: Motivation, Methods, Miscalculations and Why it Matters.

Authors:  Shona L Halson
Journal:  Sports Med       Date:  2019-10       Impact factor: 11.136

3.  Discrepancy between wrist-actigraph and polysomnographic measures of sleep in patients with stable heart failure and a novel approach to evaluating discrepancy.

Authors:  Sangchoon Jeon; Samantha Conley; Nancy S Redeker
Journal:  J Sleep Res       Date:  2018-06-25       Impact factor: 3.981

4.  Use of actigraphy to characterize inactivity and activity in patients in a medical ICU.

Authors:  Prerna Gupta; Jennifer L Martin; Dale M Needham; Sitaram Vangala; Elizabeth Colantuoni; Biren B Kamdar
Journal:  Heart Lung       Date:  2020-02-24       Impact factor: 2.210

5.  Sleep Measurement Using Wrist-Worn Accelerometer Data Compared with Polysomnography.

Authors:  John D Chase; Michael A Busa; John W Staudenmayer; John R Sirard
Journal:  Sensors (Basel)       Date:  2022-07-04       Impact factor: 3.847

6.  Sleep-Wake Behavior in Elite Athletes: A Mixed-Method Approach.

Authors:  Kévin de Blasiis; Hélène Joncheray; Julia Elefteriou; Chloé Lesenne; Mathieu Nedelec
Journal:  Front Psychol       Date:  2021-08-03

7.  Sex differences in blood pressure responsiveness to spontaneous K-complexes during stage II sleep.

Authors:  Ian M Greenlund; Carl A Smoot; Jason R Carter
Journal:  J Appl Physiol (1985)       Date:  2020-12-10

Review 8.  The Variability of Sleep Among Elite Athletes.

Authors:  Mathieu Nedelec; Anis Aloulou; François Duforez; Tim Meyer; Gregory Dupont
Journal:  Sports Med Open       Date:  2018-07-27

9.  Which parameters to use for sleep quality monitoring in team sport athletes? A systematic review and meta-analysis.

Authors:  João Gustavo Claudino; Tim J Gabbet; Helton de Sá Souza; Mário Simim; Peter Fowler; Diego de Alcantara Borba; Marco Melo; Altamiro Bottino; Irineu Loturco; Vânia D'Almeida; Alberto Carlos Amadio; Julio Cerca Serrão; George P Nassis
Journal:  BMJ Open Sport Exerc Med       Date:  2019-01-13

10.  Evaluation of a Low-Cost Commercial Actigraph and Its Potential Use in Detecting Cultural Variations in Physical Activity and Sleep.

Authors:  Pavlos Topalidis; Cristina Florea; Esther-Sevil Eigl; Anton Kurapov; Carlos Alberto Beltran Leon; Manuel Schabus
Journal:  Sensors (Basel)       Date:  2021-05-29       Impact factor: 3.847

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