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

Kate L. Fuller, Laura Juliff, Christopher J. Gore, Jeremiah J. Peiffer, Shona L. Halson

Research output: Contribution to journalArticle

9 Citations (Scopus)

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 (8.5 min), sleep efficiency (1.8%) and wake after sleep onset (−4.1 min); whereas the Low threshold had the smallest bias (7.5 min) for wake bouts. Bias in sleep onset latency was the same across thresholds (−9.5 min). The standard error of the estimate was similar across all thresholds; total sleep time ∼25 min, sleep efficiency ∼4.5%, wake after sleep onset ∼21 min, 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.

Original languageEnglish
Pages (from-to)756-760
Number of pages5
JournalJournal of Science and Medicine in Sport
Volume20
Issue number8
DOIs
Publication statusPublished - 1 Aug 2017
Externally publishedYes

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Actigraphy
Polysomnography
Athletes
Sports
Sleep
Software

Cite this

Fuller, Kate L. ; Juliff, Laura ; Gore, Christopher J. ; Peiffer, Jeremiah J. ; Halson, Shona L. / Software thresholds alter the bias of actigraphy for monitoring sleep in team-sport athletes. In: Journal of Science and Medicine in Sport. 2017 ; Vol. 20, No. 8. pp. 756-760.
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abstract = "Objectives Actical{\circledR} actigraphy is commonly used to monitor athlete sleep. The proprietary software, called Actiware{\circledR}, 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{\circledR} 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{\circledR} devices. Individual night data was compared across five sleep measures for each sleep-wake threshold using Actiware{\circledR} 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 (8.5 min), sleep efficiency (1.8{\%}) and wake after sleep onset (−4.1 min); whereas the Low threshold had the smallest bias (7.5 min) for wake bouts. Bias in sleep onset latency was the same across thresholds (−9.5 min). The standard error of the estimate was similar across all thresholds; total sleep time ∼25 min, sleep efficiency ∼4.5{\%}, wake after sleep onset ∼21 min, and wake bouts ∼8 counts. Conclusions Sleep parameters measured by the Actical{\circledR} 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.",
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Software thresholds alter the bias of actigraphy for monitoring sleep in team-sport athletes. / Fuller, Kate L.; Juliff, Laura; Gore, Christopher J.; Peiffer, Jeremiah J.; Halson, Shona L.

In: Journal of Science and Medicine in Sport, Vol. 20, No. 8, 01.08.2017, p. 756-760.

Research output: Contribution to journalArticle

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AU - Juliff, Laura

AU - Gore, Christopher J.

AU - Peiffer, Jeremiah J.

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N2 - 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 (8.5 min), sleep efficiency (1.8%) and wake after sleep onset (−4.1 min); whereas the Low threshold had the smallest bias (7.5 min) for wake bouts. Bias in sleep onset latency was the same across thresholds (−9.5 min). The standard error of the estimate was similar across all thresholds; total sleep time ∼25 min, sleep efficiency ∼4.5%, wake after sleep onset ∼21 min, 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.

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