Estimating sleep duration: performance of open-source processing of actigraphy compared to in-laboratory polysomnography in the community

Sleep Advances: A Journal of the Sleep Research Society · 10 authors, 25 centres

AI SUMMARY

FIDELITY 100%

POPULATIONMiddle-aged adults from the Raine Study (n=835; 58% female; mean age 56.7 ± 5.6 years)

INTERVENTIONActigraphy (GT3X+ ActiGraph) processed in open-source GGIR software with and without a sleep diary

COMPARISONIn-laboratory polysomnography (gold standard); additionally proprietary ActiLife software with sleep diary

This summary was generated by AI from a single paper. It has not been reviewed by a clinician and is not clinical advice. Verify against the source before acting on it.

AGENT 01 · STRUCTURED SUMMARY

TRACE TO SOURCE

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TL;DR

In a community sample of 835 middle-aged adults, actigraphy processed using the open-source GGIR algorithm overestimated polysomnography total sleep time by approximately 31 minutes on average, with poor agreement (ICC = 0.27–0.44) between actigraphy and the gold standard across all processing methods tested.

Full summary

1,057 CHARS

This cohort study from the Raine Study compared actigraphy-derived total sleep time (TST) against in-laboratory polysomnography (PSG) in 835 middle-aged community adults. Participants completed one night of concurrent PSG and actigraphy (GT3X+ ActiGraph). Actigraphic TST was processed using the open-source R-package GGIR with and without a sleep diary, and additionally using proprietary ActiLife software. Actigraphy in GGIR overestimated PSG TST by 31.0 ± 50.0 minutes (with diary) and 26.4 ± 69.0 minutes (without diary), while ActiLife overestimated by 46.8 ± 50.4 minutes. Agreement between actigraphy and PSG TST was poor across all methods (ICC = 0.27–0.44). Longer sleep onset latency and longer wakefulness after sleep onset were associated with greater overestimation. GGIR without a diary performed comparably to GGIR with a diary and to proprietary ActiLife processing. Limitations include a single in-laboratory night, which may introduce first-night effects, and a predominantly Caucasian, middle-aged sample that may limit generalizability.

PICO

PPOPULATION

Middle-aged adults from the Raine Study (n=835; 58% female; mean age 56.7 ± 5.6 years)

IINTERVENTION

Actigraphy (GT3X+ ActiGraph) processed in open-source GGIR software with and without a sleep diary

OOUTCOME

Total sleep time (TST) bias, agreement (ICC), and factors associated with actigraphy–PSG discrepancy

STUDY TYPE

cohort

SPECIALTY

epidemiology

SUMMARISED BY

AI pipeline

FIDELITY CHECK

100% · A

ORIGINAL PAPER

PMC10362889

Estimating sleep duration: performance of open-source processing of actigraphy compared to in-laboratory polysomnography in the community

Sleep Advances: A Journal of the Sleep Research Society

READ THE FULL PAPER

ABSTRACT

Abstract Comparisons of actigraphy findings between studies are challenging given differences between brand-specific algorithms. This issue may be minimized by using open-source algorithms. However, the accuracy of actigraphy-derived sleep parameters processed in open-source software needs to be assessed against polysomnography (PSG). Middle-aged adults from the Raine Study ( n = 835; F 58%; Age 56.7 ± 5.6 years) completed one night of in-laboratory PSG and concurrent actigraphy (GT3X+ ActiGraph). Actigraphic measures of total sleep time (TST) were analyzed and processed using the open-source R-package GENEActiv and GENEA data in R (GGIR) with and without a sleep diary and additionally processed using proprietary software, ActiLife, for comparison. Bias and agreement (intraclass correlation coefficient) between actigraphy and PSG were examined. Common PSG and sleep health variables associated with the discrepancy between actigraphy, and PSG TST were examined using linear regression. Actigraphy, assessed in GGIR, with and without a sleep diary overestimated PSG TST by (mean ± SD) 31.0 ± 50.0 and 26.4 ± 69.0 minutes, respectively. This overestimation was greater (46.8 ± 50.4 minutes) when actigraphy was analyzed in ActiLife. Agreement between actigraphy and PSG TST was poor (ICC = 0.27–0.44) across all three methods of actigraphy analysis. Longer sleep onset latency and longer wakefulness after sleep onset were associated with overestimation of PSG TST. Open-source processing of actigraphy in a middle-aged community population, agreed poorly with PSG and, on average, overestimated TST. TST overestimation increased with increasing wakefulness overnight. Processing of actigraphy without a diary in GGIR was comparable to when a sleep diary was used and comparable to actigraphy processed with proprietary algorithms in ActiLife.

CITATION EXPORT

Kelly Sansom, Amy Reynolds, Joanne McVeigh et al.. Estimating sleep duration: performance of open-source processing of actigraphy compared to in-laboratory polysomnography in the community. Sleep Advances: A Journal of the Sleep Research Society. (2023). https://doi.org/10.1093/sleepadvances/zpad028

AUTHORS

10 · 25 CENTRES

Kelly Sansom, Amy Reynolds, Joanne McVeigh, Diego R Mazzotti, Satvinder S Dhaliwal, Kathleen Maddison, Jennifer Walsh, Bhajan Singh, Peter Eastwood, Nigel McArdle

Centre for Sleep Science, School of Human Sciences, University of Western Australia, Perth, WA, Australia
West Australian Sleep Disorders Research Institute, Sir Charles Gairdner Hospital, Perth, WA, Australia
Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia
Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia
Curtin School of Allied Health, Faculty of Health Sciences, Curtin University, Perth, WA, Australia
Movement Physiology Laboratory, School of Physiology, University of Witwatersrand, South Africa
Division of Medical Informatics, Department of Internal Medicine, University of Kansas Medical Center, KS, USA
Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of Kansas Medical Center, KS, USA
Curtin Health Innovation Research Institute, Faculty of Health Sciences, B305, Curtin University, Bentley, WA, Australia
Office of the Provost, Singapore University of Social Sciences, Clementi Road, Singapore
Duke-NUS Medical School, National University of Singapore, 8 College Road, Singapore
Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia, Pulau Pinang, Malaysia
Centre for Sleep Science, School of Human Sciences, University of Western Australia, Perth, WA, Australia
West Australian Sleep Disorders Research Institute, Sir Charles Gairdner Hospital, Perth, WA, Australia
Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Perth, WA, Australia
Centre for Sleep Science, School of Human Sciences, University of Western Australia, Perth, WA, Australia
West Australian Sleep Disorders Research Institute, Sir Charles Gairdner Hospital, Perth, WA, Australia
Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Perth, WA, Australia
Centre for Sleep Science, School of Human Sciences, University of Western Australia, Perth, WA, Australia
West Australian Sleep Disorders Research Institute, Sir Charles Gairdner Hospital, Perth, WA, Australia
Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Perth, WA, Australia
Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia
Centre for Sleep Science, School of Human Sciences, University of Western Australia, Perth, WA, Australia
West Australian Sleep Disorders Research Institute, Sir Charles Gairdner Hospital, Perth, WA, Australia
Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Perth, WA, Australia