Estimating sleep parameters using an accelerometer without sleep diary

被引：328

作者：

van Hees, Vincent Theodoor ^{[1
]}

Sabia, S. ^{[2
,3
]}

Jones, S. E. ^{[4
]}

Wood, A. R. ^{[4
]}

Anderson, K. N. ^{[5
]}

Kivimaki, M. ^{[3
]}

Frayling, T. M. ^{[4
]}

Pack, A. I. ^{[6
]}

Bucan, M. ^{[7
,8
]}

Trenell, M. I. ^{[9
]}

Mazzotti, Diego R. ^{[6
]}

Gehrman, P. R. ^{[6
,8
]}

Singh-Manoux, B. A. ^{[2
,3
]}

Weedon, M. N. ^{[4
]}

机构：

[1] Netherlands eSci Ctr, Amsterdam, Netherlands

[2] Univ Paris Saclay, Ctr Res Epidemiol & Populat Hlth, INSERM U1018, Paris, France

[3] UCL, Dept Epidemiol & Publ Hlth, London, England

[4] Univ Exeter, Sch Med, Genet Complex Traits, Exeter, Devon, England

[5] Freeman Rd Hosp, Reg Sleep Serv, Newcastle Upon Tyne, Tyne & Wear, England

[6] Univ Penn, Perelman Sch Med, Ctr Sleep & Circadian Neurobiol, Philadelphia, PA 19104 USA

[7] Univ Penn, Sch Med, Perelman Sch Med, Dept Genet, Philadelphia, PA 19104 USA

[8] Univ Penn, Sch Med, Dept Psychiat, Perelman Sch Med, Philadelphia, PA 19104 USA

[9] Newcastle Univ, Movelab, Newcastle Upon Tyne, Tyne & Wear, England

来源：

SCIENTIFIC REPORTS | 2018年 / 8卷

关键词：

ASSESSED PHYSICAL-ACTIVITY; SELF-REPORTED SLEEP; ASSOCIATION; VALIDATION; ACTIGRAPHY; DURATION;

D O I：

10.1038/s41598-018-31266-z

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Wrist worn raw-data accelerometers are used increasingly in large-scale population research. We examined whether sleep parameters can be estimated from these data in the absence of sleep diaries. Our heuristic algorithm uses the variance in estimated z-axis angle and makes basic assumptions about sleep interruptions. Detected sleep period time window (SPT-window) was compared against sleep diary in 3752 participants (range = 60-82 years) and polysomnography in sleep clinic patients (N = 28) and in healthy good sleepers (N = 22). The SPT-window derived from the algorithm was 10.9 and 2.9 minutes longer compared with sleep diary in men and women, respectively. Mean C-statistic to detect the SPT-window compared to polysomnography was 0.86 and 0.83 in clinic-based and healthy sleepers, respectively. We demonstrated the accuracy of our algorithm to detect the SPT-window. The value of this algorithm lies in studies such as UK Biobank where a sleep diary was not used.

引用

页数：11

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