Nature and Science of Sleep (Oct 2022)
Actigraphy-Based Sleep Detection: Validation with Polysomnography and Comparison of Performance for Nighttime and Daytime Sleep During Simulated Shift Work
Abstract
Chenlu Gao,1– 3 Peng Li,1– 3 Christopher J Morris,1,2 Xi Zheng,1,3 Ma Cherrysse Ulsa,1,3 Lei Gao,1– 4 Frank AJL Scheer,1– 3 Kun Hu1– 3 1Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA, USA; 2Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA; 3Broad Institute of MIT and Harvard, Cambridge, MA, USA; 4Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USACorrespondence: Kun Hu, Brigham and Women’s Hospital, 221 Longwood Avenue, 040 BLI, Boston, MA, 02115, USA, Tel +1 617-525 8694, Fax +1 617-732 7337, Email [email protected]: Actigraphy-based sleep detection algorithms were mostly validated using nighttime sleep, and their performance in detecting daytime sleep is unclear. We evaluated and compared the performance of Actiware and the Cole-Kripke algorithm (C-K) – two commonly used actigraphy-based algorithms – in detecting daytime and nighttime sleep.Participants and Methods: Twenty-five healthy young adults were monitored by polysomnography and actigraphy during two in-lab protocols with scheduled nighttime and/or daytime sleep (within-subject design). Mixed-effect models were conducted to compare the sensitivity, specificity, and F1 score (a less-biased measure of accuracy) of Actiware (with low/medium/high threshold setting, separately) and C-K in detecting sleep epochs from actigraphy recordings during nighttime/daytime. t-tests and intraclass correlation coefficients were used to assess the agreement between actigraphy-based algorithms and polysomnography in scoring total sleep time (TST).Results: Sensitivity was similar between nighttime (Actiware: 0.93– 0.99 across threshold settings; C-K: 0.61) and daytime sleep (Actiware: 0.93– 0.99; C-K: 0.66) for both the C-K and Actiware (daytime/nighttime×algorithm interaction: p > 0.1). Specificity for daytime sleep was lower (Actiware: 0.35– 0.54; C-K: 0.91) than that for nighttime sleep (Actiware: 0.37– 0.62; C-K: 0.93; p = 0.001). Specificity was also higher for C-K than Actiware (p 0.1). C-K had lower F1 (nighttime = 0.74; daytime = 0.77) than Actiware (nighttime = 0.95– 0.98; daytime = 0.90– 0.91) for both nighttime and daytime sleep (all p < 0.05). The daytime-nighttime difference in F1 was opposite for Actiware (daytime: 0.90– 0.91; nighttime: 0.95– 0.98) and C-K (daytime: 0.77; nighttime: 0.74; interaction p = 0.003). Bias in TST was lowest in Actiware (with medium-threshold) for nighttime sleep (underestimation of 5.99 min/8h) and in Actiware (with low-threshold) for daytime sleep (overestimation of 17.75 min/8h).Conclusion: Daytime/nighttime sleep affected specificity and F1 but not sensitivity of actigraphy-based sleep scoring. Overall, Actiware performed better than the C-K algorithm. Actiware with medium-threshold was the least biased in estimating nighttime TST, and Actiware with low-threshold was the least biased in estimating daytime TST.Keywords: Actiware, Cole-Kripke algorithm, sleep scoring, shift worker, circadian rhythms
