Development and testing of methods for detecting off-wrist in actimetry recordings.

Autor:	Pilz LK; Laboratório de Cronobiologia e Sono-Hospital de Clínicas de Porto Alegre (HCPA)/Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.; Graduate Program in Psychiatry and Behavioral Sciences-UFRGS, Porto Alegre, Brazil., de Oliveira MAB; Laboratório de Cronobiologia e Sono-Hospital de Clínicas de Porto Alegre (HCPA)/Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.; Graduate Program in Psychiatry and Behavioral Sciences-UFRGS, Porto Alegre, Brazil., Steibel EG; Laboratório de Cronobiologia e Sono-Hospital de Clínicas de Porto Alegre (HCPA)/Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil., Policarpo LM; Applied Computing Graduate Program (PPGCA)-Universidade do Vale do Rio dos Sinos (UNISINOS), São Leopoldo, Brazil., Carissimi A; Laboratório de Cronobiologia e Sono-Hospital de Clínicas de Porto Alegre (HCPA)/Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil., Carvalho FG; Laboratório de Cronobiologia e Sono-Hospital de Clínicas de Porto Alegre (HCPA)/Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil., Constantino DB; Laboratório de Cronobiologia e Sono-Hospital de Clínicas de Porto Alegre (HCPA)/Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.; Graduate Program in Psychiatry and Behavioral Sciences-UFRGS, Porto Alegre, Brazil., Tonon AC; Laboratório de Cronobiologia e Sono-Hospital de Clínicas de Porto Alegre (HCPA)/Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.; Graduate Program in Psychiatry and Behavioral Sciences-UFRGS, Porto Alegre, Brazil., Xavier NB; Laboratório de Cronobiologia e Sono-Hospital de Clínicas de Porto Alegre (HCPA)/Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.; Graduate Program in Psychiatry and Behavioral Sciences-UFRGS, Porto Alegre, Brazil., da Rosa Righi R; Applied Computing Graduate Program (PPGCA)-Universidade do Vale do Rio dos Sinos (UNISINOS), São Leopoldo, Brazil., Hidalgo MP; Laboratório de Cronobiologia e Sono-Hospital de Clínicas de Porto Alegre (HCPA)/Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.; Graduate Program in Psychiatry and Behavioral Sciences-UFRGS, Porto Alegre, Brazil.
Jazyk:	angličtina
Zdroj:	Sleep [Sleep] 2022 Aug 11; Vol. 45 (8).
DOI:	10.1093/sleep/zsac118
Abstrakt:	Study Objectives: In field studies using wrist-actimetry, not identifying/handling off-wrist intervals may result in their misclassification as immobility/sleep and biased estimations of rhythmic patterns. By comparing different solutions for detecting off-wrist, our goal was to ascertain how accurately they detect nonwear in different contexts and identify variables that are useful in the process. Methods: We developed algorithms using heuristic (HA) and machine learning (ML) approaches. Both were tested using data from a protocol followed by 10 subjects, which was devised to mimic contexts of actimeter wear/nonwear in real-life. Self-reported data on usage according to the protocol were considered the gold standard. Additionally, the performance of our algorithms was compared to that of visual inspection (by 2 experienced investigators) and Choi algorithm. Data previously collected in field studies were used for proof-of-concept analyses. Results: All methods showed similarly good performances. Accuracy was marginally higher for one of the raters (visual inspection) than for heuristically developed algorithms (HA, Choi). Short intervals (especially < 2 h) were either not or only poorly identified. Consecutive stretches of zeros in activity were considered important indicators of off-wrist (for both HA and ML). It took hours for raters to complete the task as opposed to the seconds or few minutes taken by the automated methods. Conclusions: Automated strategies of off-wrist detection are similarly effective to visual inspection, but have the important advantage of being faster, less costly, and independent of raters' attention/experience. In our study, detecting short intervals was a limitation across methods. (© The Author(s) 2022. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)
Databáze:	MEDLINE
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