{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T21:55:56Z","timestamp":1793915756768,"version":"4.8.0"},"reference-count":29,"publisher":"Oxford University Press (OUP)","issue":"8","license":[{"start":{"date-parts":[[2022,5,22]],"date-time":"2022-05-22T00:00:00Z","timestamp":1653177600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/501100002322","name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior\u2014Brasil","doi-asserted-by":"crossref","award":["88887.507070\/2020-00"],"award-info":[{"award-number":["88887.507070\/2020-00"]}],"id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100004263","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado do Rio Grande do Sul","doi-asserted-by":"publisher","award":["21\/2551-0000118-6"],"award-info":[{"award-number":["21\/2551-0000118-6"]}],"id":[{"id":"10.13039\/501100004263","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004263","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado do Rio Grande do Sul","doi-asserted-by":"publisher","award":["17\/2551-0001419-7"],"award-info":[{"award-number":["17\/2551-0001419-7"]}],"id":[{"id":"10.13039\/501100004263","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008627","name":"Global Affairs Canada","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100008627","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,8,11]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Study Objectives<\/jats:title>\n                  <jats:p>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.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>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.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>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 &amp;lt; 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.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>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\u2019 attention\/experience. In our study, detecting short intervals was a limitation across methods.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/sleep\/zsac118","type":"journal-article","created":{"date-parts":[[2022,5,22]],"date-time":"2022-05-22T18:01:52Z","timestamp":1653242512000},"source":"Crossref","is-referenced-by-count":15,"title":["Development and testing of methods for detecting off-wrist in actimetry recordings"],"prefix":"10.1093","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7328-6204","authenticated-orcid":false,"given":"Lu\u00edsa K","family":"Pilz","sequence":"first","affiliation":[{"name":"Laborat\u00f3rio de Cronobiologia e Sono\u2014Hospital de Cl\u00ednicas de Porto Alegre (HCPA)\/Universidade Federal do Rio Grande do Sul (UFRGS) , Porto Alegre , Brazil"},{"name":"Graduate Program in Psychiatry and Behavioral Sciences\u2014UFRGS , Porto Alegre , Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8834-0469","authenticated-orcid":false,"given":"Melissa A B","family":"de Oliveira","sequence":"additional","affiliation":[{"name":"Laborat\u00f3rio de Cronobiologia e Sono\u2014Hospital de Cl\u00ednicas de Porto Alegre (HCPA)\/Universidade Federal do Rio Grande do Sul (UFRGS) , Porto Alegre , Brazil"},{"name":"Graduate Program in Psychiatry and Behavioral Sciences\u2014UFRGS , Porto Alegre , Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eduardo G","family":"Steibel","sequence":"additional","affiliation":[{"name":"Laborat\u00f3rio de Cronobiologia e Sono\u2014Hospital de Cl\u00ednicas de Porto Alegre (HCPA)\/Universidade Federal do Rio Grande do Sul (UFRGS) , Porto Alegre , Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lucas M","family":"Policarpo","sequence":"additional","affiliation":[{"name":"Applied Computing Graduate Program 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