{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T09:12:20Z","timestamp":1773393140597,"version":"3.50.1"},"reference-count":53,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2023,8,29]],"date-time":"2023-08-29T00:00:00Z","timestamp":1693267200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Samsung Eletronica da Amazonia Ltda.","award":["465614\/2014-0"],"award-info":[{"award-number":["465614\/2014-0"]}]},{"name":"Samsung Eletronica da Amazonia Ltda.","award":["APQ-0399-1.03\/17"],"award-info":[{"award-number":["APQ-0399-1.03\/17"]}]},{"name":"Samsung Eletronica da Amazonia Ltda.","award":["APQ\/0388-1.03\/14"],"award-info":[{"award-number":["APQ\/0388-1.03\/14"]}]},{"name":"Samsung Eletronica da Amazonia Ltda.","award":["88887.136410\/2017-00"],"award-info":[{"award-number":["88887.136410\/2017-00"]}]},{"name":"Samsung Eletronica da Amazonia Ltda.","award":["314523\/2009-0"],"award-info":[{"award-number":["314523\/2009-0"]}]},{"name":"INES","award":["465614\/2014-0"],"award-info":[{"award-number":["465614\/2014-0"]}]},{"name":"INES","award":["APQ-0399-1.03\/17"],"award-info":[{"award-number":["APQ-0399-1.03\/17"]}]},{"name":"INES","award":["APQ\/0388-1.03\/14"],"award-info":[{"award-number":["APQ\/0388-1.03\/14"]}]},{"name":"INES","award":["88887.136410\/2017-00"],"award-info":[{"award-number":["88887.136410\/2017-00"]}]},{"name":"INES","award":["314523\/2009-0"],"award-info":[{"award-number":["314523\/2009-0"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The recognition of human activities (HAR) using wearable device data, such as smartwatches, has gained significant attention in the field of computer science due to its potential to provide insights into individuals\u2019 daily activities. This article aims to conduct a comparative study of deep learning techniques for recognizing activities of daily living (ADL). A mapping of HAR techniques was performed, and three techniques were selected for evaluation, along with a dataset. Experiments were conducted using the selected techniques to assess their performance in ADL recognition, employing standardized evaluation metrics, such as accuracy, precision, recall, and F1-score. Among the evaluated techniques, the DeepConvLSTM architecture, consisting of recurrent convolutional layers and a single LSTM layer, achieved the most promising results. These findings suggest that software applications utilizing this architecture can assist smartwatch users in understanding their movement routines more quickly and accurately.<\/jats:p>","DOI":"10.3390\/s23177493","type":"journal-article","created":{"date-parts":[[2023,8,29]],"date-time":"2023-08-29T08:59:05Z","timestamp":1693299545000},"page":"7493","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Deep Learning in the Recognition of Activities of Daily Living Using Smartwatch Data"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-8638-4636","authenticated-orcid":false,"given":"Ariany F.","family":"Cavalcante","sequence":"first","affiliation":[{"name":"Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife 50740-560, PE, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Victor H. de L.","family":"Kunst","sequence":"additional","affiliation":[{"name":"Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife 50740-560, PE, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thiago de M.","family":"Chaves","sequence":"additional","affiliation":[{"name":"Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife 50740-560, PE, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J\u00falia D. T.","family":"de Souza","sequence":"additional","affiliation":[{"name":"Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife 50740-560, PE, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-3767-8506","authenticated-orcid":false,"given":"Isabela M.","family":"Ribeiro","sequence":"additional","affiliation":[{"name":"Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife 50740-560, PE, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4667-2243","authenticated-orcid":false,"given":"Jonysberg P.","family":"Quintino","sequence":"additional","affiliation":[{"name":"Projeto CIn-UFPE Samsung, Centro de Inform\u00e1tica, Recife 50740-560, PE, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fabio Q. B.","family":"da Silva","sequence":"additional","affiliation":[{"name":"Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife 50740-560, PE, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6661-5970","authenticated-orcid":false,"given":"Andr\u00e9 L. M.","family":"Santos","sequence":"additional","affiliation":[{"name":"Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife 50740-560, PE, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4685-3634","authenticated-orcid":false,"given":"Veronica","family":"Teichrieb","sequence":"additional","affiliation":[{"name":"Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife 50740-560, PE, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alana Elza F.","family":"da Gama","sequence":"additional","affiliation":[{"name":"Centro de Inform\u00e1tica, Universidade Federal de Pernambuco, Recife 50740-560, PE, Brazil"},{"name":"Departamento de Engenharia Biom\u00e9dica, Universidade Federal de Pernambuco, Recife 50740-560, PE, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,29]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2022). 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