{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,17]],"date-time":"2026-05-17T13:26:52Z","timestamp":1779024412937,"version":"3.51.4"},"reference-count":43,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2019,4,3]],"date-time":"2019-04-03T00:00:00Z","timestamp":1554249600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Motivated by the importance of studying the relationship between habits of students and their academic performance, daily activities of undergraduate participants have been tracked with smartwatches and smartphones. Smartwatches collect data together with an Android application that interacts with the users who provide the labeling of their own activities. The tracked activities include eating, running, sleeping, classroom-session, exam, job, homework, transportation, watching TV-Series, and reading. The collected data were stored in a server for activity recognition with supervised machine learning algorithms. The methodology for the concept proof includes the extraction of features with the discrete wavelet transform from gyroscope and accelerometer signals to improve the classification accuracy. The results of activity recognition with Random Forest were satisfactory (86.9%) and support the relationship between smartwatch sensor signals and daily-living activities of students which opens the possibility for developing future experiments with automatic activity-labeling, and so forth to facilitate activity pattern recognition to propose a recommendation system to enhance the academic performance of each student.<\/jats:p>","DOI":"10.3390\/s19071605","type":"journal-article","created":{"date-parts":[[2019,4,4]],"date-time":"2019-04-04T03:13:42Z","timestamp":1554347622000},"page":"1605","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Monitoring Student Activities with Smartwatches: On the Academic Performance Enhancement"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7488-0333","authenticated-orcid":false,"given":"Oscar","family":"Herrera-Alc\u00e1ntara","sequence":"first","affiliation":[{"name":"Departamento de Sistemas, Universidad Aut\u00f3noma Metropolitana, Azcapotzalco 02200, Mexico"},{"name":"Centro Universitario UAEM Valle de M\u00e9xico, Universidad Aut\u00f3noma del Estado de M\u00e9xico, Atizap\u00e1n 54500, Mexico"},{"name":"Escuela de Ingenier\u00eda y Ciencias, Tecnol\u00f3gico de Monterrey, Atizap\u00e1n 52926, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8533-125X","authenticated-orcid":false,"given":"Ari Yair","family":"Barrera-Animas","sequence":"additional","affiliation":[{"name":"Escuela de Ingenier\u00eda y Ciencias, Tecnol\u00f3gico de Monterrey, Atizap\u00e1n 52926, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miguel","family":"Gonz\u00e1lez-Mendoza","sequence":"additional","affiliation":[{"name":"Escuela de Ingenier\u00eda y Ciencias, Tecnol\u00f3gico de Monterrey, Atizap\u00e1n 52926, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2818-641X","authenticated-orcid":false,"given":"F\u00e9lix","family":"Castro-Espinoza","sequence":"additional","affiliation":[{"name":"Centro de Investigaci\u00f3n en Tecnolog\u00edas de Informaci\u00f3n y Sistemas, Universidad Aut\u00f3noma del Estado de Hidalgo, Mineral de la Reforma 42184, Hidalgo, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,4,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"59192","DOI":"10.1109\/ACCESS.2018.2873502","article-title":"Sensor-Based Datasets for Human Activity Recognition\u2014A Systematic Review of Literature","volume":"6","author":"Colpas","year":"2018","journal-title":"IEEE Access"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3389\/fneur.2018.01036","article-title":"Monitoring Motor Symptoms During Activities of Daily Living in Individuals with Parkinson\u2019s Disease","volume":"9","author":"Thorp","year":"2018","journal-title":"Front. 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