{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T18:44:39Z","timestamp":1777142679178,"version":"3.51.4"},"reference-count":60,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2021,11,25]],"date-time":"2021-11-25T00:00:00Z","timestamp":1637798400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Science, Technology, and Innovation of Colombia","award":["733-2015"],"award-info":[{"award-number":["733-2015"]}]},{"DOI":"10.13039\/501100005682","name":"Universidad del Cauca","doi-asserted-by":"publisher","award":["501100005682"],"award-info":[{"award-number":["501100005682"]}],"id":[{"id":"10.13039\/501100005682","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The collection of physiological data from people has been facilitated due to the mass use of cheap wearable devices. Although the accuracy is low compared to specialized healthcare devices, these can be widely applied in other contexts. This study proposes the architecture for a tourist experiences recommender system (TERS) based on the user\u2019s emotional states who wear these devices. The issue lies in detecting emotion from Heart Rate (HR) measurements obtained from these wearables. Unlike most state-of-the-art studies, which have elicited emotions in controlled experiments and with high-accuracy sensors, this research\u2019s challenge consisted of emotion recognition (ER) in the daily life context of users based on the gathering of HR data. Furthermore, an objective was to generate the tourist recommendation considering the emotional state of the device wearer. The method used comprises three main phases: The first was the collection of HR measurements and labeling emotions through mobile applications. The second was emotional detection using deep learning algorithms. The final phase was the design and validation of the TERS-ER. In this way, a dataset of HR measurements labeled with emotions was obtained as results. Among the different algorithms tested for ER, the hybrid model of Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks had promising results. Moreover, concerning TERS, Collaborative Filtering (CF) using CNN showed better performance.<\/jats:p>","DOI":"10.3390\/s21237854","type":"journal-article","created":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T01:45:02Z","timestamp":1638323102000},"page":"7854","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Tourist Experiences Recommender System Based on Emotion Recognition with Wearable Data"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3697-7852","authenticated-orcid":false,"given":"Luz","family":"Santamaria-Granados","sequence":"first","affiliation":[{"name":"GIDINT, Faculty of Systems Engineering, Universidad Santo Tom\u00e1s Seccional Tunja, Calle 19, No. 11-64, Tunja 150001, Colombia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1480-0845","authenticated-orcid":false,"given":"Juan Francisco","family":"Mendoza-Moreno","sequence":"additional","affiliation":[{"name":"GIDINT, Faculty of Systems Engineering, Universidad Santo Tom\u00e1s Seccional Tunja, Calle 19, No. 11-64, Tunja 150001, Colombia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4031-3816","authenticated-orcid":false,"given":"Angela","family":"Chantre-Astaiza","sequence":"additional","affiliation":[{"name":"SysT\u00e9mico Research Group, Department of Tourism Sciences, Universidad del Cauca, Calle 5, No. 4-70, Popay\u00e1n 190002, Colombia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4199-2002","authenticated-orcid":false,"given":"Mario","family":"Munoz-Organero","sequence":"additional","affiliation":[{"name":"GAST, Telematics Engineering Department, Universidad Carlos III de Madrid, Av. de la Universidad, 30, 28911 Madrid, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1338-8820","authenticated-orcid":false,"given":"Gustavo","family":"Ramirez-Gonzalez","sequence":"additional","affiliation":[{"name":"GIT, Telematics Department, Universidad del Cauca, Calle 5, No. 4-70, Popay\u00e1n 190002, Colombia"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"69200","DOI":"10.1109\/ACCESS.2020.2986329","article-title":"Wearables and the Internet of Things (IoT), Applications, Opportunities, and Challenges: A Survey","volume":"8","author":"Vahidnia","year":"2020","journal-title":"IEEE Access"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Nawara, D., and Kashef, R. 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