{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T17:40:39Z","timestamp":1786556439095,"version":"3.56.0"},"reference-count":48,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2021,12,11]],"date-time":"2021-12-11T00:00:00Z","timestamp":1639180800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100017656","name":"NOVUS","doi-asserted-by":"publisher","award":["N19-17"],"award-info":[{"award-number":["N19-17"]}],"id":[{"id":"10.13039\/501100017656","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This study proposes a new index to measure the resilience of an individual to stress, based on the changes of specific physiological variables. These variables include electromyography, which is the muscle response, blood volume pulse, breathing rate, peripheral temperature, and skin conductance. We measured the data with a biofeedback device from 71 individuals subjected to a 10-min psychophysiological stress test. The data exploration revealed that features\u2019 variability among test phases could be observed in a two-dimensional space with Principal Components Analysis (PCA). In this work, we demonstrate that the values of each feature within a phase are well organized in clusters. The new index we propose, Resilience to Stress Index (RSI), is based on this observation. To compute the index, we used non-supervised machine learning methods to calculate the inter-cluster distances, specifically using the following four methods: Euclidean Distance of PCA, Mahalanobis Distance, Cluster Validity Index Distance, and Euclidean Distance of Kernel PCA. While there was no statistically significant difference (p&gt;0.01) among the methods, we recommend using Mahalanobis, since this method provides higher monotonic association with the Resilience in Mexicans (RESI-M) scale. Results are encouraging since we demonstrated that the computation of a reliable RSI is possible. To validate the new index, we undertook two tasks: a comparison of the RSI against the RESI-M, and a Spearman correlation between phases one and five to determine if the behavior is resilient or not. The computation of the RSI of an individual has a broader scope in mind, and it is to understand and to support mental health. The benefits of having a metric that measures resilience to stress are multiple; for instance, to the extent that individuals can track their resilience to stress, they can improve their everyday life.<\/jats:p>","DOI":"10.3390\/s21248293","type":"journal-article","created":{"date-parts":[[2021,12,13]],"date-time":"2021-12-13T01:29:33Z","timestamp":1639358973000},"page":"8293","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Towards a Resilience to Stress Index Based on Physiological Response: A Machine Learning Approach"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7324-7205","authenticated-orcid":false,"given":"Ramon E.","family":"Diaz-Ramos","sequence":"first","affiliation":[{"name":"Department of Computer Science, School of Engineering and Sciences, Campus Monterrey, Tecnologico de Monterrey, Monterrey 64849, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9286-9480","authenticated-orcid":false,"given":"Daniela A.","family":"Gomez-Cravioto","sequence":"additional","affiliation":[{"name":"Department of Computer Science, School of Engineering and Sciences, Campus Monterrey, Tecnologico de Monterrey, Monterrey 64849, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9741-4581","authenticated-orcid":false,"given":"Luis A.","family":"Trejo","sequence":"additional","affiliation":[{"name":"Department of Computer Science, School of Engineering and Sciences, Campus Estado de M\u00e9xico, Tecnologico de Monterrey, Atizap\u00e1n 52926, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1565-7625","authenticated-orcid":false,"given":"Carlos Figueroa","family":"L\u00f3pez","sequence":"additional","affiliation":[{"name":"Department of Psychology, School of Health, Campus Ciudad de M\u00e9xico, Tecnologico de Monterrey, Ciudad de M\u00e9xico 14380, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4511-2252","authenticated-orcid":false,"given":"Miguel Angel","family":"Medina-P\u00e9rez","sequence":"additional","affiliation":[{"name":"Department of Computer Science, School of Engineering and Sciences, Campus Estado de M\u00e9xico, Tecnologico de Monterrey, Atizap\u00e1n 52926, Mexico"},{"name":"Altair Management Consultants, Calle de Jos\u00e9 Ortega y Gasset 22-24, 5th Floor, 28006 Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1685","DOI":"10.1001\/jama.298.14.1685","article-title":"Psychological stress and disease","volume":"298","author":"Cohen","year":"2007","journal-title":"JAMA"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"837","DOI":"10.1176\/ajp.156.6.837","article-title":"Causal relationship between stressful life events and the onset of major depression","volume":"156","author":"Kendler","year":"1999","journal-title":"Am. 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