{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:39:39Z","timestamp":1760243979294,"version":"build-2065373602"},"reference-count":19,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2009,2,21]],"date-time":"2009-02-21T00:00:00Z","timestamp":1235174400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>In this paper a method for selecting features for Human Activity Recognition from sensors is presented. Using a large feature set that contains features that may describe the activities to recognize, Best First Search and Genetic Algorithms are employed to select the feature subset that maximizes the accuracy of a Hidden Markov Model generated from the subset. A comparative of the proposed techniques is presented to demonstrate their performance building Hidden Markov Models to classify different human activities using video sensors.<\/jats:p>","DOI":"10.3390\/a2010282","type":"journal-article","created":{"date-parts":[[2009,2,24]],"date-time":"2009-02-24T13:34:19Z","timestamp":1235482459000},"page":"282-300","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Recognizing Human Activities from Sensors Using Hidden Markov Models Constructed by Feature Selection Techniques"],"prefix":"10.3390","volume":"2","author":[{"given":"Rodrigo","family":"Cilla","sequence":"first","affiliation":[{"name":"Computer Science Department, Universidad Carlos III de Madrid, Avda. de la Universidad Carlos III, 22, Colmenarejo, Spain"}]},{"given":"Miguel A.","family":"Patricio","sequence":"additional","affiliation":[{"name":"Computer Science Department, Universidad Carlos III de Madrid, Avda. de la Universidad Carlos III, 22, Colmenarejo, Spain"}]},{"given":"Jes\u00fas","family":"Garc\u00eda","sequence":"additional","affiliation":[{"name":"Computer Science Department, Universidad Carlos III de Madrid, Avda. de la Universidad Carlos III, 22, Colmenarejo, Spain"}]},{"given":"Antonio","family":"Berlanga","sequence":"additional","affiliation":[{"name":"Computer Science Department, Universidad Carlos III de Madrid, Avda. de la Universidad Carlos III, 22, Colmenarejo, Spain"}]},{"given":"Jose M.","family":"Molina","sequence":"additional","affiliation":[{"name":"Computer Science Department, Universidad Carlos III de Madrid, Avda. de la Universidad Carlos III, 22, Colmenarejo, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2009,2,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1016\/j.dss.2007.04.008","article-title":"Intelligent environment for monitoring Alzheimer patients, agent technology for health care","volume":"44","author":"Corchado","year":"2008","journal-title":"Decision Support Sys."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"892","DOI":"10.1016\/j.robot.2007.07.009","article-title":"Development of intelligent multisensor surveillance systems with agents","volume":"55","year":"2007","journal-title":"Robot. 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