{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T22:36:21Z","timestamp":1769726181154,"version":"3.49.0"},"reference-count":63,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2019,12,7]],"date-time":"2019-12-07T00:00:00Z","timestamp":1575676800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","doi-asserted-by":"publisher","award":["UID\/EEA\/50008\/2019"],"award-info":[{"award-number":["UID\/EEA\/50008\/2019"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Electronics"],"abstract":"<jats:p>The identification of Activities of Daily Living (ADL) is intrinsic with the user\u2019s environment recognition. This detection can be executed through standard sensors present in every-day mobile devices. On the one hand, the main proposal is to recognize users\u2019 environment and standing activities. On the other hand, these features are included in a framework for the ADL and environment identification. Therefore, this paper is divided into two parts\u2014firstly, acoustic sensors are used for the collection of data towards the recognition of the environment and, secondly, the information of the environment recognized is fused with the information gathered by motion and magnetic sensors. The environment and ADL recognition are performed by pattern recognition techniques that aim for the development of a system, including data collection, processing, fusion and classification procedures. These classification techniques include distinctive types of Artificial Neural Networks (ANN), analyzing various implementations of ANN and choosing the most suitable for further inclusion in the following different stages of the developed system. The results present 85.89% accuracy using Deep Neural Networks (DNN) with normalized data for the ADL recognition and 86.50% accuracy using Feedforward Neural Networks (FNN) with non-normalized data for environment recognition. Furthermore, the tests conducted present 100% accuracy for standing activities recognition using DNN with normalized data, which is the most suited for the intended purpose.<\/jats:p>","DOI":"10.3390\/electronics8121499","type":"journal-article","created":{"date-parts":[[2019,12,9]],"date-time":"2019-12-09T05:54:51Z","timestamp":1575870891000},"page":"1499","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Recognition of Activities of Daily Living and Environments Using Acoustic Sensors Embedded on Mobile Devices"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3394-6762","authenticated-orcid":false,"given":"Ivan Miguel","family":"Pires","sequence":"first","affiliation":[{"name":"Instituto de Telecomunica\u00e7\u00f5es, Universidade da Beira Interior, 6200-001 Covilh\u00e3, Portugal"},{"name":"Computer Science Department, Polytechnic Institute of Viseu, 3504-510 Viseu, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5834-6571","authenticated-orcid":false,"given":"Gon\u00e7alo","family":"Marques","sequence":"additional","affiliation":[{"name":"Instituto de Telecomunica\u00e7\u00f5es, Universidade da Beira Interior, 6200-001 Covilh\u00e3, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3195-3168","authenticated-orcid":false,"given":"Nuno M.","family":"Garcia","sequence":"additional","affiliation":[{"name":"Instituto de Telecomunica\u00e7\u00f5es, Universidade da Beira Interior, 6200-001 Covilh\u00e3, Portugal"}]},{"given":"Nuno","family":"Pombo","sequence":"additional","affiliation":[{"name":"Instituto de Telecomunica\u00e7\u00f5es, Universidade da Beira Interior, 6200-001 Covilh\u00e3, Portugal"}]},{"given":"Francisco","family":"Fl\u00f3rez-Revuelta","sequence":"additional","affiliation":[{"name":"Department of Computing Technology, University of Alicante, P.O. Box 99, E-03080 Alicante, Spain"}]},{"given":"Susanna","family":"Spinsante","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, Universit\u00e0 Politecnica delle Marche, 60131 Ancona, Italy"}]},{"given":"Maria Canavarro","family":"Teixeira","sequence":"additional","affiliation":[{"name":"UTC de Recursos Naturais e Desenvolvimento Sustent\u00e1vel, Polytechnique Institute of Castelo Branco, 6001-909 Castelo Branco, Portugal"},{"name":"CERNAS-Research Centre for Natural Resources, Environment and Society, Polytechnique Institute of Castelo Branco, 6001-909 Castelo Branco, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7664-0168","authenticated-orcid":false,"given":"Eftim","family":"Zdravevski","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, Macedonia"}]}],"member":"1968","published-online":{"date-parts":[[2019,12,7]]},"reference":[{"key":"ref_1","first-page":"157","article-title":"Activities of daily living","volume":"Volume 7","author":"Foti","year":"2013","journal-title":"Pedretti\u2019s Occupational Therapy: Practical Skills for Physical Dysfunction"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"50","DOI":"10.4018\/jmhci.2013040103","article-title":"A Systematic Literature Review on Usability Heuristics for Mobile Phones","volume":"5","author":"Salazar","year":"2013","journal-title":"Int. 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