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Recognition of Activities of Daily Living Based on Environmental Analyses Using Audio Fingerprinting Techniques: A Systematic Review

2018Journal article Open access
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dc.contributor.authorPires, Ivan
dc.contributor.authorSantos, Rui
dc.contributor.authorPombo, Nuno
dc.contributor.authorGarcia, Nuno M.
dc.contributor.authorFlórez-Revuelta, Francisco
dc.contributor.authorSpinsante, Susanna
dc.contributor.authorGoleva, Rossitza
dc.contributor.authorZdravevski, Eftim
dc.date.accessioned2020-01-14T16:05:36Z
dc.date.available2020-01-14T16:05:36Z
dc.date.issued2018
dc.description.abstractAn increase in the accuracy of identification of Activities of Daily Living (ADL) is very important for different goals of Enhanced Living Environments and for Ambient Assisted Living (AAL) tasks. This increase may be achieved through identification of the surrounding environment. Although this is usually used to identify the location, ADL recognition can be improved with the identification of the sound in that particular environment. This paper reviews audio fingerprinting techniques that can be used with the acoustic data acquired from mobile devices. A comprehensive literature search was conducted in order to identify relevant English language works aimed at the identification of the environment of ADLs using data acquired with mobile devices, published between 2002 and 2017. In total, 40 studies were analyzed and selected from 115 citations. The results highlight several audio fingerprinting techniques, including Modified discrete cosine transform (MDCT), Mel-frequency cepstrum coefficients (MFCC), Principal Component Analysis (PCA), Fast Fourier Transform (FFT), Gaussian mixture models (GMM), likelihood estimation, logarithmic moduled complex lapped transform (LMCLT), support vector machine (SVM), constant Q transform (CQT), symmetric pairwise boosting (SPB), Philips robust hash (PRH), linear discriminant analysis (LDA) and discrete cosine transform (DCT).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.3390/s18010160pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.6/8262
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.subjectAlgorithmspt_PT
dc.subjectHumanspt_PT
dc.subjectLikelihood Functionspt_PT
dc.subjectPattern Recognitionpt_PT
dc.subjectSignal Processingpt_PT
dc.subjectSupport Vector Machinept_PT
dc.subjectActivities of Daily Livingpt_PT
dc.subjectComputer-Assistedpt_PT
dc.subjectAutomatedpt_PT
dc.titleRecognition of Activities of Daily Living Based on Environmental Analyses Using Audio Fingerprinting Techniques: A Systematic Reviewpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FEEA%2F50008%2F2013/PT
oaire.citation.issue2pt_PT
oaire.citation.startPage160pt_PT
oaire.citation.titleSensorspt_PT
oaire.citation.volume18pt_PT
oaire.fundingStream5876
person.familyNameSerrano Pires
person.familyNamePombo
person.familyNameGarcia dos Santos
person.familyNameSpinsante
person.familyNameGoleva
person.familyNameZdravevski
person.givenNameIvan Miguel
person.givenNameNuno
person.givenNameNuno Manuel
person.givenNameSusanna
person.givenNameRossitza
person.givenNameEftim
person.identifier-6iey0oAAAAJ
person.identifier.ciencia-id211D-8B3D-0131
person.identifier.ciencia-id0F16-A18D-96BA
person.identifier.ciencia-idE719-0DEC-9751
person.identifier.orcid0000-0002-3394-6762
person.identifier.orcid0000-0001-7797-8849
person.identifier.orcid0000-0002-3195-3168
person.identifier.orcid0000-0002-7323-4030
person.identifier.orcid0000-0002-6268-0756
person.identifier.orcid0000-0001-7664-0168
person.identifier.ridP-5437-2014
person.identifier.ridC-2465-2016
person.identifier.ridK-5276-2014
person.identifier.scopus-author-id56715367700
person.identifier.scopus-author-id55389546100
person.identifier.scopus-author-id6506113067
person.identifier.scopus-author-id55376768000
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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