Recognition of Activities of Daily Living Based on Environmental Analyses Using Audio Fingerprinting Techniques: A Systematic Review
An 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 u...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-01-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/18/1/160 |
| _version_ | 1811304693998026752 |
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| author | Ivan Miguel Pires Rui Santos Nuno Pombo Nuno M. Garcia Francisco Flórez-Revuelta Susanna Spinsante Rossitza Goleva Eftim Zdravevski |
| author_facet | Ivan Miguel Pires Rui Santos Nuno Pombo Nuno M. Garcia Francisco Flórez-Revuelta Susanna Spinsante Rossitza Goleva Eftim Zdravevski |
| author_sort | Ivan Miguel Pires |
| collection | DOAJ |
| description | An 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). |
| first_indexed | 2024-04-13T08:11:55Z |
| format | Article |
| id | doaj.art-cca2ffe3440a409d8349625eee67df84 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T08:11:55Z |
| publishDate | 2018-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-cca2ffe3440a409d8349625eee67df842022-12-22T02:54:57ZengMDPI AGSensors1424-82202018-01-0118116010.3390/s18010160s18010160Recognition of Activities of Daily Living Based on Environmental Analyses Using Audio Fingerprinting Techniques: A Systematic ReviewIvan Miguel Pires0Rui Santos1Nuno Pombo2Nuno M. Garcia3Francisco Flórez-Revuelta4Susanna Spinsante5Rossitza Goleva6Eftim Zdravevski7Instituto de Telecomunicações, Universidade da Beira Interior, 6201-001 Covilhã, PortugalInstituto de Telecomunicações, Universidade da Beira Interior, 6201-001 Covilhã, PortugalInstituto de Telecomunicações, Universidade da Beira Interior, 6201-001 Covilhã, PortugalInstituto de Telecomunicações, Universidade da Beira Interior, 6201-001 Covilhã, PortugalDepartment of Computer Technology, Universidad de Alicante, 03690 Sant Vicent del Raspeig, Alicante, SpainDepartment of Information Engineering, Marche Polytechnic University, 60121 Ancona, ItalyDepartment of Informatics, New Bulgarian University, 1618 g.k. Ovcha kupel 2 Sofia, BulgariaFaculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, MacedoniaAn 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).http://www.mdpi.com/1424-8220/18/1/160acoustic sensorsfingerprint recognitiondata processingartificial intelligencemobile computingsignal processing algorithmssystematic reviewActivities of Daily Living (ADL) |
| spellingShingle | Ivan Miguel Pires Rui Santos Nuno Pombo Nuno M. Garcia Francisco Flórez-Revuelta Susanna Spinsante Rossitza Goleva Eftim Zdravevski Recognition of Activities of Daily Living Based on Environmental Analyses Using Audio Fingerprinting Techniques: A Systematic Review Sensors acoustic sensors fingerprint recognition data processing artificial intelligence mobile computing signal processing algorithms systematic review Activities of Daily Living (ADL) |
| title | Recognition of Activities of Daily Living Based on Environmental Analyses Using Audio Fingerprinting Techniques: A Systematic Review |
| title_full | Recognition of Activities of Daily Living Based on Environmental Analyses Using Audio Fingerprinting Techniques: A Systematic Review |
| title_fullStr | Recognition of Activities of Daily Living Based on Environmental Analyses Using Audio Fingerprinting Techniques: A Systematic Review |
| title_full_unstemmed | Recognition of Activities of Daily Living Based on Environmental Analyses Using Audio Fingerprinting Techniques: A Systematic Review |
| title_short | Recognition of Activities of Daily Living Based on Environmental Analyses Using Audio Fingerprinting Techniques: A Systematic Review |
| title_sort | recognition of activities of daily living based on environmental analyses using audio fingerprinting techniques a systematic review |
| topic | acoustic sensors fingerprint recognition data processing artificial intelligence mobile computing signal processing algorithms systematic review Activities of Daily Living (ADL) |
| url | http://www.mdpi.com/1424-8220/18/1/160 |
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