Pairwise classification using combination of statistical descriptors with spectral analysis features for recognizing walking activities
The advancement of sensor technology has provided valuable information for evaluating functional abilities in various application domains. Human activity recognition (HAR) has gained high demand from the researchers to undergo their exploration in activity recognition system by utilizing Micro-machi...
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| Format: | Article |
| Language: | English |
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Universiti Teknikal Malaysia Melaka
2018
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| Online Access: | http://psasir.upm.edu.my/id/eprint/75188/ http://psasir.upm.edu.my/id/eprint/75188/1/Pairwise%20classification%20using%20combination%20of%20statistical%20descriptors%20with%20spectral%20analysis%20features%20for%20recognizing%20walking%20activities.pdf |
| _version_ | 1848857625407520768 |
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| author | Zainudin, M. N. Shah Sulaiman, Md. Nasir Mustapha, Norwati Perumal, Thinagaran |
| author_facet | Zainudin, M. N. Shah Sulaiman, Md. Nasir Mustapha, Norwati Perumal, Thinagaran |
| author_sort | Zainudin, M. N. Shah |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | The advancement of sensor technology has provided valuable information for evaluating functional abilities in various application domains. Human activity recognition (HAR) has gained high demand from the researchers to undergo their exploration in activity recognition system by utilizing Micro-machine Electromechanical (MEMs) sensor technology. Tri-axial accelerometer sensor is utilized to record various kinds of activities signal placed at selected areas of the human bodies. The presence of high inter-class similarities between two or more different activities is considered as a recent challenge in HAR. The nt of incorrectly classified instances involving various types of walking activities could degrade the average accuracy performance. Hence, pairwise classification learning methods are proposed to tackle the problem of differentiating between very similar activities. Several machine learning classifier models are applied using hold out validation approach to evaluate the proposed method. |
| first_indexed | 2025-11-15T12:00:31Z |
| format | Article |
| id | upm-75188 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T12:00:31Z |
| publishDate | 2018 |
| publisher | Universiti Teknikal Malaysia Melaka |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-751882020-04-20T14:30:05Z http://psasir.upm.edu.my/id/eprint/75188/ Pairwise classification using combination of statistical descriptors with spectral analysis features for recognizing walking activities Zainudin, M. N. Shah Sulaiman, Md. Nasir Mustapha, Norwati Perumal, Thinagaran The advancement of sensor technology has provided valuable information for evaluating functional abilities in various application domains. Human activity recognition (HAR) has gained high demand from the researchers to undergo their exploration in activity recognition system by utilizing Micro-machine Electromechanical (MEMs) sensor technology. Tri-axial accelerometer sensor is utilized to record various kinds of activities signal placed at selected areas of the human bodies. The presence of high inter-class similarities between two or more different activities is considered as a recent challenge in HAR. The nt of incorrectly classified instances involving various types of walking activities could degrade the average accuracy performance. Hence, pairwise classification learning methods are proposed to tackle the problem of differentiating between very similar activities. Several machine learning classifier models are applied using hold out validation approach to evaluate the proposed method. Universiti Teknikal Malaysia Melaka 2018 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/75188/1/Pairwise%20classification%20using%20combination%20of%20statistical%20descriptors%20with%20spectral%20analysis%20features%20for%20recognizing%20walking%20activities.pdf Zainudin, M. N. Shah and Sulaiman, Md. Nasir and Mustapha, Norwati and Perumal, Thinagaran (2018) Pairwise classification using combination of statistical descriptors with spectral analysis features for recognizing walking activities. Journal of Telecommunication, Electronic and Computer Engineering, 9 (2-11). 55 - 60. ISSN 2180-1843; ESSN: 2289-8131 https://journal.utem.edu.my/index.php/jtec/article/view/2738 |
| spellingShingle | Zainudin, M. N. Shah Sulaiman, Md. Nasir Mustapha, Norwati Perumal, Thinagaran Pairwise classification using combination of statistical descriptors with spectral analysis features for recognizing walking activities |
| title | Pairwise classification using combination of statistical descriptors with spectral analysis features for recognizing walking activities |
| title_full | Pairwise classification using combination of statistical descriptors with spectral analysis features for recognizing walking activities |
| title_fullStr | Pairwise classification using combination of statistical descriptors with spectral analysis features for recognizing walking activities |
| title_full_unstemmed | Pairwise classification using combination of statistical descriptors with spectral analysis features for recognizing walking activities |
| title_short | Pairwise classification using combination of statistical descriptors with spectral analysis features for recognizing walking activities |
| title_sort | pairwise classification using combination of statistical descriptors with spectral analysis features for recognizing walking activities |
| url | http://psasir.upm.edu.my/id/eprint/75188/ http://psasir.upm.edu.my/id/eprint/75188/ http://psasir.upm.edu.my/id/eprint/75188/1/Pairwise%20classification%20using%20combination%20of%20statistical%20descriptors%20with%20spectral%20analysis%20features%20for%20recognizing%20walking%20activities.pdf |