Development of wearable human fall detection system using multilayer perceptron neural network
This paper presents an accurate wearable fall detection system which can identify the occurrence of falls among elderly population. A waist worn tri-axial accelerometer was used to capture the movement signals of human body. A set of laboratory-based falls and activities of daily living (ADL) were p...
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Atlantis Press and Taylor & Francis
2013
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Online Access: | http://psasir.upm.edu.my/id/eprint/15345/1/Development%20of%20wearable%20human%20fall%20detection%20system%20using%20multilayer%20perceptron%20neural%20network.pdf http://psasir.upm.edu.my/id/eprint/15345/ https://www.tandfonline.com/doi/abs/10.1080/18756891.2013.761769 |
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my.upm.eprints.153452019-07-08T07:30:04Z http://psasir.upm.edu.my/id/eprint/15345/ Development of wearable human fall detection system using multilayer perceptron neural network Kerdegari, Hamideh Samsudin, Khairulmizam Ramli, Abdul Rahman Ghotoorlar, Saeid Mokaram This paper presents an accurate wearable fall detection system which can identify the occurrence of falls among elderly population. A waist worn tri-axial accelerometer was used to capture the movement signals of human body. A set of laboratory-based falls and activities of daily living (ADL) were performed by volunteers with different physical characteristics. The collected acceleration patterns were classified precisely to fall and ADL using multilayer perceptron (MLP) neural network. This work was resulted to a high accuracy wearable fall-detection system with the accuracy of 91.6%. Atlantis Press and Taylor & Francis 2013 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/15345/1/Development%20of%20wearable%20human%20fall%20detection%20system%20using%20multilayer%20perceptron%20neural%20network.pdf Kerdegari, Hamideh and Samsudin, Khairulmizam and Ramli, Abdul Rahman and Ghotoorlar, Saeid Mokaram (2013) Development of wearable human fall detection system using multilayer perceptron neural network. International Journal of Computational Intelligence Systems, 6 (1). pp. 127-136. ISSN 1875-6891; ESSN: 1875-6883 https://www.tandfonline.com/doi/abs/10.1080/18756891.2013.761769 10.1080/18756891.2013.761769 |
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This paper presents an accurate wearable fall detection system which can identify the occurrence of falls among elderly population. A waist worn tri-axial accelerometer was used to capture the movement signals of human body. A set of laboratory-based falls and activities of daily living (ADL) were performed by volunteers with different physical characteristics. The collected acceleration patterns were classified precisely to fall and ADL using multilayer perceptron (MLP) neural network. This work was resulted to a high accuracy wearable fall-detection system with the accuracy of 91.6%. |
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Article |
author |
Kerdegari, Hamideh Samsudin, Khairulmizam Ramli, Abdul Rahman Ghotoorlar, Saeid Mokaram |
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Kerdegari, Hamideh Samsudin, Khairulmizam Ramli, Abdul Rahman Ghotoorlar, Saeid Mokaram Development of wearable human fall detection system using multilayer perceptron neural network |
author_facet |
Kerdegari, Hamideh Samsudin, Khairulmizam Ramli, Abdul Rahman Ghotoorlar, Saeid Mokaram |
author_sort |
Kerdegari, Hamideh |
title |
Development of wearable human fall detection system using multilayer perceptron neural network |
title_short |
Development of wearable human fall detection system using multilayer perceptron neural network |
title_full |
Development of wearable human fall detection system using multilayer perceptron neural network |
title_fullStr |
Development of wearable human fall detection system using multilayer perceptron neural network |
title_full_unstemmed |
Development of wearable human fall detection system using multilayer perceptron neural network |
title_sort |
development of wearable human fall detection system using multilayer perceptron neural network |
publisher |
Atlantis Press and Taylor & Francis |
publishDate |
2013 |
url |
http://psasir.upm.edu.my/id/eprint/15345/1/Development%20of%20wearable%20human%20fall%20detection%20system%20using%20multilayer%20perceptron%20neural%20network.pdf http://psasir.upm.edu.my/id/eprint/15345/ https://www.tandfonline.com/doi/abs/10.1080/18756891.2013.761769 |
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13.18916 |