Unobstructive Body Area Networks (BAN) for Efficient Movement Monitoring
The technological advances in medical sensors, low-power microelectronics and miniaturization, wireless communications and networks have enabled the appearance of a new generation of wireless sensor networks: the so-called wireless body area networks (WBAN). These networks can be used for continuous...
| Published in: | Sensors |
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| Main Authors: | , , , |
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2012-09-01
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| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/12/9/12473 |
| _version_ | 1852702532512514048 |
|---|---|
| author | António Pereira Florentino Fdez-Riverola Filipe Felisberto Nuno Costa |
| author_facet | António Pereira Florentino Fdez-Riverola Filipe Felisberto Nuno Costa |
| author_sort | António Pereira |
| collection | DOAJ |
| container_title | Sensors |
| description | The technological advances in medical sensors, low-power microelectronics and miniaturization, wireless communications and networks have enabled the appearance of a new generation of wireless sensor networks: the so-called wireless body area networks (WBAN). These networks can be used for continuous monitoring of vital parameters, movement, and the surrounding environment. The data gathered by these networks contributes to improve users’ quality of life and allows the creation of a knowledge database by using learning techniques, useful to infer abnormal behaviour. In this paper we present a wireless body area network architecture to recognize human movement, identify human postures and detect harmful activities in order to prevent risk situations. The WBAN was created using tiny, cheap and low-power nodes with inertial and physiological sensors, strategically placed on the human body. Doing so, in an as ubiquitous as possible way, ensures that its impact on the users’ daily actions is minimum. The information collected by these sensors is transmitted to a central server capable of analysing and processing their data. The proposed system creates movement profiles based on the data sent by the WBAN’s nodes, and is able to detect in real time any abnormal movement and allows for a monitored rehabilitation of the user. |
| format | Article |
| id | doaj-art-e2dc32c250564fa597b62d5bc596f30a |
| institution | Directory of Open Access Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2012-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| spelling | doaj-art-e2dc32c250564fa597b62d5bc596f30a2025-08-19T21:19:56ZengMDPI AGSensors1424-82202012-09-01129124731248810.3390/s120912473Unobstructive Body Area Networks (BAN) for Efficient Movement MonitoringAntónio PereiraFlorentino Fdez-RiverolaFilipe FelisbertoNuno CostaThe technological advances in medical sensors, low-power microelectronics and miniaturization, wireless communications and networks have enabled the appearance of a new generation of wireless sensor networks: the so-called wireless body area networks (WBAN). These networks can be used for continuous monitoring of vital parameters, movement, and the surrounding environment. The data gathered by these networks contributes to improve users’ quality of life and allows the creation of a knowledge database by using learning techniques, useful to infer abnormal behaviour. In this paper we present a wireless body area network architecture to recognize human movement, identify human postures and detect harmful activities in order to prevent risk situations. The WBAN was created using tiny, cheap and low-power nodes with inertial and physiological sensors, strategically placed on the human body. Doing so, in an as ubiquitous as possible way, ensures that its impact on the users’ daily actions is minimum. The information collected by these sensors is transmitted to a central server capable of analysing and processing their data. The proposed system creates movement profiles based on the data sent by the WBAN’s nodes, and is able to detect in real time any abnormal movement and allows for a monitored rehabilitation of the user.http://www.mdpi.com/1424-8220/12/9/12473Wireless Body Area Networksmotion recognitionrehabilitationprofilinginertial and physiological sensors |
| spellingShingle | António Pereira Florentino Fdez-Riverola Filipe Felisberto Nuno Costa Unobstructive Body Area Networks (BAN) for Efficient Movement Monitoring Wireless Body Area Networks motion recognition rehabilitation profiling inertial and physiological sensors |
| title | Unobstructive Body Area Networks (BAN) for Efficient Movement Monitoring |
| title_full | Unobstructive Body Area Networks (BAN) for Efficient Movement Monitoring |
| title_fullStr | Unobstructive Body Area Networks (BAN) for Efficient Movement Monitoring |
| title_full_unstemmed | Unobstructive Body Area Networks (BAN) for Efficient Movement Monitoring |
| title_short | Unobstructive Body Area Networks (BAN) for Efficient Movement Monitoring |
| title_sort | unobstructive body area networks ban for efficient movement monitoring |
| topic | Wireless Body Area Networks motion recognition rehabilitation profiling inertial and physiological sensors |
| url | http://www.mdpi.com/1424-8220/12/9/12473 |
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