Development of a fall detection algorithm based on a tri-axial accelerometer
The elder population are at high risk of having a falling accident. Once it happens, timely assistance can dramatically reduce the damage. Obviously, real-time and accurate fall detection is the key. The algorithm proposed in this work can distinguish falls from ADL (activities of daily living) and...
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          | Published in | 2011 4th International Conference on Biomedical Engineering and Informatics (BMEI) Vol. 3; pp. 1371 - 1374 | 
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| Main Authors | , | 
| Format | Conference Proceeding | 
| Language | English | 
| Published | 
            IEEE
    
        01.10.2011
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| Subjects | |
| Online Access | Get full text | 
| ISBN | 142449351X 9781424493517  | 
| ISSN | 1948-2914 | 
| DOI | 10.1109/BMEI.2011.6098542 | 
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| Abstract | The elder population are at high risk of having a falling accident. Once it happens, timely assistance can dramatically reduce the damage. Obviously, real-time and accurate fall detection is the key. The algorithm proposed in this work can distinguish falls from ADL (activities of daily living) and give the information of both fall direction and lying posture through analyzing data from a accelerometer placed in the head level. The experimental results demonstrate that the algorithm is of important practical value. | 
    
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| AbstractList | The elder population are at high risk of having a falling accident. Once it happens, timely assistance can dramatically reduce the damage. Obviously, real-time and accurate fall detection is the key. The algorithm proposed in this work can distinguish falls from ADL (activities of daily living) and give the information of both fall direction and lying posture through analyzing data from a accelerometer placed in the head level. The experimental results demonstrate that the algorithm is of important practical value. | 
    
| Author | Yan Yang Xingqun Zhao  | 
    
| Author_xml | – sequence: 1 surname: Yan Yang fullname: Yan Yang organization: Dept. of Biomed. Eng., Southeast Univ., Nanjing, China – sequence: 2 surname: Xingqun Zhao fullname: Xingqun Zhao email: ndt@seu.edu.cn organization: Dept. of Biomed. Eng., Southeast Univ., Nanjing, China  | 
    
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| PublicationTitle | 2011 4th International Conference on Biomedical Engineering and Informatics (BMEI) | 
    
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| Snippet | The elder population are at high risk of having a falling accident. Once it happens, timely assistance can dramatically reduce the damage. Obviously, real-time... | 
    
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| SubjectTerms | Acceleration Accelerometers Conferences Detection algorithms fall detection Knee posture Real time systems Senior citizens tri-axial accelerometer  | 
    
| Title | Development of a fall detection algorithm based on a tri-axial accelerometer | 
    
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