Artificial Neural Networks as an alternative to traditional fall detection methods
Falls are common events among older adults and may have serious consequences. Automatic fall detection systems are becoming a popular tool to rapidly detect such events, helping family or health personal to rapidly help the person that falls. This paper presents the results obtained in the process o...
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| creator | Vallejo, Marcela Isaza, Claudia V. Lopez, Jose D. |
| description | Falls are common events among older adults and may have serious consequences. Automatic fall detection systems are becoming a popular tool to rapidly detect such events, helping family or health personal to rapidly help the person that falls. This paper presents the results obtained in the process of testing a new fall detection method, based on Artificial Neural Networks (ANN). This method intends to improve fall detection accuracy, by avoiding the traditional threshold - based fall detection methods, and introducing ANN as a suitable option on this application.Also ANN have low computational cost, this characteristic makes them easy to implement on a portable device, comfortable to be wear by the patient. |
| doi_str_mv | 10.1109/EMBC.2013.6609833 |
| format | Conference Proceeding |
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Automatic fall detection systems are becoming a popular tool to rapidly detect such events, helping family or health personal to rapidly help the person that falls. This paper presents the results obtained in the process of testing a new fall detection method, based on Artificial Neural Networks (ANN). 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Automatic fall detection systems are becoming a popular tool to rapidly detect such events, helping family or health personal to rapidly help the person that falls. This paper presents the results obtained in the process of testing a new fall detection method, based on Artificial Neural Networks (ANN). 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Automatic fall detection systems are becoming a popular tool to rapidly detect such events, helping family or health personal to rapidly help the person that falls. This paper presents the results obtained in the process of testing a new fall detection method, based on Artificial Neural Networks (ANN). This method intends to improve fall detection accuracy, by avoiding the traditional threshold - based fall detection methods, and introducing ANN as a suitable option on this application.Also ANN have low computational cost, this characteristic makes them easy to implement on a portable device, comfortable to be wear by the patient.</abstract><cop>United States</cop><pub>IEEE</pub><pmid>24110020</pmid><doi>10.1109/EMBC.2013.6609833</doi><tpages>4</tpages></addata></record> |
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| identifier | ISSN: 1094-687X |
| ispartof | 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013, Vol.2013, p.1648-1651 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Acceleration Accelerometers Accelerometry - instrumentation Accelerometry - methods Accidental Falls - statistics & numerical data Adolescent Adult Artificial neural networks Automatic Data Processing Biomedical monitoring Body Weight Female Humans Male Middle Aged Neural Networks (Computer) Neurons Sensors Training Young Adult |
| title | Artificial Neural Networks as an alternative to traditional fall detection methods |
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