Automatic Fall Detection using Smartphone Acceleration Sensor
| Autor: | Tran Tri Dang, Tran Khanh Dang, Hai Truong |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Lie detection
Acceleration General Computer Science Computer science 0206 medical engineering 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing 02 engineering and technology Fall detection False positive rate Android (operating system) 020601 biomedical engineering Simulation |
| Zdroj: | International Journal of Advanced Computer Science and Applications. 7 |
| ISSN: | 2156-5570 2158-107X |
| DOI: | 10.14569/ijacsa.2016.071216 |
| Popis: | In this paper, we describe our work on developing an automatic fall detection technique using smart phone. Fall is detected based on analyzing acceleration patterns generated during various activities. An additional long lie detection algorithm is used to improve fall detection rate while keeping false positive rate at an acceptable value. An application prototype is implemented on Android operating system and is used to evaluate the proposed technique performance. Experiment results show the potential of using this app for fall detection. However, more realistic experiment setting is needed to make this technique suitable for use in real life situations. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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