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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ozdemir, A.T. Orman, A. |
| Copyright Year | 2015 |
| Description | Author affiliation: Fen Bilimleri Enstitusu, Erciyes Univ., Kayseri, Turkey (Orman, A.) || Elektrik Elektron. Muhendisligi Bolumu, Erciyes Univ., Kayseri, Turkey (Ozdemir, A.T.) |
| Abstract | Many researchers work on human motion detection and recognition systems and have been trying to use these systems in order to solve problems in health services. Falls as one of the major health problems are especially seen more frequently among elderly people and reduce the quality of life dramatically with causing serious damages. Therefore, immediate medical intervention is required to victims of falls only in this way it is possible to minimize emotional and mental traumas may arise from physical causes. Immediate intervention is only provided when the fall is noticed and authorities are informed instantly. In this study, we developed an algorithm that automatically detects falls by benefiting from the gyroscope and accelerometer sensor data in smart phones. Tests which involve daily living activities and falls data are applied to the algorithm, and it is seen that falls are distinguished from daily living activities with 100% accuracy. |
| Starting Page | 2561 |
| Ending Page | 2564 |
| File Size | 760480 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467373869 |
| DOI | 10.1109/SIU.2015.7130407 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-05-16 |
| Publisher Place | Turkey |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Computers Reactive power Ground penetrating radar compass accelerometer first aid smart phone Fall detection gyroscope |
| Content Type | Text |
| Resource Type | Article |
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