DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Science, Engineering and Technology(IJASEAT)-IJASEAT |
 Journal Home Volume Issue |
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Issue |
Volume-6, Issue-3, Spl. Iss-1 ( Aug, 2018 ) | |||||||||
Paper Title |
Indoor Positioning and Fall Detection System Design for People with Alzheimer’s and Epilepsy Disease | |||||||||
Author Name |
Anday Duru, Kadir Ileri, Idris Kabalci | |||||||||
Affilition |
Biomedical Engineering Department, Karabuk University, Turkey Electrical & Electronics Engineering Department, Karabuk University, Turkey | |||||||||
Pages |
48-52 | |||||||||
Abstract |
Alzheimer and Epilepsy are tremendously increasing neurodegenerative diseases in the world. Alzheimer’s disease causes hallucinations, wandering, falls and incidence of getting lost. On the other hand, Epilepsy seizures may occur at any time. Hence, a smart tracking system can help to monitor and locate patients. Although global positioning systems are used in variety of tracking applications, their use is mainly based on outdoor environments and they can provide sufficient accuracy. However, patients are mostly spent their time in indoor environments. Since global positioning system signals are disrupted and attenuated by materials between user and satellite, it is hard to locate user in a building. At this point, there needs to be a different technology for tracking patients in indoor environment for both general and emergencies. In this study, ultra-wideband technology has been chosen for indoor positioning system designbecause of its very low energy consumption, precision rate, robustness and low interference feature. Also, a smart fall detector has been added to the system for emergencies. The created system can differentiate falls with the help of accelerometer and locate patients for intended area. The end product tests showed that the possibility of tracking and detecting falls with an error of 26.23 cm depending on conditions. This value also states that it is an assuring system for various positioning applications. Keywords - UWB, Indoor Positioning System, Fall Detection, Wireless Sensor Network. | |||||||||
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