Real-Time Fall Detection Using Microwave Doppler Sensor-Computational Cost Reduction Method Based on Genetic Algorithm

The risk of falling is a serious problem for the elderly. If the fall remains undetected for a considerable period, hypothermia and dehydration may occur, leading to death. Therefore, real-time detection of falls is critical. We previously proposed a fall-detection system based on a microwave Dopple...

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Bibliographic Details
Published in:IEEE sensors letters 2019-03, Vol.3 (3), p.1-4
Main Authors: Kaburagi, Takashi, Shiba, Kazuaki, Kumagai, Satoshi, Matsumoto, Toshiyuki, Kurihara, Yosuke
Format: Article
Language:English
Subjects:
Dehydration
Doppler effect
Fall detection
genetic algorithm (GA)
Genetic algorithms
Hypothermia
microwave Doppler sensor
Microwave measurement
Microwave theory and techniques
Real time
real-time data processing
Real-time systems
Sensor applications
Sensors
Template matching
Time-frequency analysis
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Summary:The risk of falling is a serious problem for the elderly. If the fall remains undetected for a considerable period, hypothermia and dehydration may occur, leading to death. Therefore, real-time detection of falls is critical. We previously proposed a fall-detection system based on a microwave Doppler sensor, which can capture the object's velocity. Our system performs template matching based on the dynamic time warping distance; hence, the processing time depends on the number of template datasets. Herein, we attempt a real-time fall detection by reducing the number of templates. We apply the genetic algorithm to select better templates. The fitness of the selected templates is evaluated by dividing the accuracy by the number of templates.
ISSN:2475-1472
2475-1472
DOI:10.1109/LSENS.2019.2892006