Browsing by Subject "Falling person detection"
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Item Open Access Fall detection using single-tree complex wavelet transform(Elsevier, 2013) Yazar, A.; Keskin, F.; Töreyin, B. U.; Çetin, A. EnisThe goal of Ambient Assisted Living (AAL) research is to improve the quality of life of the elderly and handicapped people and help them maintain an independent lifestyle with the use of sensors, signal processing and telecommunications infrastructure. Unusual human activity detection such as fall detection has important applications. In this paper, a fall detection algorithm for a low cost AAL system using vibration and passive infrared (PIR) sensors is proposed. The single-tree complex wavelet transform (ST-CWT) is used for feature extraction from vibration sensor signal. The proposed feature extraction scheme is compared to discrete Fourier transform and mel-frequency cepstrum coefficients based feature extraction methods. Vibration signal features are classified into "fall" and "ordinary activity" classes using Euclidean distance, Mahalanobis distance, and support vector machine (SVM) classifiers, and they are compared to each other. The PIR sensor is used for the detection of a moving person in a region of interest. The proposed system works in real-time on a standard personal computer.Item Open Access Vibrasyon ve PIR algılayıcılar kullanılarak çevre destekli akıllı ev tasarımı(IEEE, 2013-04) Yazar, Ahmet; Çetin, A. EnisIntelligent ambient assisted living systems for elderly and handicapped people become affordable with the recent advances in computer and sensor technologies. In this paper, fall detection algorithm using multiple passive infrared sensors is developed. As a novel method for detecting a falling person, two passive infrared sensors are used concurrently in a room and developed a determination algorithm depending on the height at which the falling event is happened. Motionles detection system is integrated with the falling person detection system to provide a complete solution. Detection algorithms are implemented using embedded microprocessors. © 2013 IEEE.