Fall detection using single-tree complex wavelet transform

Date
2013
Advisor
Supervisor
Co-Advisor
Co-Supervisor
Instructor
Source Title
Pattern Recognition Letters
Print ISSN
0167-8655
Electronic ISSN
Publisher
Elsevier
Volume
34
Issue
15
Pages
1945 - 1952
Language
English
Type
Article
Journal Title
Journal ISSN
Volume Title
Series
Abstract

The 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.

Course
Other identifiers
Book Title
Keywords
Falling person detection, Feature extraction, PIR sensor, Single-tree complex wavelet transform, Support vector machines, Vibration sensor, Ambient assisted living (AAL), Complex wavelet transforms, Feature extraction methods, Mel frequency cepstrum coefficients, Person detection, Pir sensors, Telecommunications infrastructures, Vibration sensors, Discrete Fourier transforms, Feature extraction, Image segmentation, Personal computers, Sensors, Support vector machines, Ventilation exhausts, Wavelet transforms, Forestry
Citation
Published Version (Please cite this version)