DocumentCode :
1978065
Title :
Evaluation of heart condition based on ballistocardiogram classification using compactly supported wavelet transforms and neural networks
Author :
Akhbardeh, Alireza ; Junnila, Sakari ; Koivuluoma, Mikko ; Koivistoinen, Teemu ; Värri, Alpo
Author_Institution :
Inst. of Signal Process., Tampere Univ. of Technol.
fYear :
2005
fDate :
28-31 Aug. 2005
Firstpage :
843
Lastpage :
848
Abstract :
One of the most usual causes of death of the human are among heart diseases. Several electronic devices have been developed to assist clinicians in monitoring and diagnosing heart diseases. Ballistocardiography (BCG) was one of popular methods before the 1970s but after that other methods have replaced it, partly because the devices were difficult to construct. Recently developed sensors offer new unobtrusive possibilities to evaluate the condition of the patient´s heart even at home without attaching electrodes to the patient. Thus, it is suitable for evaluation of the heart condition in any place because of being user-friendly method. In this study, we applied compactly supported (Daubechies as well as biorthogonal) wavelet transforms in a comparison way to extract essential features of the BCG signal and neural networks to classify the BCG. Initial tests with BCG from six subjects indicate that the method can classify the subjects to three classes with a high accuracy. The method is almost insensitive to latency and non-linear disturbance. Moreover, the wavelet transform requires no prior knowledge of the statistical distribution of data samples and the computational complexity and training time are reduced
Keywords :
cardiology; diseases; medical signal processing; neural nets; patient diagnosis; patient monitoring; signal classification; statistical distributions; wavelet transforms; BCG signal; Daubechies wavelet transform; ballistocardiogram classification; biorthogonal wavelet transform; computational complexity; data sampling; electronic device; heart condition; heart disease diagnosis; heart disease monitoring; neural network; statistical distribution; training time; Cardiac disease; Electrodes; Feature extraction; Heart; Humans; Joining processes; Neural networks; Patient monitoring; Testing; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Applications, 2005. CCA 2005. Proceedings of 2005 IEEE Conference on
Conference_Location :
Toronto, Ont.
Print_ISBN :
0-7803-9354-6
Type :
conf
DOI :
10.1109/CCA.2005.1507234
Filename :
1507234
Link To Document :
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