A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ten lectures on wavelets
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Computer aided diagnosis of ECG data on the least square support vector machine
Digital Signal Processing
Usage of eigenvector methods in implementation of automated diagnostic systems for ECG beats
Digital Signal Processing
Combined entropy based method for detection of QRS complexes in 12-lead electrocardiogram using SVM
Computers in Biology and Medicine
Wavelet-based ECG compression by bit-field preserving and running length encoding
Computer Methods and Programs in Biomedicine
Robust clustering methods: a unified view
IEEE Transactions on Fuzzy Systems
Block-Based Neural Networks for Personalized ECG Signal Classification
IEEE Transactions on Neural Networks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special issue on recent advances in biometrics
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This paper describes a signal processing technique for ECG signal analysis based upon the combination of wavelet analysis and fuzzy c-means clustering. The signal analysis technique is implemented into a biomedical signal diagnostic unit that is the carry on device for the Wireless Nano-Bios Diagnostic System (WNBDS) developed at National Taiwan University. The WNBDS integrates mobile devices and remote data base servers to conduct online monitoring and remote healthcare applications. The signal analysis and diagnostic algorithms in this paper are implemented in an embedded mobile device to conduct mobile biomedical signal diagnostics. At this stage, the Electrocardiogram (ECG or EKG) is analyzed for patient health monitoring. The ECG signal processing is based on the wavelet analysis, and the diagnosis is based on fuzzy clustering. The embedded system is realized with the Windows CE operating system.