Browsing by Author "Wu, Hung-Tsai"

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Biometric Identification Using JPEG2000 Compressed ECG Signals
(2015-10-01)
Wu, Hung-Tsai
;
Wu, Yi-Ting
;
Chang, Wen-Whei
;
電信工程研究所
;
Institute of Communications Engineering
In wireless telecardiology applications, electrocardiogram (ECG) signals are often represented in compressed format for efficient transmission and storage purposes. Incorporation of compressed ECG based biometric enables faster person identification as it by-passes the full decompression. This study presents a new method to combine ECG biometrics with data compression within a common JPEG2000 framework. To this end, an ECG signal is considered as an image and the JPEG2000 standard is applied for data compression. Features relating to ECG morphology and heartbeat intervals are computed directly from the compressed ECG. Different classification approaches are used for person identification. Experiments on standard ECG databases demonstrate the validity of the proposed system for biometric identification with high accuracies on both healthy and diseased subjects.
Compressed Domain ECG Biometric Identification using JPEG2000
(2015-01-01)
Wu, Yi-Ting
;
Wu, Hung-Tsai
;
Chang, Wen-Whei
;
電信工程研究所
;
Institute of Communications Engineering
In wireless telecardiology applications, electrocardiogram (ECG) signals are often represented in compressed format for efficient transmission and storage purposes. Incorporation of compressed ECG based biometric enables faster person identification as it by-passes the full decompression. This study presents a new method to combine ECG biometrics with data compression within a common JPEG2000 framework. To this end, ECG signal is considered as an image and the JPEG2000 standard is applied for data compression. Features relating to ECG morphology and heartbeat intervals are computed directly from the compressed ECG. Different classification approaches are used for person identification. Experiments on standard ECG databases demonstrate the validity of the proposed system for biometric identification with high accuracies on both healthy and diseased subjects.
Distributed Source Coding for Mobile ECG Signal Monitoring
(2012-01-01)
Wu, Hung-Tsai
;
Tsai, Wei-Ying
;
Chang, Wen-Whei
;
電信工程研究所
;
Institute of Communications Engineering
This paper describes the design and implementation of an ECG signal monitoring system that is compatible with existing mobile telecommunications networks. First, a two-dimensional ECG signal compression scheme is presented using the distributed source coding (DSC). Also proposed is a modified BCJR algorithm which further enhances the DSC decoding by exploiting the symbol-level a priori information. Finally, we implement a novel integrated system comprising a mobile telephone, with sensors for patient monitoring, and a remote receiver linked by cellular networks. The system, when fully developed, will become powerful aids to monitoring a patient for mobile telemedicine and for emergency situations.
Distributed Source Coding for Real-Time ECG Signal Monitoring
(2014-08-01)
Wu, Hung-Tsai
;
Tsai, Wei-Ying
;
Chang, Wen-Whei
;
電信工程研究所
;
Institute of Communications Engineering
Wireless patient monitoring is an active research area with the goal of ubiquitous health care services. This study presents a novel means of exploiting the distributed source coding (DSC) in low-complexity compression of ECG signals. We first convert the ECG data compression to an equivalent channel coding problem and exploit a linear channel code for the DSC construction. Performance is further enhanced by the use of a correlation channel that more precisely characterizes the statistical dependencies of ECG signals. Also proposed is a modified BCJR algorithm which performs symbol decoding of binary convolutional codes to better exploit the source's a priori information. Finally, a complete setup system for online ambulatory ECG monitoring via mobile cellular networks is presented. Experiments on the MIT-BIH arrhythmia database and real-time acquired ECG signals demonstrate that the proposed system outperforms other schemes in terms of encoder complexity and coding efficiency.
Iterative Symbol Decoding of Variable-Length Codes with Convolutional Codes
(2016-02-29)
Wu, Hung-Tsai
;
Wu, Chun-Feng
;
Chang, Wen-Whei
;
傳播研究所
;
Institute of Communication Studies
In this paper, we present a symbol-level iterative sourcechannel decoding (ISCD) algorithm for reliable transmission of variable-length codes (VLCs). Firstly, an improved source a posteriori probability (APP) decoding approach is proposed for packetized variable-length encoded Markov sources. Also proposed is a recursive implementation based on a three-dimensional joint trellis for symbol decoding of binary convolutional codes. APP channel decoding on this joint trellis is realized by modification of the Bahl-Cocke-Jelinek-Raviv algorithm and adaptation to the non-stationary VLC trellis. Simulation results indicate that the proposed ISCD scheme allows to exchange between its constituent decoders the symbol-level extrinsic information and achieves high robustness against channel noises.
Symbol-Based Joint Decoding of Convolutionally Encoded Variable-Length Codes
(2012-01-01)
Wu, Hung-Tsai
;
Lin, Chih-Hsien
;
Chang, Wen-Whei
;
電信工程研究所
;
Institute of Communications Engineering
In this paper, we present a symbol-level joint source-channel decoding (JSCD) algorithm for transmission of convolutionally encoded variable-length codes (VLCs). The proposed algorithm is based on a two-dimensional state representation which leads to a three-dimensional code trellis. JSCD on this trellis is realized by employing a modified BCJR algorithm which allows to fully exploit the symbol-level source a priori information. Experimental results indicate that the proposed JSCD scheme achieves high robustness against channel noises.