Beat-based ECG compression using gain-shape vector quantization

An electrocardiogram (ECG) data compression scheme is presented using the gain-shape vector quantization. The proposed approach utilizes the fact that ECG signals generally show redundancy among adjacent heartbeats and adjacent samples. An ECG signal is QRS detected and segmented according to the de...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 2005-11, Vol.52 (11), p.1882-1888
Main Authors: Sun, Chia-Chun, Tai, Shen-Chuan
Format: Article
Language:English
Subjects:
Algorithms
AREA
Arrhythmias, Cardiac - diagnosis
Arrhythmias, Cardiac - physiopathology
Artificial Intelligence
Bit rate
Data compression
Data Compression - methods
Diagnosis, Computer-Assisted - methods
Discrete cosine transforms
Discrete wavelet transforms
ECG compression
Electrocardiography
Electrocardiography - methods
Heart Rate
Humans
Image coding
Pattern Recognition, Automated - methods
Signal detection
Signal Processing, Computer-Assisted
Sun
Vector quantization
vector quantization (VQ)
Visual databases
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Summary:An electrocardiogram (ECG) data compression scheme is presented using the gain-shape vector quantization. The proposed approach utilizes the fact that ECG signals generally show redundancy among adjacent heartbeats and adjacent samples. An ECG signal is QRS detected and segmented according to the detected fiducial points. The segmented heartbeats are vector quantized, and the residual signals are calculated and encoded using the AREA algorithm. The experimental results show that with the proposed method both visual quality and the objective quality are excellent even in low bit rates. An average PRD of 5.97% at 127 b/s is obtained for the entire 48 records in the MIT-BIH database. The proposed method also outperforms others for the same test dataset.
ISSN:0018-9294
1558-2531
DOI:10.1109/TBME.2005.856270