A filter bank-based algorithm for ECG compression is developed. The proposed method utilises a nearly-perfect reconstruction cosine modulated filter bank to split the incoming signals into several subband signals that are then quantised through thresholding and Huffman encoded. The advantage of the proposed method is that the threshold is chosen so that the quality of the retrieved signal is guaranteed. It is shown that the compression ratio achieved is an improvement over those obtained by previously reported thresholding-based algorithms.Introduction: Several wavelet-based ECG compression methods have recently been developed that report good performance [1][2][3]. Among the reported algorithms, those based on wavelet coefficient thresholding have been shown to be efficient and yield high compression ratios (CRs) [3]. In this Letter, we present an easy to use and efficient ECG compression scheme based on an M-channel maximally decimated filter bank with a parallel structure [4] that guarantees the quality of the retrieved signal. This method is based on that originally reported in [5]. The proposed method incorporates several innovations, including the quantisation of the subband signal samples with less resolution than the original signal samples and entropy-coding by means of a Huffman coder. As a result, the algorithm performs significantly better than other approaches developed using similar techniques.Tests are carried out using the MIT-BIH Arrhythmia Database and the percentage root-mean-square difference (PRD) measurement criteria to evaluate the quality of the retrieved signal. Accordingly, let x[n] and x[n] be the original and the reconstructed signals. The PRD is then defined as:

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We present a new method to design prototype filters for conventional cosine-modulated pseudo-quadrature mirror filter (QMF) banks. This method is based on windowing, and sets the 3-dB cutoff frequency of the filter obtained at 2 . In this way, the filter bank performance can be significantly improved compared to other existing design methods.

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Most of the recent electrocardiogram (ECG) compression approaches developed with the wavelet transform are implemented using the discrete wavelet transform. Conversely, wavelet packets (WP) are not extensively used, although they are an adaptive decomposition for representing signals. In this paper, we present a thresholding-based method to encode ECG signals using WP. The design of the compressor has been carried out according to two main goals: (1) The scheme should be simple to allow real-time implementation; (2) quality, i.e., the reconstructed signal should be as similar as possible to the original signal. The proposed scheme is versatile as far as neither QRS detection nor a priori signal information is required. As such, it can thus be applied to any ECG. Results show that WP perform efficiently and can now be considered as an alternative in ECG compression applications.