Computationally efficient sub-band coding of ECG signals

Abstract

A data compression technique is presented for the compression of discrete time electrocardiogram (ECG) signals. The compression system is based on sub-band coding, a technique traditionally used for compressing speech and images. The sub-band coder employs quadrature mirror filter banks (QMF) with up to 32 critically sampled sub-bands. Both finite impulse response (FIR) and the more computationally efficient infinite impulse response (IIR) filter banks are considered as candidates in a complete ECG coding system. The sub-bands are threshold, quantized using uniform quantizers and run-length coded. The output of the run-length coder is further compressed by a Huffman coder. Extensive simulations indicate that 16 sub-bands are a suitable choice for this application. Furthermore, IIR filter banks are preferable due to their superiority in terms of computational efficiency. We conclude that the present scheme, which is suitable for real time implementation on a PC, can provide compression ratios between 5 and 15 without loss of clinical information.