Electrocardiogram Signal Coding via Adaptive Sampling and 2-D Transform Domain Methods

• Main Authors: Wan-Yu Wang, 王琬瑜
• Other Authors: Yu T. Su
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/pfnnk2

碩士 === 國立交通大學 === 電信工程系所 === 95 === The electrocardiogram (ECG) is an important biomedical signal for the diagnosis of heart diseases. Efficicient ECG waveform coding for long-term recording and effective real-time transmission have received constant intensive attention in modern clinical applications. In this thesis, we propose two new ECG waveform coding methods that require reduced memory and provide high compression ratio (CR) performance. The first approach uses a variable sampling rate analog-to-digital converter that adapts to the waveform variation rate. It reduces not only the computational complexity but also the memory requirement for subsequent discrete cosine transform as well. The second approach is based on the observation that ECG signals often exhibit a near-periodic behavior. We first convert the one-dimensional ECG waveform into a two dimensional (2D) array by the Average Magnitude Difference Function (AMDF) method then apply a two dimension time/frequency transform to increase CR as much as possible. The resulting CR is about 21.87 and the percent-root-mean-square (PRD) is 3.25% which is much better than that of the 1-D approach based on adaptive sampling. In order to further improve the performance of the 2-D approach and capture the important part of ECG signals (QRS wave), we employ a sample-dependent multi-rate quatization approach which gives an improved CR of 22.05 and PRD of 2.88%.