The Research Of ECG Signal Preprocessing And QRS Complex Detection Techniques

As the only electrical signal that reflects cardiac activity, electrocardiograph (ECG) is an important basis for the prevention and diagnosis of cardiovascular disease. With the rapid development of electronic science and technology, the emergence of computer-aided diagnosis makes the ECG automatic analysis become a hot research topic in the field of Medical and Biomedical Engineering.In the thesis, we analyze the generation mechanism and characteristics of ECG at first, then describe and simulate the common algorithms of ECG pretreatment and QRS complex detection in detail. Finally we propose a new algorithm of ECG preprocessing and QRS complex detection to address the deficiencies of the existing algorithms. The new algorithm includes two aspects:ECG preprocessing and QRS detection.We test the new algorithm with MIT/BIH database and QT database, the results show that the new algorithm with a high accuracy and low computational complexity is easier to implement and more suitable for the portable ECG monitor. The main work of the thesis as follows:1. At first, the research background and significance of the ECG automatic analysis technology are described briefly. And introduce the technology developments from two aspects:preprocessing and feature extraction. At the same time, we expound the generation mechanism, physiological significance and acquisition method of the ECG signal, then explain the difficulties in ECG automatic analysis field.2. Introduce the traditional digital filter and the wavelet filter after analyzing the characters of the different noise of ECG. Then design an ECG filter based on lifting wavelet transform, the experimental results prove that the new filter has a good effect with less computation complexity.3. For the QRS complex detection, we introduce the classic algorithm including the difference threshold value algorithm and wavelet transform algorithm.To address the traditional algorithms shortcomings, we propose a new algorithm to detect the QRS complex according to the extreme value points’distribution. The new algorithm is simulated on matlab7.10.0and tested with the MIT/BIH database and QT database. Comparing with other algorithms, implementation of new algorithm is significantly simplified while the detection accuracy is favorable.It is more suitable for the real-time processing in portable ECG instruments.