ECG QRS Complex detection with programmable hardware.

In recent years, algorithm based on Mathematical Morphology and wavelet transform has been proposed for ECG QRS Complex detection. However, its intensity of computation is high. This paper proposes the algorithm and hardware architecture for the whole system of QRS Complex detection based on Mathematical Morphology and Quadratic Spline wavelet transform, with implementation in Field Programmable Gate Array (FPGA). The system consists of Morphological filtering, Quadratic Spline wavelet transform and Modulus Maxima Pair Recognition modules. The parallel and pipelined architecture of system can operate in the maximum 35MHz with throughput of one sample per clock cycle. The QRS Complex detection accuracy for MIT/BIH arrhythmia database recordings and resource consumption are reported. The design is suitable for both batch processing of huge volume ECG data and real time applications for portable devices.

[1]  P.E. Trahanias,et al.  An approach to QRS complex detection using mathematical morphology , 1993, IEEE Transactions on Biomedical Engineering.

[2]  Pablo Laguna,et al.  A wavelet-based ECG delineator: evaluation on standard databases , 2004, IEEE Transactions on Biomedical Engineering.

[3]  Liu Shaoying Detection of QRS complex using mathematical morphology and wavelet transform , 2004 .

[4]  Mak Peng Un,et al.  QRS Recognition with Programmable Hardware , 2008, 2008 2nd International Conference on Bioinformatics and Biomedical Engineering.

[5]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Peng Un Mak,et al.  ECG Parameter Extractor of Intelligent Home Healthcare Embedded System , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[7]  Hui-long Duan,et al.  [The application of mathematical morphology in ECG signal processing]. , 2006, Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation.

[8]  C. Li,et al.  Detection of ECG characteristic points using wavelet transforms. , 1995, IEEE transactions on bio-medical engineering.

[9]  Y Gao,et al.  [An ECG waves separation technique based on mathematical morphology]. , 2001, Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi.