Iterative Time-Varying Filter Algorithm Based on Discrete Linear Chirp Transform

Denoising of broadband non--stationary signals is a challenging problem in communication systems. In this paper, we introduce a time-varying filter algorithm based on the discrete linear chirp transform (DLCT), which provides local signal decomposition in terms of linear chirps. The method relies on the ability of the DLCT for providing a sparse representation to a wide class of broadband signals. The performance of the proposed algorithm is compared with the discrete fractional Fourier transform (DFrFT) filtering algorithm. Simulation results show that the DLCT algorithm provides better performance than the DFrFT algorithm and consequently achieves high quality filtering.Comment: 6 pages, conference pape

P and R Wave Detection in Complete Congenital Atrioventricular Block

Complete atrioventricular block (type III AVB) is characterized by an absence of P wave transmission to ventricles. This implies that QRS complexes are generated in an autonomous way and are not coordinated with P waves. This work introduces a new algorithm for the detection of P waves for this type of pathology using non-invasive electrocardiographic surface leads. The proposed algorithm is divided into three stages. In the first stage, the R waves located by a QRS detector are used to generate the RR series and time references for the other stages of the algorithm. In the second stage, the ventricular activity (QT segment) is removed by using an adaptive filter that obtains an averaged pattern of the QT segment. In the third stage, a new P wave detector is applied to the residual signal obtained after QT cancellation in order to detect P wave locations and get the PP time series. Eight Holter records from patients with congenital type III AVB were used to verify the proposed algorithm. Although further improvements should be made to improve the algorithm¿s performance, the results obtained show high average values of sensitivity (90.52 %) and positive prediction (90.98%)

Development and analysis of electrocardiography circuit on flexible polymers

Recently, flexible printed circuit (FPC) technology is utilized in electronic industry to reduce the device size and weight. Electrocardiography (ECG) device is one of the healthcare devices needed in small size as to give comfort to user. There are various technique of fabricating circuit on flexible substrate were proposed such as etching, screen printing, and inkjet printing. However, the conductive traces fabricated using those techniques were easily cracked and led to loose of circuit continuity. Thus, the aim of this study is to find the best flexible material to be used with copper tape as conductive traces to replace the method of using nano-scale particle material. ECG circuit is integrated and fabricated on flexible substrate material using vinyl cutting technique. There were three different materials chosen to be used in this study; silicone rubber sheet, Thermoplastic Polyurethane (TPU) and Polyethylene Terephthalate (PET). Material characterization analysis such as Atomic Force Microscopy (AFM), contact angle and peel adhesion test were done on these materials to know the best material suit to be used with conductive copper tape (Copper tape 1181 from 3M). From that, this study has found that PET is the most suitable material to be used because its peel adhesion strength is the highest. Then, ECG circuit was developed using vinyl cutting technique and the circuit performance between flexible substrate and rigid substrate were compared. In the data processing stage, ECG data were denoised using sym20 from Wavelet Transform tool in MATLAB. Signal to noise ratio (SNR) parameter was calculated and used as the signal quality indicator. The data then further analyzed using statistical ANOVA to determine the significant features. Results showed that vinyl cutting method is a successful method to fabricate circuit on PET substrate as the performance of the flexible ECG circuit is comparable with rigid ECG circuit

Removal of artifacts from electrocardiogram

The electrocardiogram is the recording of the electrical potential of heart versus time. The analysis of ECG signal has great importance in the detection of cardiac abnormalities. The electrocardiographic signals are often contaminated by noise from diverse sources. Noises that commonly disturb the basic electrocardiogram are power line interference, instrumentation noise, external electromagnetic field interference, noise due to random body movements and respirational movements. These noises can be classified according to their frequency content. It is essential to reduce these disturbances in ECG signal to improve accuracy and reliability. Different types of adaptive and non-adaptive digital filters have been proposed to remove these noises. In this thesis, window based FIR filters, adaptive filters and wavelet filter bank are applied to remove the noises. Performances of the filters are compared based on the PSNR values. It is difficult to apply filters with fixed filter coefficients to reduce the instrumentation noise, because the time varying behaviour of this noise is not exactly known. Adaptive filter technique is required to overcome this problem, as the filter coefficients can be varied to track the dynamic variations of the signals. In wavelet transform, a signal is analyzed and expressed as a linear combination of the summation of the product of the wavelet coefficients and mother wavelet. The wavelet decomposition offers an excellent resolution both in time and frequency domain. Better estimation of the amplitudes is also obtained in wavelet based denoising