Md. Maniruzzaman

Least-Mean-Square algorithm based adaptive filters for removing power line interference from ECG signal

The 50 Hz power line is one of the main sources of interference in ECG signal measurement, and it distorts the original ECG signal while recording. Recently, adaptive filtering has become one of the effective and popular methods for the processing and analysis of the ECG signal. In this study, we have used adaptive filters to remove the power line interference from the ECG signal. We have used different adaptive filter algorithms, such as, Least-Mean-Square (LMS), Block LMS (BLMS), Delay LMS (DLMS), Adjoint LMS, Filtered-X (XLMS), Normalized LMS (NLMS) and Fast Fourier Transform BLMS (FFT BLMS). We have used the Signal Processing Toolbox of the mentioned algorithms built in MATLAB®. It reveals that among all the adaptive filters, the adaptive NLMS filter removes the 50 Hz power line interference more effectively.

Removing power line interference from ECG signal using adaptive filter and notch filter

Performance of two adaptive filters, such as, normalized least-mean-square (NLMS) adaptive filter and recursive-least-square (RLS) adaptive filter are compared with a traditional notch filter both in time and frequency domains to remove the power line interference from the ECG signal. The power spectral density (PSD) and spectrogram analyses are also performed. Different performance parameters, such as, SNR, %PRD and MSE are also calculated. Real time recorded data from the benchmark MIT-BIH arrhythmia database has been used. The result demonstrates superior performance of adaptive NLMS filter for removing power line interference over adaptive RLS and notch filters.

Denoising ECG signal using different wavelet families and comparison with other techniques

Electrocardiogram (ECG) is a non-stationary biological signal. It detects the cardiac abnormalities by measuring the electrical activity generated in the heart. But ECG is very much sensitive. Its amplitude and duration can be corrupted by various types of noise, especially, power line interference, which sometimes leads to misdiagnosis. In this study different wavelet families identification and performance estimation is done for denoising ECG signal and the results are compared with adaptive NLMS and notch filter in both time and frequency domain. For evaluating the performance magnitude squared coherence (MSC), amplitude spectrum, power spectral density (PSD) and spectrogram are analyzed. SNR, %PRD, MSE, NMSE, RMSE, NRMSE and ESD performance parameter are also examined. Simulation is based on Signal Processing Toolbox built in MATLAB®. The simulation result represent that wavelet transform is an excellent technique for denoising ECG signal.

Preferentially Oriented Cu[111] Layer Formed on Thin Nb Barrier on SiO2

The texture of preferentially oriented Cu[111] deposited on a thin Nb layer is characterized in a thin-film stacked structure of Cu/Nb/SiO2/Si in an attempt to prepare a Cu[111] seed layer of interconnects on an extremely thin diffusion barrier. The Cu[111] layer is obtained on Nb films of [110] orientation at various thicknesses; however, the mosaic spread of Cu[111] texture depends on the thickness of Nb film underneath. The full width at half maximum of the ω-rocking curve measurement is ~3° for the Cu[111] layer on a 100-nm-thick Nb layer, which increases to ~4 and ~5° for that on 20- and 10-nm-thick Nb layers, respectively. Transmission electron microscopy reveals the 10-nm-thick Nb layer consisting of fine relatively mosaic-spread [110] grains, which is a result of the initial stage of the nucleation type growth of the Nb film in a columnar structure on SiO2. It is revealed that the Cu[111] texture of relatively good mosaicity in a columnar structure is obtained on an extremely thin Nb layer of 10 nm thickness.

ECG signal for artrial fibrillation detection

Atrial Fibrillation (AF) is one of the most common cardiac arrhythmias. The number of patients related to heart failure due to AF is increasing day by day. Early detection of AF may reduce the risk of death due to heart failure. So, it has become more important to detect AF. There are various methods to detect AF. In this paper, we use ECG signal for AF detection based on RR interval. The MIT-BIH Atrial Fibrillation database is used to import ECG data for analysis. We use the algorithm that mainly follows statistical method for detection of AF. Parametric statistic RMSSD and SE, and non-parametric statistic, TPR are used for this purpose. The threshold value of RMSSD divided by Mean RR is 0.1, SE is 0.7 and TPR is greater than 0.54 and less than 0.77 is considered for AF detection. The resultant value of RMSSD, SE and TPR of every beat is checked weather it crosses the threshold level or not. If all the three parameters cross the threshold level then the beat flagged as AF. The result is compared with the annotations of the database and the sensitivity, specificity and accuracy is determined. The algorithm has the sensitivity of 98%, specificity of 98% and accuracy of 95%. The result obtained in this study is appreciable compared to the other study found in the literature.

FPGA implementation of LBlock lightweight block cipher

The ubiquitous computing era is characterized by wide deployment of resource constraint devices. Secure communication between such devices encounters a big challenge due to their resource limitation. The lightweight cryptographic algorithms are developed to address this challenge. In this work, implementation of LBlock, a lightweight encryption algorithm is investigated in Altera DE1 FPGA board. The encryption algorithm involves a Feistal structure and requires 32 clock cycles to encrypt 64-bit data. The implementation results show that it requires 326 Logic Elements (LEs) in Cyclone II EP2C20F484C7 platform. The maximum clock frequency was reported as 156.32 MHz and a corresponding power consumption of 107.62 mW. Also, the throughput is found as 312 Mbps. These results are better as compared to some other lightweight encryption such as XTEA and Hummingbird for the same FPGA platform.

Estimation of crosstalk noise for RLC interconnects in deep submicron VLSI circuit

The modeling of interconnections is very much important, as the performance of VLSI circuit is limited by interconnect related failure modes, such as coupled noise and delay. Inductance along with capacitance causes noise in the signals, which may adversely affect the performance of the circuit and signal integrity. An analytical expression for crosstalk noise voltage is derived in this study using L model for RLC global interconnects in deep submicron VLSI circuit. Then the noise voltage is estimated by simulation using HSPICE. The result shows that the L model is good enough to compute crosstalk noise for RLC interconnects.

Analysis of dispersion and confinement loss in photonic crystal fiber

Chromatic dispersion and confinement loss are two significant issues in the design of photonic crystal fiber. This paper presents a systematic study of these two issues for five rings hexagonal photonic crystal fiber along with its dependence on structure and material used. The values of these two propagation characteristics obtained for different refractive indices and hole diameters reveal that optimization of these two characteristics depend on the application requirements, but not for determining which fiber structure is the best. Photonic crystal fiber structure is modeled using OPTI FDTD 8 simulation software and dispersion as well as loss is plotted by MATHCAD 2000i Professional tool.

Interpretation of Cu(111)//Nb(110) growth on SiO 2 by Transmission Electron Microscopy

The [110]-textured extremely thin Nb barrier layer is prepared on an amorphous SiO2 substrate, on which the preferentially oriented Cu [111] texture is obtained. Transmission Electron Microscopy (TEM) observation indicates that nanocrystalline grains no larger than ~10 nm with a spread [110] orientation along the substrate normal direction is characteristic of a 10 nm thick Nb barrier on SiO2, whereas for the 100 nm thick barrier, the well-oriented columnar structure of a Nb [110] layer is obtained by ordering the orientation during the increase in the thickness of the Nb film by the coalescence of the initially deposited nanocrystalline grains. The quality of Cu [111] layer is much better when deposited on 100 nm thick Nb layer than that on a 10 nm thick barrier.

Formation of Preferentially Oriented Cu [111] Layer on Nb [110] Barrier on SiO2

A preferentially oriented Cu [111] layer is obtained on an oriented Nb [110] barrier formed on thermally grown SiO2. We examine the characteristics of the orientation and textures in the Cu/Nb/SiO2/Si model system by X-ray diffraction analysis and cross-sectional transmission electron microscopy (TEM). It was confirmed by X-ray pole figures and ω-rocking curve measurements that the preferentially oriented Cu [111] layer in the fiber structure showing a good mosaicity with a full width at half maximum of ~3° in the ω-rocking curve was grown on an oriented Nb [110] barrier. The TEM observation shows a pronounced columnar structure in the oriented Cu and Nb layers on amorphous SiO2 and the textures are stable due to annealing at 500°C.