Search results for: Biomedical Signal Processing

Authors: Batel Noureddine, Mehenni Mohamed, Kouadik Smain

Abstract:

In a transcutanious inductive coupling of a biomedical implant, a new formula is given for the study of the Radio Frequency power attenuation by the biological tissue. The loss of the signal power is related to its interaction with the biological tissue and the composition of this one. A confrontation with the practical measurements done with a synthetic muscle into a Faraday cage, allowed a checking of the obtained theoretical results. The supply/data transfer systems used in the case of biomedical implants, can be well dimensioned by taking in account this type of power attenuation.

Keywords: Biological tissue, coupled coils, implanted device, power attenuation.

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Authors: Surinder Singh, Gursewak Singh Lovkesh

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We have designed wavelength conversion based on four wave mixing in an optical fiber at 10 Gb/s. The power of converted signal increases with increase in signal power. The converted signal power is investigated as a function of input signal power and pump power. On comparison of converted signal power at different value of input signal power, we observe that best converted signal power is obtained at -2 dBm input signal power for both up conversion as well as for down conversion. Further, FWM efficiency, quality factor is observed for increase in input signal power and optical fiber length.

Keywords: FWM, Optical fiber, Quality, Wavelength Converter.

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Authors: Morteza Moazami-Goudarzi, Ali Taheri, Mohammad Pooyan, Reza Mahboobi

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In this paper we are to find the optimum multiwavelet for compression of electrocardiogram (ECG) signals and then, selecting it for using with SPIHT codec. At present, it is not well known which multiwavelet is the best choice for optimum compression of ECG. In this work, we examine different multiwavelets on 24 sets of ECG data with entirely different characteristics, selected from MIT-BIH database. For assessing the functionality of the different multiwavelets in compressing ECG signals, in addition to known factors such as Compression Ratio (CR), Percent Root Difference (PRD), Distortion (D), Root Mean Square Error (RMSE) in compression literature, we also employed the Cross Correlation (CC) criterion for studying the morphological relations between the reconstructed and the original ECG signal and Signal to reconstruction Noise Ratio (SNR). The simulation results show that the Cardinal Balanced Multiwavelet (cardbal2) by the means of identity (Id) prefiltering method to be the best effective transformation. After finding the most efficient multiwavelet, we apply SPIHT coding algorithm on the transformed signal by this multiwavelet.

Keywords: ECG compression, Prefiltering, Cardinal Balanced Multiwavelet.

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Authors: Waqas Ahmed, S Sajjad Haider Zaidi

Abstract:

For the past couple of decades Weak signal detection is of crucial importance in various engineering and scientific applications. It finds its application in areas like Wireless communication, Radars, Aerospace engineering, Control systems and many of those. Usually weak signal detection requires phase sensitive detector and demodulation module to detect and analyze the signal. This article gives you a preamble to intrusion detection system which can effectively detect a weak signal from a multiplexed signal. By carefully inspecting and analyzing the respective signal, this system can successfully indicate any peripheral intrusion. Intrusion detection system (IDS) is a comprehensive and easy approach towards detecting and analyzing any signal that is weakened and garbled due to low signal to noise ratio (SNR). This approach finds significant importance in applications like peripheral security systems.

Keywords: Data Acquisition, fast frequency transforms, Lab VIEW software, weak signal detection.

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Authors: Negar Riazifar, Nigel G. Stocks

Abstract:

This paper proposes strategies in level crossing (LC) sampling and reconstruction that provide high fidelity signal reconstruction for speech signals; these strategies circumvent the problem of exponentially increasing number of samples as the bit-depth is increased and hence are highly efficient. Specifically, the results indicate that the distribution of the intervals between samples is one of the key factors in the quality of signal reconstruction; including samples with short intervals does not improve the accuracy of the signal reconstruction, whilst samples with large intervals lead to numerical instability. The proposed sampling method, termed reduced conventional level crossing (RCLC) sampling, exploits redundancy between samples to improve the efficiency of the sampling without compromising performance. A reconstruction technique is also proposed that enhances the numerical stability through linear interpolation of samples separated by large intervals. Interpolation is demonstrated to improve the accuracy of the signal reconstruction in addition to the numerical stability. We further demonstrate that the RCLC and interpolation methods can give useful levels of signal recovery even if the average sampling rate is less than the Nyquist rate.

Keywords: Level crossing sampling, numerical stability, speech processing, trigonometric polynomial.

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Authors: Chun-Yao Lee, Yao-chen Lee

Abstract:

This paper describes a method of signal process applied on an end effects of Hilbert-Huang transform (HHT) to provide an improvement in the reality of spectrum. The method is based on back-propagation network (BPN). To improve the effect, the end extension of the original signal is obtained by back-propagation network. A full waveform including origin and its extension is decomposed by using empirical mode decomposition (EMD) to obtain intrinsic mode functions (IMFs) of the waveform. Then, the Hilbert transform (HT) is applied to the IMFs to obtain the Hilbert spectrum of the waveform. As a result, the method is superiority of the processing of end effect of HHT to obtain the real frequency spectrum of signals.

Keywords: Neural network, back-propagation network, Hilbert-Huang transform

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Authors: Olesya Bolkhovskaya, Alexander Maltsev

Abstract:

Antenna arrays are widely used in modern radio systems in sonar and communications. The solving of the detection problems of a useful signal on the background of noise is based on the GLRT method. There is a large number of problem which depends on the known a priori information. In this work, in contrast to the majority of already solved problems, it is used only difference  spatial properties of the signal and noise for detection. We are analyzing the influence of the degree of non-coherence of signal and noise unhomogeneity on the performance characteristics of different GLRT statistics. The description of the signal and noise is carried out by means of the spatial covariance matrices C in the cases of different number of known information. The partially coherent signalis is simulated as a plane wave with a random angle of incidence of the wave concerning a normal. Background noise is simulated as random process with uniform distribution function in each element. The results of investigation of degradation of performance characteristics for different cases are represented in this work.

Keywords: GLRT, Neumann-Pearson’s criterion, test-statistics, degradation, spatial processing, multielement antenna array

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Authors: Nur Ilyani Ramli, Mansour Youseffi, Peter Widdop

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This paper presents a low cost design of heart beat monitoring device using reflectance mode PhotoPlethysmography (PPG). PPG is known for its simple construction, ease of use and cost effectiveness and can provide information about the changes in cardiac activity as well as aid in earlier non-invasive diagnostics. The proposed device is divided into three phases. First is the detection of pulses through the fingertip. The signal is then passed to the signal processing unit for the purpose of amplification, filtering and digitizing. Finally the heart rate is calculated and displayed on the computer using parallel port interface. The paper is concluded with prototyping of the device followed by verification procedure of the heartbeat signal obtained in laboratory setting.

Keywords: Reflectance mode PPG, Heart beat detection, Circuitdesign, PCB design

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Authors: M.I.S. Ismail, Z. Taha

Abstract:

In this paper, the experimental design of using the Taguchi method is employed to optimize the processing parameters in the plasma arc surface hardening process. The processing parameters evaluated are arc current, scanning velocity and carbon content of steel. In addition, other significant effects such as the relation between processing parameters are also investigated. An orthogonal array, signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are employed to investigate the effects of these processing parameters. Through this study, not only the hardened depth increased and surface roughness improved, but also the parameters that significantly affect the hardening performance are identified. Experimental results are provided to verify the effectiveness of this approach.

Keywords: Plasma arc, hardened depth, surface roughness, Taguchi method, optimization.

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Authors: Tuhin Subhra Sarkar, Subir Das

Abstract:

Several research works have been done in recent times utilizing grayscale image for the measurement of many physical phenomena. In this present paper, we have designed an embedded based inclination sensor utilizing the grayscale image with a resolution of 0.3º. The sensor module consists of a circular shaped metal disc, laminated with grayscale image and an optical transreceiver. The sensor principle is based on temporal changes in light intensity by the movement of grayscale image with the inclination of the target surface and the variation of light intensity has been detected in terms of voltage by the signal processing circuit (SPC).The output of SPC is fed to a microcontroller program to display the inclination angel digitally. The experimental results are shown a satisfactory performance of the sensor in a small inclination measuring range of -40º to + 40º with a sensitivity of 62 mV/°.

Keywords: Grayscale image, Inclination Sensor, Microcontroller Program, Signal Processing Circuit.

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Authors: Adnan Al-Smadi, Mahmoud Smadi

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This paper presents an algorithm for reconstructing phase and magnitude responses of the impulse response when only the output data are available. The system is driven by a zero-mean independent identically distributed (i.i.d) non-Gaussian sequence that is not observed. The additive noise is assumed to be Gaussian. This is an important and essential problem in many practical applications of various science and engineering areas such as biomedical, seismic, and speech processing signals. The method is based on evaluating the bicepstrum of the third-order statistics of the observed output data. Simulations results are presented that demonstrate the performance of this method.

Keywords: Cepstrum, bicepstrum, third order statistics

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Authors: Lei Lei, Chao Wang, Xin Liu

Abstract:

Discrete wavelet transform (DWT) has been widely adopted in biomedical signal processing for denoising, compression and so on. Choosing a suitable decomposition level (DL) in DWT is of paramount importance to its performance. In this paper, we propose to exploit sparseness of the transformed signals to determine the appropriate DL. Simulation results have shown that the sparseness of transformed signals after DWT increases with the increasing DLs. Additional Monte-Carlo simulation results have verified the effectiveness of sparseness measure in determining the DL.

Keywords: Sparseness, DWT, decomposition level, ECG.

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Authors: R. M. Farouk

Abstract:

In this paper, we present an analytical analysis of the representation of images as the magnitudes of their transform with the discrete wavelets. Such a representation plays as a model for complex cells in the early stage of visual processing and of high technical usefulness for image understanding, because it makes the representation insensitive to small local shifts. We found that if the signals are band limited and of zero mean, then reconstruction from the magnitudes is unique up to the sign for almost all signals. We also present an iterative reconstruction algorithm which yields very good reconstruction up to the sign minor numerical errors in the very low frequencies.

Keywords: Wavelets, Image processing signal processing, Image reconstruction

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Authors: Ali Shatnawi

Abstract:

Signal processing applications which are iterative in nature are best represented by data flow graphs (DFG). In these applications, the maximum sampling frequency is dependent on the topology of the DFG, the cyclic dependencies in particular. The determination of the iteration bound, which is the reciprocal of the maximum sampling frequency, is critical in the process of hardware implementation of signal processing applications. In this paper, a novel technique to compute the iteration bound is proposed. This technique is different from all previously proposed techniques, in the sense that it is based on the natural flow of tokens into the DFG rather than the topology of the graph. The proposed algorithm has lower run-time complexity than all known algorithms. The performance of the proposed algorithm is illustrated through analytical analysis of the time complexity, as well as through simulation of some benchmark problems.

Keywords: Data flow graph, Iteration period bound, Rateoptimalscheduling, Recursive DSP algorithms.

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Authors: Yunjung Lee, Pil Un Kim, Gyhyoun Lee, Jin Ho Cho, Myoung Nam Kim

Abstract:

Various sounds generated in the chest are included in auscultation sound. Adaptive Noise Canceller (ANC) is one of the useful techniques for biomedical signal. But the ANC is not suitable for auscultation sound. Because the ANC needs two input channels as a primary signal and a reference signals, but a stethoscope can provide just one input sound. Therefore, in this paper, it was proposed the Single Input ANC (SIANC) for suppression of breath sound in a cardiac auscultation sound. For the SIANC, it was proposed that the reference generation system which included Heart Sound Detector, Control and Reference Generator. By experiment and comparison, it was confirmed that the proposed SIANC was efficient for heart sound enhancement and it was independent of variations of a heartbeat.

Keywords: Adaptive noise canceller, Auscultation, Breath soundsuppression, Signal enhancement.

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Authors: A. Mahfurdz, Sunardi, H. Ahmad

Abstract:

An envelope echo signal measurement is proposed in this paper using echo signal observation from the 200 kHz echo sounder receiver. The envelope signal without any object is compared with the envelope signal of the sphere. Two diameter size steel ball (3.1 cm & 2.2 cm) and two diameter size air filled stainless steel ball (4.8 cm & 7.4 cm) used in this experiment. The target was positioned about 0.5 m and 1.0 meter from the transducer face using nylon rope. From the echo observation in time domain, it is obviously shown that echo signal structure is different between the size, distance and type of metal sphere. The amplitude envelope voltage for the bigger sphere is higher compare to the small sphere and it confirm that the bigger sphere have higher target strength compare to the small sphere. Although the structure signal without any object are different compare to the signal from the sphere, the reflected signal from the tank floor increase linearly with the sphere size. We considered this event happened because of the object position approximately to the tank floor.

Keywords: echo sounder, target strength, sphere, echo signal

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Authors: Ritu Vijay, Rekha Govil

Abstract:

The design of a complete expansion that allows for compact representation of certain relevant classes of signals is a central problem in signal processing applications. Achieving such a representation means knowing the signal features for the purpose of denoising, classification, interpolation and forecasting. Multilayer Neural Networks are relatively a new class of techniques that are mathematically proven to approximate any continuous function arbitrarily well. Radial Basis Function Networks, which make use of Gaussian activation function, are also shown to be a universal approximator. In this age of ever-increasing digitization in the storage, processing, analysis and communication of information, there are numerous examples of applications where one needs to construct a continuously defined function or numerical algorithm to approximate, represent and reconstruct the given discrete data of a signal. Many a times one wishes to manipulate the data in a way that requires information not included explicitly in the data, which is done through interpolation and/or extrapolation. Tidal data are a very perfect example of time series and many statistical techniques have been applied for tidal data analysis and representation. ANN is recent addition to such techniques. In the present paper we describe the time series representation capabilities of a special type of ANN- Radial Basis Function networks and present the results of tidal data representation using RBF. Tidal data analysis & representation is one of the important requirements in marine science for forecasting.

Keywords: ANN, RBF, Tidal Data.

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Authors: Nazaket Gazieva

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Voice biometric data associated with physiological, psychological and other factors are widely used in forensic phonoscopy. There are various methods for identifying and verifying a person by voice. This article explores the minimum speech signal data as individual parameters of a speech signal. Monozygotic twins are believed to be genetically identical. Using the minimum data of the speech signal, we came to the conclusion that the voice imprint of monozygotic twins is individual. According to the conclusion of the experiment, we can conclude that the minimum indicators of the speech signal are more stable and reliable for phonoscopic examinations.

Keywords: Biometric voice prints, fundamental frequency, phonogram, speech signal, temporal characteristics.

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Authors: Mohsin T. Mohammed, Zahid A. Khan, Arshad N. Siddiquee

Abstract:

The field of biomedical materials plays an imperative requisite and a critical role in manufacturing a variety of biological artificial replacements in a modern world. Recently, titanium (Ti) materials are being used as biomaterials because of their superior corrosion resistance and tremendous specific strength, free- allergic problems and the greatest biocompatibility compared to other competing biomaterials such as stainless steel, Co-Cr alloys, ceramics, polymers, and composite materials. However, regardless of these excellent performance properties, Implantable Ti materials have poor shear strength and wear resistance which limited their applications as biomaterials. Even though the wear properties of Ti alloys has revealed some improvements, the crucial effectiveness of biomedical Ti alloys as wear components requires a comprehensive deep understanding of the wear reasons, mechanisms, and techniques that can be used to improve wear behavior. This review examines current information on the effect of thermal and thermomechanical processing of implantable Ti materials on the long-term prosthetic requirement which related with wear behavior. This paper focuses mainly on the evolution, evaluation and development of effective microstructural features that can improve wear properties of bio grade Ti materials using thermal and thermomechanical treatments.

Keywords: Wear Resistance, Heat Treatment, Thermomechanical Processing, Biomedical Titanium Materials.

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Authors: E. Irankhah, M. Zarif, E. Mazrooei Rad, K. Ghandehari

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Alzheimer's prevalence is on the rise, and the disease comes with problems like cessation of treatment, high cost of treatment, and the lack of early detection methods. The pathology of this disease causes the formation of protein deposits in the brain of patients called plaque amyloid. Generally, the diagnosis of this disease is done by performing tests such as a cerebrospinal fluid, CT scan, MRI, and spinal cord fluid testing, or mental testing tests and eye tracing tests. In this paper, we tried to use the Medial Temporal Atrophy (MTA) method and the Leave One Out (LOO) cycle to extract the statistical properties of the three Fz, Pz, and Cz channels of ERP signals for early diagnosis of this disease. In the process of CT scan images, the accuracy of the results is 81% for the healthy person and 88% for the severe patient. After the process of ERP signaling, the accuracy of the results for a healthy person in the delta band in the Cz channel is 81% and in the alpha band the Pz channel is 90%. In the results obtained from the signal processing, the results of the severe patient in the delta band of the Cz channel were 89% and in the alpha band Pz channel 92%.

Keywords: Alzheimer's disease, image and signal processing, medial temporal atrophy, LOO Cycle.

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Authors: Alexey V. Klyuev, Valery P. Samarin, Viktor F. Klyuev, Andrey V. Klyuev

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A power measurement algorithm of the input mix components of the noise signal and pulse interference is considered. The algorithm efficiency analysis has been carried out for different interference-to-signal ratio. Algorithm performance features have been explored by numerical experiment results.

Keywords: Noise signal, pulse interference, signal power, spectrum width, detection.

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Authors: Nuawi M. Z., Lamin F., Ismail A. R., Abdullah S., Wahid Z.

Abstract:

A filter is used to remove undesirable frequency information from a dynamic signal. This paper shows that the Znotch filter filtering technique can be applied to remove the noise nuisance from a machining signal. In machining, the noise components were identified from the sound produced by the operation of machine components itself such as hydraulic system, motor, machine environment and etc. By correlating the noise components with the measured machining signal, the interested components of the measured machining signal which was less interfered by the noise, can be extracted. Thus, the filtered signal is more reliable to be analysed in terms of noise content compared to the unfiltered signal. Significantly, the I-kaz method i.e. comprises of three dimensional graphical representation and I-kaz coefficient, Z∞ could differentiate between the filtered and the unfiltered signal. The bigger space of scattering and the higher value of Z∞ demonstrated that the signal was highly interrupted by noise. This method can be utilised as a proactive tool in evaluating the noise content in a signal. The evaluation of noise content is very important as well as the elimination especially for machining operation fault diagnosis purpose. The Z-notch filtering technique was reliable in extracting noise component from the measured machining signal with high efficiency. Even though the measured signal was exposed to high noise disruption, the signal generated from the interaction between cutting tool and work piece still can be acquired. Therefore, the interruption of noise that could change the original signal feature and consequently can deteriorate the useful sensory information can be eliminated.

Keywords: Digital signal filtering, I-kaz method, Machiningmonitoring, Noise Cancelling, Sound

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Authors: Karima Siham Aoubid, Mohamed Boulemden

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The development of the signal compression algorithms is having compressive progress. These algorithms are continuously improved by new tools and aim to reduce, an average, the number of bits necessary to the signal representation by means of minimizing the reconstruction error. The following article proposes the compression of Arabic speech signal by a hybrid method combining the wavelet transform and the linear prediction. The adopted approach rests, on one hand, on the original signal decomposition by ways of analysis filters, which is followed by the compression stage, and on the other hand, on the application of the order 5, as well as, the compression signal coefficients. The aim of this approach is the estimation of the predicted error, which will be coded and transmitted. The decoding operation is then used to reconstitute the original signal. Thus, the adequate choice of the bench of filters is useful to the transform in necessary to increase the compression rate and induce an impercevable distortion from an auditive point of view.

Keywords: Compression, linear prediction analysis, multiresolution analysis, speech signal.

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Authors: Young-Seok Choi

Abstract:

The Adaptive Line Enhancer (ALE) is widely used for enhancing narrowband signals corrupted by broadband noise. In this paper, we propose novel ALE methods to improve the enhancing capability. The proposed methods are motivated by the fact that the output of the ALE is a fine estimate of the desired narrowband signal with the broadband noise component suppressed. The proposed methods preprocess the input signal using ALE filter to regenerate a finer input signal. Thus the proposed ALE is driven by the input signal with higher signal-to-noise ratio (SNR). The analysis and simulation results are presented to demonstrate that the proposed ALE has better performance than conventional ALE’s.

Keywords: Adaptive filter, adaptive line enhancer, noise, feedback.

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Authors: Commander Sunil Tyagi

Abstract:

Effectiveness of Artificial Neural Networks (ANN) and Support Vector Machines (SVM) classifiers for fault diagnosis of rolling element bearings are presented in this paper. The characteristic features of vibration signals of rotating driveline that was run in its normal condition and with faults introduced were used as input to ANN and SVM classifiers. Simple statistical features such as standard deviation, skewness, kurtosis etc. of the time-domain vibration signal segments along with peaks of the signal and peak of power spectral density (PSD) are used as features to input the ANN and SVM classifier. The effect of preprocessing of the vibration signal by Discreet Wavelet Transform (DWT) prior to feature extraction is also studied. It is shown from the experimental results that the performance of SVM classifier in identification of bearing condition is better then ANN and pre-processing of vibration signal by DWT enhances the effectiveness of both ANN and SVM classifier

Keywords: ANN, Artificial Intelligence, Fault Diagnosis, Pattern Recognition, Rolling Element Bearing, SVM. Wavelet Transform

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Authors: Jeong Yup Han, Su Kyung Lee, Hong Bae Park

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In this paper, we propose a method to reduce the various kinds of noise while gathering and recording the electrocardiogram (ECG) signal. Because of the defects of former method in the noise elimination of ECG signal, we use translation invariant (TI) multiwavelet denoising method to the noise elimination. The advantage of the proposed method is that it may not only remain the geometrical characteristics of the original ECG signal and keep the amplitudes of various ECG waveforms efficiently, but also suppress impulsive noise to some extent. The simulation results indicate that the proposed method are better than former removing noise method in aspects of remaining geometrical characteristics of ECG signal and the signal-to-noise ratio (SNR).

Keywords: ECG, TI multiwavelet, denoise.

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Authors: Fan Gao, Lior Pachter

Abstract:

The primary tool currently used to pre-process 10X chromium single-cell ATAC-seq data is Cell Ranger, which can take very long to run on standard datasets. To facilitate rapid pre-processing that enables reproducible workflows, we present a suite of tools called scATAK for pre-processing single-cell ATAC-seq data that is 15 to 18 times faster than Cell Ranger on mouse and human samples. Our tool can also calculate chromatin interaction potential matrices and generate open chromatin signal and interaction traces for cell groups. We use scATAK tool to explore the chromatin regulatory landscape of a healthy adult human brain and unveil cell-type specific features, and show that it provides a convenient and computational efficient approach for pre-processing single-cell ATAC-seq data.

Keywords: single-cell, ATAC-seq, bioinformatics, open chromatin landscape, chromatin interactome

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Authors: Ramesh Rajagopalan, Adam Dahlstrom

Abstract:

Noise removal techniques play a vital role in the performance of electrocardiographic (ECG) signal processing systems. ECG signals can be corrupted by various kinds of noise such as baseline wander noise, electromyographic interference, and powerline interference. One of the significant challenges in ECG signal processing is the degradation caused by additive 50 or 60 Hz powerline interference. This work investigates the removal of power line interference and suppression of transient response for filtering noise corrupted ECG signals. We demonstrate the effectiveness of infinite impulse response (IIR) notch filter with time varying pole radius for improving the transient behavior. The temporary change in the pole radius of the filter diminishes the transient behavior. Simulation results show that the proposed IIR filter with time varying pole radius outperforms traditional IIR notch filters in terms of mean square error and transient suppression.

Keywords: Notch filter, ECG, transient, pole radius.

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Authors: Igor Luiz Bernardes de Moura, Luan Carlos de Sena Monteiro Ozelim, Fabiano Araujo Soares

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The development of an low cost acquisition system of S-EMG signals which are reliable, comfortable for the user and with high mobility shows to be a relevant proposition in modern biomedical engineering scenario. In the study, the sampling capacity of the Arduino microcontroller Atmel Atmega328 with an A / D converter with 10-bit resolution and its reconstructing capability of a signal of surface electromyography is analyzed. An electronic circuit to capture the signal through two differential channels was designed, signals from Biceps Brachialis of a healthy man of 21 years was acquired to test the system prototype. ARV, MDF, MNF and RMS estimators were used to compare de acquired signals with physiological values. The Arduino was configured with a sampling frequency of 1.5kHz for each channel, and the tests with the circuit designed offered a SNR of 20.57dB.

Keywords: Eletromyography, Arduino, Low-Cost, Atmel Atmega328 microcontroller.

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Authors: Chun-Yao Lee, Hung-Chi Lin

Abstract:

This paper presents a signal analysis process for improving energy completeness based on the Hilbert-Huang Transform (HHT). Firstly, the vibration signal of a DC Motor obtained by employing an accelerometer is the model used to analyze the signal. Secondly, the intrinsic mode functions (IMFs) and Hilbert spectrum of the decomposed signal are obtained by applying HHT. The results of the IMFs constituent and the original signal are compared and the process of energy loss is discussed. Finally, the differences between Wavelet Transform (WT) and HHT in analyzing the signal are compared. The simulated results reveal the analysis process based on HHT is advantageous for the enhancement of energy completeness.

Keywords: Hilbert-Huang transform, Hilbert spectrum, Wavelettransform, Wavelet spectrum, DC Motor.

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