Butterworth High-pass Filter Research Articles

Artifact-free recordings in human bidirectional brain–computer interfaces

Objective. Intracortical microstimulation has shown promise as a means of evoking somatosensory percepts as part of a bidirectional brain–computer interface (BCI). However, microstimulation generates large electrical artifacts that dominate the recordings necessary for BCI control. These artifacts must be eliminated from the signal in real-time to allow for uninterrupted BCI decoding. Approach. We present a simple, robust modification to an existing clinical BCI system to allow for simultaneous recording and stimulation using a combination of signal blanking and digital filtering, without needing to explicitly account for varying parameters such as electrode locations or amplitudes. We validated our artifact rejection scheme by recording from microelectrodes in primary motor cortex (M1) while stimulating in somatosensory cortex of a person with a spinal cord injury. Main results. M1 recordings were digitally blanked using a sample-and-hold circuit triggered just prior to stimulus onset and a first-order 750 Hz high-pass Butterworth filter was used to reduce distortion of the remaining artifact. This scheme enabled spike detection in M1 to resume as soon as 740 µs after each stimulus pulse. We demonstrated the effectiveness of the complete bidirectional BCI system by comparing functional performance during a 5 degree of freedom robotic arm control task, with and without stimulation. When stimulation was delivered without this artifact rejection scheme, the number of objects the subject was able to move across a table in 2 min under BCI control declined significantly compared to trials without stimulation (p < 0.01). When artifact rejection was implemented, performance was no different than in trials that did not include stimulation (p = 0.621). Significance. The proposed technique uses simple changes in filtering and digital signal blanking with FDA-cleared hardware and enables artifact-free recordings during bidirectional BCI control.

A template subtraction method for reducing electrocardiographic artifacts in EMG signals of low intensity

Abstract The electromyogram (EMG) has been used in several studies for different areas. Whenever recorded on trunk muscles and close to heart, the EMG may be contaminated by electrocardiographic signal (ECG), which may hamper information based on EMG measures, by either decreasing the median frequency (MDF) or increasing the root mean square value (RMS). Therefore, ECG removal from this contaminated EMG is an issue, but the signal processing task is challenging due to the spectral overlapping of signals. The Butterworth high-pass filter with a 30 Hz cutoff frequency has been considered a suitable removal technique in the literature. However, the frequency band below 30 Hz is strongly attenuated, leading thus to information loss on the EMG. In order to mitigate this problem, a simple template subtraction method is proposed, in which the template is based on the contaminated signal itself. Real contamination and emulated mixtures based in real signals were used and the MDF, RMS, correlation coefficient and Kulback-Leibler divergence were analyzed as performance measures. The performance of the proposed method was compared to a Butterworth high-pass filter and it is shown that the template subtraction method has preserved better the EMG information.

Reduction of Visual Disruptions in Coronary Cine-Angiography for Better Diagnostic Viewing

Coronary angiography is an invasive medical imaging modality which is widely used as a preliminary diagnostic method in Interventional Cardiology for detection of luminal obstructions in Coronary Arteries (CA). Noise, non-uniform illumination, low contrast and epicardial motion are considered as the reported visual degradations which are automatically recorded in Coronary angiography. Further, those factors form certain unpredictable obstructions during the angiography based disease diagnosis. In this study, it has been proposed a frequency filtering based frame enhancement method for surmounting those problems and improving the visual quality of the angiograms. The proposed method is based on homomorphic butter worth high pass filter and empirically validated contrast stretching technique. Further, the optical flow based frame stabilization method has been applied in the later stages of the proposed method for correcting the epicardial deformations. The results of the study clearly emphasized the visual improvement obtained from this method. The enhanced angiography frames produced in this study can be recommended for reliable stenosis detection. Further, these enhanced frames can be further used for quantitative stenosis assessment.

DESIGN OF SECOND ORDER BUTTERWORTH HIGHPASS FILTER USING CMOS TECHNOLOGY

The research Complementary Metal-Oxide Semiconductor (CMOS) Technology for Design of second order butterworth highpass filter IC. This is caused CMOS have excellence low power dissipation and small size. This research aims to know performance, quality and reliability second order butterworth highpass filter circuit. The method used to problem solving, analysis with the literature and the simulation use pspice program for exam the specification of circuit. To make IC picture using DSCH software and layout circuit using Microwind program. From examination result -2,99dB for gain voltage parameter, frequency -40dB and 88,25° phase shift second order highpass filter. The result of this circuit have low power dissipation although applied to second order highpass filter equal 2,28mW better than generality IC second order highpass filter (GH580). Wide of layout circuit is 1110µm x 385µm DOI : https://doi.org/10.26905/jeemecs.v1i1.2299

A temperature-compensated fiber Bragg grating sensor system based on digital filtering for monitoring the pantograph–catenary contact force

Optical sensors based on fiber Bragg gratings have become an important type of sensing element for strain measurements. In this study, fiber Bragg grating strain sensors and corresponding reference temperature sensors were integrated into a pantograph strip. The results of an online test indicated that the temperature of the pantograph strip impacting the strain measurement reaches about 80 ℃ while the vehicle was running. In addition, Fourier analysis showed that the energies of the temperature measurement signals dominated the relatively low-frequency band (less than 0.02 Hz), whereas the strain signals prevailed in the relatively high-frequency band. Thus, a novel method based on a digital filtering technique was proposed for temperature compensation in fiber Bragg grating sensor systems for monitoring the conditions in electrified pantograph–catenary systems. A Butterworth high-pass filter was designed to reject the temperature-related signal component with a stopband and to capture the real strain in the passband in frequency domain. To achieve this filtering, the cutoff frequencies and the filter order were calculated adaptively according to the frequency-domain characteristics of the measured temperature signal. With the designed filter, the temperature effect to the strain signals can be eliminated so that the strain can be estimated accurately. In comparison with the traditional temperature compensation technique, the proposed method is more effective in terms of estimating the real strain of the pantograph strip in practical applications. Compensated by the proposed method, the time-domain and frequency-domain analyses of the contact force denote the frequencies corresponding to the support span, and the dropper can be distinguished. Further, the first-order (4 Hz) and second-order (8.3 Hz) natural frequencies of the pantograph are visible in the measurements from catenary sections, which demonstrates the sufficiency and rationality of the proposed temperature compensation method for fiber Bragg grating sensor systems.

Separation of electrocardiographic from electromyographic signals using dynamic filtration

Trunk muscle electromyographic (EMG) signals are often contaminated by the electrical activity of the heart. During low or moderate muscle force, these electrocardiographic (ECG) signals disturb the estimation of muscle activity. Butterworth high-pass filters with cut-off frequency of up to 60 Hz are often used to suppress the ECG signal. Such filters disturb the EMG signal in both frequency and time domain. A new method based on the dynamic application of Savitzky-Golayfilter is proposed. EMG signals of three left trunk muscles and pure ECG signal were recorded during different motor tasks. The efficiency of the method was tested and verified both with the experimental EMG signals and with modeled signals obtained by summing the pure ECG signal with EMG signals at different levels of signal-to-noise ratio. The results were compared with those obtained by application of high-pass, 4th order Butterworth filter with cut-off frequency of 30 Hz. The suggested method is separating the EMG signal from the ECG signal without EMG signal distortion across its entire frequency range regardless of amplitudes. Butterworth filter suppresses the signals in the 0–30 Hz range thus preventing the low-frequency analysis of the EMG signal. An additional disadvantage is that it passes high-frequency ECG signal components which is apparent at equal and higher amplitudes of the ECG signal as compared to the EMG signal. The new method was also successfully verified with abnormal ECG signals.

Evaluation of (1 + α) Fractional-Order Approximated Butterworth High-Pass and Band-Pass Filter Transfer Functions

This paper summarizes multiple cases of high-pass (HP) and band-pass (BP) analogue filter transfer functions with fractional order 1 &lt; (1 + α) &lt; 2. All HP and BP transfer functions are evaluated against the magnitude characteristics of ideal Butterworth responses when coefficients previously determined to approximate fractional-order (FO) Butterworth low-pass (LP) transfer functions are utilized. Comparisons of the simulated FO HP and BP responses against the ideal Butterworth responses are presented, with a least squares error analysis applied to determine the transfer functions that best approximate the Butterworth response for both HP and BP FO filters.DOI: http://dx.doi.org/10.5755/j01.eie.24.2.20634

Constructing a Guided Filter by Exploiting the Butterworth Filter for ECG Signal Enhancement

Electrocardiogram (ECG) signal enhancement is necessary in telemedicine. In such ECG monitoring systems, noises like muscle artifacts, electrode motion and baseline wander are often embedded in the ECG signals during acquisition and transmission. In this study, a novel method is proposed for the ECG signal enhancement based on the finding that ECG signals extracted over a big data share significant similarities in the morphology for a particular person. We construct a guided filter and reform it by a Butterworth high-pass filter. The Butterworth high-pass filter is utilized to remove the baseline wander. The advantageous edge-preserving guided filter is then applied to remove the rest noise, of which frequencies are between the ECG signals. Very promising results with high accuracy and the edge-preserving features have been achieved in the comparative experiments. We evaluated the proposed denoising method using ECG signals from the MIT-BIH Arrhythmia database and the Noise Stress Test database. The experimental results demonstrate that the proposed method achieves better signal-to-noise ratio (SNR) and lower root mean square error (RMSE) when compared to the wavelet with subband dependent thresholding (WT-Subband), Back Propagation Neural Network and Stockwell transform methods. Using the proposed method, the average output SNR ranges from 8.57 to 19.28 dB, and the average RMSE is less than 0.41.

Minimum passive components based lossy and lossless inductor simulators employing a new active block

In this paper a new active element namely Dual X current conveyor differential input transconductance amplifier (DXCCDITA) is proposed. The DXCCDITA is utilized in designing eight topologies of lossy and lossless grounded inductor simulators and two topologies of floating inductor simulators. All the designed grounded simulators require only two passive elements and a single active block. The two floating inductor simulators require a single active block and one or three grounded passive elements. In addition, all the designs make use of only grounded capacitors for implementation which is advantageous for fabrication. All the proposed active inductors, except two, did not require any component matching conditions for realization and all the inductor simulators are perfectly tunable. The effect of non-idealities on the proposed grounded simulator structures is also studied. To demonstrate the workability of the inductor simulators they are used in design of second order low pass filter, parallel RLC resonance circuit, third order Butterworth high pass filter, parallel RLC current mode multifunction filter and a voltage mode band pass filter. The DXCCDITA is implemented in 0.35μm TSMC CMOS technology parameters and tested in Tanner EDA. Sufficient number of simulations are provided to establish the functionality of the active inductor structures.

Comparison of Baseline Wander Removal Techniques considering the Preservation of ST Changes in the Ischemic ECG: A Simulation Study.

The most important ECG marker for the diagnosis of ischemia or infarction is a change in the ST segment. Baseline wander is a typical artifact that corrupts the recorded ECG and can hinder the correct diagnosis of such diseases. For the purpose of finding the best suited filter for the removal of baseline wander, the ground truth about the ST change prior to the corrupting artifact and the subsequent filtering process is needed. In order to create the desired reference, we used a large simulation study that allowed us to represent the ischemic heart at a multiscale level from the cardiac myocyte to the surface ECG. We also created a realistic model of baseline wander to evaluate five filtering techniques commonly used in literature. In the simulation study, we included a total of 5.5 million signals coming from 765 electrophysiological setups. We found that the best performing method was the wavelet-based baseline cancellation. However, for medical applications, the Butterworth high-pass filter is the better choice because it is computationally cheap and almost as accurate. Even though all methods modify the ST segment up to some extent, they were all proved to be better than leaving baseline wander unfiltered.

A New Strategy for ECG Baseline Wander Elimination Using Empirical Mode Decomposition

Electrocardiogram (ECG) signals might be affected by various artifacts and noises that have biological and external sources. Baseline wander (BW) is a low-frequency artifact that may be caused by breathing, body movements and loose sensor contact. In this paper, a novel method based on empirical mode decomposition (EMD) for removal of baseline noise from ECG is presented. When compared to other EMD-based methods, the novelty of this research is to reach the optimized number of decomposed levels for ECG BW de-noising using mean power frequency (MPF), while the reduction of processing time is considered. To evaluate the performance of the proposed method, a fifth-order Butterworth high pass filtering (BHPF) with cut-off frequency at 0.5[Formula: see text]Hz and wavelet approach are applied. Three performance indices, signal-to-noise ratio (SNR), mean square error (MSE) and correlation coefficient (CC), between pure and filtered signals have been utilized for qualification of presented techniques. Results suggest that the EMD-based method outperforms the other filtering method.

Power Efficient Edge Sharpening

This paper studies power efficient image processing method for power consuming display device. Power is consumed by display device and its portion is large. We developed unsharp masking under power-constrained condition. For this system, we assume an image is dark with low contrast. The presented unsharp masking adopts high pass filter, Butterworth filter, and histogram equalization. Simulation results compare visual performance in several power-constrained conditions with factors of n. Results show that the proposed method achieved good visual quality and significant power saving performance.

Application of high-pass filtering techniques on gravity and magnetic data of the eastern Qattara Depression area, Western Desert, Egypt

In this work, a reconnaissance study is presented to delineate the subsurface tectonics and lithological inferences of the eastern area of Qattara Depression using the Bouguer gravity and aeromagnetic data. To achieve this goal, several transformation techniques and filtering processes are accomplished on these maps. At first, the total intensity aeromagnetic map is processed through the application of reduction to the magnetic north pole technique. The fast Fourier transform is carried out on the gravity and RTP magnetic data for establishing and defining the residual (shallow) sources. The frequency high-pass filtering is used to enhance the anomaly wavelengths associated with the shallow sources. The used processing techniques are the polynomial surface fitting enhancement, Laplacian, Strike Filtering, Enhancement Utilization, Suppression Utilization, Butterworth Filtering Utilization, Butterworth high-pass filter, Euler’s deconvolution and forward modeling. The equivalent depths of the isolated short wavelength anomalies are 0.759 and 0.340km below the flight surface, and the depths of the intermediate wavelength anomalies are 1.28 and 2.00km for the gravity and magnetic data, respectively. Finally, the quantitative interpretations of the Bouguer gravity and RTP magnetic maps of the study area, reflect the occurrence of the various types of structures and their components. The main tectonic deformations of the study area have NNW–SSE, NNE–SSW, NE–SW, NW–SE and E–W trends.

Multimodal medical image fusion using Butterworth high pass filter and Cross bilateral filter

Multimodal Medical Image fusion is a prominent area of interest. Medical image fusion is the process of combining images from different modalities. It improves imaging quality and reduces the redundant information. The main aim of Medical Image fusion is in having better quality of fused image for the diagnostic purposes. Image fusion improves capability and reliability of images. In medical background, sharpness of fused image is the basic criteria of quality. In this paper, quality of fused image can be enhanced by using combination of Butterworth High Pass filter and Cross Bilateral filter. Cross bilateral filter is a nonlinear filter, which takes both range domain and spatial domain filtering into account. It is an edge preserving filter, which fuse images by taking weighted average of source image pixels. For better quality of fused results, the input images are sharpened using high order, Butterworth high pass filter and then images are fused with Cross Bilateral filter. Results show that the modified image fusion framework is effective in preserving fine details, information content and contrast of image.

Effect of Epidermal Growth Factor on the Network Spiking Activity in Cultured Hippocampal Neurons

Effect of Epidermal Growth Factor on the Network Spiking Activity in Cultured Hippocampal Neurons

A novel filtering technique for enhancing mineralization associated geochemical and geophysical anomalies

A novel method named optimal filtering is introduced in this paper. This method is aimed at producing maps resulting from the filtering of geochemical or geophysical data in order to indicate occurrences of mineral deposits most effectively. Two measures are proposed to enhance the capability of indicating deposits: (1) area under operating characteristic curve (AUC); and (2) Fisher's measure for discriminant analysis. Six Fourier filter functions introduced for different situations are ideal high-pass filter (IHPF), ideal low-pass filter (ILPF), Butterworth high-pass filter (BHPF), Butterworth low-pass filter (BLPF), Gauss high-pass filter (GHPF) and Gauss low-pass filter (GLPF). The effectiveness of this approach is demonstrated in a case study using a geochemical and aeromagnetic dataset from southwestern Nova Scotia, Canada. The anomalies resulting from ILPF and IHPF show strong association with the occurrences of gold deposits in this area. The high-pass cutoff wavelength correctly predicts regular spacing between mineralization zones. Pros and cons of the parameters for optimal filtering are discussed, and preliminary guidelines are proposed for how to choose these parameters. Additionally, a test of the case study results shows the method is robust to lack of deposits.

An evaluation criterion of infrared image complexity based on background optimal filter scale

An evaluation of infrared image complexity is proposed based on the background optimal filtering to solve the problem that the traditional methods have given poor results in the background evaluation. Meanwhile, the optimal filtering scale for infrared image filtering can be given by this method, it will provide a guidance for optimal infrared image filtering. First, we generate the Gaussian simulated target and fuse it to the infrared image to obtain the real infrared image with the simulated target. Then, this image is filtered in different scales and the signal-to-noise ratio of the target after filtering is calculated. Finally, the maximal value of signal-to-noise ratio of the target is used as the background optimal filter scale, to evaluate the infrared image complexity. Besides, the infrared filtering scale is deduced by establishing the mathematic model, and then the mathematical expression of optimal filtering scale is obtained. A lot of experiments indicate that: 1) The mathematical expression of optimal filtering scale agrees with the experimental results. 2) The result of our method is better than that of the traditional methods based on information entropy. Because the optimal filtering scale is obtained by using our method, we can use this scale to filter the infrared image to effectively detect a small target. 3) When the scale of simulated target increases, the optimal filtering scale increases accordingly. So, when we calculate the infrared image complexity, the scale of simulated target must be the same. We can compare the infrared image complexity between different images. Moreover, the optimal filtering scale is independent of the intensity of simulated target. 4) The effect of Gaussian and Butterworth high-pass filter is better than that of the ideal high-pass filter in the proposed method. 5) The infrared image complexity can be analyzed by the proposed method effectively. Moreover, changes of different image contents can be analyzed by using the optimal filtering scale.

Image Sharpening By Gaussian And Butterworth High Pass Filter

Many significant images contains some extent of noise, that is unexplained variation in data disturbances in image intensity which are either uninterpretable or out of interest. Image analysis is often simplified if this unwanted noise is filtered. For this image simplification, filtering in frequency domain is done. In this paper we will demonstrate the image sharpening by Gaussian & Butterworth high pass filter and jot some points revealing their differences.

Bioelectric signal detrending using smoothness prior approach

Bioelectric signals such as electromyogram (EMG) and electrocardiogram (ECG) are often affected by various low-frequency trending interferences. It is critical to remove these interferences from the recordings so that the critical features of the bioelectric signals could be clearly observed. In this study, an advanced method based on smoothness prior approach (SPA) was proposed to solve this problem. EMG and ECG signals from both the MIT-BIH database and the experiments were employed to evaluate the detrending performance of the proposed method. For comparison purposes, a conventional high-pass Butterworth filter was also used for the detrending of the EMG and ECG signals. Two numerical measures, the correlation coefficient (CC) and root mean square error (RMSE) between the clean data and the detrended data, were calculated to evaluate the detrending performance. The results showed that the proposed SPA method outperformed the high-pass filtering method in reducing various kinds of trending interferences and preserving the desired frequency contents of the EMG and ECG signals. The study suggested that the SPA method might be a promising approach in detrending bioelectric signals.

Evaluation of image based Abbott–Firestone curve parameters using machine vision for the characterization of cylinder liner surface topography

In this paper, a method is proposed for the evaluation of image based Abbott–Firestone curve parameters aiming to characterize the cylinder bore surface topography using machine vision. Plateau honing experiments are performed to generate sixteen cylinder liners with different surface topographies and the 2-D and 3-D Abbott–Firestone parameters are measured using a stylus instrument and Coherence Scanning Interferometer (CSI), respectively. The images are captured from the corresponding portions of the cylinder liner surfaces using a Charge Coupled Device (CCD) camera connected with different microscopic attachments. The captured images are filtered using a Butterworth high pass filter followed by the adaptation of the double step Gaussian filtering procedure specified by the ISO 13565-1. An Abbott–Firestone curve is constructed by finding the cumulative of the intensity histogram of the filtered images. Five image based parameters are evaluated from the constructed Abbott curve by adapting the procedures presented in ISO 13565-2. The computed image based Abbott–Firestone curve parameters are observed to bear a statistically significant correlation with the measured 2-D and 3-D Abbott–Firestone curve parameters. An artificial neural network (ANN) is trained and tested to arrive at the actual values of the Abbott–Firestone curve parameters using the computed image based feature parameters. The results indicate that the multiple surface topography parameters of the cylinder bore surface could be estimated/predicted with a reasonable accuracy using machine vision technique coupled with ANN.