scholarly journals Digital ECG Phantom Design to Represent the Human Heart Signal for Early Test on ECG Machine in Hospital

2021 ◽  
Vol 1 (1) ◽  
pp. 14-19
Author(s):  
Sella Octa Ardila ◽  
Endro Yulianto ◽  
Sumber Sumber
Keyword(s):  
Signal Processing ◽  
Electrical Activity ◽  
Human Heart ◽  
Analog Circuit ◽  
Digital Signal ◽  
Calibration Procedure ◽  
Ecg Signal ◽  
Recording Device ◽  
Ecg Signals ◽  
Measurement Results

Electrocardiograph (ECG) is a diagnostic tool that can record the electrical activity of the human heart. By analyzing the resulting waveforms of the recorded electrical activity of the heart, it is possible to record and diagnose disease. Given the importance of the ECG recording device, it is necessary to check the function of the ECG recording device, namely by performing a device calibration procedure using the Phantom ECG which aims to simulate the ECG signal. The purpose of this research is to check the ECG device during repairs, besides that the Electrocardiograph (EKG) tool functions for research purposes on ECG signals or for educational purposes. Electrocardiograph (EKG) simulator or often called Phantom ECG is in principle a signal generator in the form of an ECG like signal or a recorded ECG signal. This device can be realized based on microcontroller and analog circuit. The advantage of this simulator research is that the ECG signal displayed is the original ECG recording and has an adequate ECG signal database. ECG This simulator also has the advantage of providing convenience for research on digital signal processing applications for ECG signal processing. In its application this simulator can be used as a tool to study various forms of  ECG signals. Based on the measurement results, the error value at BPM 30 and 60 is 0.00% at the sensitivity of 0.5mV, 1.0mV, and 2.0mV, then the measurement results for the error value at BPM 120 are 0.33% and at the BPM 180 value, the error value is 0.22%. From these results, it can be concluded that the highest error value is at BPM 120 with sensitivities of 0.5mV, 1.0mV, and 2.0mV.  

scholarly journals Sensitivity and Positive Prediction of Secured Electrocardiograph (ECG) Transmission using Fully Homomorphic Encryption Technique (FHE)

2021 ◽  
pp. 97-104
Author(s):  
Dr. P. Balashanmuga Vadivu ◽  
K. Narmatha
Keyword(s):  
Signal Processing ◽  
Homomorphic Encryption ◽  
Heart Diseases ◽  
Digital Signal ◽  
Ecg Signal ◽  
Medical Provider ◽  
Fully Homomorphic Encryption ◽  
Positive Prediction ◽  
Clinical Method ◽  
Ecg Signals

Health connected is a technology that links medical devices, telecommunications and security techniques. It empowers patients to be observed and treated remotely from their homes. Patient’s healthcare records with a connected healthcare system should be stored securely before transmitted for further investigation and interpretation. Electrocardiogram (ECG) is the clinical method utilized to screen heart execution and utilized for the detection of various arrhythmias. For diagnostic purposes, individuals with a background of heart diseases have long records of ECGs, which results in the requirement of a large amount of storage space and labor. Hence, there is a requirement for a system that involves digital signal processing and signal security so that the spared information is made sure about at one spot and an only authentic individual can see and utilize this ECG signal for additional findings. This study presents a set of security solutions that can be deployed in a connected healthcare territory, which includes the fully homomorphic encryption (FHE) techniques used to secure the ECG signals. The study helps the medical provider to record ECG signals confidentially and to prevent mistreatment. The study focuses on Pan and Tompkins algorithm methods for the detection of the ECG Signal. As a result, the output of the Pan and Tompkins algorithm for ECG signal processing with the FHE technique shows a sensitivity of 92.59% and a positive prediction of 90.00%.

scholarly journals Secured Electrocardiograph (ECG) Signal Using Partially Homomorphic Encryption Technique–RSA Algorithm

2020 ◽  
Vol 28 (S2) ◽  
Author(s):  
Muhammad Umair Shaikh ◽  
Wan Azizun Wan Adnan ◽  
Siti Anom Ahmad
Keyword(s):  
Signal Processing ◽  
Homomorphic Encryption ◽  
Digital Signal ◽  
Ecg Signal ◽  
The Public ◽  
Ecg Signals ◽  
Rsa Algorithm ◽  
Before And After ◽  
Ecg Signal Processing ◽  
Electrocardiogram Ecg

ECG signal differs from individual to individual, making it hard to be emulated and copied. In recent times ECG is being used for identifying the person. Hence, there is a requirement for a system that involves digital signal processing and signal security so that the saved data are secured at one place and an authentic person can see and use the ECG signal for further diagnosis. The study presents a set of security solutions that can be deployed in a connected healthcare territory, which includes the partially homomorphic encryption (PHE) techniques used to secure the electrocardiogram (ECG) signals. This is to record confidentially and prevent the information from meddling, imitating and replicating. First, Pan and Tompkins’s algorithm was applied to perform the ECG signal processing. Then, partially homomorphic encryption (PHE) technique - Rivest-Shamir-Adleman (RSA) algorithm was used to encrypt the ECG signal by using the public key. The PHE constitutes a gathering of semantically secure encryption works that permits certain arithmetical tasks on the plaintext to be performed straightforwardly on the ciphertext. The study shows a faster and 90% accurate result before and after encryption that indicates the lightweight and accuracy of the RSA algorithm. Secure ECG signal provides innovation in multiple healthcare sectors such as medical research, patient care and hospital database.

scholarly journals Compact Radar Cross-Section Measurement Setup and Performance Evaluation

2021 ◽  
Vol 19 ◽  
pp. 147-152
Author(s):  
Maximilian F. Sundermeier ◽  
Dirk Fischer
Keyword(s):  
Signal Processing ◽  
Cross Section ◽  
Digital Signal ◽  
Radar Cross Section ◽  
Calibration Procedure ◽  
Calibration Target ◽  
Improve Measurement ◽  
Anechoic Chambers ◽  
Overall Performance ◽  
And Performance

Abstract. Radar cross-section measurements require the background reflections to be much lower than the reflections of the device under test. Although, anechoic chambers with special target holders meet this requirement, they are expensive and still have imperfections. To further reduce background reflections or to measure in environments where an anechoic chamber is not suitable, digital signal processing can be used to reduce background reflections. In this paper, a complete signal processing chain realized in Matlab is proposed, involving time gating of the measured target response and a background subtraction technique. Furthermore, the proposed signal processing includes a calibration procedure with either a single known calibration target or multiple known targets to improve measurement uncertainties. A compact measurement setup, consisting of a vector network analyzer and two horn antennas, is used to evaluate the overall performance and the advantages of a multiple known target calibration in a practical manner. The calibrated setup is able to measure the radar cross-section in a frequency range from 2 to 12 GHz with a mean error of less than 0.2 dB for both, VV and HH polarization combinations. It could also be shown, that a multi target calibration can result in an improvement of the measurement uncertainty by about 2.5 %.

A Non-Linear Approach to ECG Signal Processing using Morphological Filters

2013 ◽  
Vol 3 (3) ◽  
pp. 46-59 ◽  
Author(s):  
Vikrant Bhateja ◽  
Rishendra Verma ◽  
Rini Mehrotra ◽  
Shabana Urooj
Keyword(s):  
Signal Processing ◽  
Noise Removal ◽  
High Signal ◽  
Ecg Signal ◽  
Processing Scheme ◽  
Baseline Drift ◽  
Ecg Signals ◽  
Non Linear ◽  
Ecg Signal Processing ◽  
Electrocardiogram Ecg

Analysis of the Electrocardiogram (ECG) signals is the pre-requisite for the clinical diagnosis of cardiovascular diseases. ECG signal is degraded by artifacts such as baseline drift and noises which appear during the acquisition phase. The effect of impulse and Gaussian noises is randomly distributed whereas baseline drift generally affects the baseline of the ECG signal; these artifacts induce interference in the diagnosis of cardio diseases. The influence of these artifacts on the ECG signals needs to be removed by suitable ECG signal processing scheme. This paper proposes combination of non linear morphological operators for the noise and baseline drift removal. Non flat structuring elements of varying dimensions are employed with morphological filtering to achieve low distortion as well as good noise removal. Simulation outcomes illustrate noteworthy improvement in baseline drift yielding lower values of MSE and PRD; on the other hand high signal to noise ratios depicts suppression of impulse and Gaussian noises.

scholarly journals WAVELET-CONVERSION IN ELECTROCARDIO SIGNAL PROCESSING

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
V.F. Telezhkin ◽  
◽  
B.B. Saidov ◽  
P.А. Ugarov ◽  
A.N. Ragozin ◽  
...  
Keyword(s):  
Signal Processing ◽  
Wavelet Transform ◽  
Signal To Noise Ratio ◽  
Digital Signal ◽  
Automated Analysis ◽  
Discrete Wavelet ◽  
Ecg Signal ◽  
Signal To Noise ◽  
Time Frequency ◽  
Fourth Level

In the present work, processing of an electro cardio signal using a wavelet transform is consi-dered. In electrocardiography, various digital signal-processing techniques are used to detect, extract, and analyze the various components of an electrocardiogram. Among them, the wavelet transform technique gives promising results in the analysis of the time-frequency characteristics of the electrocardiogram components. The urgency of solving the problem of improving the quality of life of people with the help of early diagnosis and timely treatment of various cardiac diseases is obvious. The process of automated analysis of a huge database of electrocardiographic data is especially important. Wavelet analysis can be successfully used to smooth and remove noise in the ECG signal. Electrocardiogram signal, cleaned from noise components, looks clearer, while its volume is from 10 to 5% of the original signal, which largely solves the problem of storing cardiac records. Aim. Development of an algorithm for threshold processing of wavelet coefficients and filtering of an electrocardiography signal. Materials and methods. Cardiograms were taken for analysis. Then they were digitized and entered into a computer for processing. A program was written in the MATLAB environment that implements continuous and discrete wavelet transform. Results. The work shows the result of filtering the ECG signal with the addition of noise with a signal-to-noise ratio of 35 and 45 dB using the decomposition levels N = 2, N = 3, N = 4. Conclusion. Based on the analysis of the data obtained, it can be concluded that the second level of decomposition is the most optimal for filtering the ECG signal. With an increase in the level of decomposition, the output ratio decreases, at the level N = 4 the output signal-to-noise almost does not exceed the input one, therefore, the filtering becomes ineffective. The correlation coefficient to the fourth level is significantly reduced, which means a significant increase in the distortion introduced by the filtering algorithm.

scholarly journals Development of A Low-Cost Arduino-Based 12-Lead Ecg Acquisition System And Accompanied Labview Application

2019 ◽  
Vol 9 (1) ◽  
pp. 1641-1648
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Low Cost ◽  
Numerical Data ◽  
Digital Signal ◽  
Acquisition System ◽  
Signal Acquisition ◽  
Frequency Noise ◽  
Ecg Signal ◽  
Active Analog

In this paper, the design of a real-time digital multi--channel ECG signal acquisition system is presented. With the purpose of fabrication towards a simple, compact and low-cost tool for bioelectrical signal processing laboratories, the system is developed to acquire the 12 leads EGC signals and converted to numerical data based on an Arduino module named as Leonardo equipped 12 channels ADC. To observe the EGC waves, the ECG signals are amplified through designed amplifiers with the gain of 60 dB. To reduce the effects from the DC component as well as the baseline wandering and the high frequency noise, the active analog bandpass filter ranged in 0,05 Hz to 100 Hz was designed. The power line noise of 50 Hz also decreased with an active analog bandstop filter with attenuation -38 dB. Under the PC application was built using Labview programing, the low-cost digital ECG signal acquisition system was demonstrated with the requirement of observation in real-time. To clarify the small wave in the digital EGG signal, the limitation of the analog signal processing is improved through the digital filters parameterized in the software to increase the SNR from 1.4 dB to 27.6 dB. Practically, the system is evaluated through a series of experiments on a volunteer person resulting the ECG data is recorded and stored in a TDMS file. Since the system is designed as opened-system, a series of developments towards various applications in biomedical diagnosis based on digital signal analysis techniques is promised to be feasible in the near future.

scholarly journals A novel quasi-peak-detector for time-domain EMI-measurements

2005 ◽  
Vol 2 ◽  
pp. 27-32 ◽  
Author(s):  
F. Krug ◽  
S. Braun ◽  
P. Russer
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Measurement System ◽  
Time Domain ◽  
Electromagnetic Interference ◽  
Digital Signal ◽  
Peak Detection ◽  
Peak Detector ◽  
Measurement Results ◽  
Signal Recording

Abstract. In this paper, an advanced ultra-fast, broadband time domain EMI measurement system is described. Measurements were performed in the 30–1000MHz range. The digital signal processing of EMI measurements allows to emulate in real-time the modes of conventional analogous equipment, e.g. Peak-, Average-, RMS- and Quasi-Peak- Detector. With the presented time domain measurement system the measurement time can be reduced by a factor of 10. A novel signal recording routine for time-domain EMI (TDEMI) measurements and Quasi-Peak-Detection is described. Measurement results obtained from the investigation of a drillmachine, monitor and laptop obtained with the timedomain electromagnetic interference (TDEMI) measurement system are discussed. The results obtained with the described system have been compared with measurements performed with a conventional EMI receiver.

Sign in / Sign up

Export Citation Format

Share Document