Fft of ecg signal using matlab. ecg=load ('ecg. (d)Collection dataset of ECG signals. I am trying to plot the frequency spectrum of an ECG signal using fft,without a in built function. example. This MATLAB function returns the periodogram power spectral density (PSD) estimate, pxx, of the input signal, x, found using a rectangular window. Blue whale moan audio signal decomposed into its FILTER ELECTROCARDIOGRAM (ECG) SIGNAL USING DIGITAL SIGNAL PROCESSING (DSP) WITH MATLAB Author: Thi Lan Nhi Pham Date: January 2022 ABSTRACT: Electrocardiogram (ECG) is commonly used in medical field in order to diagnose different cardiovascular diseases and patient’s general health. Although IIR filters have nonlinear phase, data processing within MATLAB ® software is commonly performed “offline,” that is, the entire data sequence is available 3. function [f amp] = getspectrum( Mdata, Mf ) % Mdata data . 2 and 14 respectively. My ECG simulator is a matlab based simulator and is able to produce normal lead II ECG waveform. The best option is to use a Savitzky-Golay filter (sgolayfilt) to eliminate most of the noise while keeping the essential parts of the EKG signal. In frequency domain you can observe what type of sine waves (amplitude and frequencies) are combined to obtain the signal. We used the fast Fourier transform (FFT) algorithm to calculate R peaks and calculate the heart rate. Open Signal Analyzer and drag the timetable to a display. Learn more about fft, ecg, electrocardiogram MATLAB and Simulink Student Suite Hi all, currently i'am trying to transform an ecg signal into frequency domain. The sampling period for this signal is 0. Jan 3, 2012 · Hi Lukas, Please try using the Zoom tool from the figure window's toolbar to zoom in closer to the plot; I think you will see that it looks a lot more like an ECG when you zoom in to an appropriate scale than it does from the global view. The minimum and maximum scales are determined automatically based on the energy spread of the The signal length is 1000 samples. Now that the data has been reduced to a feature vector for each signal, the next step is to use these feature vectors for classifying the ECG signals. 1. 3)its PSD was estimated as the square of the amplitude of the fast Fourier transform, zero padded to 4096 points. Apr 23, 2024 · I am trying to recover a signal by inverse Fourier-transforming the single-sided spectrum, but I am getting the wrong result. SpectrumEstimator System object™ in MATLAB This example shows how to use transfer learning and continuous wavelet analysis to classify three classes of ECG signals by leveraging the pretrained CNNs GoogLeNet and SqueezeNet. This code generates all possible forms of ECG signals with the parameters specified by the user. FFT of Signal in MATLAB | Fast Fourier Transform in MATLAB | MATLAB Tutorial for BeginnersIn this video, we are discussing Fast Fourier Transform (FTT) in MA Oct 16, 2017 · Copy. (b)Improved R peaks detection and calculation of average of heart rate. Feb 28, 2019 · The present code is a Matlab function that provides a Short-Time Fourier Transform (STFT) of a given signal x [n]. fft. The signal is real-valued and has even length. Theta= 4-7 Hz . I'm looking for FFT analysis to EEG or ECG signals in MATLAB. 2) Change input signal from time domain to frequency domain (FFT analysis) 3) Filter the signal in frequency domain using. The filter removes at least half the power of the frequency components lying in that range. Nevertheless I don't know how to obtain a normalized result. Examine the features and limitations of the time-frequency analysis functions provided by Signal Processing Toolbox. the original signal, 2. ECG SIGNAL ANALYSIS C. The Fourier transform is a powerful tool for analyzing data across many applications, including Fourier analysis for signal processing. 5)Obtain the performance parameter of step (3) using the following mathematical tools I) Signal to noise ratio (SNR) The discrete Fourier transform, or DFT, is the primary tool of digital signal processing. Electrical Engineering. Learn more about #signal #ecg #qrs #filter #filters #noise #highpass #smooth MATLAB, Filter Design Toolbox, Signal Processing Toolbox This is my ECG signal I wanna improve. selection of a periodicity of the above alternating initial signal. collapse all in page. 2 s segment of the ECG was Hamming windowed. V. Perform and interpret time-frequency analysis of signals using the continuous wavelet transform. Feb 1, 2008 · This paper proposes a method for electrocardiogram (ECG) heartbeat discrimination using novel grey relational analysis (GRA). Nov 7, 2022 · sum(PS(1:round(0. The signals are recorded from the patients and compared with pre-fed signals to detect the arrhythmias such as atrial fibrillation. Use designfilt to design the filter. If the heart rate is abnormal, the system sends SMS messages to doctors via a technology platform (Twilio) using the Python programming language. Let's start with an ECG signal: a) Import the ECG. The result of test simulations using the MIT/BIH Arrhythmia database shows high sensitivity and positive A signal can be converted between the time and frequency domains with a pair of mathematical operators called a transform. wt = cwt(x) returns the continuous wavelet transform (CWT) of x . You can control the filtering by giving your parameters. Feb 15, 2016 · 1Split your assigned ECG waveform into individual PQRST segments. # 2D numpy array storing the actual signal data. In order to conserve the total power, multiply all Apr 28, 2022 · Learn how you can do Fast Fourier Transform (FFT) in MATLAB. ECG signals are frequently nonstationary meaning that their frequency content changes over time. rdann - For reading PhysioNet annotation data into matlab. Construct a timetable with the duration array and the signal. Sorted by: 2. Empirical mode decomposition sees the signal as z. e. Apr 1, 2013 · At present many of the ECG recording instruments are based on analog recording circuitry. [Please watch the video in HD- to see the code clearly]ECG Signal Processing in MATLAB - Detecting R-Peaks: FullThis is a video tutorial on Detection of R-Pe Oct 18, 2017 · 1. Savitzky-Golay filter. Apr 19, 2014 · FFT of ECG signal in MATLAB. Matlab uses the FFT to find the frequency components of a discrete signal. Mar 14, 2021 · This article focuses on ECG signal recognition based on acoustic feature extraction techniques. Create a signal to use in the examples. A fast Fourier transform (FFT) is a highly optimized implementation of the discrete Fourier transform (DFT), which convert discrete signals from the time domain to the frequency domain. Two analyses are performed. May 9, 2012 · I can read and extract the data from the csv into Matlab and I apply FFT. Matlab code to study the EMG signal. The FFT and IFFT System objects and blocks in DSP System Toolbox™ enable you to convert a streaming time-domain signal into the frequency-domain, and vice versa. mat']). [imf,~,info] = emd(s); Spectral analysis lets you characterize the frequency content of a signal. Y = fft(X) Y = fft(X,n) Y = fft(X,n,dim) Description. . The function is an alternative of the Matlab command “spectrogram”. Below is my code. The wavelet analysis of ECG signal is performed using MATLAB. Once you get Fourier transform per time window, you can add or average the absolute signal across the frequencies of interest. Aug 2, 2020 · Time-frequency analysis of non-stationary signals in time, frequency and time-frequency domain. x[n] = 1 NN − 1 ∑ k = 0e2πjkn Ny[k]. For example, in the periodogram with the default rectangular window, the magnitude squared DFT values are "normalized" by dividing by the length of the input and the sampling rate as you state in your post, although for a one-sided PSD estimate, the This MATLAB function filters the input signal x using a lowpass filter with normalized passband frequency wpass in units of π rad/sample. csv file. The FFT y [k] of length N of the length- N sequence x [n] is defined as. These transforms can be calculated by means of fft and ifft , respectively, as shown in the following example. PNG. I now need to extract certain frequencies (Alpha, Beta, Theta, Gamma) from the FFT. Matlab's spectrogram does that, time-frequency analysis with short-time Fourier transform. To do that we use windowed filter that “sees” only maximum in his window and ignores all other FFT of Signal in MATLAB | Fast Fourier Transform in MATLAB | MATLAB Tutorial for BeginnersIn this video, we are discussing Fast Fourier Transform (FTT) in MA May 9, 2023 · Learn more about fft, ecg, electrocardiogram MATLAB and Simulink Student Suite Hi all, currently i'am trying to transform an ecg signal into frequency domain. Options include the FFT window and length. You can use the Classification Learner app to quickly evaluate a large number of classifiers. Frequency_plot. Oct 25, 2018 · This paper aims to address the issue of denoising a noisy ECG signal using the Fast Fourier Transform based bandpass filter. For example, mhrv. s = stft(x) returns the Short-Time Fourier Transform (STFT) of x. Determine the pulse times using the locations of the signal peaks. 1 Answer. Savitzky-Golay Filters. Ts = 1/50; 1-D discrete Fourier transforms #. To hear audio signals, click Play in the Playback section of the toolstrip to play the entire signal once. % Mf sampling rate / frequency (Hz) NFFT = 2 ^ nextpow2(length(Mdata)); . A long short-term memory (LSTM) network is a type of recurrent neural network (RNN) well-suited to study sequence and time-series data. rdsamp - For reading PhysioNet signal data into matlab. ts = seconds(t)'; tx = timetable(ts,x); [~,lc] = findpeaks(x,t); tsa(tx,lc) Compute the time-synchronous average. Learn more about fft, signal processing, dsp, digital signal processing, matlab, ecg I'm trying to calculate the FFT of a Physionet ECG signal and not sure what's wrong with my code. Feb 27, 2019 · Learn more about ecg, fft, time to frequncy domain This is my program to generate time-amplitde ECG signal, now i want to convert this output signal into frequency-amplitude domain. The function plots. About 9. Where Delta = 1-3 Hz . Because the signal is real-valued, you only need power estimates for the positive or negative frequencies. The following is an example of how to use the FFT to analyze an audio file in Matlab. Transform 2-D optical data into frequency space. Electrical Engineering questions and answers. This can be quite useful, for example, if you want to see if the power lines on the walls (50/60Hz) are causing any disturbance. In this proposed technique, ECG signals are previously transformed into a successive series of Mel-frequency cepstral coefficients for computing the This example shows how to design and implement an FIR filter using two command line functions, fir1 and designfilt, and the interactive Filter Designer app. Dec 16, 2022 · The purpose our work is to analyze and study the waveform of the Electrocardiograph (ECG). 100. Cardiovascular diseases (CVD) are a key factor behind casualties worldwide among both women and men. EEG Emotiv - Matlab. 4 million deaths occur due to high Blood Pressure (BP) only, out of which 51% deaths are due to strokes and 45% deaths are due to coronary heart diseases. Frequency Voltage Graph from May 19, 2024 · 2. The SVM and k-NN classification approaches are proposed for recognizing the ECG heart sound as well as for calculating the recognition efficiency. FFT filtered ECG. Nov 16, 2012 · The nonparametric PSD estimates in MATLAB like the periodogram and Welch estimator already "normalize" the result to create the PSD estimate. (c)Classification normal or abnormal of ECG paper. The procedure explores a binary classifier that can differentiate Normal ECG signals from signals showing signs of AFib. Use. For example, in the periodogram with the default rectangular window, the magnitude squared DFT values are "normalized" by dividing by the length of the input and the sampling rate as you state in your post, although for a one-sided PSD estimate, the Jan 9, 2020 · Learn more about ecg, fit, fft, fourier transform, fast fourier transform, heart beat, heart rate Hi, I am trying to use the fft function to compute the power spectrum of an ECG. Alpha = 8-12 Hz. Load 4 more related questions Show fewer related questions Sorted by: Reset to default Know someone who can answer? Dec 7, 2021 · The 5 Hz signal is well within the spectrum of the normal EKG (0-100 Hz), so a bandstop or other frequency-selective filter is inappropriate, as it will remove some of the EKG energy. e) sample number,in the coding. To compute the spectral estimate of the signal, use the dsp. As the ECG signal is used for the primary diagnosis and analysis of heart diseases, a good quality of ECG signal is The fft function in MATLAB® uses a fast Fourier transform algorithm to compute the Fourier transform of data. Fast Fourier transform. To track the signal a little more closely, you can use a weighted moving average filter that attempts to fit a polynomial of a specified order over a specified number of samples in a least-squares sense. Fig. This is what I did so far: Dec 9, 2010 · The Fast Fourier Transform (FFT) is an efficient way to do the DFT, and there are many different algorithms to accomplish the FFT. Basically, ECG signal is the electrical activity of the heart over a period. s = stft(x,ts) returns the STFT of x using sample time ts. fs = 1000; t = 0:1/fs:1-1/fs; x = cos (2*pi*100*t) + randn (size (t)); Obtain the periodogram using fft. Perform and interpret basic signal multiresolution analysis (MRA). Firstly i would like to cut and make high frequencies kind of equal: Secondly I would like to smooth the noise below. zip. I need to give N value(i. I have read in the documentation that I ne Oct 4, 2020 · So various signal processing techniques such as Frequency-domain analysis (FFT), Time- and Frequency-domain analysis (STFT), and Feature Vector ECG Signal Analysis (FVESA) are applied to extract the data. The output of the function is: 3) a time vector. The idea is to apply direct fast Fourier transform — FFT, remove low frequencies and restore ECG with the help of inverse FFT. 2. MATLAB program to detect R peaks in an ECG signal using discrete wavelet transform - atinwb/ECG-R-peak-Detection Feb 1, 2021 · The cardiovascular system is a combination of the heart, blood and blood vessels. Wavelets decompose signals into time-varying frequency (scale) components. 3. gqrs - A QRS detection algorithm. Create one period of an ECG signal. The signal is a 100 Hz sine wave in additive N (0, 1 / 4) white Gaussian noise. Smooth noisy, 2-D data using convolution. For example, in the periodogram with the default rectangular window, the magnitude squared DFT values are "normalized" by dividing by the length of the input and the sampling rate as you state in your post, although for a one-sided PSD estimate, the Divide the signal into 8 sections of equal length, with 50% overlap between sections. Signal Calculating ECG Intervals & Self Diagnosis Software can be developed in MATLAB to process each acquired ECG signal. Jun 14, 2023 · FFT of ECG signal in MATLAB. Comprehensive help is included (>>help fftf). Y is the same size as X. If X is a vector, then fft(X) returns the Fourier transform of the vector. The nonparametric PSD estimates in MATLAB like the periodogram and Welch estimator already "normalize" the result to create the PSD estimate. csv'); A=fft(ecg); L=length(ecg); X_mag=abs(A); X_phase=angle(A); fs=350/2; Fbins=((0 Nov 16, 2012 · The nonparametric PSD estimates in MATLAB like the periodogram and Welch estimator already "normalize" the result to create the PSD estimate. You can also observe high frequency components related with acquistion noise and many other Oct 10, 2022 · The contributions of this work are as follows: (a)Proposed a system that automatically extracts the features from ECG paper (image) and saves these features in CSV. We convert each QRS complexes to a Fourier spectrum from ECG signals, the spectrum varies with the rhythm origin and conduction path. Plot, and comment on the results. The present code is a Matlab program for Time-Frequency analysis of a given (non-stationary) signal. EEG bandpass filter in mat lab. val; Removing High-Frequency Noise from an ECG Signal. For example, in the periodogram with the default rectangular window, the magnitude squared DFT values are "normalized" by dividing by the length of the input and the sampling rate as you state in your post, although for a one-sided PSD estimate, the May 12, 2021 · load ( 'ecg lab2. 1 Reading ECG signal. For example, in the periodogram with the default rectangular window, the magnitude squared DFT values are "normalized" by dividing by the length of the input and the sampling rate as you state in your post, although for a one-sided PSD estimate, the The nonparametric PSD estimates in MATLAB like the periodogram and Welch estimator already "normalize" the result to create the PSD estimate. The results are: 3) graphical representation of the signal in the time-frequency domain (via STFT). I use an ecg signal from MIT-BIH Arrhythmia Database (physionet). An example is given in order to clarify the usage of the function. Wavelet-based time-frequency representations of ECG signals are used to create scalograms. Set the random number generator to the default state for reproducible Convert the signal to a MATLAB® timetable. mat') fs=1000; T=500; x= ecg (:,1:T*1000); t=1/fs:1/fs:T; plot (t,x) fig2. Y = fft(X) computes the discrete Fourier transform (DFT) of X using a fast Fourier transform (FFT) algorithm. Perform the FFT of the same signal given in the example but using three different window lengths (i. For example, in the periodogram with the default rectangular window, the magnitude squared DFT values are "normalized" by dividing by the length of the input and the sampling rate as you state in your post, although for a one-sided PSD estimate, the Jul 31, 2020 · Steps involved. Use the Fourier transform for frequency and power spectrum analysis of time-domain signals. Due to this, noises from various sources are inherently added to the signal. The function by default outputs a table that indicates the number of sifting iterations, the relative tolerance, and the sifting stop criterion for each IMF. Since, spectrun is the distribution of the amplitudes and phases of each frequency component against frequency, we are using abs function to get the amplitude of each frequency component. ECG signal processing by mean s of MATLAB tool effectively. This example shows how to lowpass filter an ECG signal that contains high frequency noise. 67/df))) must be real and non-negative (but could be empty if df > 4/3 meaning that the signal was less than 3/4 of one period) df is non-negative (because we assume that Fs is positive). Use the following commands to remove Engineering. and the inverse transform is defined as follows. But if i give it ,am getting error Nov 16, 2012 · The nonparametric PSD estimates in MATLAB like the periodogram and Welch estimator already "normalize" the result to create the PSD estimate. Sign in to comment. 1². Eliminate the 60 Hz noise using a Butterworth notch filter. ) # load the aami3a ECG signal using special package wfdb for python. What is strange is the X-axis, it should be centered to zero, which makes your whole spectrum range from 0 to ~500 and considering the properties of an ECG signal you should focus on the low frequencies (LF and VLF) that range < 1Hz. c = fft (a); takes the fft of both columns independently and then when you plot () that you get both plots on the same axis. The CWT is obtained using the analytic Morse wavelet with the symmetry parameter, gamma ( γ ), equal to 3 and the time-bandwidth product equal to 60. Syntax. Generate a sinusoidal signal sampled at 1 kHz for 296 milliseconds and embedded in white Gaussian noise. About Press Copyright Contact us Creators Advertise Developers Terms Privacy Policy & Safety How YouTube works Test new features NFL Sunday Ticket Press Copyright May 8, 2021 · %% FFT of ECG signal with Butterworth High Pass filter and Low pass filter:%% Matlab Code:clc; clear all;Fs = 360; % Sampling frequency Aug 7, 2022 · ECG noise removal is complicated due to time varying nature of ECG signal. ECG signal proccessing using Fourier tansform. The ecg function creates an ECG signal of length 500. Multi-stage adaptive peak detection is then applied to identify the R-peak in the QRS complex of the ECG signal. The Electrocardiogram (ECG) represents the heart After that, the system retrieves the signals for further processing of the raw signals. 0. Consider a sinusoidal signal x that is a function of time t with frequency components of 15 Hz and 20 Hz. Dec 23, 2020 · The class was written to allow for the easy analysis of ECG signals and their components. The code is based on the theory described in: May 13, 2020 · You will only see them in fft if it is computed for the short time around the spikes, and not by using fft for the whole signal. The problem, as you can see, that it is not the correct Fourier transform. EEG raw data band filtering using matlab. This example shows how to use wavelets to analyze electrocardiogram (ECG) signals. Gamma = 31-40 Hz . cwt uses 10 voices per octave. The foundation of the product is the fast Fourier transform (FFT), a method for computing the DFT with reduced execution time. b) Plot the frequency spectrum of the ECG signal in terms of power vs frequency using the fft Jul 30, 2020 · Calculate the FFT of a Physionet ECG signal. Store the signal and its time information in a MATLAB® timetable. , 1 second, 20 seconds, 100 seconds). Display the time-synchronous average. I do successfully transform the single-sided spectrum back to double-sided spectrum but from there I get lost. Our second step is to find local maxima. (40 points) Add high-frequency and low-frequency noise into an ECG signal, then implement high-pass and low-pass filters to remove the noise from the signal. I have tested some codes. wfdb. Feb 9, 2016 · I didn’t look at that signal in detail, but the number of Q-waves and R-waves should not differ by more than 1, if the EKG trace was cut off in the middle of a QRS complex. I tried using FFT technique but it is invalid taking fft(x,y). Use MATLAB to perform the following computer exploration: 1. 5–35 Hz band pass filter) 2)each 3. signal Apr 26, 2006 · ECG simulation using MATLAB. The waveforms with normality and abnormalities are shown in Fig. Apri in MATLAB Online. It starts with generating a synthesized signal and then using the FFT function to convert the si Jul 18, 2020 · fft is a method used to transform from the time domain to the frequency domain and gives a complex result. In this example, a multi-class SVM with a quadratic kernel is used. Oct 8, 2019 · Learn more about fft, ecg, electrocardiogram MATLAB and Simulink Student Suite Hi all, currently i'am trying to transform an ecg signal into frequency domain. The 'spectrum' of frequency components is the frequency domain R Wave Detection in the ECG. RGB images of the scalograms are generated. The aim of the ECG simulator is to produce the typical ECG waveforms of different leads and as many arrhythmias as possible. Plot the FFT of the windowed segments and inspect a couple to make sure the windows make sense (you should include one or two of these plots in your report). Here is the result of FFT processing — fig. 4)Convert step (3) to time domain. the reconstructed (filtered) signal. Specify a sinusoid frequency of 200 Hz and a noise variance of 0. These changes are the events of interest. its transform, 3. You'll note that by smoothing the data, the extreme values were somewhat clipped. cutoff = cutoff/(360. Once created, varName. Hi all, currently i'am trying to transform an ecg signal into frequency domain. record is an object of wfdb which has many attributes. mat into MATLAB using load() function. Four features stand out from the noise. Use emd to compute the intrinsic mode functions (IMFs) of the signal and additional diagnostic information. 67/df) will be 0 or positive -- in particular not negative. Below is the Fourier transform. An example is the Fourier transform, which decomposes a function into the sum of a (potentially infinite) number of sine wave frequency components. The width of the notch is defined by the 59 to 61 Hz frequency interval. Specify the same FFT length as in the preceding step. s = stft(x,fs) returns the STFT of x using sample rate fs. Use a time vector sampled in increments of 1/50 seconds over a period of 10 seconds. The code is extensively commented. Study of ECG signal includes ge neration & simulation of ECG. May 23, 2019 · Use the fft routine from MATLAB to find out the beats per minute (BPM) in the myecg. View the types of the output arguments. Use wavelet packets to remove harmonic interference from an A small subset of the PhysioNet WFDB tools are wrapped with matlab functions, to allow using them directly from matlab. Beta = 13-30 Hz. Dec 16, 2012 · Dec 16, 2012 at 15:24. 00192 seconds and the signal was recorded with an attenuation of 10 on the digital scope (what do you have to do to put the signal with the proper amplitude)? So basically I would have to get the BPM. A typical ECG signal consists of the P-wave, QRS complexes and T-wave. The sgolayfilt function smoothes the ECG signal using a Savitzky-Golay (polynomial) smoothing filter. Multiply each segment by a window. Create an ECG object using: (varName) = ECG (Signal, SamplingFrequency, Name (optional)) Note: the signal must be inputted as a numeric array. mhrv. I'm working on a little project involving digital filters and DFT, what I want to do is, given a sampled ECG, get the heart rate using power spectral density. So, by analysis of the Jun 6, 2018 · I personally do the fft calculation slightly different (I don't use fftshift) but I assume the theory behind is correct. An LSTM network can learn long-term dependencies between time steps of a sequence. I got the samples from this database. Compute the short-time Fourier transform and verify that it gives the same result as the previous two procedures. It looks like there is a pretty significant distortion in the signal between t = 115 and t = 118. s = stft( ___,Name=Value) specifies additional options using name-value arguments. Matlab code to import the data in the file "P-10_3 Matlab code to study the ECG signal; Matlab code to import the date in the file “MyocIn Matlab code to import the data in the file Atrflut Matlab code to study the EEG signal; Matlab code to estimate the power spectrum of the Aug 16, 2009 · The function introduces the implementation of fft and ifft in filtering and cleaning of signals. Y = fft(double(Mdata), NFFT) / length(Mdata); f = (double(Mf) / 2 * linspace(0, 1, NFFT / 2))'; % Vector containing frequencies in Hz. round(0. The primary advantage of IIR filters over FIR filters is that they typically meet a given set of specifications with a much lower filter order than a corresponding FIR filter. Select Play in Loop and then click Play to play the signal repeatedly. FFT computations provide information about the frequency content, phase, and other properties of the signal. The dt will be a single spike and much larger magnitude than the spectrum of the signal so that's what is visible in the plot. init will eliminate offsets, detrend the signal, then identify peaks and calculate: Sep 17, 2011 · 1)First the ECGs were preprocessed (1. Many of the toolbox functions (including Z -domain frequency response, spectrum and cepstrum analysis, and some filter design and Jan 1, 2012 · Abstract —This paper deals with the study and analysis of. Here's the MATLAB code I wrote: ecg_samples = [ecg_samples zeros(1,3600)]; ecg_samples((3600)*i+1:end) = load([filename ' (',num2str(i),'). oq rc cn rw bi qz mn hi ae ej