A New Method for Acquisition and Analysis of ECG Signal using Virtual Environment

A New Method for Acquisition and Analysis of ECG Signal using Virtual Environment

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2019 by IJETT Journal
Volume-67 Issue-3
Year of Publication : 2019
Authors : Divya Savani, Ukshit Prajapati, Harsh Shingala, Prashant Tanti
DOI :  10.14445/22315381/IJETT-V67I3P220

Citation 

MLA Style: Divya Savani, Ukshit Prajapati, Harsh Shingala, Prashant Tanti "A New Method for Acquisition and Analysis of ECG Signal using Virtual Environment" International Journal of Engineering Trends and Technology 67.3 (2019): 105-110.

APA Style:Divya Savani, Ukshit Prajapati, Harsh Shingala, Prashant Tanti (2019). A New Method for Acquisition and Analysis of ECG Signal using Virtual Environment. International Journal of Engineering Trends and Technology, 67(3), 105-110.

Abstract
Electrocardiogram is used to measure the rate and regularity of heartbeats and to detect any heart arrhythmia. Different ways are submitted and used for cardiogram feature extraction with a reasonable percentage of right detection. Al-though the problem stays open especially with respect to superior detection accuracy in ECGs. The ECG signal is very sensitive in nature having voltage level as low as 0.5 to 5mv and frequency components fall into the range of 0.05-100Hz and most of the information contained in the range of 0.05- 45Hz. The recorded ECG signal contains different type of noises such as baseline wander, channel noise which becomes very essential for us to remove for the better clinical result which helps in the treatment of the patient. For the feature extraction and classification task we`ll be using discrete wavelet transform (DWT) as wavelet transform could be a two dimensional timescale process technique, there-fore it`s appropriate for the nonstationary ECG signals(due to adequate scale values and shifting in time) in LabVIEW. The flexibility, standard na-ture and simplicity to use programming possible with LabVIEW, makes it less complex. The pro-posed algorithm is executed in two steps. First step, it pre-processes de-noises the signal to get rid of the noise from the cardiogram signal, Then it detects pulse, Our extracted parameters are Heart rate, P wave amplitude, T wave amplitude, S value, Q value, R-value, P offset location, P onset location, T onset location, T offset location and the location of P, Q, R, S and T wave.

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Keywords
Electrocardiogram, discrete wavelet transform, heart arrhythmia, LabVIEW.