Key result
A newly developed LabVIEW-based graphical user interface successfully extracted time and frequency domain features from heart rate variability signals to differentiate healthy and congestive heart failure ECGs.
A graphical programming approach using LabVIEW can extract HRV features from ECG signals to aid in the classification of congestive heart failure.
Heart Rate Variability (HRV) signal which is providing information about variation between consecutive heartbeats has been employed for extracting the parameter related to Congestive Heart Failure (CHF) from Electrocardiography (ECG). There are several studies on HRV analysis and CHF however most of the studies were performed by text-based methods. The main objective of this work is not only search to extract parameters but also to accomplish the difficulties in the text based program. This study presents graphical programming language to investigate features of HRV. Graphical User Interface (GUI) has been developed in LabVIEW to create some method for extraction features related to CHF. HRV are analyzed in the time and frequency domains. Parameters related to the time and frequency domains are derived for healthy ECG and ECG signals having Congestive Heart Failure. Several parameters which are necessary for classification algorithms are obtained.
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Aydın et al. (2016) studied Congestive Heart Failure. LabVIEW-based graphical user interface for HRV feature extraction vs. Healthy ECG signals was evaluated on Extraction of HRV parameters in time and frequency domains. A newly developed LabVIEW-based graphical user interface successfully extracted time and frequency domain features from heart rate variability signals to differentiate healthy and congestive heart failure ECGs.
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