Abstract
ECG signals occupy a vital role in the diagnosis of cardiac abnormalities. These abnormalities can be detected by the variation in the ECG parameters. This paper deals with the implementation of real-time acquisition, conditioning, and feature extraction of the ECG signal so as to monitor and detect various cardiac abnormalities. NI educational laboratory virtual instrumentation suite (NI ELVIS) is used for interfacing the acquired signal with LabVIEW. Further, LabVIEW-based virtual system is designed to create modules for conditioning and feature extraction. The detection of cardiovascular abnormalities such as bradycardia and tachycardia is based on the calculation of heart rate from extracted ECG features. Other abnormalities are detected by determining the deviation of the extracted features such as duration and amplitude, from their standard values.
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Kalaivani, S., Shahnaz, I., Shirin, S.R., Tharini, C. (2016). Real-Time ECG Acquisition and Detection of Anomalies. In: Dash, S., Bhaskar, M., Panigrahi, B., Das, S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 394. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2656-7_46
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DOI: https://doi.org/10.1007/978-81-322-2656-7_46
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