Detection of Arrhythmia using ECG and Machine learning

  • Mrs. Shalini K J, Mrs. Prabhavathi K, Ms. Nischitha S, Mr. Balaji B S
Keywords: Electrocardiography, Machine learning, cardiac arrhythmia


In Arrhythmia, the heartbeat is unpredictable and it can be very fast or sluggish. An Electrocardiogram is used to find arrhythmias. It uses a terminal connected to the skin to record the patient's core electrical exercise over a period of time. Since the electrocardiogram signal reflects the physiological condition of the intestines, doctors tend to use the electrocardiogram signal to diagnose arrhythmia [2]. “Be prepared to distinguish dangerous types of arrhythmias from electrocardiogram signals is an important skill for clinical experts” [2]. Nevertheless, the interpretation of electrocardiogram waveforms by competent clinicians is physiologically tedious. Subsequently, In order to recognize irregularities from the daily ECG information, it is necessary to improve the electrocardiogram methods. In addition, if these abnormal heart conditions can be distinguished so as to use health monitoring equipment that uses artificial intelligence calculations internally, ideal medical care measures can be appropriately applied.

How to Cite
Ms. Nischitha S, Mr. Balaji B S, M. S. K. J. M. P. K. (2021). Detection of Arrhythmia using ECG and Machine learning. Design Engineering, 2616-2625. Retrieved from