SMART MOTIF DISCOVERY ON ECG SIGNAL USING AUTOCORRELATION AND VARIABLE THRESHOLD
Journal Title: International Journal of Computer Science Engineering and Information Technology Research (IJCSEITR) - Year 2017, Vol 7, Issue 2
Abstract
The ECG signal is the prominent solution to determine the heart beat rate of the person to evaluate the health of heart. The telemedicine or body area networks have enabled the remote live ECG monitoring of the patients staying at their homes or remote areas. The device used to sense the ECG signal is called Holter, and is a wearable device. The Holter collect the ECG signal from the human body and forwards it towards the healthcare database. Then the data is evaluated on the cloud healthcare server to determine the heart beat rate obtained from the signal by using the motif discovery method. The motif discovery method evaluates the signal and finds the appropriate and valid heart beats to determine the beat rate along with the abnormalities in the signal to examine the patient’s critical health report. In case the heart beat rate is too high or contain number of abnormalities, the alarm is raised towards the concerned physician and the patient to take the preventive measure. In this paper, the flexible length motif discovery algorithm has been designed for the variable motif detection. The proposed model is used to detect the motifs in the input ECG signal. The motif discovery is performed between the given minimum and maximum motif length. The experimental results have proven the efficiency of the proposed model in detecting the motifs in the input signal.
Authors and Affiliations
HARJEET KAUR, RAJINDER KAUR2
Keywords
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