Abstract
The Cardiovascular disease (CVD) is the most of death in the world. Electrocardiogram (ECG) is the graph that shows heart electrical activities. The physician record and detect the abnormal Electrocardiogram (ECG) signal by the Holter monitor that patient need to carry on the device for record ECG signal in 24 hours. Pan-Tomkins algorithm was appropriate for Real-time ECG signal recognition because high accuracy and rapidly analysis. This research propose the Real-time ECG Signal monitoring system for detect the abnormal ECG signal by using Pan-Tomkins algorithm with Wireless Sensor Network. The system separated into 2 part; sender module and receiver module. Experimental the system by using the ECG signal data from MIT-BIH database. Selected 20 samples of abnormal ECG signal then experimental at 10 and 20 meters sender module-receiver module distance, calculate R-R interval and R amplitude threshold The results show that the Real-time ECG signal monitoring system detect 17 abnormal ECG signal, the accuracy is 85%. This systems efficient for detect the abnormal of ECG signal in real-time.
Highlights
The Cardiovascular disease (CVD) is the most of death in the world
Wavelet transform applied to ECG signal, extract feature and classify by Probabilistic Neural Network [8]
Wireless Sensor Network (WSN) is low energy consumption, secure and flexible so it can develop to wearable device that use for Real-time analysis
Summary
The Cardiovascular disease (CVD) is the most of death in the world. CVD is effect to quality of life and government disbursement [1]. Detected QRS Complex by Pan-Tomkins Algorithm and identify the abnormal of ECG signal by Machine Learning; Feed forward Multilayer Perceptron Artificial Neural Network. Wavelet transform applied to ECG signal, extract feature and classify by Probabilistic Neural Network [8]. Pan-Tomkins algorithm was appropriate for Real-time ECG signal recognition because high accuracy and rapidly analysis. WSN is low energy consumption, secure and flexible so it can develop to wearable device that use for Real-time analysis. Oleg Lejvinov proposed 4 important technologies for wearable device; Sensor for detect user environment, Microcontroller for processing, Power management and Wireless communication for communicate with nearby devices and remote devices. This research propose the Real-time ECG Signal monitoring system for detect the abnormal ECG signal by using Pan-Tomkins algorithm with Wireless Sensor Network. The remaining of the this research is organized as follows: the first section is Introduction, section 2 are Background and Notation; Heart Anatomy, Electrocardiogram and Electrocardiogram for Diagnostic, section 3 is Proposed method; Conceptual Framework, Implementation and System Evaluation, section 4 is Results and section 5 is the Conclusions
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