Application of Support Vector Machine Classifier on Developed Wireless ECG System
Arjon Turnip 1, M. Ilham Rizgyawan 1,
Dwi Esti Kusumandari 1, and
I. Dewa Putu Hermida 2
1. Technical Implementation Unit for Instrumentation Development, Indonesian Institute of Sciences, Kompleks LIPI Gd. 30, Jl. Sangkuriang Bandung, Indonesia
2. Sensor and Microelectronics Division, Research Center for Electronics and Telecommunications, Indonesian Institute of Sciences, Kompleks LIPI Gd. 30, Jl. Sangkuriang Bandung, Indonesia
2. Sensor and Microelectronics Division, Research Center for Electronics and Telecommunications, Indonesian Institute of Sciences, Kompleks LIPI Gd. 30, Jl. Sangkuriang Bandung, Indonesia
Abstract—The Electrocardiogram (ECG) is a principal diagnostic instrument used to measure and record the electrical activity of the heart. The heart conditions can be detected and evaluated when the recorded ECG signals is available. The normally ECG used for monitoring and diagnosis at present hospital is expensive and stationary. With the recent advance in technology, there are possibilities to create a small sized wireless ECG system capable of processing, transmitting, and viewing ECG signal via Bluetooth technology through a smart phone to internet at low cost and at low power. In this work a small sized wireless ECG embedded system is developed to make the patient more mobile without losing the reliability of the ECG sensor. It consists of an amplifier, filtering, microcontroller, Bluetooth Technology and anroid as a platform for wireless transmission. The transmitted data is processed in the microcontroller and graphically displayed in the website.
Index Terms—electrocardiogram, real time, monitoring, signal processing
Cite: Arjon Turnip, M. Ilham Rizgyawan, Dwi Esti Kusumandari, and I. Dewa Putu Hermida, "Application of Support Vector Machine Classifier on Developed Wireless ECG System," International Journal of Pharma Medicine and Biological Sciences, Vol. 5, No. 3, pp. 189-193, July 2016. 10.18178/ijpmbs.5.3.189-193
Cite: Arjon Turnip, M. Ilham Rizgyawan, Dwi Esti Kusumandari, and I. Dewa Putu Hermida, "Application of Support Vector Machine Classifier on Developed Wireless ECG System," International Journal of Pharma Medicine and Biological Sciences, Vol. 5, No. 3, pp. 189-193, July 2016. 10.18178/ijpmbs.5.3.189-193
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