System on Chip (SOC) Based Cardiac Monitoring System Using Kalman Filtering with Fast Fourier Transform (FFT) Signal Analysis Algorithm

Cardio vascular diseases account for a high number of deaths in the world due to sudden cardiac arrest. In literature, the available patient monitoring system produces only off line analysis of cardiac patients. Hence, a real time monitoring system, invaluable for patients affected by cardio vascular diseases is proposed herein. This system continuously monitors Electrocardiogram (ECG) parameters and analyzes the symptoms of cardiac arrest on the onset of the ECG signal. The proposed monitoring system consists of an analog and a digital circuit. The signal analysis is performed by Field Programmable Gate Array (FPGA) hardware. NIOS II Embedded processor is also used to perform complicated tasks such as signal measurements and signal analysis. The functional blocks of the proposed system are preprocessing block, analog-to-digital convertor (ADC), and digital filter. The blocks also include a signal classification algorithm which is based on Kalman filtering employing Fast Fourier Transform (FFT) signal analysis. The proposed method has add-on advantages such as visualizing the output signal in oscilloscope, indicating the cardiac output through buzzer, Short Message Service (SMS) alert through Global System Mobile (GSM) and storing the continuous recorded signal in a digital storage card which is used for future analysis.