Real-time monitoring of heart conditions via electrocardiogram processing at different lifestyle situations

Electrocardiogram (ECG) is a clinical tool to monitor heart rate (rhythm), regularity or irregularity of heartbeats. In this work a real-time heart conditions monitoring system is designed that can produce and process ECG signal in MATLAB tool developed within the system. QRS peaks from the ECG signal are detected by passing the signal through FIR low pass filter with rectangular window because QRS peaks are different at different lifestyle situations. The patterns of recorded signals from the body surface are analyzed for decision-making whether the condition of hear is infected or non-infected. Using the system the variations of power spectral density (PSD) are observed in 0-10 Hz frequency range for normal life style, in sleep, after walking and after exercise of a sound hearted subject. Average heart rate, and PSD increases from rest (normal life style) to different lifestyle situations indicating more healthy condition of heart after walking and after exercise. Statistical analysis shows sound heart condition of the subject as kurtosis becomes positive and the sharp peak is obtained. The system can provide real-time information about the condition of heart and fitness of a subject.