ec21d0008
PRIYA K • Joined a month ago
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ec21d0008/Slope-Detection-Final-Priya
This project proposes a time-based ventricular arrhythmia detection and classification system that works on the features extracted from ECG even in the presence of baseline wander and noise. The system first encodes the ECG using an Adaptive Exponential Integrate and Fire neuron and then extracts the features from the inter-spike distance (ISD) which is the inverse of spike rate. The difference between successive spike rates gives the slope. If the difference is continuously negative, it indicates a rising slope of the waveform; if it is positive, it indicates a dropping slope. rising and dropping slopes imply the presence of a wave whereas rising and falling slopes at very high frequency indicates noise. By tracking the slope change, the characteristics of ECG such as peak location and width of each wave, RR, QRS, QT, PR etc. are determined.