ECG Biometrics in Forensic Application for Crime Detection

The physiological property of the human being is unique for each individual. This provides the identity of specific human. Biometric features are used with the help of engineering through machines in recent years for better operation. Similar features can be used for crime detection and security purpose. The biometric features provides information and useful in forensic science. Unlike many methods, heart signal is considered in this work. In different mental condition ECG is collected experimentally in our laboratory using cardio track device. The experiment is carried with eighty subjects. The age range is between nineteen to twenty one years. The data is verified for frighten boy committed some mistakes related to academic environment. Spectral analysis using Fractional fourier transform (FFT) and Wavelet transform (WT) has been performed for R peak detection. The wavelet coefficients are considered as the weights of neural network model for detection purpose. The standard neural network structure multi layer perceptron (MLP) is utilized with wavelet coefficients. The result found excellent as compare to earlier method and exhibited in result section