Second-degree correlation surface features from Optimal Trade-off Synthetic Discriminant Function filters for subject identification using radio frequency cardiosynchronous waveforms

Radio Frequency Impedance Interrogation (RFII) measures hemodynamic function via resonance frequency coupling to a hydrophilic protein molecule. The RFII device generates a cardiosynchronous waveform from the identification of blood movement in the time, frequency, and voltage domains. This paper examines RFII signals with the end goal of allowing confirmation of the identity of a subject in an operational setting. An Optimal Trade-off Synthetic Discriminant Function (OT-SDF) was applied to filter the data stream for subject identification. Preliminary results using the OT-SDF Filters demonstrate 63.3% successful single-heartbeat subject identification. However, each individual's correlation surfaces appear to have a unique waveform morphology that is visually distinct from the other individuals in the data set. Improved identification was seen with second-degree correlation suggesting that a second-degree correlation may hold great potential as a biometric feature extraction identifier. We show that using correlation plane outputs as features actually provide a robust biometric identifier and significant higher identification accuracy.