The cardiosynchronous signal obtained through Radio Frequency Impedance Interrogation (RFII) is a non-invasive method for monitoring hemodynamics with potential applications in combat triage and biometric identification. The RFII signal is periodic in nature dominated by the heart beat cycle. The first step in both of these applications is to segment the signal by identifying a fiducial point in each heart beat cycle. A continuous wavelet transform was utilized to locate the fiducial points with high temporal resolution. Cepstral Analysis was used to estimate the average heart rate to focus on the appropriate portion of the time-frequency spectrum. Robust heartbeats from RFII signals collected from four subjects were segmented using this method.

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.

UNLABELLED: Dblox and RDblox provide a simple statistical test for duplicated genomic structure; the same programs can also be used to identify putatively duplicated regions. The method focuses on ancient duplication events involving protein-coding genes. AVAILABILITY: http://www.biol.sc.edu/~austin/