A significant number of subjects with normal vision have physiologic GEN at gaze angles as small as 10 degrees. This could potentially refute the "failing" grade that is the hallmark of the HGNT and propagates further testing of the validity of this test in the conviction of intoxicated drivers.

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Vergence eye movements were recorded from three different populations: healthy young (ages 18-35 years), adaptive presbyopic and non-adaptive presbyopic(the presbyopic groups aged above 45 years) to determine how the variability of the eye movements made by the populations differs. The variability was determined using Shannon Entropy calculations of Wavelet transform coefficients, to yield a non-linear analysis of the vergence movement variability. The data were then fed through a k-means clustering algorithm to classify each subject, with no a priori knowledge of true subject classification. The results indicate a highly significant difference in the total entropy values between the three groups, indicating a difference in the level of information content, and thus hypothetically the oculomotor adaptability, between the three groups.Further, the frequency distribution of the entropy varied across groups.

Dynamic changes in physiologic systems have become an increasingly important topic in biomedical signal processing. To demonstrate a novel approach to this type of analysis, we recorded the cardiac and respiratory rhythms of six normal subjects over 5 minutes. We used cross-wavelet transforms to identify any correlations between these signals and then a unique approach to surrogate data generation in the frequency domain to confirm the statistical significance of the correlations that were found. The cross-wavelet transform provides a means of statistically quantifying weak correlations between systems that might otherwise not show significant interactions, while the method of surrogate data generation is a robust way of confirming a true physiological relationship.

Correlations between jaw muscle hyperactivity and temporomandibular joint disorders and emotional stress are well known, but not well defined. Understanding and further analyzing these correlations using tools that were not heretofore available provides a means of quantifying the modulation of muscle recruitment in the jaw that results from emotional stimulation as opposed to normal muscle functionality. This paper compares the traditional techniques of amplitude and mean power frequency analysis with the continuous quantification of frequency content of a signal over time, known as multi-resolution wavelet analysis.