The demand of non-invasive ocular screening is rapidly growing due to an increase of age related eye diseases
worldwide. An indeed in-depth understanding of optical properties is required to elucidate nature of retinal tissue. The
research aims to investigate an effective biomedical engineering approach to allow process region of interests (ROIs) in
eyes to reveal physiological status. A dynamic opto-physiological model (DOPM) representing retinal microvascular
circulation underlying a diffusion approximation to solve radiative transport theorem (RTT) has being developed to
interpret patho-physiological phenomena. DOPM is being applied in imaging photoplethysmography (iPPG) to extract
PPG signals from a series of 2D matrix images to access blood perfusion and oxygen saturation distributions. A variation
of microvascular circulation could be mapped for an effectively diagnostic screening. The work presents mathematical
modelling based ten layers of ocular tissue tested with four set of controlled parameters demontrated detection ratio
between normal tissue damage or abnormal tissue and significant change of AC signal amplitude in these tissues. The
result shows signicant change of AC signal amplitude in abnormal tissue. The preliminary results show extractable PPG
signals from eye fundus video; experimented at five ROIs: whole fundus, optical disk, main vein vessel, lesion area and
affected area. The outcome shows optical disk region gave a better performance compared to whole fundus region and
main vein vessel. The robustness, miniaturization and artefact reduction capability of DOPM to discriminate oxygenation
levels in retina could offer a new insight to access retinal patho-physiological status.
Spontaneous expression is associated with physiological states, i.e., heart rate, respiration, oxygen saturation (SpO2%),
and heart rate variability (HRV). There have yet not sufficient efforts to explore correlation of physiological change and
spontaneous expression. This study aims to study how spontaneous expression is associated with physiological changes
with an approved protocol or through the videos provided from Denver Intensity of Spontaneous Facial Action Database.
Not like a posed expression, motion artefact in spontaneous expression is one of evitable challenges to be overcome in
the study. To obtain a physiological signs from a region of interest (ROI), a new engineering approach is being
developed with an artefact-reduction method consolidated 3D active appearance model (AAM) based track, affine
transformation based alignment with opto-physiological mode based imaging photoplethysmography. Also, a statistical
association spaces is being used to interpret correlation of spontaneous expressions and physiological states including
their probability densities by means of Gaussian Mixture Model. The present work is revealing a new avenue of study
associations of spontaneous expressions and physiological states with its prospect of applications on physiological and
psychological assessment.
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