Assessing blood vessel perfusion and vital signs through retinal imaging photoplethysmography

One solution to the global challenge of increasing ocular disease is a cost-effective technique for rapid screening and assessment. Current ophthalmic imaging techniques, e.g. scanning and ocular blood flow systems, are expensive, complex to operate and utilize invasive contrast agents during assessment. The work presented here demonstrates a simple retinal imaging photoplethysmography (iPPG) system with the potential to provide screening, diagnosis, monitoring and assessment that is non-invasive, painless and radiationless. Time series of individual retinal blood vessel images, captured with an eye fundus camera, are processed using standard filtering, amplitude demodulation and principle component analysis (PCA) methods to determine the values of the heart rate (HR) and respiration rate (RR), which are in compliance with simultaneously obtained measurements using commercial pulse oximetry. It also seems possible that some information on the dynamic changes in oxygen saturation levels (SpO2) in a retinal blood vessel may also be obtained. As a consequence, the retinal iPPG modality system demonstrates a potential avenue for rapid ophthalmic screening, and even early diagnosis, against ocular disease without the need for fluorescent or contrast agents

A study of the dynamic relation between physiological changes and spontaneous expressions

Recent progress in Affective Computing (AC) has enabled integration of physiological cues and spontaneous expressions to reveal a subject’s emotional state. Due to the lack of an effective technique for evaluating multimodal correlations, experience and intuition play a main role in present AC studies when fusing affective cues or modalities, resulting in unexpected outcomes. This study seeks to demonstrate a dynamic correlation between two such affective cues, physiological changes and spontaneous expressions, which were obtained by a combination of stereo vision based tracking and imaging photoplethysmography (iPPG), with a designed protocol involving 20 healthy subjects. The two cues obtained were sampled into a Statistical Association Space (SAS) to evaluate their dynamic correlation. It is found that the probability densities in the SAS increase as the peaks in two cues are approached. Also the complex form of the high probability density region in the SAS suggests a nonlinear correlation between two cues. Finally the cumulative distribution on the zero time-difference surface is found to be small (<0.047) demonstrating a lack of simultaneity. These results show that the two cues have a close interrelation, that is both asynchronous and nonlinear, in which a peak of one cue heralds a peak in the other

Smart garment fabrics to enable non-contact opto-physiological monitoring

Imaging photoplethysmography (iPPG) is an emerging technology used to assess microcirculation and cardiovascular signs by collecting backscattered light from illuminated tissue using optical imaging sensors. The aim of this study was to study how effective smart garment fabrics could be capturing physiological signs in a non-contact mode. The present work demonstrates a feasible approach of, instead of using conventional high-power illumination sources, integrating a grid of surface-mounted light emitting diodes (LEDs) into cotton fabric to spotlight the region of interest (ROI). The green and the red LEDs (525 and 660 nm) placed on a small cotton substrate were used to locally illuminate palm skin in a dual-wavelength iPPG setup, where the backscattered light is transmitted to a remote image sensor through the garment fabric. The results show that the illuminations from both wavelength LEDs can be used to extract heart rate (HR) reaching an accuracy of 90% compared to a contact PPG probe. Stretching the fabric over the skin surface alters the morphology of iPPG signals, demonstrating a significantly higher pulsatile amplitude in both channels of green and red illuminations. The skin compression by the fabric could be potentially utilised to enhance the penetration of illumination into cutaneous microvascular beds. The outcome could lead a new avenue of non-contact opto-physiological monitoring and assessment with functional garment fabrics

A dynamic opto-physiological model to effectively interpret retinal microvascular circulation

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

A new engineering approach to reveal correlation of physiological change and spontaneous expression from video images

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