Towards health monitoring using remote heart rate measurement using digital camera: A feasibility study.

The paper presents a feasibility study for heart rate measurement using a digital camera to perform health monitoring. The feasibility study investigates the reliability of the state of the art heart rate measuring methods in realistic situations. Therefore, an experiment was designed and carried out on 45 subjects to investigate the effects caused by illumination, motion, skin tone, and distance variance. The experiment was conducted for two main scenarios; human-computer interaction scenario and health monitoring scenario. The human-computer scenario investigated the effects caused by illumination variance, motion variance, and skin tone variance. The health monitoring scenario investigates the feasibility of health monitoring at public spaces (i.e. airports, subways, malls). Five state of the art heart rate measuring methods were re-implemented and tested with the feasibility study database. The results were compared with ground truth to estimate the heart rate measurement error. The heart rate measurement error was analyzed using mean error, standard deviation; root means square error and Pearson correlation coefficient. The findings of this experiment inferred promising results for health monitoring of subjects standing at a distance of 500 cm.

Subcutaneous veins depth measurement using diffuse reflectance images.

Intravenous (IV) procedures are often difficult due to the poor visualization of subcutaneous veins. Because existing vein locators lack the ability to assess depth, and also because mis-punctures and poor vascular access remain problematic, we propose an imaging system that employs diffuse reflectance images at three isosbestic wavelengths to measure both the depth and thickness of subcutaneous veins. This paper describes the proposed system as well as proof-of-principle experimental demonstrations. We initially introduce the working principle and structure of the system. All measurements were based on the Monte Carlo (MC) method and accomplished by referring an optical density (OD) ratio to a multi-layer diffuse reflectance model. Results were all validated by comparative ultrasound measurements. Experimental trials included 11 volunteers who were subjected to both ultrasound measurements and the proposed optical process to validate the system's applicability. However, the unreliability of the "thickness" measurement of the vein may be due to the fact that the veins have collapsible walls - so excess pressure by the transducer will give a false thickness.

Deep learning architectures analysis for age-related macular degeneration segmentation on optical coherence tomography scans.

BACKGROUND AND OBJECTIVES: Aged people usually are more to be diagnosed with retinal diseases in developed countries. Retinal capillaries leakage into the retina swells and causes an acute vision loss, which is called age-related macular degeneration (AMD). The disease can not be adequately diagnosed solely using fundus images as depth information is not available. The variations in retina volume assist in monitoring ophthalmological abnormalities. Therefore, high-fidelity AMD segmentation in optical coherence tomography (OCT) imaging modality has raised the attention of researchers as well as those of the medical doctors. Many methods across the years encompassing machine learning approaches and convolutional neural networks (CNN) strategies have been proposed for object detection and image segmentation. METHODS: In this paper, we analyze four wide-spread deep learning models designed for the segmentation of three retinal fluids outputting dense predictions in the RETOUCH challenge data. We aim to demonstrate how a patch-based approach could push the performance for each method. Besides, we also evaluate the methods using the OPTIMA challenge dataset for generalizing network performance. The analysis is driven into two sections: the comparison between the four approaches and the significance of patching the images. RESULTS: The performance of networks trained on the RETOUCH dataset is higher than human performance. The analysis further generalized the performance of the best network obtained by fine-tuning it and achieved a mean Dice similarity coefficient (DSC) of 0.85. Out of the three types of fluids, intraretinal fluid (IRF) is more recognized, and the highest DSC value of 0.922 is achieved using Spectralis dataset. Additionally, the highest average DSC score is 0.84, which is achieved by PaDeeplabv3+ model using Cirrus dataset. CONCLUSIONS: The proposed method segments the three fluids in the retina with high DSC value. Fine-tuning the networks trained on the RETOUCH dataset makes the network perform better and faster than training from scratch. Enriching the networks with inputting a variety of shapes by extracting patches helped to segment the fluids better than using a full image.

Effect of motion artifact on digital camera based heart rate measurement.

Remote health monitoring is an emerging field in biomedical technology. Digital camera based heart rate measurement method is a recent development which would make remote health monitoring reliable and sustainable in future. This paper presents an investigation on the effect of motion artifact on digital camera-based heart rate measurement. The paper will discuss details on the principles and effects of motion artifacts on photoplethysmography signals. An experiment is conducted using publicly available MAHNOB-HCI database. We have investigated the effects of static scenarios, scenarios involving rigid motion and scenarios involving non-rigid motion. The experiment was tested on state of the art digital camera based heart rate measuring methods. The results showed the effectiveness of the methods and provide a direction to overcome/minimize the effect of motion artifacts for future research.

Novel health monitoring method using an RGB camera.

In this paper we present a novel health monitoring method by estimating the heart rate and respiratory rate using an RGB camera. The heart rate and the respiratory rate are estimated from the photoplethysmography (PPG) and the respiratory motion. The method mainly operates by using the green spectrum of the RGB camera to generate a multivariate PPG signal to perform multivariate de-noising on the video signal to extract the resultant PPG signal. A periodicity based voting scheme (PVS) was used to measure the heart rate and respiratory rate from the estimated PPG signal. We evaluated our proposed method with a state of the art heart rate measuring method for two scenarios using the MAHNOB-HCI database and a self collected naturalistic environment database. The methods were furthermore evaluated for various scenarios at naturalistic environments such as a motion variance session and a skin tone variance session. Our proposed method operated robustly during the experiments and outperformed the state of the art heart rate measuring methods by compensating the effects of the naturalistic environment.

Facial geometry and speech analysis for depression detection.

Depression is one of the most prevalent mental disorders, burdening many people world-wide. A system with the potential of serving as a decision support system is proposed, based on novel features extracted from facial expression geometry and speech, by interpreting non-verbal manifestations of depression. The proposed system has been tested both in gender independent and gender based modes, and with different fusion methods. The algorithms were evaluated for several combinations of parameters and classification schemes, on the dataset provided by the Audio/Visual Emotion Challenge of 2013 and 2014. The proposed framework achieved a precision of 94.8% for detecting persons achieving high scores on a self-report scale of depressive symptomatology. Optimal system performance was obtained using a nearest neighbour classifier on the decision fusion of geometrical features in the gender independent mode, and audio based features in the gender based mode; single visual and audio decisions were combined with the OR binary operation.

Observation of Knudsen effect with microcantilevers.

The Knudsen effect is estimated theoretically and observed experimentally using a U-shaped silicon microcantilever. Though Knudsen forces are extremely small in most cases involving microcantilevers, there exist situations where these forces can be significant and may be important in atomic force microscopy and in microelectromechanical systems (MEMS). The criteria for the presence of Knudsen forces are outlined and an analytical expression in the form of a linear function of the pressure is given for the force in the free molecular regime. The experimental results display peaks in the transitional regime while varying linearly in the molecular regime.

Probing large area surface plasmon interference in thin metal films using photon scanning tunneling microscopy.

The interference of surface plasmons can provide important information regarding the surface features of the hosting thin metal film. We present an investigation of the interference of optically excited surface plasmons in the Kretschmann configuration in the visible spectrum. Large area surface plasmon interference regions are generated at several wavelengths and imaged with the photon scanning tunneling microscope. Furthermore, we discuss the non-retarded dispersion relations for the surface plasmons in the probe-metal system modeled as confocal hyperboloids of revolution in the spheroidal coordinate systems.

Joint probability of shape and image similarities to retrieve 2D TRUS-MR slice correspondence for prostate biopsy.

This paper presents a novel method to identify the 2D axial Magnetic Resonance (MR) slice from a pre-acquired MR prostate volume that closely corresponds to the 2D axial Transrectal Ultrasound (TRUS) slice obtained during prostate biopsy. The method combines both shape and image intensity information. The segmented prostate contours in both the imaging modalities are described by shape-context representations and matched using the Chi-square distance. Normalized mutual information and correlation coefficient between the TRUS and MR slices are computed to find image similarities. Finally, the joint probability values comprising shape and image similarities are used in a rule-based framework to provide the MR slice that closely resembles the TRUS slice acquired during the biopsy procedure. The method is evaluated for 20 patient datasets, of which 18 results match at least one of the two clinical expert choices.

Spectral clustering of shape and probability prior models for automatic prostate segmentation.

Imaging artifacts in Transrectal Ultrasound (TRUS) images and inter-patient variations in prostate shape and size challenge computer-aided automatic or semi-automatic segmentation of the prostate. In this paper, we propose to use multiple mean parametric models derived from principal component analysis (PCA) of shape and posterior probability information to segment the prostate. In contrast to traditional statistical models of shape and intensity priors, we use posterior probability of the prostate region determined from random forest classification to build, initialize and propagate our model. Multiple mean models derived from spectral clustering of combined shape and appearance parameters ensure improvement in segmentation accuracies. The proposed method achieves mean Dice similarity coefficient (DSC) value of 0.96±0.01, with a mean segmentation time of 0.67±0.02 seconds when validated with 46 images from 23 datasets in a leave-one-patient-out validation framework.

Microaneurysm detection with radon transform-based classification on retina images.

The creation of an automatic diabetic retinopathy screening system using retina cameras is currently receiving considerable interest in the medical imaging community. The detection of microaneurysms is a key element in this effort. In this work, we propose a new microaneurysms segmentation technique based on a novel application of the radon transform, which is able to identify these lesions without any previous knowledge of the retina morphological features and with minimal image preprocessing. The algorithm has been evaluated on the Retinopathy Online Challenge public dataset, and its performance compares with the best current techniques. The performance is particularly good at low false positive ratios, which makes it an ideal candidate for diabetic retinopathy screening systems.

Elliptical local vessel density: a fast and robust quality metric for retinal images.

A great effort of the research community is geared towards the creation of an automatic screening system able to promptly detect diabetic retinopathy with the use of fundus cameras. In addition, there are some documented approaches for automatically judging the image quality. We propose a new set of features independent of field of view or resolution to describe the morphology of the patient's vessels. Our initial results suggest that these features can be used to estimate the image quality in a time one order of magnitude shorter than previous techniques.

Environment effects on surface-plasmon spectra in gold-island films potential for sensing applications.

The effects of the local dielectric environment on the surface-plasmon resonances of annealed gold-island films as a potential for sensing applications are studied experimentally and modeled theoretically. Gold-island films were annealed at 600 degrees C to produce spheroidal shape particles that exhibit well-resolved resonances in polarized, angle-resolved, absorption spectra. These resonances are shifted in different amounts by the depolarization effect of the surrounding medium (liquids with various refraction indices). Cross-section calculations based on nonretarded, single-particle, dielectric interaction for these various configurations are presented and are found to be in good agreement with the experimental observations. The results show an interesting potential for biosensing or environmental monitoring applications.

Photon scanning-tunneling microscopy of unstained Mammalian cells and chromosomes.

The photon scanning-tunneling microscope (PSTM) yields optical topographical images of samples that are thin or that are transparent at the wavelength used. A range of sample sizes can be imaged extending to well below the diffraction limit for sufficiently flat samples. But samples of the order of several to many micrometers in size can be analyzed with less-refined resolution if total internal reflection can be made to occur in the sample. We used the PSTM to examine the optical topography of mouse and human cells and of chromosomes that are unstained. Our objectives were to demonstrate the images as an alternative to conventional microscopy and to provide a sample-preparation methodology that will later permit localized, simultaneous fluorescence or absorption spectroscopy with the signals collected by the probe tip. Furthermore, the PSTM's ability to produce optical profiles in air and in water was tested to establish the basis for future investigation of possible abnormalities in the chromosomes. That is, we considered both physical and biological objectives. To this end we utilized the 442-nm line of a He-Cd laser as well as the 633-nm line from a He-Ne laser, the resulting image quality being tested partly to ascertain the increased effects of scattering at the smaller wavelength. It is shown that adequate resolution and signal-to-noise ratio can be obtained with the shorter wavelength even in the presence of intensity fluctuations from the laser, thus showing that fluorescence and absorption studies can be expected to be practicable.