Quantification of Active Visual Attention using RGB camera.

Active visual attention (AVA) is the cognitive ability that helps to focus on important visual information while responding to a stimulus and is important for human-behavior and psychophysiological research. Existing eye-trackers/camera-based methods are either expensive or impose privacy issues as face videos are recorded for analysis. Proposed approach using blink-rate variability (BRV), is inexpensive, easy to implement, efficient and handles privacy issues, making it amenable to real-time applications. Our solution uses laptop camera/webcams and a single blink feature, namely BRV. First, we estimated participant's head pose to check camera alignment and detect if he is looking at the screen. Next, subject-specific threshold is computed using eye aspect ratio (EAR) to detect blinks from which BRV signal is constructed. Only EAR values are saved, and participant's face video is NOT saved or transmitted. Finally, a novel AVA score is computed. Results shows that the proposed score is robust across participants, ambient light conditions and occlusions like spectacles.

Design of a Realtime Photoplethysmogram Signal Quality Checker for Wearables and Edge Computing.

Photoplethysmogram (PPG) signal is extensively used for deducing health parameters of patients in order to infer about physiological conditions of heart, blood pressure, respiratory patterns, and so on. Such analysis and estimations can be done accurately only on high quality PPG signals with very minimal artifacts. PPG signals collected from fitness grade and smart phone scenarios are prone to muscle artifacts and hence there is a need to assess the signal quality before using the signal. Although there are approaches available in the realm of machine learning and deep learning, they are computationally expensive and may not be suitable for a wearable or edge computing scenario. In this paper, we propose the design of a quality checker to check the quality of the signal that can be directly implemented on edge devices like smartwatch. The algorithm is tested on PPG data collected from wearable, ICU and medical grade devices. In the wearable scenario where the noise levels are very high, our algorithm has performed significantly better with a Fscore of over 0.92. Further we show that by applying the proposed quality checker, the accuracy of the computed heart rate from a smart phone PPG-application significantly improves.

Cost Effective Real-time System for cognitive computing using Personalized Eye Blink Detection from Camera.

Eye blink is indicative of various mental states. Generally, vision based approaches are used for detecting eye blinks. However, performance of such approaches varies across participants. Standard eye tracker or eye glasses used for detecting blinks, are very costly. Here, we are proposing a personalized vision based eye blink detector system. Proposed approach is ubiquitous and unobtrusive in nature and can be implemented using standard webcams/mobile camera, making it deployable for real world scenarios. Our approach has been validated on a set of data collected from our lab and on an open data set. Results show that in both cases, our system performs well for various conditions like natural/artificial light, with or without spectacles. We achieved a Fscore of 0.98 for own collected data and 0.91 for open dataset, which outperform state of the art approaches.

Mechanics of a granular skin.

Magic sand, a hydrophobic toy granular material, is widely used in popular science instructions because of its nonintuitive mechanical properties. A detailed study of the failure of an underwater column of magic sand shows that these properties can be traced to a single phenomenon: the system self-generates a cohesive skin that encapsulates the material inside. The skin, consisting of pinned air-water-grain interfaces, shows multiscale mechanical properties: they range from contact-line dynamics in the intragrain roughness scale, to plastic flow at the grain scale, all the way to sample-scale mechanical responses. With decreasing rigidity of the skin, the failure mode transforms from brittle to ductile (both of which are collective in nature) to a complete disintegration at the single-grain scale.

Graph theoretical analysis on the kinetic rate equations of linear chain and cyclic reaction networks.

Graph theoretical solutions for kinetic rate equations of some reaction networks involving linear chains and cycles have been derived; condensation polymerization and long chain of radioactive decay come under the purview of the former whereas the interconversion of the species in cycles under the later. The reactions for the linear chains considered here proceed monotonically to the steady states with time whereas the cycle with all irreversible steps has been found to have either periodic or monotonic time evaluation of concentrations depending on the values of rate constants of the involved paths. In case of a cyclic reaction having all reversible paths, the condition for the microscopic reversibility has been derived on the basis of the assumption that the decay constants obtained for this case are all real.

Graph theoretical solutions for the coupled kinetic rate equations.

A graph theoretical procedure for solving multistep coupled kinetic rate equations and thereby obtaining the concentrations of the species involved in the reaction has been developed. The method so developed has been illustrated with some well-known reaction schemes.