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.

A Novel Optimization Algorithm Leveraging a Three-Dimensional Approach of Periscopic, Pheromonic and Fractal Search.

This paper focuses on a new algorithm for solving optimization problems using the nature of food search behaviour of caterpillars. The paper describes how the periscopic, pheromonic and fractal search properties analogous to the caterpillars, can aid in designing a new optimization algorithm. The performance characteristics of the new method is compared using 26 standard test functions and the area under the curve of the fitness evaluations is used to validate and compare the proposed algorithms against existing related works. The proposed algorithm is found to be efficient when compared with the existing methods. The proposed algorithm is then tested on a real world problem to remove signal noise from eye gaze data, effectively.

A trial study of using DSST to evaluate cognitive impairment in older adults.

Non-invasive means of monitoring mild cognitive impairments (MCI) is recently gaining popularity. With the advent of easy to use physiological sensors, there have been an outburst of studies from the last decade which aim at detecting a target's mental health condition. However, not many studies present the experience or insights gained from carrying out such in-situ research work, particularly when working with older adults. Such insights could not only assist researchers in related areas when designing their study but also avoid potential pitfalls. Clinical trials were conducted by our organization in collaboration with the Geriatric Educational Research Institute, Singapore (GERI) and Singapore Management University (SMU) for detecting mild cognitive impairments in a geriatric population. Digitized versions of the standard pen & paper psychological tests were used along with gaze tracking technologies for MCI detection. Details of our user study and it's outcomes are discussed as well as a generic approach of digitizing any given psychological test battery is highlighted.

Affective response to tunes synthesized with musical pitch curves.

Tunes perceived as happy may help a user reach an affective state of positive valence. However, a user with negative valence may not be ready to listen to such a tune immediately. In this paper, we consider nudging a user from their current affective state to a target affective state in small steps. We propose a technique to generate a gradation of tunes between an initial-reference tune and a target-reference tune, to achieve the affect transition. The two-dimensional gradation is realized in time and in pitch, respectively, by varying the tempo and by the use of musical pitch curves, i.e. pitch transients or simply 'transients'. We exploit the duration and scaling of transients observed in South Indian music (Carnatic) to introduce transients into existing tunes. In our experiment, we have introduced the transients into Western music tunes. The results of perceptual evaluation show that the affective response to transients is likely to be higher at slow tempos than at fast tempos. Further, when felt, transient-tunes are twice as likely to be associated with positive valence than with negative valence, irrespective of tempo.

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.

Evaluating Age-Related Variations of Gaze Behavior for a Novel Digitized-Digit Symbol Substitution Test.

Analysis of cognitive functioning from gaze behavior might serve as an early indicator of age related decline of cognitive functions. Standard psychological tests like the digit-symbol substitution test or the symbol-digit modalities test is used exclusively in this regard. In this paper, we have designed and developed a digitized version of the digit symbol substitution test. Three different versions have been designed in order to derive deeper insights of the user behavior. The test-retest validation of the versions reveals good correlation across sessions. Further, the difference in gaze behavior which might be used as an indicator of cognitive functions is tested for two different age groups (13 participants <30 years and 11 participants >40 years). It is seen that the designed digitized version along with the usage of physiological markers like eye tracking bestows additional information and is sensitive to age related factors which might be used for the assessment as well as for the training purpose in rehabilitation systems. Results show that the performance can be analyzed using gaze and pupillometric features in addition to the conventional test performance metrics. We derived an index to measure the performance related to visuo-spatial functioning on one of the designed versions of the test. Results of this index on the number of fixations for two age groups are found to be separated in a statistically significant (p<0.05) manner. The age related difference (p<0.05) is also evident in the pupillometric responses obtained.

Eye movements - an early marker of cognitive dysfunctions.

Cognitive impairments or dysfunctions are one of the major issues of aging population and medical conditions like brain damage, stroke etc. Assessment of cognitive functioning is usually done by medical practitioners using various standard psychological tests which require expert interventions. In the present study we have tried to use eye tracking as a possible option for assessment of cognitive functions while executing a digitized digit symbol substitution task. The standard task has been modified so that more detail insights of one's cognitive state can be obtained without any manual intervention. Results show that it is possible to get more information like attention, perception etc. It also gives insight about the performance of an individual and can be used for analyzing the executive functions like processing speed, memory etc.

Enhancing the usability of low-cost eye trackers for rehabilitation applications.

Eye tracking is one of the most widely used technique for assessment, screening and human-machine interaction related applications. There are certain issues which limit the usage of eye trackers in practical scenarios, viz., i) need to perform multiple calibrations and ii) presence of inherent noise in the recorded data. To address these issues, we have proposed a protocol for one-time calibration against the "regular" or the "multiple" calibration phases. It is seen that though it is always desirable to perform multiple calibration, the one-time calibration also produces comparable results and might be better for individuals who are not able to perform multiple calibrations. In that case, "One-time calibration" can also be done by a participant and the calibration results are used for the rest of the participants, provided the chin rest and the eye tracker positions are unaltered. The second major issue is the presence of the inherent noise in the raw gaze data, leading to systematic and variable errors. We have proposed a signal processing chain to remove these two types of errors. Two different psychological stimuli-based tasks, namely, recall-recognition test and number gazing task are used as a case study for the same. It is seen that the proposed approach gives satisfactory results even with one-time calibration. The study is also extended to test the effect of long duration task on the performance of the proposed algorithm and the results confirm that the proposed methods work well in such scenarios too.