Ultrasensitive Mesh-Structured Position-Sensitive Detectors Enabling Eye Tracking for Human-Machine Interaction.

This study proposes a simple, affordable and available technology for controlling the computer cursor with only your eyes. The proposed design method was designed and developed for people with significant upper limb disabilities that don’t use a keyboard or a mouse, and has been framed as a standard input method re-defining the notion of input by an eye-re-URL sing interface. Based upon a standard web camera and real-time image processing, the eye tracking system uses the direction of an individual’s facial gaze and blinking detect and translate that into the movement needed for the cursor action. The proposed eye tracking system is lighter and less accessible because it is not dependent upon sophisticated input-device hardware, thus able to obtain reliable cursor movement whenever the lit conditions in the environment are suitable to allow the eye-tracking input system to function smoothly. Based upon early trials, there has been a reported ease-of-use and high responsivity to potential use of a system using assistive technology capabilities. Keywords— Eye tracking ,Cursor control, Webcam interface Blink detection, Physically disabled

Eye tracking has become an essential human–machine interaction modality in virtual reality (VR) and augmented reality (AR) applications requiring high throughput (e.g., more than 240 frames per second), small form factor, and enhanced visual privacy. Existing eye tracking systems have adopted bulky, lens-based cameras, and thus suffer from both a large form factor and high communication cost between the camera and back-end processor. This work presents a camera, algorithm, and accelerator co-designed lensless eye tracking system dubbed EyeCoD, which, to the best of our knowledge, is the first to provide a general, front-end eye tracking solution for AR/VR while satisfying the requirements for both high throughput and smaller form factor. Specifically, EyeCoD integrates system-, algorithm-, and accelerator-level techniques to boost system efficiency without sacrificing eye tracking accuracy. We believe that our EyeCoD system will pave the way for next-generation eye tracking solutions in VR/AR and shed light on future innovations for intelligent imaging systems.

Eye tracking techniques enable high-efficient, natural, and effortless human-machine interaction by detecting users’ eye movements and decoding their attention and intentions. Here, a miniature, imperceptible, and biocompatible smart contact lens is proposed for in situ eye tracking and wireless eye-machine interaction. Employing the frequency encoding strategy, the chip-free and battery-free lens successes in detecting eye movement and closure. Using a time-sequential eye tracking algorithm, the lens has a great angular accuracy of <0.5°, which is even less than the vision range of central fovea. Multiple eye-machine interaction applications, such as eye-drawing, Gluttonous Snake game, web interaction, pan-tilt-zoom camera control, and robot vehicle control, are demonstrated on the eye movement model and in vivo rabbit. Furthermore, comprehensive biocompatibility tests are implemented, demonstrating low cytotoxicity and low eye irritation. Thus, the contact lens is expected to enrich approaches of eye tracking techniques and promote the development of human-machine interaction technology.

This paper describes a flexible method for synchronizing electroencephalography (EEG) and eye tracking (ET) recordings to the presentation of visual stimuli. The method consists of embedding a synchronization signal in the visual stimuli, and recording this signal with both the EEG and ET equipment. The signal is recorded by the EEG device as an additional data channel, and with the camera used in the ET equipment by modulating the global illumination of the scene in time with the synchronizing signal. The prototype system where this method was implemented resulted in a single sample of jitter in both the EEG and ET system, while the ET system achieved a spatial resolution of 1.26 degrees. The system will be used in future work with augmented memory applications.

In recent years, eye tracking systems have greatly improved, beginning to play an important role in the assistive technology field. Eye tracking relates to the capability of some devices to detect and measure eye movements, with the aim to precisely identify the user's gaze direction on a screen. The acquired data can then be exploited to provide commands to the computer. In this paper we present WeyeB, a browsing system which allows the two basic Web surfing operations, namely page scrolling and link selection, to be easily performed without using the hands.

Real-time human eye recognition and tracking systems with human-computer interaction mechanism are being adopted to advance user experience in smart devices and consumer electronic systems. Eye tracking systems measure eye gaze and pupil response non-intrusively. This paper presents an analysis of pupil response to video structure and content. A consumer device that can assess user response to a video can provide better experiences with approaches such as real-time content adaptation. The first set of experiments involved presenting different video content to subjects and measuring eye response with an eye tracker. Results show that pupil constrictions and magnitude of constrictions vary with content. Significant changes in video and scene cuts led to sharp constrictions. User response to videos can provide insights that can improve subjective quality assessment metrics. This paper also presents an analysis of the pupillary response to quality changes in videos with the second set of experiments. The results of the tests show pupil constrictions for noticeable changes in perceived quality. Using real-time eye tracking systems for video analysis and quality evaluation can open a new class of applications for consumer electronic systems.

Investigating the relationship between eye movements and situation awareness in weather forecasting

The advancement of eye tracking technology, including improved portability, usability, and affordability, has facilitated the transition of eye trackers from controlled laboratory settings to diverse real-world environments. One significant challenge in these real-world settings is the wide variation in illumination levels, potentially affecting eye tracking accuracy. Despite anecdotal evidence suggesting the sensitivity of head-mounted eye trackers to environmental light conditions, systematic research on this topic has been limited. This study introduces a standardized protocol for investigating the influence of lighting conditions on the accuracy of head-mounted eye trackers. We examined the performance of SMI Eye Tracking Glasses 2 Wireless under three distinct illumination levels: Low (Dark), Moderate (Normal), and High (Bright). Our experiment involved 9 participants performing accuracy tests under each lighting condition. We measured gaze accuracy while varying the illumination level during both the calibration and data recording phases. Results indicate that eye tracking accuracy is affected by the illumination level used during data collection. Best accuracy was achieved when data recording was performed under the same illumination level as the calibration. Notably, calibration under moderate illumination led to the most consistent performance across all lighting conditions. These findings provide valuable insights for researchers and practitioners using head-mounted eye trackers in varying lighting environments. The standardized protocol presented can be applied to evaluate other eye tracking systems, contributing to developing more robust mobile eye tracking techniques. Future research should investigate the generalizability of these results across different eye tracking technologies and explore potential software solutions to mitigate illumination-related accuracy issues.

Entrainment is a natural inclination of people who interact with each other to develop similar, matching, or synchronized forms of behavior. In spoken interactions, this was observed at many linguistic (syntactic structures, referring expressions, dialectal features) and para-linguistic (intensity, speech rate) levels. Numerous studies have shown that the degree of spoken entrainment correlates with several social conversational attributes such as task success, likability, attractiveness, power distribution, and others. This feature of human-human interactions promises great potential for improving the naturalness and social acceptability of voice applications in human-machine interactions. However, despite many findings of various forms of entrainment in various languages and cultures, there is very little work on analyzing the effect of language or culture on speech entrainment in comparable spoken corpora. This is a significant gap since many applications utilizing spoken interaction and entrainment will be deployed to be used by native and non-native speakers of many cultures and languages. A welcome exception filling this gap is a recent paper by Xia et al. (2014) comparing entrainment in Standard American English and Mandarin Chinese. In this paper we provide a first analysis of speech entrainment in Slovak based on comparable corpus to the ones analyzed in Xia et al. This work contributes to our understanding and future modeling of cross-cultural aspects of behavioral entrainment.

In recent years, extensive research has been conducted on the development of high-performance flexible tactile sensors, pursuing the next generation of highly intelligent electronics with diverse potential applications in self-powered wearable sensors, human-machine interactions, electronic skin, and soft robotics. Among the most promising materials that have emerged in this context are functional polymer composites (FPCs), which exhibit exceptional mechanical and electrical properties, enabling them to be excellent candidates for tactile sensors. Herein, this review provides a comprehensive overview of recent advances in FPCs-based tactile sensors, including the fundamental principle, the necessary property parameter, the unique device structure, and the fabrication process of different types of tactile sensors. Examples of FPCs are elaborated with a focus on miniaturization, self-healing, self-cleaning, integration, biodegradation, and neural control. Furthermore, the applications of FPC-based tactile sensors in tactile perception, human-machine interaction, and healthcare are further described. Finally, the existing limitations and technical challenges for FPCs-based tactile sensors are briefly discussed, offering potential avenues for the development of electronic products.

A biocompatible triboelectric nanogenerator-based edible electronic skin for morse code transmitters and smart healthcare applications

3D hybrid porous Mxene-sponge network and its application in piezoresistive sensor

Electronic skins (e‐skins) are a promising design paradigm for health care systems and human–machine interactions. Piezoresistive sensors made with simple structures, high sensitivity, mass production methods, light weight, and comfort for long‐term wearing and physiological signal monitoring remain a challenge and are urgently desirable. Here, a breathable and lightweight all‐nanofiber piezoresistive (ANFP) sensor is presented, which is composed of three layers of electrospun nanofibers (NFs). A specific interpenetrating network of conductive polyvinylpyrrolidone NFs coated by polypyrrole (PVP@PPy) and insulating polyacrylonitrile NFs is constructed by controlling the vapor growth position of PPy to enhance the sensitivity. The ANFP sensor can achieve the real‐time monitoring of multiple parts of physiological signals, and a wireless detection system is designed for the online monitoring of human pulses. The NF network endows excellent breathability and heat dissipation to the ANFP sensors during practical application, which ensures comfort and device stability during long‐term wearing. Finally, a pressure sensing array with 5 × 5 pixels is fabricated to demonstrate the potential applications in spatial pressure detection. This work provides a viable strategy to improve the wearability of e‐skins, which can promote health care and human–machine interaction applications.

A system for stabilising and monitoring eye movements for linac-based stereotactic radiotherapy associated with the mobile eye, the Eye Tracker, was developed. Whilst the Eye Tracker design is based on a previously reported system, the purpose of this study was to confirm that the modified version can be used with clinically acceptable treatment margins. We report the estimates of the margin required to account for inter- and intra-fraction eye motion based on data from 12 consecutive patients treated with the Eye Tracker system in place. Patients were immobilised in a head and neck mask and were required to fixate on a light source. A camera system monitored eye movements relative to CT simulation baseline measurements. The Exactrac system (Brainlab, Feldkirchen, Germany) combined with the Varian TrueBeamSTx (Varian Medical Systems, Palo Alto, CA) confirmed pre- and intra-treatment setup of the head position. Displacement/rotation of the image of the pupil/iris was determined in the lateral and superior-inferior directions using a video display. A standard margin equation was applied to estimate the margin required to account for inter- and intra-fraction eye movement. The average displacement in both directions was 0.1-0.2mm (0.36mm SD). All patients maintained a position within 1mm of the intended position during treatment. Based on a Bayesian estimation of the systematic and treatment errors, accounting for displacements in two-planes and a standard deviation of the penumbral width of 1.3mm, the estimated margins to achieve coverage of the GTV with the 95% isodose in 90% of patients was found to be less than 1mm. Small random and systematic uncertainties due to inter- and intra-fraction movement of the eye were achieved with the Eye Tracker. Whilst the estimated margins are small (<1mm) they need to be considered in addition to contouring and treatment delivery uncertainties.

The process of eye tracking has been subject of intensive research during the last years. The main aim consists in the determination of the point of gaze or the eye movement relative to the head. In this work, we use a static video camera to realize the tracking of the eyes movement mainly due to its important features such as low cost, fully automated and easy application. The proposed approach encompasses a solution to the problems of eye detection and eye tracking. Our eye detection method employs a set of cascaded Haar classifiers that enable the fast recognition of eye regions in a real-time sequence of images. On the other hand, the eye tracking method uses particle filtering that is robust in clutter environments and allows the fusion of sensor data as well as the tracking of nonlinear systems. The results demonstrate that the eye tracking system is capable of robustly track the eyes under variable light conditions and under several different face orientations.