Head-worn Devices Research Articles

Cognitive load in tele-robotic surgery: a comparison of eye tracker designs.

Eye gaze tracking and pupillometry are evolving areas within the field of tele-robotic surgery, particularly in the context of estimating cognitive load (CL). However, this is a recent field, and current solutions for gaze and pupil tracking in robotic surgery require assessment. Considering the necessity of stable pupillometry signals for reliable cognitive load estimation, we compare the accuracy of three eye trackers, including head and console-mounted designs. We conducted a user study with the da Vinci Research Kit (dVRK), to compare the three designs. We collected eye tracking and dVRK video data while participants observed nine markers distributed over the dVRK screen. We compute and analyze pupil detection stability and gaze prediction accuracy for the three designs. Head-worn devices present better stability and accuracy of gaze prediction and pupil detection compared to console-mounted systems. Tracking stability along the field of view varies between trackers, with gaze predictions detected at invalid zones of the image with high confidence. While head-worn solutions show benefits in confidence and stability, our results demonstrate the need to improve eye tacker performance regarding pupil detection, stability, and gaze accuracy in tele-robotic scenarios.

Wearable Sensors for Learning Enhancement in Higher Education.

Wearable sensors have traditionally been used to measure and monitor vital human signs for well-being and healthcare applications. However, there is a growing interest in using and deploying these technologies to facilitate teaching and learning, particularly in a higher education environment. The aim of this paper is therefore to systematically review the range of wearable devices that have been used for enhancing the teaching and delivery of engineering curricula in higher education. Moreover, we compare the advantages and disadvantages of these devices according to the location in which they are worn on the human body. According to our survey, wearable devices for enhanced learning have mainly been worn on the head (e.g., eyeglasses), wrist (e.g., watches) and chest (e.g., electrocardiogram patch). In fact, among those locations, head-worn devices enable better student engagement with the learning materials, improved student attention as well as higher spatial and visual awareness. We identify the research questions and discuss the research inclusion and exclusion criteria to present the challenges faced by researchers in implementing learning technologies for enhanced engineering education. Furthermore, we provide recommendations on using wearable devices to improve the teaching and learning of engineering courses in higher education.

Predicting Perceptual Transparency of Head-Worn Devices

Predicting Perceptual Transparency of Head-Worn Devices

Mobile Health With Head-Worn Devices: Challenges and Opportunities

Monitoring human behavior and health status using mobile devices, a.k.a. Mobile Health, has gained increasing attention from both academia and industry in recent years. It allows imperceptible health tracking from the users and remote health management from the healthcare service providers. Head-worn devices, such as earbuds, glasses, and brain–computer interfaces, exhibit great potential for mobile health due to their advantageous wearing position, the human head, which is motion-resilient and full of human biosignals. Although initial attempts have been conducted for different healthcare applications with head-worn devices, this fast-growing area is still underexplored and retains great promises. With this work, we investigate the most pressing challenges to fully exploit the potential of head-worn devices for mobile health, from the perspective of sensing, computing, and system design. Our exploration reveals key guidelines and lessons to inform future efforts in this space.

XTAL VR System Use in a Novel AAM Research Cockpit

The Flight Simulation Facilities (FSF) at the National Aeronautics and Space Administration's (NASA) Langley Research Center (LaRC) provide high-fidelity, man-in-the-loop (MITL) and hardware-in-the-loop (HITL) simulation services to a number of research customers including NASA, academia, aviation industry partners, and other government agencies such as the Federal Aviation Administration (FAA) and the National Transportation Safety Board (NTSB). The Simulation Development and Analysis Branch (SDAB) management has determined that future research related to the emerging Advanced Air Mobility (AAM) sector will require a new type of simulator with a vastly different cockpit layout and field of view requirements for the out-the-window visual systems than any of the current cockpits. This new simulator might also benefit from integrated head-mounted displays (HMD). For these reasons, SDAB has decided to design and build a new cockpit that will meet the future AAM electric Vertical Take-Off and Landing (eVTOL) simulator needs. In this paper, the authors discuss the novel use of state-of-the-art head worn devices (HWD) to present augmented reality (AR) and virtual reality (VR) environments to researchers to improve the quality of the cockpit design and reduce the time-to-market and cost to obtain the new cockpit.

Auditory model-based estimation of the effect of head-worn devices on frontal horizontal localisation

Auditory localisation accuracy may be degraded when a head-worn device (HWD), such as a helmet or hearing protector, is used. A computational method is proposed in this study for estimating how horizontal plane localisation is impaired by a HWD through distortions of interaural cues. Head-related impulse responses (HRIRs) of different HWDs were measured with a KEMAR and a binaural auditory model was used to compute interaural cues from HRIR-convolved noise bursts. A shallow neural network (NN) was trained with data from a subjective listening experiment, where horizontal plane localisation was assessed while wearing different HWDs. Interaural cues were used as features to estimate perceived direction and position uncertainty (standard deviation) of a sound source in the horizontal plane with the NN. The NN predicted the position uncertainty of localisation among subjects for a given HWD with an average estimation error of 1°. The obtained results suggest that it is possible to predict the degradation of localisation ability for specific HWDs in the frontal horizontal plane using the method.

Head Trajectory Diagrams for Gait Symmetry Analysis Using a Single Head-Worn IMU.

Gait symmetry analysis plays an important role in the diagnosis and rehabilitation of pathological gait. Recently, wearable devices have also been developed for simple gait analysis solutions. However, measurement in clinical settings can differ from gait in daily life, and simple wearable devices are restricted to a few parameters, providing one-sided trajectories of one arm or leg. Therefore, head-worn devices with sensors (e.g., earbuds) should be considered to analyze gait symmetry because the head sways towards the left and right side depending on steps. This paper proposed new visualization methods using head-worn sensors, able to facilitate gait symmetry analysis outside as well as inside. Data were collected with an inertial measurement unit (IMU) based motion capture system when twelve participants walked on the 400-m running track. From head trajectories on the transverse and frontal plane, three types of diagrams were displayed, and five concepts of parameters were measured for gait symmetry analysis. The mean absolute percentage error (MAPE) of step counting was lower than 0.65%, representing the reliability of measured parameters. The methods enable also left-right step recognition (MAPE ≤ 2.13%). This study can support maintenance and relearning of a balanced healthy gait in various areas with simple and easy-to-use devices.

Cross-Validated Locally Polynomial Modeling for 2-D/3-D Gaze Tracking With Head-Worn Devices

In the context of wearable gaze tracking techniques, the problems of two-dimensional (2-D) and three-dimensional (3-D) gaze estimation can be viewed as inferring 2-D epipolar lines and 3-D visual axes from eye monitoring cameras. To this end, in this article, a simple local polynomial model is proposed to back-project a pupil center onto its corresponding visual axis. Based on this approximation, a homographylike relation is derived in a local manner, and via the Leave-One-Out cross-validation criterion, training gaze samples at one certain depth is leveraged to partition entire input space into multiple overlapping subregions. Then, the gaze data at another depth are utilized to recover the epipolar point, i.e., the image eyeball center. Thus, given a pupil image, the corresponding epipolar line can be determined by the resolved homographylike mapping and the epipolar point. By using the same partition structure, 3-D gaze prediction model can be inferred by solving a nonlinear optimization problem, which aims to minimize the angular disparities between training visual directions and prediction ones. Meanwhile, it is necessary to form a good starting point and suitable constraints for the optimization problem. Otherwise, it may end up with trivial solutions, i.e., faraway eye positions. To facilitate the practical implementation of our proposed method, we also analyze how the spatial distribution of calibration points impacts the model learning accuracy. The experiment results justify the effectiveness of our proposed gaze estimation method for both the normal vision and eyewear users.

Comparison of localization assessments for hearing protection

Sound localization is a critical component of the assessment of situational awareness for hearing protection devices (HPDs). A new standard is being developed for the assessment of sound localization in the horizontal-plane concerning head-worn devices. One of the methodologies offered by this standard is a quick and easy-to-use paradigm for rapid prototyping of hearing devices. This study compared the results of this new assessment methodology with a more traditional assessment of horizontal-plane sound localization. Four devices (including open-ear) were tested on normal-hearing individuals using both paradigms. A comparison of localization errors, front-back-reversals, hardware for data collection set-ups, and expected data collection time is presented. Results suggest comparable differences between the two methodologies.

Sound localization performance of sample hearing protectors using standardized measurement methods

Sound localization is an important aspect in the performance of many tasks. These tasks frequently require the use of hearing protection to mitigate the potentially adverse effects of noise exposure. ANSI/ASA working group S3/WG94 has described four standard methods for measuring the effect of head-worn devices on sound localization. Data using three different hearing protectors and open ear and using three of the four methods described will be presented. The analysis techniques used for each of the three methods will be described in detail including the removal of front-back reversals and assessment of fine resolution location discrimination. The performance of the three hearing protectors and the open ear condition will be compared and contrasted. Data will be presented on proportion of localization discrimination and front/back reversals using Method 1 as well as localization error performance using Methods 2, and visual target acquisition and response time using Method 3. The performance will also be compared across the three methods. The results show that the measurement methods described are viable for the assessment of the effects of HPDs on performance associated with localization.

Standard methods to measure the effects of head-worn devices on sound localization

Four standard methods for measuring the effect of head-worn devices on sound localization in the horizontal plane have been developed by the working group S3/WG94. The objective was to establish methods that enable accurate, repeatable, and reliable measurement of sound localization performance for human listeners. The standard describes four measurement methods: (1) a low complexity, coarser method to estimate the proportion of location discrimination and front/back reversal errors using 8 loudspeakers; (2) a more complex, more robust method to measure localization error using 36 loudspeakers and a fine resolution response method; (3) a method to measure the functional impact of localization with degraded cues using 36 loudspeakers and an aurally guided visual search task; and (4) a method using 180 loudspeakers to precisely measure localization acuity. The methods will be described in detail.

The effects of head-worn attire on measured head-related transfer functions

In this paper, we investigate measured changes in spatial perception presented by hats and other head-worn equipment. Particularly, helmets worn in sports, military and civil services (firefighters, police etc.) can affect spatial awareness and localization of wearers, possibly putting the wearer and others in danger. For this paper, a variety of hats were placed on a Head And Torso Simulator (HATS). The Head Related Transfer Function (HRTF) was measured in an anechoic chamber at a variety of angles around the HATS. The data will be analyzed to show the differences between various head-worn devices.

Text Readability in Head-Worn Displays: Color and Style Optimization in Video versus Optical See-Through Devices

Efficient text visualization in head-worn augmented reality (AR) displays is critical because it is sensitive to display technology, text style and color, ambient illumination and so on. The main problem for the developer is to know the optimal text style for the specific display and for applications where color coding must be strictly followed because it is regulated by laws or internal practices. In this work, we experimented the effects on readability of two head-worn devices (optical and video see-through), two backgrounds (light and dark), five colors (white, black, red, green, and blue), and two text styles (plain text and billboarded text). Font type and size were kept constant. We measured the performance of 15 subjects by collecting about 5,000 measurements using a specific test application and followed by qualitative interviews. Readability turned out to be quicker on the optical see-through device. For the video see-through device, background affects readability only in case of text without billboard. Finally, our tests suggest that a good combination for indoor augmented reality applications, regardless of device and background, could be white text and blue billboard, while a mandatory color should be displayed as billboard with a white text message.