In the last decade researchers have increasingly considered eye tracking of the operators of cars and airplanes as a means to address human error and evaluate operational effectiveness. This article presents a systematic survey of recently published papers about this approach in service to the question as to whether eye tracking can be used to address operational safety in marine operations. The surveyed

Brain-controlled wheelchairs (BCWs) are a promising solution for people with severe motor disabilities, who cannot use conventional interfaces. However, the low reliability of electroencephalographic signal decoding and the high user's workload imposed by continuous control of a wheelchair requires effective approaches. In this article, we propose a self-paced P300-based brain–computer interface (BCI)

With the majority of brain–computer interface (BCI) research currently restricted to the controlled settings in labs, there is a growing interest to study the feasibility of BCI applications in the real world. This interest is largely driven by the availability of ergonomic electroencephalography (EEG) recording devices. In this article, we investigate the feasibility of applying a commercial EEG device

The cooperation between robots and astronauts will become a core element of future space missions. This is accompanied by the demand for suitable input devices. An interface based on electromyography (EMG) represents a small, light, and wearable device to generate a continuous three-dimensional (3D) control signal from voluntarily muscle activation of the operator's arm. We analyzed the influence of

We present results from an experiment in which 55 human subjects interact with a dynamic system 40 times over a one-week period. The subjects are divided into five groups. For each interaction, a subject performs a command-following task, where the reference command is the same for all subjects and all trials; however, each group interacts with a different linear time-invariant dynamic system. We use

Recent studies have shown that gestures are useful indicators of understanding, learning, and memory retention. However, and specially in collaborative settings, current metrics that estimate task understanding often neglect the information expressed through gestures. This work introduces the physical instruction assimilation (PIA) metric, a novel approach to estimate task understanding by analyzing

Finger microgestures have been widely used in human computer interaction (HCI), particularly for interactive applications, such as virtual reality (VR) and augmented reality (AR) technologies, to provide immersive experience. However, traditional 2D image-based microgesture recognition suffers from low accuracy due to the limitations of 2D imaging sensors, which have no depth information. In this article

In this article, we demonstrate the ability to recognize hand gestures in a noncontact wireless fashion using only incoherent light signals reflected from a human subject. Fundamentally distinguished from radar, lidar, and camera-based sensing systems, this sensing modality uses only a low-cost light source (e.g., LED) and a sensor (e.g., photodetector). The lightwave-based gesture recognition system

Sensor-based human activity recognition (HAR) aims to recognize a human's physical actions by using sensors attached to different body parts. As a user-specific application, HAR often suffers poor generalization from training on an individual to testing on another individual, or from one body part to another body part. To tackle this cross-domain HAR problem, this article proposes a domain adaptation

Objective: This study creates linear and generalized additive models (GAMs) of video-recorded two-dimensional hand motion (synonymously referred to as hand movements or hand kinematics) to predict expert-rated performance along a series of surgical motion scales. Background : Surgical performance assessments are costly and time consuming. Automatically quantifying hand motion may offload some burden

Gesture recognition is key to enabling natural human–computer interactions. Existing approaches based on wireless sensing focus on accurate identification of arm gesture types. It remains a challenge to recognize and profile the details of arm gestures for precise interaction control. In addition, current approaches have strict positioning requirements between radars and users, making them difficult

This article investigates the use of acoustic signals recorded at the human wrist for hand gesture recognition. The prototype consists of 40 microphones to be worn at the wrist. The gesture recognition performance is evaluated through the identification of 36 gestures in American sign language (ASL), including 26 ASL alphabetical characters and 10 ASL numbers. The optimal area for sensor band placement

Decoding the subjective perception of task difficulty may help improve operator performance, i.e., automatically optimize the task difficulty level. Here, we aim to decode a compound of cognitive states that covaries with the task difficulty level. We designed a protocol composed of two different subtasks, flying and visual recognition, to induce different difficulty levels. We first showed that e

Traditional 3D gaze estimation methods are usually based on the models of pupil refraction and corneal reflection. These methods typically rely on multiple light sources. The 3D gaze can be estimated using single-camera-single-light-source systems only when certain user-dependent eye parameters are available a priori , which is rarely the case. This article proposes a 3D gaze estimation method which

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The last decade has shown an increasing interest on advanced driver assistance systems (ADAS) based on shared control, where automation is continuously supporting the driver at the control level with an adaptive authority. A first look at the literature offers two main research directions: 1) an ongoing effort to advance the theoretical comprehension of shared control, and 2) a diversity of automotive

Blindness prevents a person from gaining knowledge of the surrounding environment and makes unassisted navigation, object recognition, obstacle avoidance, and reading tasks a major challenge. In this work, we propose a novel visual aid system for the completely blind. Because of its low cost, compact size, and ease-of-integration, Raspberry Pi 3 Model B+ has been used to demonstrate the functionality

Road accidents and safe driving are one of the main concerns of transportation systems and the companies that explore different solutions to reduce the accident rate. The most interesting option to achieve this goal is through an on-board training of professional drivers to apply safe driving techniques during their work activity. The purpose of this study is to analyze a monitoring system that is

Mobility of teleoperated unmanned ground vehicles can be significantly compromised under large communication delays, if the delays are not compensated. This article considers a recently developed delay compensation theory and presents its first empirical evaluation in improving mobility and drivability of a high-speed teleoperated vehicle under large delays. The said delay compensation theory is a

Conflict is one of the important factors affecting user satisfaction and trust in smart environments, yet conflict modeling in mixed initiative smart environments has not been sufficiently explored. Most of the existing literature on conflict in smart homes are centered on conflicts between users. Although research has shown that about 75% of conflicts are between users and system [1] , only a few

Biomechanical measures are the gold standard in the assessment of gait in healthy and chronic disease populations. Augmented reality (AR) systems represent an opportunity to evaluate human movement under more realistic and interactive conditions. A barrier to integrating AR into healthcare is the unknown accuracy of systems in the quantification of human movement. This project aimed to determine the

To learn motor skills using a finger in many haptic training systems, a user places his or her finger in a holder to communicate with a haptic interface. It is known that the force-detection capability at the fingertip is reduced when the user's finger is enclosed in a holder. The learning performance might therefore be impaired in training. Stochastic resonance is known to improve sensitivity at the

A brain–computer interface (BCI) is a common device for communication between the human brain and a computer. This article investigates the efficiency of using a 3-D interface for BCI machines. For this purpose, the P300 speller, which is a BCI device that enables the user to spell characters on a screen using brain waves, is modified. The classical virtual keyboard of the P300 speller is replaced

Bimanual coordination is critical in many robotic and haptic systems, such as surgical robots and rehabilitation robots. While these systems often incorporate two robotic manipulators for each limb, there may be a missed opportunity to leverage overarching models of human bimanual coordination to improve the way in which the robotic manipulators are controlled and respond to the dynamic human operator

In hospitals, clinicians are presented with varied and disorganized alarm sounds from disparate devices. While there has been attention to reducing inactionable alarms to address alarm overload, little effort has been focused on organizing, simplifying, or improving the informativeness of alarms. In this article, we sought to elicit nurses' tacit interpretation of alarm events to create an organizational

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The goal for a virtual reality (VR) training system is to enable trainees to acquire all the knowledge they need to perform effectively in a real environment. Such a system should provide an experience so authentic that no further real-world training is necessary, meaning that it is sufficient to train in VR. We evaluate the impact of a haptic thermal stimulus, which is of paramount importance to decision

In this article, a new type-2 fuzzy-based modeling approach is proposed to assess human operators’ psychophysiological states for both safety and reliability of human–machine interface systems. Such a new modeling technique combines type-2 fuzzy sets with state tracking to update the rule base through a Bayesian process. These new configurations successfully lead to an adaptive, robust, and transparent

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Eye-tracking-based human fatigue detection at traffic control centers suffers from an unavoidable problem of low-quality eye-tracking data caused by noisy and missing gaze points. In this article, the authors conducted pioneering work by investigating the effects of data quality on eye-tracking-based fatigue indicators and by proposing a hierarchical-based interpolation approach to extract the eye-tracking-based

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Sight is an important sensory input for humans to navigate their surrounding environment independently. Tasks that are simple for the sighted are often difficult for a visually impaired person. Throughout the years, many researchers dedicated their time and efforts to design and implement technologies and devices that can help a visually impaired person to navigate in unknown areas independently. An

In this work, a computational method is proposed to automatically investigate the perception of the origin of full-body human movement and its propagation. The method is based on a mathematical game built over a suitably defined graph structure representing the human body. The players of this game are the graph vertices, which form a subset of body joints. Since each vertex contributes to a shared

To improve the space–time similarity and motion smoothness of facial expression imitation (FEI), a real-time FEI method for a humanoid robot is proposed based on smooth-constraint reversed mechanical model (SRMM) by combining a sequence-to-sequence deep learning model and a motion-smoothing constraint. First, on the basis of facial data from a Kinect capture device, a facial feature vector is characterized

Although a wearable assist robot helps to enhance the gait ability of the wearer, it can cause gait instability in an emergency. A collision with an environmental object is one source of such instability. Insufficient adaptation to change by the physical frame, and restriction of joint motion, increases the risk of collision and fall of the wearer owing to the robot. In this article, the reaction motion

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Computer cursor control using electroencephalogram (EEG) signals is a common and well-studied brain-computer interface (BCI). The emphasis of the literature has been primarily on evaluation of the objective measures of assistive BCIs such as accuracy of the neural decoder whereas the subjective measures such as user's satisfaction play an essential role for the overall success of a BCI. As far as we

Emerging technology for brain-state monitoring offers the possibility to conduct measurements outside the laboratory. However, user-experience research is lacking. In this article, we present and test an approach for determining the development of user experience in the course of time using the so-called cross-modality matching (CMM). We conducted experiments with 24 subjects and evaluated seven mobile

Anatomy training with real cadavers poses many practical problems for which new training and educational solutions have been developed making use of technologies based on real-time 3-D graphics. Although virtual reality (VR) and augmented reality (AR) have been previously used in the medical field, it is not easy to select the right 3-D technology or setup for each particular problem. For this reason

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Humans can rapidly change their low-frequency arm dynamics to resist forces or give way to them. Quantifying driver time-varying arm dynamics is important to develop steer-by-wire and haptic support systems. Conventional linear time-invariant (LTI) identification, and even time-varying techniques such as wavelets, fail to capture fast changing dynamics. Moreover, such techniques require perturbation

Synchrony at the physiological level is an objective measure that can be used to investigate cooperation between human agents. This physiological synchrony has been experimentally observed in different dyadic contexts through measures of the autonomous system such as cardiac measures. Various metrics are used to characterize synchrony between participants such as cross-correlation, weighted coherence

Reciprocal cooperation is prevalent in human society. Understanding human reciprocal cooperation in human-agent interaction can help design human-agent systems that promote cooperation and joint performance. Studies have found that people reciprocate cooperative behavior when interacting with computer agents in social dilemma games. However, few studies have investigated human reciprocal cooperation

Choosing adequate gestures for touchless interfaces is a challenging task that has a direct impact on human–computer interaction. Such gestures are commonly determined by the designer, ad-hoc, rule-based, or agreement-based methods. Previous approaches to assess agreement grouped the gestures into equivalence classes and ignored the integral properties that are shared between them. In this article

Limitations of a haptic device can cause distortions of the force feedback it presents. Just-noticeable difference (JND) in system dynamics is important for creating transparent haptic interaction. Based on the previous work, this article presents a unified model that extends the existing JND rule. Our approach projects the JNDs in the mechanical properties of a second-order mass-spring-damper system

In autonomous multiagent or multirobotic systems, the ability to quickly and accurately respond to threats and uncertainties is important for both mission outcomes and survivability. Such systems are never truly autonomous, often operating as part of a human-agent team. Artificial intelligent agents (IAs) have been proposed as tools to help manage such teams; e.g., proposing potential courses of action