When interacting with technical systems, users experience mental workload. Particularly in multitasking scenarios (e.g. the car navigation system while driving) it is desired to not distract from their primary task. For such purposes, human-machine interfaces (HCIs) are desirable which continuously monitor users' workload and dynamically adapt behavior of interface measured While memory tasks have been shown illicit hemodynamic responses brain when averaging over multiple trials, a robust...

For multimodal Human-Computer Interaction (HCI), it is very useful to identify the modalities on which user currently processing information. This would enable a system select complementary output reduce user's workload. In this paper, we develop hybrid Brain-Computer Interface (BCI) uses Electroencephalography (EEG) and functional Near Infrared Spectroscopy (fNIRS) discriminate detect visual auditory stimulus processing. We describe experimental setup used for collection of our data corpus...

Questionnaires are among the most common research tools in virtual reality (VR) evaluations and user studies. However, transitioning from worlds to physical world respond VR experience questionnaires can potentially lead systematic biases. Administering (inVRQs) is becoming more contemporary research. This based on intuitive notion that inVRQs may ease participation, reduce Break Presence (BIP) avoid In this paper, we perform a investigation into effects of interrupting through using...

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A Bloom filter is a very compact data structure that supports approximate membership queries on set, allowing false positives. We propose several new variants of filters and replacements with similar functionality. All them have better cache-efficiency need less hash bits than regular filters. Some use SIMD functionality, while the others provide an even space efficiency. As consequence, we get more flexible trade-off between false-positive rate, space-efficiency, cache-efficiency,...

One problem faced in the design of Augmented Reality (AR) applications is interference virtually displayed objects user's visual field, with current attentional focus user. Newly generated content can disrupt internal thought processes. If we detect such internally-directed attention periods, interruption could either be avoided or even used intentionally. In this work, designed a spacial alignment task AR two conditions: one externally-directed and attention. Apart from direction attention,...

Virtual reality finds various applications in productivity, entertainment, and training scenarios requiring working memory attentional resources. Working relies on prioritizing relevant information suppressing irrelevant through internal attention, which is fundamental for successful task performance training. Today, virtual systems do not account the impact of loads resulting over or under-stimulation. In this work, we designed an adaptive system based EEG correlates external attention to...

Functional near infrared spectroscopy (fNIRS) is rapidly gaining interest in both the Neuroscience, as well Brain-Computer-Interface (BCI) community. Despite these efforts, most single-trial analysis of fNIRS data focused on motor-imagery, or mental arithmetics. In this study, we investigate suitability different tasks, namely arithmetics, word generation and rotation for based BCIs. We provide first systematic comparison classification accuracies achieved a sample study. Data was collected...

We investigate the integration of eye-tracking and a Brain-Computer Interface into an Augmented Reality system to control smart home environment. Through head-mounted display, we present context-dependent elements which user selects by directing attention towards them. show that combination both modalities leads most robust detection selections interface is accepted its users.

We previously reported that after virtual tool use training, younger as compared to older adults experienced a higher sense of ownership over tools associated with changes in sensorimotor representation (i.e., body schema). Moreover, agency ratings were contingent on their performance levels and the extent which was integrated into arm representation. In contrast, exhibited heightened agency, strongly improvements use. Regardless, no schema, emergence revealed adults. Comparing data from...

Attribute manipulation deals with the problem of changing individual attributes a data point or time series, while leaving all other aspects unaffected. This work focuses on domain human motion, more precisely karate movement patterns. To best our knowledge, it presents first success at manipulating motion data. One key requirements for achieving attribute is suitable pose representation. Therefore, we design novel rotation-based representation that enables disentanglement skeleton and...

Recently, the idea of using BCIs in Augmented Reality settings to operate systems has emerged. One problem such head-mounted displays is distraction caused by an unavoidable display control elements even when focused on internal thoughts. In this project, we reduced including information about current attentional state. A multimodal smart-home environment was altered adapt user's state attention. The system only responded if orientation classified as "external". classification based EEG and...

Abstract Eye behavior is increasingly used as an indicator of internal versus external focus attention both in research and application. However, available findings are partly inconsistent, which might be attributed to the different nature employed types cognition tasks. The present study, therefore, investigated how consistently eye parameters respond attentional across three task modalities: numerical, verbal, visuo‐spatial. Three robustly differentiated between all Blinks, pupil diameter...

This work describes the development and evaluation of a recognizer for different levels cognitive workload in car. We collected multiple biosignal streams (skin conductance, pulse, respiration, EEG) during an experiment driving simulator which drivers performed primary task several secondary tasks varying difficulty. From this data, SVM based classifier was trained evaluated, yielding recognition rates up to three workload.

Dealing with fear of falling is a challenge in sport climbing. Virtual reality (VR) research suggests that using physical and reality-based interaction increases the presence VR. In this paper, we present study investigates influence props on presence, stress anxiety VR climbing environment involving whole body movement. To help climbers overcoming falling, compared three different conditions: Climbing at 10 m height, (with attached to wall) virtual game controllers. From subjective reports...

In human-computer interaction (HCI), there has been a push towards open science, but to date, this not happened consistently for HCI research utilizing brain signals due unclear guidelines support reuse and reproduction. To understand existing practices in the field, paper examines 110 publications, exploring domains, applications, modalities, mental states processes, more. This analysis reveals variance how authors report experiments, which creates challenges understand, reproduce, build on...

Virtual Reality (VR) has emerged as a novel paradigm for immersive applications in training, entertainment, rehabilitation, and other domains. In this paper, we investigate the automatic classification of mental workload from brain activity measured through functional near-infrared spectroscopy (fNIRS) VR. We present results study which implements established n-back task an visual scene, including physical interaction. Our show that user can be detected fNIRS signals VR tasks both...

Adding attention-awareness to an Augmented Reality setting by using a Brain-Computer Interface promises many interesting new applications and improved usability. The possibly complicated setup relatively long training period of EEG-based BCIs however, reduce this positive effect immensely. In study, we aim at finding solutions for person-independent, training-free BCI integration into AR classify internally externally directed attention. We assessed several different classifier settings on...

It has been shown that conclusions about the human mental state can be drawn from eye gaze behavior by several previous studies. For this reason, tracking recordings are suitable as input data for attentional classifiers. In current state-of-the-art studies, extracted feature set usually consists of descriptive statistics specific movement characteristics (i.e., fixations, saccades, blinks, vergence, and pupil dilation). We suggest an Imaging Time Series approach followed classification...

In expert video analysis, the selection of certain events in a continuous stream is frequently occurring operation, e.g., surveillance applications. Due to dynamic and rich visual input, constantly high attention required hand-eye coordination for mouse interaction, this very demanding exhausting task. Hence, relevant might be missed. We propose use eye tracking electroencephalography (EEG) as additional input modalities event selection. From tracking, we derive spatial location perceived...