Automated interpretation of eye–hand coordination in mobile eye tracking recordings

Mussgnug, Moritz; Singer, Daniel; Lohmeyer, Quentin; Meboldt, Mirko

doi:10.1007/s13218-017-0503-y

Cited by 14 publications

(14 citation statements)

References 20 publications

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“…In humancomputer interaction, for instance, stationary eye-tracking systems are well established to investigate usability aspects of software tools or websites [53]. Usability testing of portable products, however, requires the use of mobile eye-tracking glasses, which allow the participant to move freely without restrictions while interacting with the product [48,49]. A camera integrated in the glasses records the participant's field of view ('scene video'), while two additional cameras located in the lower frame of the glasses record eye movement.…”

Section: Methodsmentioning

confidence: 99%

“…Eye-tracking data showed how long a participant's gaze focused on a given user interface element; that is, the dwell time on an AOI. Whereas long dwell times on an AOI reflect intensive cognitive efforts, short dwell times correspond to simple interface elements and thus to better product ease of use [49,66]. The user interface of the connected selfinjection system was dissected in distinct user interface elements/AOIs as depicted in Figure 3.…”

Section: Methodsmentioning

confidence: 99%

“…It does so by presenting a longitudinal case study applying video-based mobile eye-tracking [47] to iterative formative usability testing of a connected self-injection system. The article employs eyetracking to continuously follow users' eye movements and/or absolute point of gaze in order to assess visual and cognitive attention processes related to the use of products [48,49]. In so doing, the study advances eye-tracking as a methodology to evaluate three key dimensions of medical device usability: product effectiveness, product efficiency, and product ease of use.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Toward a new age of patient centricity? The application of eye-tracking to the development of connected self-injection systems

Lohmeyer

Schneider

Jordi

et al. 2019

Expert Opinion on Drug Delivery

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Background: Increasing interest in digitally enhanced drug delivery tools urges both industry and academia to rethink current approaches to product usability testing. This article introduces mobile eyetracking, generating detailed contextual data about user engagement with connected self-injection systems as a new methodological approach to formative usability assessment. Methods: A longitudinal case study with a total of 35 injection-naïve participants was conducted. In three consecutive experiments, eye-tracking was applied to formative usability testing of a novel connected self-injection device. Three eye-tracking derived usability indicators were established to assess product effectiveness, efficiency, and ease of use. Results: Analysis of the data revealed events of user hesitation, process interruption and unintended action, and these occurrences could either be completely eliminated or significantly reduced throughout the process (product effectiveness). At the same time, the overall use duration decreased from 86.1 to 58.7 sec (product efficiency). Analysis revealed that product modifications successfully guided user attention to those interface elements most relevant during each task, thereby improving product easeof-use. Conclusions: The step-wise improvement in the usability indicators demonstrates that iteratively applying eye-tracking methods effectively supports the user-centered design of connected selfinjection systems. The results highlight how eye-tracking can be employed to gain an in-depth understanding of patient engagement with novel healthcare technologies. ARTICLE HISTORY

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Toward a new age of patient centricity? The application of eye-tracking to the development of connected self-injection systems

Lohmeyer

Schneider

Jordi

et al. 2019

Expert Opinion on Drug Delivery

Self Cite

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“…Closely linked is the work by [6], which focusses on the automatic interpretation of specific gestural instances involving eye-hand co-ordination in the context of mobile eyetracking. To quote [6]: this work aims to automatically detect cognitive demanding phases in mobile eye tracking recordings.…”

Section: Contentmentioning

confidence: 99%

“…To quote [6]: this work aims to automatically detect cognitive demanding phases in mobile eye tracking recordings. The approach presented combines the user's perception (gaze) and action (hand) to isolate demanding interactions based upon a multi-modal feature level fusion.…”

Section: Contentmentioning

confidence: 99%

Semantic Interpretation of Multi-Modal Human-Behaviour Data

Bhatt

Kersting

2017

Künstl Intell

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multi-modal sensory data relevant to a range of application domains and problem contexts where interpreting human behaviour is central. The overall motivation and driving theme of the special issue pertains to artificial intelligence based methods and tools that may serve a foundational purpose toward the high-level semantic interpretation of largescale, dynamic, multi-modal sensory data, or data streams. A crucial focus of the special issue has been on foundational methods supporting the development of human-centred technologies and cognitive interaction systems aimed at assistance and empowerment, e.g. in everyday life and activity, professional problem solving for creative and analytical decision-making, planning etc. Multi-Modal Event and Activity InterpretationThe multi-modality that is alluded to in the context of this special issue stems from an inherent synergistic value in the integrated processing and interpretation of a range of data sources that are common in the context of cognitive interaction systems, computational cognition, and human-computer interaction scenarios.Multi-modal data-sources that may be envisaged include, but are not limited to, one or more of the following:• Visuo-spatial imagery: -Image, video, video and depth (RGB-D), pointclouds. -Geospatial satellite imagery, remote sensing data, crowd-sourced data, survey data.• Movement and interaction data:Abstract This special issue presents interdisciplinary research-at the interface of artificial intelligence, cognitive science, and human-computer interaction-focussing on the semantic interpretation of human behaviour. The special issue constitutes an attempt to highlight and steer foundational methods research in artificial intelligence, in particular knowledge representation and reasoning, for the development of human-centred cognitive assistive technologies.Of specific interest and focus have been application outlets for basic research in knowledge representation and reasoning and computer vision for the cognitive, behavioural, and social sciences.

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Inferring task performance and confidence from displays of eye movements

Emhardt

Wermeskerken

Scheiter

et al. 2020

Applied Cognitive Psychology

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Eye movements reveal what is at the center of people's attention, which is assumed to coincide with what they are thinking about. Eye-movement displays (visualizations of a person's fixations superimposed onto the stimulus, for example, as dots or circles) might provide useful information for diagnosing that person's performance. However, making inferences about a person's task performance based on eyemovement displays requires substantial interpretation. Using graph-comprehension tasks, we investigated to what extent observers (N = 46) could make accurate inferences about a performer's multiple-choice task performance (i.e., chosen answer), confidence, and competence from displays of that person's eye movements. Observers' accuracy when judging which answer the performer chose was above chance level and was higher for displays reflecting confident performance. Observers were also able to infer performers' confidence from the eye-movement displays; moreover, their own task performance and perceived similarity with the performer affected their judgments of the other's competence.

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Automated interpretation of eye–hand coordination in mobile eye tracking recordings

Cited by 14 publications

References 20 publications

Toward a new age of patient centricity? The application of eye-tracking to the development of connected self-injection systems

Toward a new age of patient centricity? The application of eye-tracking to the development of connected self-injection systems

Semantic Interpretation of Multi-Modal Human-Behaviour Data

Inferring task performance and confidence from displays of eye movements

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