Gaze-Based Assistive Technologies

Pfeiffer, Thies

doi:10.4018/978-1-4666-4438-0.ch004

Cited by 4 publications

(3 citation statements)

References 32 publications

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“…The earliest attention-based assistance systems were those for gaze-typing or mimicking mouse movements, which allowed people with restricted (manual) interaction capabilities to operate a computer by eye movements. An overview of different gaze-based assistive technologies for desktop computers, 3D Virtual Reality and natural environments can be found in [1]. One problem for designing such systems is that eye movements often occur involuntarily and thus fixations do not necessarily indicate a an intent to interact with a particular element at the screen [2].…”

Section: Assistive Systemsmentioning

confidence: 99%

Adamaas

Essig¹,

Strenge²,

Schack³

2016

Proceedings of the 9th ACM International Conference on PErvasive Technologies Related to Assistive Environments

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In this paper, we describe the assistive system ADAMAAS (Adaptive and Mobile Action Assistance) introducing a new advanced smartglasses technology. The aim of ADAMAAS is to move from stationary status diagnosis systems to a mobile and adaptive action support and monitoring system, which is able to dynamically react in a context sensitive way to human error (slips and mistakes) and to provide individualized feedback on a transparent virtual plane superimposed on user's field of view. For this purpose ADAMAAS uses advanced technologies like augmented reality (AR), eye tracking, object recognition, and systematic analysis of users' mental representations in long term memory. Preliminary user tests with disabled participants at an early prototype stage revealed no substantial physical restrictions in the execution of their activities, positive feedback regarding the assistive hints, and that participants could imagine wearing the glasses for long periods of time. CCS Concepts•Human-centered computing → Mixed / augmented reality; Ubiquitous and mobile computing; HCI design and evaluation methods; •Applied computing → Computerassisted instruction; •Computing methodologies → Activity recognition and understanding;

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Section: Assistive Systemsmentioning

confidence: 99%

Adamaas

Essig¹,

Strenge²,

Schack³

2016

Proceedings of the 9th ACM International Conference on PErvasive Technologies Related to Assistive Environments

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“…In the experiment, a touchscreen mobile device was used for manual input; however, the TAGSwipe framework can work with any triggering device; and, so, TAGSwipe also stands for "Tag your device to Swipe for fast and comfortable gaze-based text entry". The framework is feasible for people who lack fine motor skills but can perform coarse interaction with their hands (tap) [33,27]. A majority of such users already use switch inputs and this can be used to support gaze interaction.…”

Section: Introductionmentioning

confidence: 99%

TAGSwipe: Touch Assisted Gaze Swipe for Text Entry

Kumar

Hedeshy

MacKenzie

et al. 2020

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

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The conventional dwell-based methods for text entry by gaze are typically slow and uncomfortable. A swipe-based method that maps gaze path into words offers an alternative. However, it requires the user to explicitly indicate the beginning and ending of a word, which is typically achieved by tedious gazeonly selection. This paper introduces TAGSwipe, a bi-modal method that combines the simplicity of touch with the speed of gaze for swiping through a word. The result is an efficient and comfortable dwell-free text entry method. In the lab study TAGSwipe achieved an average text entry rate of 15.46 wpm and significantly outperformed conventional swipe-based and dwell-based methods in efficacy and user satisfaction.

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“…Gaze-based assistive systems have, along with the advances in mobile eye tracking technologies, moved into real-world environments in the last decade (Pfeiffer 2013). Our work is related to work in attentive assistance systems (Maglio et al 2000) and human–robot and human–agent interactions, where gaze is relevant for the social aspects of interaction (Sidner et al 2004) as well as for grounding verbal utterances using mechanisms of joint attention (Imai et al 2003).…”

Section: Introductionmentioning

confidence: 99%

Towards efficient human–machine collaboration: effects of gaze-driven feedback and engagement on performance

et al. 2018

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Referential success is crucial for collaborative task-solving in shared environments. In face-to-face interactions, humans, therefore, exploit speech, gesture, and gaze to identify a specific object. We investigate if and how the gaze behavior of a human interaction partner can be used by a gaze-aware assistance system to improve referential success. Specifically, our system describes objects in the real world to a human listener using on-the-fly speech generation. It continuously interprets listener gaze and implements alternative strategies to react to this implicit feedback. We used this system to investigate an optimal strategy for task performance: providing an unambiguous, longer instruction right from the beginning, or starting with a shorter, yet ambiguous instruction. Further, the system provides gaze-driven feedback, which could be either underspecified (“No, not that one!”) or contrastive (“Further left!”). As expected, our results show that ambiguous instructions followed by underspecified feedback are not beneficial for task performance, whereas contrastive feedback results in faster interactions. Interestingly, this approach even outperforms unambiguous instructions (manipulation between subjects). However, when the system alternates between underspecified and contrastive feedback to initially ambiguous descriptions in an interleaved manner (within subjects), task performance is similar for both approaches. This suggests that listeners engage more intensely with the system when they can expect it to be cooperative. This, rather than the actual informativity of the spoken feedback, may determine the efficiency of information uptake and performance.

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Gaze-Based Assistive Technologies

Abstract: The eyes play an important role both in perception and communication. Technical

Cited by 4 publications

References 32 publications

Adamaas

Adamaas

TAGSwipe: Touch Assisted Gaze Swipe for Text Entry

Towards efficient human–machine collaboration: effects of gaze-driven feedback and engagement on performance

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