Analyzing the Impact of Cognitive Load in Evaluating Gaze-based Typing

Gaze-based virtual keyboards provide an effective interface for text entry by eye movements. The efficiency and usability of these keyboards have traditionally been evaluated with conventional text entry performance measures such as words per minute, keystrokes per character, backspace usage, etc. However, in comparison to the traditional text entry approaches, gaze-based typing involves natural eye movements that are highly correlated with human brain cognition. Employing eye gaze as an input could lead to excessive mental demand, and in this work we argue the need to include cognitive load as an eye typing evaluation measure. We evaluate three variations of gaze-based virtual keyboards, which implement variable designs in terms of word suggestion positioning. The conventional text entry metrics indicate no significant difference in the performance of the different keyboard designs. However, STFT (Short-time Fourier Transform) based analysis of EEG signals indicate variances in the mental workload of participants while interacting with these designs. Moreover, the EEG analysis provides insights into the user's cognition variation for different typing phases and intervals, which should be considered in order to improve eye typing usability.Comment: 6 pages, 4 figures, IEEE CBMS 201

Haptic feedback in eye typing

Proper feedback is essential in gaze based interfaces, where the same modality is used for both perception and control. We measured how vibrotactile feedback, a form of haptic feedback, compares with the commonly used visual and auditory feedback in eye typing. Haptic feedback was found to produce results that are close to those of auditory feedback; both were easy to perceive and participants liked both the auditory ”click” and the tactile “tap” of the selected key. Implementation details (such as the placement of the haptic actuator) were also found important

Enhancing an Eye-Tracker based Human-Computer Interface with Multi-modal Accessibility Applied for Text Entry

In natural course, human beings usually make use of multi-sensory modalities for effective communication or efficiently executing day-to-day tasks. For instance, during verbal conversations we make use of voice, eyes, and various body gestures. Also effective human-computer interaction involves hands, eyes, and voice, if available. Therefore by combining multi-sensory modalities, we can make the whole process more natural and ensure enhanced performance even for the disabled users. Towards this end, we have developed a multi-modal human-computer interface (HCI) by combining an eye-tracker with a soft-switch which may be considered as typically representing another modality. This multi-modal HCI is applied for text entry using a virtual keyboard appropriately designed in-house, facilitating enhanced performance. Our experimental results demonstrate that using multi-modalities for text entry through the virtual keyboard is more efficient and less strenuous than single modality system and also solves the Midas-touch problem, which is inherent in an eye-tracker based HCI system where only dwell time is used for selecting a character

Using Variable Dwell Time to Accelerate Gaze-Based Web Browsing with Two-Step Selection

In order to avoid the "Midas Touch" problem, gaze-based interfaces for selection often introduce a dwell time: a fixed amount of time the user must fixate upon an object before it is selected. Past interfaces have used a uniform dwell time across all objects. Here, we propose a gaze-based browser using a two-step selection policy with variable dwell time. In the first step, a command, e.g. "back" or "select", is chosen from a menu using a dwell time that is constant across the different commands. In the second step, if the "select" command is chosen, the user selects a hyperlink using a dwell time that varies between different hyperlinks. We assign shorter dwell times to more likely hyperlinks and longer dwell times to less likely hyperlinks. In order to infer the likelihood each hyperlink will be selected, we have developed a probabilistic model of natural gaze behavior while surfing the web. We have evaluated a number of heuristic and probabilistic methods for varying the dwell times using both simulation and experiment. Our results demonstrate that varying dwell time improves the user experience in comparison with fixed dwell time, resulting in fewer errors and increased speed. While all of the methods for varying dwell time resulted in improved performance, the probabilistic models yielded much greater gains than the simple heuristics. The best performing model reduces error rate by 50% compared to 100ms uniform dwell time while maintaining a similar response time. It reduces response time by 60% compared to 300ms uniform dwell time while maintaining a similar error rate.Comment: This is an Accepted Manuscript of an article published by Taylor & Francis in the International Journal of Human-Computer Interaction on 30 March, 2018, available online: http://www.tandfonline.com/10.1080/10447318.2018.1452351 . For an eprint of the final published article, please access: https://www.tandfonline.com/eprint/T9d4cNwwRUqXPPiZYm8Z/ful

Dwell-free input methods for people with motor impairments

Millions of individuals affected by disorders or injuries that cause severe motor impairments have difficulty performing compound manipulations using traditional input devices. This thesis first explores how effective various assistive technologies are for people with motor impairments. The following questions are studied: (1) What activities are performed? (2) What tools are used to support these activities? (3) What are the advantages and limitations of these tools? (4) How do users learn about and choose assistive technologies? (5) Why do users adopt or abandon certain tools? A qualitative study of fifteen people with motor impairments indicates that users have strong needs for efficient text entry and communication tools that are not met by existing technologies. To address these needs, this thesis proposes three dwell-free input methods, designed to improve the efficacy of target selection and text entry based on eye-tracking and head-tracking systems. They yield: (1) the Target Reverse Crossing selection mechanism, (2) the EyeSwipe eye-typing interface, and (3) the HGaze Typing interface. With Target Reverse Crossing, a user moves the cursor into a target and reverses over a goal to select it. This mechanism is significantly more efficient than dwell-time selection. Target Reverse Crossing is then adapted in EyeSwipe to delineate the start and end of a word that is eye-typed with a gaze path connecting the intermediate characters (as with traditional gesture typing). When compared with a dwell-based virtual keyboard, EyeSwipe affords higher text entry rates and a more comfortable interaction. Finally, HGaze Typing adds head gestures to gaze-path-based text entry to enable simple and explicit command activations. Results from a user study demonstrate that HGaze Typing has better performance and user satisfaction than a dwell-time method