Low Vision Users Research Articles

LoVi App: Android Application-based Image Classification for Low Vision

In Indonesia, many people with visual impairments are drawing public attention to their rights as fellow humans. One of the limitations that individuals with low vision face is their ability to recognize objects and navigate their surroundings due to difficulties in visual perception. In this modern era, deep learning technologies, especially in image classification, can help people with low vision overcome these challenges. In this paper, we discuss a deep learning system that optimizes image classification on users' smartphones to enhance visual support for individuals with low vision. We present an Android-based app, LoVi, designed to assist users with low vision. Powered by core systems within Sherpa models (TrotoarNet, IndoorNet, and CurrencyNet), LoVi has three modes: outdoor, indoor, and currency. The LoVi application provides over 80% accuracy for navigation on sidewalks, indoor object recognition, and currency identification. TrotoarNet aids in sidewalk navigation, IndoorNet assists with indoor object identification, and CurrencyNet recognizes Rupiah banknotes. Additionally, low-vision users can receive voice feedback for further accessibility.

Haptic2FA: Haptics-Based Accessible Two-Factor Authentication for Blind and Low Vision People

Two-factor Authentication (also known as 2FA or two-step verification) is an authentication method that provides an extra layer of protection to ensure online account security. 2FA methods are used along with other primary authentication methods like PINs and Passwords to verify that the person trying to access any digital account is the person they are claiming to be. However, 2FA methods can be inaccessible for blind and low vision (BLV) users due to the requirement of multiple steps, apps, and/or devices for authentication. In addition, it can be a security risk as screen readers may read out the verification codes to bystanders. To address this, we present Haptic2FA, a haptic-based authentication method to improve 2FA accessibility for BLV users. Here, as a part of the 2FA process, the users are sent a 'haptic pattern' (similar to a one-time passcode in traditional 2FA methods) that they are required to enter or select for verification. Through a usability study with 10 BLV participants, we evaluated haptic patterns and input methods for the haptic patterns in the Haptic2FA method. Through the findings, we discuss the accessibility and usability of the Haptic2FA method.

Are your apps accessible? A GCN-based accessibility checker for low vision users

Context:Accessibility issues (e.g., small size and narrow interval) in mobile applications (apps) lead to obstacles for billions of low vision users in interacting with Graphical User Interfaces (GUIs). Although GUI accessibility scanning tools exist, most of them perform rule-based check relying on complex GUI hierarchies. This might make them detect invisible redundant information, cannot handle small deviations, omit similar components, and is hard to extend. Objective:In this paper, we propose a novel approach, named ALVIN (Accessibility Checker for Low Vision), which represents the GUI as a graph and adopts the Graph Convolutional Neural Networks (GCN) to label inaccessible components. Method:ALVIN removes invisible views to prevent detecting redundancy and uses annotations from low vision users to handle small deviations. Also, the GCN model could consider the relations between GUI components, connecting similar components and reducing the possibility of omission. ALVIN only requires users to annotate the relevant dataset when detecting new kinds of issues. Results:Our experiments on 48 apps demonstrate the effectiveness of ALVIN, with precision of 83.5%, recall of 78.9%, and F1-score of 81.2%, outperforming baseline methods. In RQ2, the usefulness is verified through 20 issues submitted to open-source apps. The RQ3 also illustrates the GCN model is better than other models. Conclusion:To summarize, our proposed approach can effectively detect accessibility issues in GUIs for low vision users, thereby guiding developers in fixing them efficiently.

Comparative effectiveness between two types of head-mounted magnification modes using a smartphone-based virtual display.

This work shows the benefits of using two different magnification strategies to improve the reading ability of low-vision patients using a head-mounted technology. The aim of this study was to conduct a comparative clinical trial evaluating the effectiveness of two magnification strategies in a head-mounted virtual reality display. Eighty-eight eligible low-vision subjects were randomized into two arms: (1) the full-field magnification display or (2) the virtual bioptic telescope mode. Subjects completed baseline testing and received training on how to use the device properly and then took the device home for a 2- to 4-week intervention period. An adaptive rating scale questionnaire (Activity Inventory) was administered before and after the intervention (home trial) period to measure the effect of the system. A Simulator Sickness Questionnaire was also administered. Baseline and follow-up results were analyzed using Rasch analysis to assess overall effectiveness of each magnification mode for various functional domain categories. Both magnification modes showed a positive effect for reading, visual information, and the overall goals functional domain categories, with only reading reaching statistical significance after correction for multiple comparisons. However, there were no significant between-group differences between the two modes. The results of the Simulator Sickness Questionnaire showed that the magnification modes of the head-mounted display device were overall well tolerated among low-vision users. Both the full-field and virtual bioptic magnification strategies were effective in significantly improving functional vision outcomes for self-reported reading ability.

Accessibility evaluation of major assistive mobile applications available for the visually impaired

People with visual impairments face numerous challenges in their daily lives, including mobility, access to information, independent living, and employment. Artificial Intelligence (AI) with Computer Vision (CV) has the potential to improve their daily lives, provide them with necessary independence, and it will also spawn new opportunities in education and employment. However, while many such AI/CV-based mobile applications are now available, these apps are still not the preferred choice amongst visually impaired persons and are generally limited to advanced users only, due to certain limitations. This study evaluates the challenges faced by visually impaired persons when using AI/CV-based mobile apps. Four popular AI/CV-based apps, namely Seeing AI, Supersense, Envision and Lookout, are assessed by blind and low-vision users. Hence these mobile applications are evaluated on a set of parameters, including generic parameters based on the Web Content Accessibility Guidelines (WCAG) and specific parameters related to mobile app testing. The evaluation not only focused on the guidelines but also on the feedback that was gathered from these users on parameters covering the apps' accuracy, response time, reliability, accessibility, privacy, energy efficiency and usability. The paper also identifies the areas of improvement in the development and innovation of these assistive apps. This work will help developers create better accessible AI-based apps for the visually impaired.

Invited Session IV: Extended reality--applications in vision science and beyond: Augmented reality systems for people with low vision.

Low vision is a visual impairment that falls short of blindness but cannot be corrected by eyeglasses or contact lenses. While current low vision aids (e.g., magnifier, CCTV) support basic vision enhancements, such as magnification and contrast enhancement, these enhancements often arbitrarily alter a user's full field of view without considering the user's context, such as their visual abilities, tasks, and environmental factors. As a result, these low vision aids are not sufficient or preferred by low vision users in many important tasks. Augmented reality (AR) technology presents a unique opportunity to enhance low vision people's visual experience by automatically recognizing the surrounding environment and presenting tailored visual augmentations. In this talk, I will talk about how we design and build intelligent AR systems to support low vision people in visual tasks, such as a head-mounted AR system that presents visual cues to orient users' attention in a visual search task, as well as a projection-based AR system that projects visual highlights on the stair edges to support safe stair navigation. I will conclude my talk by discussing our future research direction on AR for low vision accessibility.

“Consent notices are obstructing my view”: Viewing sticky elements on responsive websites under the magnifying glass

The practice of using consent notices on websites has received much criticism and attention among researchers. Much of the research has addressed unethical aspects of consent notices while less attention has been devoted to implications for accessibility. This study thus set out to explore implications of such elements for low vision users who rely on browser magnification to access information on the web. A selection of the 100 most frequently used or formally important websites in Norway was manually studied with heuristic evaluation to assess their accessibility with high magnification. The results show that a large portion of the websites contained blocking consent notices that make the websites inaccessible while magnified. Also, most of the websites employed sticky permanent elements such as navigation menus that obstruct much, in some cases all, of the screen real estate in the magnified view. The study also uncovered patterns that preserve accessibility. A key implication of this study is that web developers should consider narrow use cases explicitly. Recommendations are provided on how to avoid inaccessibility for users relying on magnification in narrow viewports.

To wrap or not to wrap? A study of how long words are split when reflowed on magnified web pages

AbstractMany low-vision users adjust the browser zoom level to make text more comfortable to read. Responsive websites attempt to fit the content within the viewport width, but several types of problems can potentially occur; long words may be wider than the viewport and thus partially hidden, they may cause large vertical space breaks, and words may be unnecessarily split or incorrectly split. This study set out to get insight into such word wrapping problems on responsive web pages. To help identify word wrapping issues, the tool HYPHERSPACE was developed. Experiments run on 91 websites suggest that hyphenation-related problems are prevalent. Excessive wrapping of words and overflowing words were the most notable problem on about 90% of the websites. One implication of this study is that web designers need to explicitly design for narrow viewports. The proposed tool can help web designers identify hyphenation problems on responsive web pages viewed with high magnification.

SpaceX Mag

Low-vision users interact with smartphones via screen magnifiers, which uniformly magnify raw screen pixels, including whitespace and user interface (UI) elements. Screen magnifiers thus occlude important contextual information, such as visual cues, from the user's viewport. This requires low-vision users to pan over the occluded portions and mentally reconstruct the context, which is cumbersome, tiring, and mentally demanding. Prior work aimed to address these usability issues with screen magnifiers by optimizing the representation of UI elements suitable for low-vision users or by magnifying whitespace and non-whitespace content (e.g., text, graphics, borders) differently. This paper combines both techniques and presents SpaceXMag, an optimization framework that automatically reduces whitespace within a smartphone app, thereby packing more information within the current magnification viewport. A study with 11 low-vision users indicates that, with a traditional screen magnifier, the space-optimized UI is more usable and saves at least 28.13% time for overview tasks and 42.89% time for target acquisition tasks, compared to the original, unoptimized UI of the same app. Furthermore, our framework is scalable, fast, and automatable. For example, on a public dataset containing 16, 566 screenshots of different Android apps, it saves approximately 47.17% of the space (area) on average, with a mean runtime of around 1.44 seconds, without requiring any human input. All are indicative of the promise and potential of SpaceXMag for low-vision screen magnifier users.

Multivalent Cartographic Accessibility: Tactile Maps for Collaborative Decision-Making

Conventional visual maps present significant accessibility challenges for blind or low vision users, leaving them with few or no options for interpreting spatial data. This need not be the case: tactile maps, designed to be read through touch, have been published for more than a century. But they have most often been categorized as a navigation tool, or mere “tactile graphics” (i.e., not as expressly spatial documents). Tactile maps that allow their users to explore and synthesize thematic spatial data are rare, as are studies evaluating them. As our world continues to face existential threats that are spatial in nature—pandemics, supply chain disruptions, floods, etc.—maps will continue to provide critical information in ways that other media are unable to match. In the absence of accessible thematic maps, blind people will not only be left out of the loop, but their capacity for contributing valuable input will be severely diminished. In response, I describe here a study that evaluates the potential of thematic tactile maps for providing blind users an accessible means of analyzing spatial data when working in collaboration with sighted partners. Findings indicate that while the maps did not prove to be useful tools on their own, they did facilitate collaboration between blind or low vision participants and sighted participants. This suggests that, with some refinements, similar maps could be feasibly distributed as a means for people with visual disabilities to meaningfully participate in an otherwise inaccessible process that requires the synthesis of thematic spatial information.

Real-time imaging processing with augmented reality glasses for mobile low-vision users

Real-time imaging processing with augmented reality glasses for mobile low-vision users

Are your Apps Accessible? A GCN-based Android Accessibility Checker for Low Vision Users

Are your Apps Accessible? A GCN-based Android Accessibility Checker for Low Vision Users

OneButtonPIN: A Single Button Authentication Method for Blind or Low Vision Users to Improve Accessibility and Prevent Eavesdropping

A Personal Identification Number (PIN) is a widely adopted authentication method used by smartphones, ATMs, etc. PINs offer strong security and can be reset when compromised (unlike biometric authentication). However, PINs can be inaccessible for blind or low vision (BLV) users due to screen readers voicing PINs to bystanders or potential shoulder surfing attack risks---bystanders could watch the PIN being entered without the user noticing. To address this, we present OneButtonPIN, an interface to improve PIN entry accessibility and security for BLV users. Here, a single on-screen button, when pressed and held, triggers a haptic vibration sequence. A digit is entered by counting the vibrations and releasing the button. We explored introducing random timings to the vibration sequence to increase security. A week-long evaluation with 9 BLV participants and a security study with 10 sighted participants acting as shoulder surfers demonstrated OneButtonPIN's usability and resilience against eavesdropping.

LiSee

Reaching surrounding target objects is difficult for blind and low-vision (BLV) users, affecting their daily life. Based on interviews and exchanges, we propose an unobtrusive wearable system called LiSee to provide BLV users with all-day assistance. Following a user-centered design method, we carefully designed the LiSee prototype, which integrates various electronic components and is disguised as a neckband headphone such that it is an extension of the existing headphone. The top-level software includes a series of seamless image processing algorithms to solve the challenges brought by the unconstrained wearable form so as to ensure excellent real-time performance. Moreover, users are provided with a personalized guidance scheme so that they can use LiSee quickly based on their personal expertise. Finally, a system evaluation and a user study were completed in the laboratory and participants' homes. The results show that LiSee works robustly, indicating that it can meet the daily needs of most participants to reach surrounding objects.

Are Your Apps Accessible? A GCN-based Accessibility Checker for Low Vision Users

Are Your Apps Accessible? A GCN-based Accessibility Checker for Low Vision Users

Are Your Apps Accessible? A GCN-based Accessibility Checker for Low Vision Users

Are Your Apps Accessible? A GCN-based Accessibility Checker for Low Vision Users

Customizable Tabular Access to Web Data Records for Convenient Low-vision Screen Magnifier Interaction

To interact with webpages, people with low vision typically rely on screen magnifier assistive technology that enlarges screen content and also enables them to pan the content to view the different portions of a webpage. This back-and-forth panning between different webpage portions makes it especially inconvenient and arduous for screen magnifier users to interact with web data records (e.g., list of flights, products, job advertisements), as this interaction typically involves making frequent comparisons between the data records based on their attributes, e.g., comparing available flights in a travel website based on their prices, durations. To address this issue, we present TableView+, an enhanced version of our previous TableView prototype—a browser extension that leverages a state-of-the-art data extraction method to automatically identify and extract information in web data records, and subsequently presents the information to a screen magnifier user in a compactly arranged data table to facilitate easier comparisons between records. TableView+ introduces new features aimed mostly at addressing the critical shortcomings of TableView, most notably the absence of interface customization options. In this regard, TableView+ enables low-vision users to customize the appearance of the data table based on their individual needs and eye conditions. TableView+ also saves these customizations to automatically apply them to the best extent possible the next time the users interact with the data records on either the same or other similar websites. A user study with 25 low-vision participants showed that with TableView+, the panning time further decreased by 8.5% on unfamiliar websites and by 8.02% on a familiar website than with TableView when compared to a screen magnifier.

Are Your Apps Accessibile? A GCN-based Accessibility Checker for Low Vision Users

Are Your Apps Accessibile? A GCN-based Accessibility Checker for Low Vision Users

I see therefore i read: improving the reading capabilities of individuals with visual disabilities through immersive virtual reality

We aim to help improve the quality of life of people with visual disabilities through the application of emerging technologies. Our current research investigates the viability of virtual reality (VR) as an aid for persons with visual disabilities. In this article, we explore the potential of VR-assisted reading. We investigate the reading effects of VR equipment on persons with visual disabilities by utilising variations of standardised optometry-informed reading tests conducted across 24 participants. Test results uncovered that, when comparing a worn VR head-mounted display (HMD) to physical unaided tests, results within a HMD scaled better at closer distances, while unaided tests scaled better with further distances. Using the findings collected and requirements elicited from participants, a prototype document reader was developed for reading text within a VR-immersed 3D environment, allowing low-vision users to customise and configure accessibility features for enhanced reading. This software was tested with 11 new participants alongside user evaluations, allowing us to discover how users perceived text best within our 3D virtual environments, and what features and techniques are required to evolve this accessibility tool further. The user test reported an overwhelmingly positive response to our tool as a feasible reading aid, allowing persons who could not engage (or, due to the difficulty, refusing to) in the reading of material to do so. We also register some limitations and areas for improvement, such as a need for non-functional requirements to be improved, and the aesthetics of our design to be improved going forward.

EVALUATION MODEL FOR LOW VISION USERS IN MOBILE APPLICATION

This paper aims to discuss the usability evaluation model for mobile applications used by low vision users. Low vision users have difficulties using mobile applications due to limited view, bright sunshine, small text, and other reasons. This type of user uses mobile applications designed for users with normal vision, and they have many difficulties in reading, accessing, and understanding. Therefore, this paper provides a mobile application usability evaluation model for this type of user, and the proposed model includes usability measures that fulfill their usability requirements. This study employed a systematic review of previous research on good practices and requirements for low vision users to use mobile applications. Also, the new model was evaluated by the domain experts through a focus group session. This model aims to support the development of a mobile application that low vision users can use, which has not been supported in previous studies since it guides mobile application developers to develop mobile applications that fulfill low vision users' usability requirements. It also helps to identify usability problems in the current mobile applications for this type of user. This study will benefit low vision people in using mobile applications effectively, easily, and comfortably.