Towards the development of haptic-based interface for teaching visually impaired arabic handwriting

Bayousuf, Abeer; Al‐Khalifa, Hend S.; Al-Salman, AbdulMalik S.

doi:10.1145/2513383.2513400

Cited by 3 publications

(1 citation statement)

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“…Special mechanical devices were necessary to use the EdgeWrite and McSig systems. Similarly, hapticbased systems have also been developed to teach Arabic [35], and Kanji [36] handwriting. To avoid this problem, Wu et al [37] created a mobile application called LightWrite to teach lowercase English letters and Arabic numerals in a specially designed font using voice-based detailed lessons.…”

Section: Related Workmentioning

confidence: 99%

A Multilingual Handwriting Learning System for Visually Impaired People

Islam,

Jahangir,

Mohim

et al. 2024

IEEE Access

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Visually impaired people have previously been brought into learning and educational systems through various forms of assistive technology, such as haptic feedback systems. Haptic systems generally need expensive equipment and support from sighted teachers. Moreover, the learning has always been carried out with letters of different alphabets mapped into some tactile pattern. Writing is a big concern for the visually impaired as most official work, like signing, is still carried out by conventional handwriting methods. Most of the existing systems are limited to teaching a single language's alphabet and basic grammar or may not provide feedback to let the learners know of their learning progress. Therefore, the objectives of this research are to develop an efficient system that includes voice-over guidance to teach writing in multiple alphabets to visually impaired people and to evaluate the performance of the proposed system. As such, a system was developed for teaching multilingual alphabets to visually impaired people with voice instructions. With the aid of a voice-over guide, learners were able to write letters with a stylus on a graphics pad. The progress assessment of the learners is carried out by an image processing algorithm and scored by a machine learning (ML) model. The Random Forest model was used due to its high accuracy (f1score of 99.8% on test data) among the existing ten different ML algorithms. Finally, the performance and usability of this system were evaluated through an empirical study replicated with 16 participants, including four teachers and twelve visually impaired people. It was found that visually impaired people made fewer attempts to learn handwriting with the proposed system than with the normal handwriting teaching system. 100% of the participants agreed to recommend the system in the future.

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Section: Related Workmentioning

confidence: 99%

A Multilingual Handwriting Learning System for Visually Impaired People

Islam,

Jahangir,

Mohim

et al. 2024

IEEE Access

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μGraph: Haptic Exploration and Editing of 3D Chemical Diagrams

Bernareggi

Ahmetovic

Mascetti

2019

The 21st International ACM SIGACCESS Conference on Computers and Accessibility

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People with visual impairments or blindness (VIB) encounter diffculties in exploring graphical representations that are widely used for the study of STEM subjects. In particular, graphs are used to represent many different scientifc notations: fowcharts, automata, cognitive maps, and more. Among these, structural chemical formulae are characterized by a complex, often 3-dimensional structure, which makes them hard to access and author with traditional assistive tools.We propose µGraph, a multimodal system that combines haptic and speech feedback to enable people with VIB to explore and edit structural chemical formulae. Two main contributions are presented: (i) a novel, non-visual interaction paradigm for exploring graphs and its implementation in the µGraph system, and (ii) an extensive evaluation of the proposed system with 10 participants with VIB showing that µGraph is thoroughly accessible and that the haptic feedback enhances understanding of the geometric properties of a graph.

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User Performance Testing Indicator

Iyawe

2017

Design Solutions for User-Centric Information Systems

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A growing area of research in Human Computer Interaction (HCI) and Human Robotic Interaction (HRI) is the development of haptic-based user performance testing. User performance testing Usability forms a vital part of these test objectives. As a result, diverse usability methods/strategies and test features are being employed. Apparently, with the robustness of haptic-based user performance testing features, user performance still has challenges. With this regard, it is vital to identify the direction and effectiveness of these methods/strategies and test features, and improvements required in the test objectives and evaluation. This chapter seeks to investigate the challenges of user performance and the user performance indicators in some HCI and HRI researches involving haptic-based test, as well as presents a User Performance Indicator Tool (UPIT) as a test validation tool to aid designers/testers in enhancing their user performance test and test evaluation outcomes.

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Towards the development of haptic-based interface for teaching visually impaired arabic handwriting

Abstract: This paper serves to introduce an initial haptic based system for teaching handwriting of Arabic letters to students with visual impairments. The proposed system provides full and partial guidance through haptic playback. In addition, the system automatically evaluates student progress.

Cited by 3 publications

References 4 publications

A Multilingual Handwriting Learning System for Visually Impaired People

A Multilingual Handwriting Learning System for Visually Impaired People

μGraph: Haptic Exploration and Editing of 3D Chemical Diagrams

User Performance Testing Indicator

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