A Review of Design and Evaluation Practices in Mobile Text Entry for Visually Impaired and Blind Persons
<p>The Braille cell (<b>left</b>) and the pattern representing the letter <span class="html-italic">t</span> (<b>right</b>).</p> "> Figure 2
<p>Examples of Braille input interaction styles using touchscreens.</p> "> Figure 3
<p>Research selection process.</p> "> Figure 4
<p>Design approaches for prototypes aimed at VIBPs and non-impaired persons.</p> "> Figure 5
<p>Participation levels in experiments reported by studies.</p> "> Figure 6
<p>Participant group diversity in terms of age and gender.</p> "> Figure 7
<p>Evaluation environment settings for prototypes aimed at VIBPs and non-impaired persons.</p> "> Figure 8
<p>Evaluation design aspects for prototypes aimed at VIBPs and non-impaired persons.</p> "> Figure 9
<p>Proportion of studies using WPM or other text entry speed metrics.</p> "> Figure 10
<p>Proportion of studies using each of the error metrics.</p> ">
Abstract
:1. Introduction
The Braille Writing System
2. Survey Methodology
2.1. Research Questions
- RQ1: What are the design approaches used in text entry research for VIBPs (e.g., theory driven, use of human participants in the design process or use of computational methods)?
- RQ2: What are the community standards and practices in conducting text entry evaluations with VIBPs (e.g., sample sizes, evaluation tasks, sample characteristics, study design and materials and metrics captured during evaluation)?
- RQ3: Do the design and evaluation practices for text entry methods for VIBPs differ from the community standards in research addressing non-impaired persons?
2.2. Search Strategy
2.2.1. Planning Stage
- The publication year was 2013 or later;
- The publication was a scientific article published in reputable conference proceedings or journals;
- The publication was written in English (for example, a few papers provided an English title and abstract, but the rest of the paper was written in another language).
- Does the paper propose a prototype text entry method or input support system (e.g., error correction) for mobile devices (smartphone, tablet or smartwatch)?
- Is the proposed prototype intended for use by VIBPs?
- Do the researchers conduct at least one evaluation study with users (non-impaired or VIBPs)?
- Do the researchers mention details about the evaluation procedure (study environment, task type, etc.)?
- Do the researchers present evaluation results (e.g., typing speed or error metrics)?
2.2.2. Conducting Stage
2.2.3. Analysis Stage
- Prototype
- Writing script which the user could employ with the prototype (see Section 3.1.1);
- Input style: single-tap, chording or gestural (see Section 3.1.1);
- Target device (smartphone, tablet or smartwatch).
- Design Phase
- Main design approach (see Section 3.1.2);
- Use of focus groups in the design;
- Use of pilot study to inform the design;
- Number of non-impaired participants in the pilot;
- Number of blind participants in the pilot;
- Number of vision-impaired participants in pilot.
- Main Study Participants
- Total number of participants;
- Number of non-impaired participants;
- Number of blind participants;
- Number of vision-impaired participants;
- Number of female participants;
- Participant ages (minimum, maximum, average and standard deviation).
- Main Study Design
- Ethics approval;
- Study environment (single lab trial, repeated lab trials and field);
- Method of participant familiarization;
- Type of task performed in the study;
- Phrase set used (in the case of transcription tasks);
- Phrase set language (in the case of transcription tasks);
- Number of phrases to be entered (in case of transcription task);
- Corrections allowed during entry.
- Main Study Metrics
- Text entry speed metric(s) used in analysis
- Error metric(s) used in analysis.
- Post-Experiment
- Use of post- or mid-experiment questionnaires;
- Use of post- or mid-experiment interviews.
2.2.4. Evaluation Studies for Non-Impaired Persons
- Does the paper propose a text entry method or input support system (e.g., error correction) for mobile devices (smartphone, tablet or smartwatch)?
- Do the researchers conduct at least one study with users without vision impairment or blindness?
- Do the researchers mention the details of the evaluation procedure (study environment, task type, etc.)?
- Do the researchers present evaluation results (e.g., speed typing metric)?
3. Results
3.1. Design Methods
3.1.1. Design Concept and Target Device
Publication | Input Symbology 1 | Single Tap | Chorded Entry | Gesture Entry |
---|---|---|---|---|
Anu Bharath et al. [43] | AC | • | • | |
Billah et al. [39] | AC | • | • | |
Buzzi et al. [44] | AC | • | • | |
Gaines et al. [45] | AC | • | • | |
Lai et al. [46] | AC | • | ||
Lottridge et al. [38] | AC | • | ||
Rakhmetulla and Arif [47] | AC | • | • | |
Raynal and Roussille [48] | AC | • | • | |
Samanta and Chakraborty [49] | AC | • | • | |
Shi et al. [50] | AC | • | ||
Alhussaini et al. [32] | BC | • | ||
Alnfiai and Sampalli [51] | BC | • | ||
Alnfiai and Sampalli [37] | BC | • | • | |
Alnfiai and Sampali [52] | BC | • | ||
Dobosz and Szuścik [53] | BC | • | • | |
Šepić et al. [54] | BC | • | • | |
Facanha et al. [55] | BC | • | • | |
Luna et al. [34] | BC | • | • | • |
Luna et al. [35] | BC | • | • | • |
Li et al. [56] | BC | • | ||
Mattheiss et al. [36] | BC | • | • | |
Southern et al. [33] | BC | • | ||
Zhang and Zeng [57] | BC | • | • | |
Heni et al. [40] | CS | • |
3.1.2. Design Methodology
- User-led: This approach produces designs by involving users in all process stages, including before the conceptual phase, through methodologies such as human-centered design, design thinking or activity-centered design;
- Designer-led: This approach produces designs based on designer inspiration. Designs are guided by classic human–computer interaction theory and principles or are informed by previous work without any involvement from users in the conceptual phase, although users may be involved in prototype refinement activities;
- Computation-led: This approach produces designs by making significant use of data-driven or computational optimization approaches without any direct involvement from users, other than users serving as the source of raw data fed into the design process.
- Combination: designs which are the product of combining user involvement and computational methods as part of the design process.
3.2. Evaluation Methods
3.2.1. Participants
3.2.2. Study Environment
3.2.3. Evaluation Metrics
3.3. Comparisons with Text Entry Research for Non-Impaired Persons
3.3.1. Design Methodology
3.3.2. Participants
3.3.3. Study Environment
3.3.4. Evaluation Metrics
4. Discussion
4.1. Design Approaches
4.2. Evaluation Practice
4.3. Limitations
5. Conclusions
Funding
Conflicts of Interest
References
- Allmann, K.; Blank, G. Rethinking Digital Skills in the Era of Compulsory Computing: Methods, Measurement, Policy and Theory. Inform. Commun. Soc. 2021, 24, 633–648. [Google Scholar] [CrossRef]
- Reddy, P.; Sharma, B.; Chaudhary, K. Digital Literacy: A Review of Literature. Int. J. Technoethics (IJT) 2020, 11, 65–94. [Google Scholar] [CrossRef]
- de Araujo, M.H.; Reinhard, N. Substituting Computers for Mobile Phones? An Analysis of the Effect of Device Divide on Digital Skills in Brazil. In Proceedings of the Electronic Participation, San Benedetto Del Tronto, Italy, 2–4 September 2019; Panagiotopoulos, P., Edelmann, N., Glassey, O., Misuraca, G., Parycek, P., Lampoltshammer, T., Re, B., Eds.; Springer International Publishing: Cham, Switzerland, 2019. Lecture Notes in Computer Science. pp. 142–154. [Google Scholar] [CrossRef]
- Lee, H.; Park, N.; Hwang, Y. A New Dimension of the Digital Divide: Exploring the Relationship between Broadband Connection, Smartphone Use and Communication Competence. Telemat. Inform. 2015, 32, 45–56. [Google Scholar] [CrossRef]
- Kumar, D.; Hemmige, V.; Kallen, M.A.; Giordano, T.P.; Arya, M. Mobile Phones May Not Bridge the Digital Divide: A Look at Mobile Phone Literacy in an Underserved Patient Population. Cureus 2019, 11. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Komninos, A.; Simou, I. Text Entry Research-the Last 5 Years (2018–2022). In Proceedings of the TEXT2030 Workshop Held at MobileHCI’22, Vancouver, BC, Canada, 1 October 2022. [Google Scholar]
- Flaxman, S.R.; Bourne, R.R.A.; Resnikoff, S.; Ackland, P.; Braithwaite, T.; Cicinelli, M.V.; Das, A.; Jonas, J.B.; Keeffe, J.; Kempen, J.H.; et al. Global Causes of Blindness and Distance Vision Impairment 1990–2020: A Systematic Review and Meta-Analysis. Lancet Glob. Health 2017, 5, e1221–e1234. [Google Scholar] [CrossRef] [Green Version]
- International Classification of Diseases 11th Revision (ICD-11). Available online: https://icd.who.int/en (accessed on 7 February 2023).
- Steinmetz, J.D.; Bourne, R.R.A.; Briant, P.S.; Flaxman, S.R.; Taylor, H.R.B.; Jonas, J.B.; Abdoli, A.A.; Abrha, W.A.; Abualhasan, A.; Abu-Gharbieh, E.G.; et al. Causes of Blindness and Vision Impairment in 2020 and Trends over 30 Years, and Prevalence of Avoidable Blindness in Relation to VISION 2020: The Right to Sight: An Analysis for the Global Burden of Disease Study. Lancet Glob. Health 2021, 9, e144–e160. [Google Scholar] [CrossRef]
- Elsman, E.B.M.; Al Baaj, M.; van Rens, G.H.M.B.; Sijbrandi, W.; van den Broek, E.G.C.; van der Aa, H.P.A.; Schakel, W.; Heymans, M.W.; de Vries, R.; Vervloed, M.P.J.; et al. Interventions to Improve Functioning, Participation, and Quality of Life in Children with Visual Impairment: A Systematic Review. Surv. Ophthalmol. 2019, 64, 512–557. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Brown, R.L.; Barrett, A.E. Visual Impairment and Quality of Life Among Older Adults: An Examination of Explanations for the Relationship. J. Gerontol. Ser. B 2011, 66B, 364–373. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Demmin, D.L.; Silverstein, S.M. Visual Impairment and Mental Health: Unmet Needs and Treatment Options. Clin. Ophthalmol. 2020, 14, 4229–4251. [Google Scholar] [CrossRef] [PubMed]
- Vu, H.T.V.; Keeffe, J.E.; McCarty, C.A.; Taylor, H.R. Impact of Unilateral and Bilateral Vision Loss on Quality of Life. Br. J. Ophthalmol. 2005, 89, 360–363. [Google Scholar] [CrossRef] [Green Version]
- Stefanis, V.; Komninos, A.; Garofalakis, J. Challenges in Mobile Text Entry Using Virtual Keyboards for Low-Vision Users. In Proceedings of the 19th International Conference on Mobile and Ubiquitous Multimedia, Essen, Germany, 22–25 November 2020; Association for Computing Machinery: New York, NY, USA, 2020. MUM ’20. pp. 42–46. [Google Scholar] [CrossRef]
- Siqueira, J.; Soares, F.; Ferreira, D.J.; Silva, C.R.G.; Silva, C.R.G.; Berretta, L.d.O.; Ferreira, C.B.R.; Felix, I.M.; Soares, A.d.S.; da Costa, R.M.; et al. Braille Text Entry on Smartphones: A Systematic Review of the Literature. In Proceedings of the 2016 IEEE 40th Annual Computer Software and Applications Conference (COMPSAC), Atlanta, GA, USA, 10–14 June 2016. [Google Scholar] [CrossRef]
- Shahid, H.; Ali Shah, M.; Dar, B.K.; Fizzah, F. A Review of Smartphone’s Text Entry for Visually Impaired. In Proceedings of the 2018 24th International Conference on Automation and Computing (ICAC), Newcastle upon Tyne, UK, 6–7 September 2018; pp. 1–7. [Google Scholar] [CrossRef]
- Shokat, S.; Riaz, R.; Rizvi, S.S.; Khan, K.; Riaz, F.; Kwon, S.J. Analysis and Evaluation of Braille to Text Conversion Methods. Mob. Inf. Syst. 2020, 2020, 1–14. [Google Scholar] [CrossRef]
- Xiao, Y.; Watson, M. Guidance on Conducting a Systematic Literature Review. J. Plan. Educ. Res. 2019, 39, 93–112. [Google Scholar] [CrossRef]
- Mengist, W.; Soromessa, T.; Legese, G. Method for Conducting Systematic Literature Review and Meta-Analysis for Environmental Science Research. MethodsX 2020, 7, 100777. [Google Scholar] [CrossRef]
- Torres-Carrión, P.V.; González-González, C.S.; Aciar, S.; Rodríguez-Morales, G. Methodology for Systematic Literature Review Applied to Engineering and Education. In Proceedings of the 2018 IEEE Global Engineering Education Conference (EDUCON), Santa Cruz de Tenerife, Spain, 17–20 April 2018; pp. 1364–1373. [Google Scholar] [CrossRef]
- Lame, G. Systematic Literature Reviews: An Introduction. Proc. Des. Soc. Int. Conf. Eng. Des. 2019, 1, 1633–1642. [Google Scholar] [CrossRef] [Green Version]
- Nightingale, A. A Guide to Systematic Literature Reviews. Surgery (Oxford) 2009, 27, 381–384. [Google Scholar] [CrossRef]
- Okoli, C. A Guide to Conducting a Standalone Systematic Literature Review. Commun. Assoc. Inf. Syst. 2015, 37. [Google Scholar] [CrossRef] [Green Version]
- Snyder, H. Literature Review as a Research Methodology: An Overview and Guidelines. J. Bus. Res. 2019, 104, 333–339. [Google Scholar] [CrossRef]
- Liberati, A.; Altman, D.G.; Tetzlaff, J.; Mulrow, C.; Gøtzsche, P.C.; Ioannidis, J.P.A.; Clarke, M.; Devereaux, P.J.; Kleijnen, J.; Moher, D. The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration. PLoS Med. 2009, 6, e1000100. [Google Scholar] [CrossRef]
- PRISMA Statement Checklist. Available online: https://prisma-statement.org/PRISMAStatement/Checklist (accessed on 13 February 2023).
- Tranfield, D.; Denyer, D.; Smart, P. Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review. Br. J. Manag. 2003, 14, 207–222. [Google Scholar] [CrossRef]
- Gusenbauer, M. Google Scholar to Overshadow Them All? Comparing the Sizes of 12 Academic Search Engines and Bibliographic Databases. Scientometrics 2019, 118, 177–214. [Google Scholar] [CrossRef] [Green Version]
- Canalys Newsroom-Majority of Smart Phones Now Have Touch Screens. Available online: https://www.canalys.com/newsroom/majority-smart-phones-now-have-touch-screens (accessed on 13 February 2023).
- Walker, G. Fundamentals of Projected-Capacitive Touch Technology. Available online: https://www.walkermobile.com/Touch_Technologies_Tutorial_Latest_Version.pdf (accessed on 13 February 2023).
- ResearchRabbit. Available online: https://www.researchrabbit.ai (accessed on 13 February 2023).
- Alhussaini, H.; Ludi, S.; Leone, J. An Evaluation of AccessBraille: A Tablet-Based Braille Keyboard for Individuals with Visual Impairments. In HCI International 2015—Posters’ Extended Abstracts; Stephanidis, C., Ed.; Springer International Publishing: Cham, Switzerland, 2015; Volume 529, pp. 369–374. [Google Scholar] [CrossRef]
- Southern, C.; Clawson, J.; Frey, B.; Abowd, G.; Romero, M. An Evaluation of BrailleTouch: Mobile Touchscreen Text Entry for the Visually Impaired. In Proceedings of the 14th International Conference on Human-computer Interaction with Mobile Devices and Services—MobileHCI ’12, San Francisco, CA, USA, 21–24 September 2012; ACM Press: San Francisco, CA, USA, 2012; p. 317. [Google Scholar] [CrossRef] [Green Version]
- Luna, M.M.; de M. N. Soares, F.A.A.; Nascimento, H.A.D.; Quigley, A. Braille Text Entry on Smartwatches: An Evaluation of Methods for Composing the Braille Cell. In Proceedings of the ACM SIGCHI Symposium on Engineering Interactive Computing Systems, Valencia, Spain, 18–21 June 2019; ACM: Valencia, Spain, 2019; pp. 1–6. [Google Scholar] [CrossRef] [Green Version]
- Luna, M.M.; Nascimento, H.A.D.; Quigley, A.; Soares, F. Text Entry for the Blind on Smartwatches: A Study of Braille Code Input Methods for a Novel Device. Univers. Access Inf. Soc. 2022. [Google Scholar] [CrossRef]
- Mattheiss, E.; Regal, G.; Schrammel, J.; Garschall, M.; Tscheligi, M. Dots and Letters: Accessible Braille-Based Text Input for Visually Impaired People on Mobile Touchscreen Devices. In Computers Helping People with Special Needs: 14th International Conference, ICCHP 2014, Paris, France, July 9–11, 2014, Proceedings, Part I 14; Springer: Berlin/Heidelberg, Germany, 2014. [Google Scholar] [CrossRef]
- Alnfiai, M.; Sampalli, S. An Evaluation of SingleTapBraille Keyboard: A Text Entry Method That Utilizes Braille Patterns on Touchscreen Devices. In Proceedings of the 18th International ACM SIGACCESS Conference on Computers and Accessibility, Reno, NV, USA, 23–26 October 2016; ACM: Reno, NV, USA, 2016; pp. 161–169. [Google Scholar] [CrossRef]
- Lottridge, D.; Yoon, C.; Burton, D.; Wang, C.; Kaye, J. Ally: Understanding Text Messaging to Build a Better Onscreen Keyboard for Blind People. ACM Trans. Access. Comput. 2022, 15, 3533707. [Google Scholar] [CrossRef]
- Billah, S.M.; Ko, Y.J.; Ashok, V.; Bi, X.; Ramakrishnan, I. Accessible Gesture Typing for Non-Visual Text Entry on Smartphones. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Scotland, UK, 4–9 May 2019; Association for Computing Machinery: New York, NY, USA, 2019. CHI ’19. pp. 1–12. [Google Scholar] [CrossRef]
- Heni, S.; Abdallah, W.; Archambault, D.; Archambault, D.; Archambault, D.; Uzan, G.; Bouhlel, M.S. An Empirical Evaluation of MoonTouch: A Soft Keyboard for Visually Impaired People. In Computers Helping People with Special Needs: 15th International Conference, ICCHP 2016, Linz, Austria, July 13–15, 2016, Proceedings, Part II 15; Springer: Berlin/Heidelberg, Germany, 2016. [Google Scholar] [CrossRef]
- Goldberg, D.; Richardson, C. Touch-Typing with a Stylus. In Proceedings of the INTERACT ’93 and CHI ’93 Conference on Human Factors in Computing Systems, Amsterdam, The Netherlands, 24–29 April 1993; Association for Computing Machinery: New York, NY, USA, 1993. CHI ’93. pp. 80–87. [Google Scholar] [CrossRef]
- Wu, Z.; Yu, C.; Xu, X.; Wei, T.; Zou, T.; Wang, R.; Shi, Y. LightWrite: Teach Handwriting to The Visually Impaired with A Smartphone. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, Yokohama, Japan, 8–13 May 2021; Association for Computing Machinery: New York, NY, USA, 2021. CHI ’21. pp. 1–15. [Google Scholar] [CrossRef]
- Anu Bharath, P.; Jadhav, C.; Ahire, S.; Joshi, M.; Ahirwar, R.; Joshi, A. Performance of Accessible Gesture-Based Indic Keyboard. In Proceedings of the Human-Computer Interaction—INTERACT 2017, Mumbai, India, 25–29 September 2017; Bernhaupt, R., Dalvi, G., Joshi, A.K., Balkrishan, D., O’Neill, J., Winckler, M., Eds.; Springer International Publishing: Cham, Switzerland, 2017. Lecture Notes in Computer Science. pp. 205–220. [Google Scholar] [CrossRef] [Green Version]
- Buzzi, M.C.; Buzzi, M.; Leporini, B.; Trujillo, A. Designing a Text Entry Multimodal Keypad for Blind Users of Touchscreen Mobile Phones. In Proceedings of the 16th International ACM SIGACCESS Conference on Computers & Accessibility—ASSETS ’14, Rochester, NY, USA, 20–22 October 2014; ACM Press: Rochester, NY, USA, 2014; pp. 131–136. [Google Scholar] [CrossRef]
- Gaines, D. Exploring an Ambiguous Technique for Eyes-Free Mobile Text Entry. In Proceedings of the 20th International ACM SIGACCESS Conference on Computers and Accessibility, Galway, Ireland, 22–24 October 2018; Association for Computing Machinery: New York, NY, USA, 2018. ASSETS ’18. pp. 471–473. [Google Scholar] [CrossRef]
- Lai, J.; Zhang, D.; Wang, S.; Kilic, I.D.Y.; Zhou, L. ThumbStroke: A Virtual Keyboard in Support of Sight-Free and One-Handed Text Entry on Touchscreen Mobile Devices. ACM Trans. Manag. Inf. Syst. 2019, 10, 1–19. [Google Scholar] [CrossRef]
- Rakhmetulla, G.; Arif, A.S. Senorita: A Chorded Keyboard for Sighted, Low Vision, and Blind Mobile Users. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, Honolulu, HI, USA, 25–30 April 2020; ACM: Honolulu, HI, USA, 2020; pp. 1–13. [Google Scholar] [CrossRef]
- Raynal, M.; Roussille, P. DUCK: A DeDUCtive Soft Keyboard for Visually Impaired Users. In Harnessing the Power of Technology to Improve Lives; IOS Press: Amsterdam, The Netherlands, 2017; pp. 902–909. [Google Scholar] [CrossRef]
- Samanta, D.; Chakraborty, T. VectorEntry: Text Entry Mechanism Using Handheld Touch-Enabled Mobile Devices for People with Visual Impairments. ACM Trans. Access. Comput. 2020, 13, 1–29. [Google Scholar] [CrossRef]
- Shi, W.; Yu, C.; Fan, S.; Wang, F.; Wang, T.; Yi, X.; Bi, X.; Shi, Y. VIPBoard: Improving Screen-Reader Keyboard for Visually Impaired People with Character-Level Auto Correction. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Glasgow, Scotland, UK, 4–9 May 2019; ACM: Glasgow, UK, 2019; pp. 1–12. [Google Scholar] [CrossRef]
- Alnfiai, M.; Sampalli, S. SingleTapBraille: Developing a Text Entry Method Based on Braille Patterns Using a Single Tap. Procedia Comput. Sci. 2016, 94, 248–255. [Google Scholar] [CrossRef] [Green Version]
- Alnfiai, M.; Sampali, S. An Evaluation of the BrailleEnter Keyboard: An Input Method Based on Braille Patterns for Touchscreen Devices. In Proceedings of the 2017 International Conference on Computer and Applications (ICCA), Doha, United Arab Emirates, 6–7 September 2017; pp. 107–119. [Google Scholar] [CrossRef]
- Dobosz, K.; Szuścik, M. OneHandBraille: An Alternative Virtual Keyboard for Blind People. In Man-Machine Interactions 5; Gruca, A., Czachórski, T., Harezlak, K., Kozielski, S., Piotrowska, A., Eds.; Springer International Publishing: Cham, Switzerland, 2018; Volume 659, pp. 62–71. [Google Scholar] [CrossRef]
- Šepić, B.; Ghanem, A.; Vogel, S. BrailleEasy: One-handed Braille Keyboard for Smartphones. Assist. Technol. 2015, 1030–1035. [Google Scholar] [CrossRef]
- Façanha, A.R.; Viana, W.; Pequeno, M.C.; Campos, M.d.B.; Sánchez, J. Touchscreen Mobile Phones Virtual Keyboarding for People with Visual Disabilities. In Human-Computer Interaction. Applications and Services: 16th International Conference, HCI International 2014, Heraklion, Crete, Greece, June 22–27, 2014, Proceedings, Part III 16; Springer: Berlin/Heidelberg, Germany, 2014. [Google Scholar] [CrossRef]
- Li, M.; Fan, M.; Truong, K.N. BrailleSketch: A Gesture-based Text Input Method for People with Visual Impairments. In Proceedings of the 19th International ACM SIGACCESS Conference on Computers and Accessibility, Baltimore, MD, USA, 20 October–1 November 2017; ACM: Baltimore, MD, USA, 2017; pp. 12–21. [Google Scholar] [CrossRef] [Green Version]
- Zhang, J.; Zeng, X. Multi-Touch Gesture Recognition of Braille Input Based on Petri Net and RBF Net. Multimed. Tools Appl. 2022, 81, 19395–19413. [Google Scholar] [CrossRef]
- Saffer, D. Designing for Interaction: Creating Innovative Applications and Devices; New Riders: Indianapolis, IN, USA, 2010. [Google Scholar]
- Oulasvirta, A. Optimizing User Interfaces for Human Performance. In Proceedings of the Intelligent Human Computer Interaction, Paris, France, 11–13 December 2017; Horain, P., Achard, C., Mallem, M., Eds.; Springer International Publishing: Cham, Switzerland, 2017. Lecture Notes in Computer Science. pp. 3–7. [Google Scholar] [CrossRef] [Green Version]
- Dunlop, M.; Levine, J. Multidimensional Pareto Optimization of Touchscreen Keyboards for Speed, Familiarity and Improved Spell Checking. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Austin, TX, USA, 5–10 May 2012; Association for Computing Machinery: New York, NY, USA, 2012. CHI ’12. pp. 2669–2678. [Google Scholar] [CrossRef] [Green Version]
- Feit, A.M. Computational Design of Input Methods. In Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, Denver, CO, USA, 6–11 May 2017; Association for Computing Machinery: New York, NY, USA, 2017. CHI EA ’17. pp. 274–279. [Google Scholar] [CrossRef]
- van Turnhout, K.; Bennis, A.; Craenmehr, S.; Holwerda, R.; Jacobs, M.; Niels, R.; Zaad, L.; Hoppenbrouwers, S.; Lenior, D.; Bakker, R. Design Patterns for Mixed-Method Research in HCI. In Proceedings of the 8th Nordic Conference on Human-Computer Interaction: Fun, Fast, Foundational, Helsinki, Finland, 26–30 October 2014; Association for Computing Machinery: New York, NY, USA, 2014. NordiCHI ’14. pp. 361–370. [Google Scholar] [CrossRef] [Green Version]
- Mattheiss, E.; Regal, G.; Schrammel, J.; Garschall, M.; Tscheligi, M. EdgeBraille: Braille-based Text Input for Touch Devices. J. Assist. Technol. 2015, 9, 147–158. [Google Scholar] [CrossRef]
- Vertanen, K.; Kristensson, P.O. Complementing Text Entry Evaluations with a Composition Task. ACM Trans. -Comput.-Hum. Interact. 2014, 21, 1–33. [Google Scholar] [CrossRef] [Green Version]
- MacKenzie, I.S.; Soukoreff, R.W. Phrase Sets for Evaluating Text Entry Techniques. In Proceedings of the CHI ’03 Extended Abstracts on Human Factors in Computing Systems, Ft. Lauderdale, FL, USA, 5–10 April 2003; Association for Computing Machinery: New York, NY, USA, 2003. CHI EA ’03. pp. 754–755. [Google Scholar] [CrossRef] [Green Version]
- Yi, X.; Yu, C.; Shi, W.; Bi, X.; Shi, Y. Word Clarity as a Metric in Sampling Keyboard Test Sets. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, Denver, CO, USA, 6–11 May 2017; Association for Computing Machinery: New York, NY, USA, 2017. CHI ’17. pp. 4216–4228. [Google Scholar] [CrossRef]
- Soukoreff, R.W.; MacKenzie, I.S. Recent Developments in Text-Entry Error Rate Measurement. In Proceedings of the CHI ’04 Extended Abstracts on Human Factors in Computing Systems, Vienna, Austria, 24–29 April 2004; Association for Computing Machinery: New York, NY, USA, 2004. CHI EA ’04. pp. 1425–1428. [Google Scholar] [CrossRef]
- Arif, A.S.; Stuerzlinger, W. Analysis of Text Entry Performance Metrics. In Proceedings of the 2009 IEEE Toronto International Conference Science and Technology for Humanity (TIC-STH), Toronto, ON, Canada, 26–27 September 2009; pp. 100–105. [Google Scholar] [CrossRef]
- MacKenzie, I.S.; Soukoreff, R.W. Text Entry for Mobile Computing: Models and Methods, Theory and Practice. Hum. Comput. Interact. 2002, 17, 147–198. [Google Scholar] [CrossRef]
- MacKenzie, I.S.; Tanaka-Ishii, K. Text Entry Systems: Mobility, Accessibility, Universality; Morgan Kaufmann Publishers Inc.: San Francisco, CA, USA, 2007. [Google Scholar]
- Lee, D.; Kim, J.; Oakley, I. FingerText: Exploring and Optimizing Performance for Wearable, Mobile and One-Handed Typing. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, Yokohama, Japan, 8–13 May 2021; Association for Computing Machinery: New York, NY, USA, 2021. CHI ’21. pp. 1–15. [Google Scholar] [CrossRef]
- Streli, P.; Jiang, J.; Fender, A.R.; Meier, M.; Romat, H.; Holz, C. TapType: Ten-finger Text Entry on Everyday Surfaces via Bayesian Inference. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, New Orleans, LA, USA, 29 April–5 May 2022; Association for Computing Machinery: New York, NY, USA, 2022. CHI ’22. pp. 1–16. [Google Scholar] [CrossRef]
- Wong, P.C.; Zhu, K.; Fu, H. FingerT9: Leveraging Thumb-to-finger Interaction for Same-side-hand Text Entry on Smartwatches. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, Montreal, QC, Canada, 21–26 April 2018; Association for Computing Machinery: New York, NY, USA, 2018. CHI ’18. pp. 1–10. [Google Scholar] [CrossRef]
- Cui, W.; Zhu, S.; Li, Z.; Xu, Z.; Yang, X.D.; Ramakrishnan, I.; Bi, X. BackSwipe: Back-of-device Word-Gesture Interaction on Smartphones. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, Yokohama, Japan, 8–13 May 2021; Association for Computing Machinery: New York, NY, USA, 2021. CHI ’21. pp. 1–12. [Google Scholar] [CrossRef]
- Dobosz, K.; Pindel, M. Increasing the Efficiency of Text Input in the 8pen Method. In Proceedings of the Computers Helping People with Special Needs, Virtual, 9–11 September 2020; Miesenberger, K., Manduchi, R., Covarrubias Rodriguez, M., Peňáz, P., Eds.; Springer International Publishing: Cham, Switzerland, 2020. Lecture Notes in Computer Science. pp. 355–362. [Google Scholar] [CrossRef]
- Xu, Z.; Meng, Y.; Bi, X.; Yang, X.D. Phrase-Gesture Typing on Smartphones. In Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology, Bend, OR, USA, 29 October–2 November 2022; Association for Computing Machinery: New York, NY, USA, 2022. UIST ’22. pp. 1–11. [Google Scholar] [CrossRef]
- Ye, L.; Sandnes, F.E.; MacKenzie, I.S. QB-Gest: Qwerty Bimanual Gestural Input for Eyes-Free Smartphone Text Input. In Proceedings of the Universal Access in Human-Computer Interaction, Design Approaches and Supporting Technologies, Copenhagen, Denmark, 19–24 July 2020; Antona, M., Stephanidis, C., Eds.; Springer International Publishing: Cham, Switzerland, 2020. Lecture Notes in Computer Science. pp. 223–242. [Google Scholar] [CrossRef]
- Zhong, M.; Yu, C.; Wang, Q.; Xu, X.; Shi, Y. ForceBoard: Subtle Text Entry Leveraging Pressure. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, Montreal, QC, Canada, 21–26 April 2018; Association for Computing Machinery: New York, NY, USA, 2018. CHI ’18. pp. 1–10. [Google Scholar] [CrossRef]
- Banovic, N.; Sethapakdi, T.; Hari, Y.; Dey, A.K.; Mankoff, J. The Limits of Expert Text Entry Speed on Mobile Keyboards with Autocorrect. In Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, Taipei, Taiwan, 1–4 October 2019; Association for Computing Machinery: New York, NY, USA, 2019. MobileHCI ’19. pp. 1–12. [Google Scholar] [CrossRef]
- Cui, W.; Zhu, S.; Zhang, M.R.; Schwartz, H.A.; Wobbrock, J.O.; Bi, X. JustCorrect: Intelligent Post Hoc Text Correction Techniques on Smartphones. In Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology, Virtual Event, 20–23 October 2020; Association for Computing Machinery: New York, NY, USA, 2020. UIST ’20. pp. 487–499. [Google Scholar] [CrossRef]
- Li, T.; Quinn, P.; Zhai, S. C-PAK: Correcting and Completing Variable-length Prefix-based Abbreviated Keystrokes. ACM Trans. -Comput.-Hum. Interact. 2022. [Google Scholar] [CrossRef]
- Yadav, A.; Arif, A.S. Effects of Keyboard Background on Mobile Text Entry. In Proceedings of the 17th International Conference on Mobile and Ubiquitous Multimedia, Cairo, Egypt, 25–28 November 2018; Association for Computing Machinery: New York, NY, USA, 2018. MUM ’18. pp. 109–114. [Google Scholar] [CrossRef]
- Zhang, M.R.; Wen, H.; Cui, W.; Zhu, S.; Andrew Schwartz, H.; Bi, X.; Wobbrock, J.O. AI-Driven Intelligent Text Correction Techniques for Mobile Text Entry. In Artificial Intelligence for Human Computer Interaction: A Modern Approach; Li, Y., Hilliges, O., Eds.; Human–Computer Interaction Series; Springer International Publishing: Cham, Switzerland, 2021; pp. 131–168. [Google Scholar] [CrossRef]
- Zhang, M.R.; Wen, H.; Wobbrock, J.O. Type, Then Correct: Intelligent Text Correction Techniques for Mobile Text Entry Using Neural Networks. In Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology, New Orleans, LA, USA, 20–23 October 2019; Association for Computing Machinery: New York, NY, USA, 2019. UIST ’19. pp. 843–855. [Google Scholar] [CrossRef]
- Go, K.; Kikawa, M.; Kinoshita, Y.; Mao, X. Eyes-Free Text Entry with EdgeWrite Alphabets for Round-Face Smartwatches. In Proceedings of the 2019 International Conference on Cyberworlds (CW), Kyoto, Japan, 2–4 October 2019; pp. 183–186. [Google Scholar] [CrossRef]
- Gong, J.; Xu, Z.; Guo, Q.; Seyed, T.; Chen, X.A.; Bi, X.; Yang, X.D. WrisText: One-handed Text Entry on Smartwatch Using Wrist Gestures. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, Montreal, QC, Canada, 21–26 April 2018; Association for Computing Machinery: New York, NY, USA, 2018. CHI ’18. pp. 1–14. [Google Scholar] [CrossRef]
- Lee, L.H.; Yeung, N.Y.; Braud, T.; Li, T.; Su, X.; Hui, P. Force9: Force-assisted Miniature Keyboard on Smart Wearables. In Proceedings of the 2020 International Conference on Multimodal Interaction, Virtual Event, 25–29 October 2020; Association for Computing Machinery: New York, NY, USA, 2020. ICMI ’20. pp. 232–241. [Google Scholar] [CrossRef]
- Rakhmetulla, G.; Arif, A.S. SwipeRing: Gesture Typing on Smartwatches Using a Segmented Qwerty Around the Bezel. In Proceedings of the Graphics Interface 2021, Virtual Event, 27–28 May 2021. [Google Scholar]
- Vertanen, K.; Fletcher, C.; Gaines, D.; Gould, J.; Kristensson, P.O. The Impact of Word, Multiple Word, and Sentence Input on Virtual Keyboard Decoding Performance. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, Montreal, QC, Canada, 21–26 April 2018; Association for Computing Machinery: New York, NY, USA, 2018. CHI ’18. pp. 1–12. [Google Scholar] [CrossRef] [Green Version]
- Vertanen, K.; Gaines, D.; Fletcher, C.; Stanage, A.M.; Watling, R.; Kristensson, P.O. VelociWatch: Designing and Evaluating a Virtual Keyboard for the Input of Challenging Text. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Glasgow, Scotland, UK, 4–9 May 2019; Association for Computing Machinery: New York, NY, USA, 2019. CHI ’19. pp. 1–14. [Google Scholar] [CrossRef]
- De Rosa, M.; Fuccella, V.; Costagliola, G.; Adinolfi, G.; Ciampi, G.; Corsuto, A.; Di Sapia, D. T18: An Ambiguous Keyboard Layout for Smartwatches. In Proceedings of the 2020 IEEE International Conference on Human-Machine Systems (ICHMS), Rome, Italy, 7–9 September 2020; pp. 1–4. [Google Scholar] [CrossRef]
- Jang, R.; Jung, C.; Mohaisen, D.; Lee, K.; Nyang, D. A One-Page Text Entry Method Optimized for Rectangle Smartwatches. IEEE Trans. Mob. Comput. 2022, 21, 3443–3454. [Google Scholar] [CrossRef]
- Min, K.B.; Seo, J. Efficient Typing on Ultrasmall Touch Screens with In Situ Decoder and Visual Feedback. IEEE Access 2021, 9, 75187–75201. [Google Scholar] [CrossRef]
- Xu, Z.; Wong, P.C.; Gong, J.; Wu, T.Y.; Nittala, A.S.; Bi, X.; Steimle, J.; Fu, H.; Zhu, K.; Yang, X.D. TipText: Eyes-Free Text Entry on a Fingertip Keyboard. In Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology, New Orleans, LA, USA, 20–23 October 2019; Association for Computing Machinery: New York, NY, USA, 2019. UIST ’19. pp. 883–899. [Google Scholar] [CrossRef]
- Jones, P.R.; Somoskeöy, T.; Chow-Wing-Bom, H.; Crabb, D.P. Seeing Other Perspectives: Evaluating the Use of Virtual and Augmented Reality to Simulate Visual Impairments (OpenVisSim). npj Digit. Med. 2020, 3, 1–9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Caine, K. Local Standards for Sample Size at CHI. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, San Jose, CA, USA, 7–12 May 2016; ACM: New York, NY, USA, 2016. CHI ’16. pp. 981–992. [Google Scholar] [CrossRef] [Green Version]
- Reyal, S.; Zhai, S.; Kristensson, P.O. Performance and User Experience of Touchscreen and Gesture Keyboards in a Lab Setting and in the Wild. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, Seoul, Republic of Korea, 18–23 April 2015; Association for Computing Machinery: New York, NY, USA, 2015. CHI ’15. pp. 679–688. [Google Scholar] [CrossRef] [Green Version]
- Gaines, D.; Kristensson, P.O.; Vertanen, K. Enhancing the Composition Task in Text Entry Studies: Eliciting Difficult Text and Improving Error Rate Calculation. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, Yokohama, Japan, 8–13 May 2021; Association for Computing Machinery: New York, NY, USA, 2021. CHI ’21. pp. 1–8. [Google Scholar] [CrossRef]
- Nicol, E.; Komninos, A.; Dunlop, M.D. A Participatory Design and Formal Study Investigation into Mobile Text Entry for Older Adults. Int. J. Mob. Hum. Comput. Interact. (IJMHCI) 2016, 8, 20–46. [Google Scholar] [CrossRef] [Green Version]
- Franco-Salvador, M.; Leiva, L.A. Multilingual Phrase Sampling for Text Entry Evaluations. Int. J. -Hum.-Comput. Stud. 2018, 113, 15–31. [Google Scholar] [CrossRef]
- Leiva, L.A.; Sanchis-Trilles, G. Representatively Memorable: Sampling the Right Phrase Set to Get the Text Entry Experiment Right. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Toronto, ON, Canada, 26 April–1 May 2014; Association for Computing Machinery: Toronto, ON, Canada, 2014. CHI ’14. pp. 1709–1712. [Google Scholar] [CrossRef]
- Wyrich, M.; Preikschat, A.; Graziotin, D.; Wagner, S. The Mind Is a Powerful Place: How Showing Code Comprehensibility Metrics Influences Code Understanding. In Proceedings of the 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE), Madrid, Spain, 22–30 May 2021; pp. 512–523. [Google Scholar] [CrossRef]
- Meyer, J.T.; Gassert, R.; Lambercy, O. An Analysis of Usability Evaluation Practices and Contexts of Use in Wearable Robotics. J. Neuroeng. Rehabil. 2021, 18, 170. [Google Scholar] [CrossRef]
Section | Omitted Item | Omitted Subitem(s) |
---|---|---|
Abstract | 2. Abstract | - |
Methods | 10. Data items | 10a |
11. Study risk of bias assessment | - | |
12. Effect measures | - | |
13. Synthesis methods | 13a–13f | |
14. Reporting bias assessment | - | |
15. Certainty assessment | - | |
Results | 16. Study selection | 16b |
18. Risk of bias in studies | - | |
19. Results of individual studies | - | |
20. Results of syntheses | 20a–20d | |
21. Reporting biases | - | |
22. Certainty of evidence | - | |
Other Information | 24. Registration and protocol | 24a–24c |
User-Led | Designer-Led | Computation-Led | Combination |
---|---|---|---|
[44,55] | [32,33,34,35,36,37,40,43,45,46,48,50,51,52,53,54,56,57,63] | - | [38,39,47] |
2 | 19 | 0 | 3 |
Speed | Errors | ||||||||
---|---|---|---|---|---|---|---|---|---|
WPM | Other | ER | CER | NCER | TER | MSD-ER | KSPC | GPC | Other |
[33,35,36,37,38,39,40,45,46,47,49,50,52,53,56] | [38,43,47,48,54,55] | [47] | [37,38,43,45,46,48,49,50,52,56] | [37,38,43,46,50,52,56] | [33,37,38,52,56] | [35,36,37,38,52,53] | [37,38,52] | [32,56] | [32,39,45,47,50,55] |
15 | 6 | 1 | 10 | 7 | 5 | 6 | 3 | 2 | 6 |
Publication | Target Device 1 | Prototype Type | Primary Interaction 2 |
---|---|---|---|
Lee et al. [71] | ED | Virtual keyboard | ST |
Lee et al. [72] | ED | Virtual keyboard | ST |
Lee et al. [73] | ED | Virtual keyboard | ST |
Lee et al. [74] | SP | Gestural entry | GS |
Dobosz and Pindel [75] | SP | Gestural entry | GS |
Xu et al. [76] | SP | Gestural entry | GS |
Ye et al. [77] | SP | Gestural entry | GS |
Zhong et al. [78] | SP | Gestural entry | GS |
Banovic et al. [79] | SP | Input support | ST |
Cui et al. [80] | SP | Input support | ST |
Li et al. [81] | SP | Input support | ST |
Yadav and Arif [82] | SP | Input support | ST |
Zhang et al. [83] | SP | Input support | GS |
Zhang et al. [84] | SP | Input support | GS |
Go et al. [85] | SW | Gestural entry | GS |
Gong et al. [86] | SW | Gestural entry | GS |
Lee et al. [87] | SW | Gestural entry | GS |
Rakhmetulla and Arif [88] | SW | Gestural entry | GS |
Vertanen et al. [89] | SW | Input support | ST |
Vertanen et al. [90] | SW | Input support | ST |
De Rosa et al. [91] | SW | Virtual keyboard | ST |
Jang et al. [92] | SW | Virtual keyboard | ST |
Min and Seo [93] | SW | Virtual keyboard | ST |
Xu et al. [94] | SW | Virtual keyboard | ST |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Komninos, A.; Stefanis, V.; Garofalakis, J. A Review of Design and Evaluation Practices in Mobile Text Entry for Visually Impaired and Blind Persons. Multimodal Technol. Interact. 2023, 7, 22. https://doi.org/10.3390/mti7020022
Komninos A, Stefanis V, Garofalakis J. A Review of Design and Evaluation Practices in Mobile Text Entry for Visually Impaired and Blind Persons. Multimodal Technologies and Interaction. 2023; 7(2):22. https://doi.org/10.3390/mti7020022
Chicago/Turabian StyleKomninos, Andreas, Vassilios Stefanis, and John Garofalakis. 2023. "A Review of Design and Evaluation Practices in Mobile Text Entry for Visually Impaired and Blind Persons" Multimodal Technologies and Interaction 7, no. 2: 22. https://doi.org/10.3390/mti7020022
APA StyleKomninos, A., Stefanis, V., & Garofalakis, J. (2023). A Review of Design and Evaluation Practices in Mobile Text Entry for Visually Impaired and Blind Persons. Multimodal Technologies and Interaction, 7(2), 22. https://doi.org/10.3390/mti7020022