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Disability
Published in Céline McKeown, Office Ergonomics and Human Factors, 2018
Virtual keyboards are widely used to help people with disabilities to interact both with desktop and laptop computers. Most of these keyboards have a set of features that facilitate the writing process, such as word completion methods (Li and Hirst 2005). A virtual keyboard for mobile devices, called BigKey has been developed (Faraj et al. 2009) to be used by people with motor disabilities. BigKey makes the keys of a virtual keyboard easier to access as it predicts what the next likely key to be used will be. There are alternatives to virtual keyboards that simplify text entry in mobile devices including interaction methods which work by recognising gestures (Wobbrock et al. 2004).
Influence of virtual keyboard design and usage posture on typing performance and muscle activity during tablet interaction
Published in Ergonomics, 2020
Ming-I Brandon Lin, Ruei-Hong Hong, Yu-Ping Huang
This study demonstrated that the split virtual keyboard allows better task performance with reduced muscle activity of the right EDC muscle than the standard virtual keyboard when performing text entry activities with two hands on a tablet computer. Using tablets on a desk increased muscle activity in the neck and shoulder region, whereas typing with tablets on the lap showed greater and more dynamic EDC and FDS muscle activity and increased typing speed. Regarding the duration of tablet use, the typing performance decreased over time with a significant increase in right CES muscle activity. These findings suggest that the effects of usage postures on the musculoskeletal system were further compounded by the virtual keyboard design. To improve the user experience of using tablets outside a traditional office setting, it is important to gain a better understanding of the relationships between design features of virtual keyboards, task performance, and musculoskeletal outcomes incurred under various usage scenarios.
TapSix: A Palm-Worn Glove with a Low-Cost Camera Sensor that Turns a Tactile Surface into a Six-Key Chorded Keyboard by Detection Finger Taps
Published in International Journal of Human–Computer Interaction, 2020
Dongseok Yang, Kanghee Lee, Younggeun Choi
We evaluated the text entry performance of TapSix using a traditional transcription task. Before the experiment, we demonstrated how to use the four devices and explained the tasks. Participants performed 10 practice trials for each device. The Leapmotion keyboard and Vive stick keyboard needed a virtual keyboard layout on a VR screen, unlike TapSix and Twiddler. However, the users had to learn the letter-to-tap mapping for the non-VR systems. Therefore, the experimental environment was designed such that participants could refer to the letter-to-tap mapping on the right-hand screen, as shown in Figure 11(f). The participants could easily check the letter-to-tap mapping by turning their heads during the evaluation. We only provided the mapping at first and users hardly needed it by the end of the experiments. For the transcription task, participants were instructed to enter the provided texts as quickly and accurately as possible. We also allowed backspace modifications with no auto-correction enabled. The experiment took a total of 5 days at 60 min per day.
Exploring the usability of the text-based CAPTCHA on tablet computers
Published in Connection Science, 2019
The experiment for the usability analysis of the text-based CAPTCHA on tablet computer was conducted on a population of 125 Internet users who were recruited by email and tested in real-life contexts. All participants had normal or corrected to normal colour vision. The participation in the study was voluntary and all users agreed to an online consent form before participating. In particular, participants were informed that the provided data and their interactions with the system would be processed and anonymously used as a part of an experimental user study of the research group. No further details about the aim of the study or the type of recorded interaction data (e.g. time to complete the challenge) were provided to the participants in order to avoid bias effects. After that, an investigator asked each user to solve two types of text-based CAPTCHA on tablet computer: (i) containing only text and (ii) containing only numbers. The used CAPTCHAs were composed of six lowercased alphanumeric characters altered with complex coloured background, waving and extra lines in background (see Figures 1 and 2). The used tablet computer had a Liquid Crystal Display (LCD) 7” wide in its diagonal, internal virtual keyboard and Android operating system. The investigator measured using a chronometer the CAPTCHA response time from the beginning to the end of the process. This time was given in seconds. After solving the CAPTCHA, it was checked if the result is accurate. If the CAPTCHA was not successfully solved, then the success was given as no. Otherwise, the success in solving the CAPTCHA was given as yes.