Pickup usability dominates: a brief history of mobile text entry research and adoption

Text entry on mobile devices (e.g. phones and PDAs) has been a research challenge since devices shrank below laptop size: mobile devices are simply too small to have a traditional full-size keyboard. There has been a profusion of research into text entry techniques for smaller keyboards and touch screens: some of which have become mainstream, while others have not lived up to early expectations. As the mobile phone industry moves to mainstream touch screen interaction we will review the range of input techniques for mobiles, together with evaluations that have taken place to assess their validity: from theoretical modelling through to formal usability experiments. We also report initial results on iPhone text entry speed

Optimizing Human Performance in Mobile Text Entry

Although text entry on mobile phones is abundant, research strives to achieve desktop typing performance "on the go". But how can researchers evaluate new and existing mobile text entry techniques? How can they ensure that evaluations are conducted in a consistent manner that facilitates comparison? What forms of input are possible on a mobile device? Do the audio and haptic feedback options with most touchscreen keyboards affect performance? What influences users' preference for one feedback or another? Can rearranging the characters and keys of a keyboard improve performance? This dissertation answers these questions and more. The developed TEMA software allows researchers to evaluate mobile text entry methods in an easy, detailed, and consistent manner. Many in academia and industry have adopted it. TEMA was used to evaluate a typical QWERTY keyboard with multiple options for audio and haptic feedback. Though feedback did not have a significant effect on performance, a survey revealed that users' choice of feedback is influenced by social and technical factors. Another study using TEMA showed that novice users entered text faster using a tapping technique than with a gesture or handwriting technique. This motivated rearranging the keys and characters to create a new keyboard, MIME, that would provide better performance for expert users. Data on character frequency and key selection times were gathered and used to design MIME. A longitudinal user study using TEMA revealed an entry speed of 17 wpm and a total error rate of 1.7% for MIME, compared to 23 wpm and 5.2% for QWERTY. Although MIME's entry speed did not surpass QWERTY's during the study, it is projected to do so after twelve hours of practice. MIME's error rate was consistently low and significantly lower than QWERTY's. In addition, participants found MIME more comfortable to use, with some reporting hand soreness after using QWERTY for extended periods

RotoSwype : word-gesture typing using a ring

Funding: NSERC Discovery Grant #2018-05187, the Canada Foundation for Innovation Infrastructure Fund “Facility for Fully Interactive Physio-digital Spaces” (#33151), and Ontario Early Researcher Award #ER16-12-184.We propose RotoSwype, a technique for word-gesture typing using the orientation of a ring worn on the index finger. RotoSwype enables one-handed text-input without encumbering the hand with a device, a desirable quality in many scenarios, including virtual or augmented reality. The method is evaluated using two arm positions: with the hand raised up with the palm parallel to the ground; and with the hand resting at the side with the palm facing the body. A five-day study finds both hand positions achieved speeds of at least 14 words-per-minute (WPM) with uncorrected error rates near 1%, outperforming previous comparable techniques.Postprin

Enabling single-handed interaction in mobile and wearable computing

Mobile and wearable computing are increasingly pervasive as people carry and use personal devices in everyday life. Screen sizes of such devices are becoming larger and smaller to accommodate both intimate and practical uses. Some mobile device screens are becoming larger to accommodate new experiences (e.g., phablet, tablet, eReader), whereas screen sizes on wearable devices are becoming smaller to allow them to fit into more places (e.g., smartwatch, wrist-band and eye-wear). However, these trends are making it difficult to use such devices with only one hand due to their placement, limited thumb reach and the fat-finger problem. This is especially true as there are many occasions when a user’s other hand is occupied (encumbered) or not available. This thesis work explores, creates and studies novel interaction techniques that enable effective single-hand usage on mobile and wearable devices, empowering users to achieve more with their smart devices when only one hand is available.Postprin

Light on horizontal interactive surfaces: Input space for tabletop computing

In the last 25 years we have witnessed the rise and growth of interactive tabletop research, both in academic and in industrial settings. The rising demand for the digital support of human activities motivated the need to bring computational power to table surfaces. In this article, we review the state of the art of tabletop computing, highlighting core aspects that frame the input space of interactive tabletops: (a) developments in hardware technologies that have caused the proliferation of interactive horizontal surfaces and (b) issues related to new classes of interaction modalities (multitouch, tangible, and touchless). A classification is presented that aims to give a detailed view of the current development of this research area and define opportunities and challenges for novel touch- and gesture-based interactions between the human and the surrounding computational environment. © 2014 ACM.This work has been funded by Integra (Amper Sistemas and CDTI, Spanish Ministry of Science and Innovation) and TIPEx (TIN2010-19859-C03-01) projects and Programa de Becas y Ayudas para la Realización de Estudios Oficiales de Máster y Doctorado en la Universidad Carlos III de Madrid, 2010

Text Entry in Immersive Head-Mounted Display-Based Virtual Reality Using Standard Keyboards

We study the performance and user experience of two popular mainstream text entry devices, desktop keyboards and touchscreen keyboards, for use in Virtual Reality (VR) applications. We discuss the limitations arising from limited visual feedback, and examine the efficiency of different strategies of use. We analyze a total of 24 hours of typing data in VR from 24 participants and find that novice users are able to retain about 60% of their typing speed on a desktop keyboard and about 40-45\% of their typing speed on a touchscreen keyboard. We also find no significant learning effects, indicating that users can transfer their typing skills fast into VR. Besides investigating baseline performances, we study the position in which keyboards and hands are rendered in space. We find that this does not adversely affect performance for desktop keyboard typing and results in a performance trade-off for touchscreen keyboard typing

Beginners Performance with MessagEase and QWERTY

With the increased use of mobile phones, interest in text entry with them has also amplified. Many new mobile phones are equipped with a QWERTY keypad; new methods to surpass the QWERTY performance are also being developed. This thesis compares user performance of virtual QWERTY keypad to MessagEase. MessagEase uses 9 keys and can therefore be used even on very small touch displays. 9 characters are entered with tapping and the rest with a tap-and-slide gesture. An experiment was conducted with 10 participants transcribing text with both text entry techniques. The experiment consisted of three sessions. In each session, the participants transcribed 30 phrases in total - 15 phrases using each text entry technique. Responses to the System Usability Scale (SUS) for each text entry technique and informal interview data were also collected. From a Repeated-measures analysis of variance a significant effect of the text entry method on text entry rate was seen (F1,19= 47.140, p < 0.0001). The effect of the session (i.e. learning) was also statistically significant (F2,18= 3.631, p = 0.047).The interaction of the session and method was also statistically significant (F2,18= 10.286, p = 0.001) indicating different learning rates. Average text entry speed with MessagEase was 7.43 words per minute (wpm) in the first session and 10.96 wpm in the third session. Likewise, text entry speed with the QWERTY soft keyboard was 17.75 wpm in the first session and 17.16 wpm in the third session. No significant difference was found in the error rates. Keywords: text entry method, MessagEase, QWERT

Text Entry Performance and Situation Awareness of a Joint Optical See-Through Head-Mounted Display and Smartphone System

Optical see-through head-mounted displays (OST HMDs) are a popular output medium for mobile Augmented Reality (AR) applications. To date, they lack efficient text entry techniques. Smartphones are a major text entry medium in mobile contexts but attentional demands can contribute to accidents while typing on the go. Mobile multi-display ecologies, such as combined OST HMD-smartphone systems, promise performance and situation awareness benefits over single-device use. We study the joint performance of text entry on mobile phones with text output on optical see-through head-mounted displays. A series of five experiments with a total of 86 participants indicate that, as of today, the challenges in such a joint interactive system outweigh the potential benefits.Comment: To appear in IEEE Transactions on Visualization and Computer Graphics On page(s): 1-17 Print ISSN: 1077-2626 Online ISSN: 1077-262

Predicting and Reducing the Impact of Errors in Character-Based Text Entry

This dissertation focuses on the effect of errors in character-based text entry techniques. The effect of errors is targeted from theoretical, behavioral, and practical standpoints. This document starts with a review of the existing literature. It then presents results of a user study that investigated the effect of different error correction conditions on popular text entry performance metrics. Results showed that the way errors are handled has a significant effect on all frequently used error metrics. The outcomes also provided an understanding of how users notice and correct errors. Building on this, the dissertation then presents a new high-level and method-agnostic model for predicting the cost of error correction with a given text entry technique. Unlike the existing models, it accounts for both human and system factors and is general enough to be used with most character-based techniques. A user study verified the model through measuring the effects of a faulty keyboard on text entry performance. Subsequently, the work then explores the potential user adaptation to a gesture recognizer’s misrecognitions in two user studies. Results revealed that users gradually adapt to misrecognition errors by replacing the erroneous gestures with alternative ones, if available. Also, users adapt to a frequently misrecognized gesture faster if it occurs more frequently than the other error-prone gestures. Finally, this work presents a new hybrid approach to simulate pressure detection on standard touchscreens. The new approach combines the existing touch-point- and time-based methods. Results of two user studies showed that it can simulate pressure detection more reliably for at least two pressure levels: regular (~1 N) and extra (~3 N). Then, a new pressure-based text entry technique is presented that does not require tapping outside the virtual keyboard to reject an incorrect or unwanted prediction. Instead, the technique requires users to apply extra pressure for the tap on the next target key. The performance of the new technique was compared with the conventional technique in a user study. Results showed that for inputting short English phrases with 10% non-dictionary words, the new technique increases entry speed by 9% and decreases error rates by 25%. Also, most users (83%) favor the new technique over the conventional one. Together, the research presented in this dissertation gives more insight into on how errors affect text entry and also presents improved text entry methods