Pickup Usability Dominates

Author(s):  
Mark David Dunlop ◽  
Michelle Montgomery Masters

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.

Author(s):  
Mark David Dunlop ◽  
Michelle Montgomery Masters

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 stylus input: some of which have become mainstream, while others have not lived up to early expectations. This chapter will review the range of input techniques, together with evaluations, that have taken place to assess their validity: from theoretical modelling through to formal usability experiments. Finally, the chapter will discuss criteria for acceptance of new techniques, and how market perceptions can overrule laboratory successes.


2020 ◽  
Vol 4 (ISS) ◽  
pp. 1-16
Author(s):  
Ohoud Alharbi ◽  
Wolfgang Stuerzlinger ◽  
Felix Putze
Keyword(s):  

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3087
Author(s):  
Sandi Ljubic ◽  
Franko Hržić ◽  
Alen Salkanovic ◽  
Ivan Štajduhar

In this paper, we investigate the possibilities for augmenting interaction around the mobile device, with the aim of enabling input techniques that do not rely on typical touch-based gestures. The presented research focuses on utilizing a built-in magnetic field sensor, whose readouts are intentionally affected by moving a strong permanent magnet around a smartphone device. Different approaches for supporting magnet-based Around-Device Interaction are applied, including magnetic field fingerprinting, curve-fitting modeling, and machine learning. We implemented the corresponding proof-of-concept applications that incorporate magnet-based interaction. Namely, text entry is achieved by discrete positioning of the magnet within a keyboard mockup, and free-move pointing is enabled by monitoring the magnet’s continuous movement in real-time. The related solutions successfully expand both the interaction language and the interaction space in front of the device without altering its hardware or involving sophisticated peripherals. A controlled experiment was conducted to evaluate the provided text entry method initially. The obtained results were promising (text entry speed of nine words per minute) and served as a motivation for implementing new interaction modalities. The use of neural networks has shown to be a better approach than curve fitting to support free-move pointing. We demonstrate how neural networks with a very small number of input parameters can be used to provide highly usable pointing with an acceptable level of error (mean absolute error of 3 mm for pointer position on the smartphone display).


Safety ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. 17
Author(s):  
Miroslava Mikusova ◽  
Joanna Wachnicka ◽  
Joanna Zukowska

The topic of the use of mobile devices and headphones on pedestrian crossings is much less explored in comparison to the use of the mobile phone while driving. Recent years have seen many discussions on this issue, especially in foreign countries. The Slovak Republic, however, has not been giving it enough attention (and it is not mentioned in the National Road Safety Plan for the Slovak Republic from 2011 to 2020). This paper aims to draw attention to this issue. It presents basic outputs of a pilot study on pedestrian safety, with a focus on the use of mobile devices and headphones at selected non-signalized pedestrian crossings in three Slovak cities. Overall, 9% of pedestrians used headphones or mobile devices at observed pedestrian crossings (4% of them used headphones, 1% used headphones and at same time used their mobile phone, 2% made phone calls and 2% used their mobile phones). While these numbers can be considered relatively low, the study proved that during weekdays every 2 min someone was using the crossing without fully focusing on crossing the road safely. Another main finding was that although the safety risk at pedestrian crossings is increased by factors such as rush hour traffic or reduced visibility, pedestrian behavior related to the use of mobile phones and headphones does not change. A safety assessment was also carried out at the crossings. The results show that pedestrian behavior is not affected by the level of safety of the crossing (e.g., visibility of the crossing for drivers). The results of the presented analysis suggest that action is needed to change that. Due to the lack of information about accidents involving pedestrians using mobile phones and headsets when crossing the road, no relevant statistical data could be analyzed. The dataset collected can be used as a basis for further investigation or comparisons with other countries of the relevant indicators. In future work, we would like to include a pedestrian–driver interaction factor focusing on driver speed behavior in relation to pedestrians (who are on or are about to step onto a pedestrian crossing) and identify critical situations caused by improper behavior of drivers and/or pedestrians. This will help to understand speed adjustment problems related to pedestrian crossings.


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