Nomadic input on mobile devices: the influence of touch input technique and walking speed on performance and offset modeling

In everyday life people use their mobile phones on-the-go with different walking speeds and with different touch input techniques. Unfortunately, much of the published research in mobile interaction does not quantify the influence of these variables. In this paper, we analyze the influence of walking speed, gait pattern and input techniques on commonly used performance parameters like error rate, accuracy and tapping speed, and we compare the results to the static condition. We examine the influence of these factors on the machine learned offset model used to correct user input and we make design recommendations. The results show that all performance parameters degraded when the subject started to move, for all input techniques. Index finger pointing techniques demonstrated overall better performance compared to thumb-pointing techniques. The influence of gait phase on tap event likelihood and accuracy was demonstrated for all input techniques and all walking speeds. Finally, it was shown that the offset model built on static data did not perform as well as models inferred from dynamic data, which indicates the speed-specific nature of the models. Also, models identified using specific input techniques did not perform well when tested in other conditions, demonstrating the limited validity of offset models to a particular input technique. The model was therefore calibrated using data recorded with the appropriate input technique, at 75% of preferred walking speed, which is the speed to which users spontaneously slow down when they use a mobile device and which presents a tradeoff between accuracy and usability. This led to an increase in accuracy compared to models built on static data. The error rate was reduced between 0.05% and 5.3% for landscape-based methods and between 5.3% and 11.9% for portrait-based methods

Ability-Based Design: Concept, Principles and Examples

Current approaches to accessible computing share a common goal of making technology accessible to users with disabilities. Perhaps because of this goal, they may also share a tendency to centralize disability rather than ability. We present a refinement to these approaches called ability-based design that consists of focusing on ability throughout the design process in an effort to create systems that leverage the full range of human potential. Just as user-centered design shifted the focus of interactive system design from systems to users, ability-based design attempts to shift the focus of accessible design from disability to ability. Although prior approaches to accessible computing may consider users’ abilities to some extent, ability-based design makes ability its central focus. We offer seven ability-based design principles and describe the projects that inspired their formulation. We also present a research agenda for ability-based design.Engineering and Applied Science

Designing an Adaptive Web Navigation Interface for Users with Variable Pointing Performance

Many online services and products require users to point and interact with user interface elements. For individuals who experience variable pointing ability due to physical impairments, environmental issues or age, using an input device (e.g., a computer mouse) to select elements on a website can be difficult. Adaptive user interfaces dynamically change their functionality in response to user behavior. They can support individuals with variable pointing abilities by 1) adapting dynamically to make element selection easier when a user is experiencing pointing difficulties, and 2) informing users about these pointing errors. While adaptive interfaces are increasingly prevalent on the Web, little is known about the preferences and expectations of users with variable pointing abilities and how to design systems that dynamically support them given these preferences. We conducted an investigation with 27 individuals who intermittently experience pointing problems to inform the design of an adaptive interface for web navigation. We used a functional high-fidelity prototype as a probe to gather information about user preferences and expectations. Our participants expected the system to recognize and integrate their preferences for how pointing tasks were carried out, preferred to receive information about system functionality and wanted to be in control of the interaction. We used findings from the study to inform the design of an adaptive Web navigation interface, PINATA that tracks user pointing performance over time and provides dynamic notifications and assistance tailored to their specifications. Our work contributes to a better understanding of users' preferences and expectations of the design of an adaptive pointing system

Improving the Accuracy of Mobile Touchscreen QWERTY Keyboards

In this thesis we explore alternative keyboard layouts in hopes of finding one that increases the accuracy of text input on mobile touchscreen devices. In particular, we investigate if a single swap of 2 keys can significantly improve accuracy on mobile touchscreen QWERTY keyboards. We do so by carefully considering the placement of keys, exploiting a specific vulnerability that occurs within a keyboard layout, namely, that the placement of particular keys next to others may be increasing errors when typing. We simulate the act of typing on a mobile touchscreen QWERTY keyboard, beginning with modeling the typographical errors that can occur when doing so. We then construct a simple autocorrector using Bayesian methods, describing how we can autocorrect user input and evaluate the ability of the keyboard to output the correct text. Then, using our models, we provide methods of testing and define a metric, the WAR rating, which provides us a way of comparing the accuracy of a keyboard layout. After running our tests on all 325 2-key swap layouts against the original QWERTY layout, we show that there exists more than one 2-key swap that increases the accuracy of the current QWERTY layout, and that the best 2-key swap is i ↔ t, increasing accuracy by nearly 0.18 percent

Investigating retrospective interoperability between the accessible and mobile webs with regard to user input

The World Wide Web (Web) has become a key technology to provide access to on-line information. The Mobile Web users, who access the Web using small devices such as mobile phones and Personal Digital Assistants (PDAs), make errors on entering text and controlling cursors. These errors are caused by both the characteristics of a device and the environment in which it is used, and are called situational impairments. Disabled Web users, on the other hand, have difficulties in accessing the Web due to their impairments in visual, hearing or motor abilities. We assert that errors experienced by the Mobile Web users share similarity in scope with those hindering motor-impaired Web users with dexterity issues, and existing solutions from the motor-impaired users domain can be migrated to the Mobile Web domain to address the common errors.Results of a systematic literature survey have revealed 12 error types that affect both the Mobile Web users and disabled Web users. These errors range from unable to locate a key to unable to pin-point a cursor. User experiments have confirmed that the Mobile Web users and motor-impaired Web users share errors in scope: they both miss key presses, press additional keys, unintentionally press a key more than once or press a key too long. In addition, both small device users and motor-impaired desktop users have difficulties in performing clicking, multiple clicking and drag selecting. Furthermore, when small device users are moving, both the scope and the magnitude of the errors are shared. In order to address these errors, we have migrated existing solutions from the disabled Web users domain into the Mobile Web users domain. We have developed a typing error correction system for the Mobile Web users. Results of the user evaluation have indicated that the proposed system can significantly reduce the error rates of the Mobile Web users.This work has an important contribution to both the Web accessibility field and the Mobile Web field. By leveraging research from the Web accessibility field into the Mobile Web field, we have linked two disjoint domains together. We have migrated solutions from one domain to another, and thus have improved the usability and accessibility of the Mobile Web.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Passphrase and keystroke dynamics authentication: security and usability

It was found that employees spend a total 2.25 days within a 60 day period on password related activities. Another study found that over 85 days an average user will create 25 accounts with an average of 6.5 unique passwords. These numbers are expected to increase over time as more systems become available. In addition, the use of 6.5 unique passwords highlight that passwords are being reused which creates security concerns as multiple systems will be accessible by an unauthorised party if one of these passwords is leaked. Current user authentication solutions either increase security or usability. When security increases, usability decreases, or vice versa. To add to this, stringent security protocols encourage unsecure behaviours by the user such as writing the password down on a piece of paper to remember it. It was found that passphrases require less cognitive effort than passwords and because passphrases are stronger than passwords, they don’t need to be changed as frequently as passwords. This study aimed to assess a two-tier user authentication solution that increases security and usability. The proposed solution uses passphrases in conjunction with keystroke dynamics to address this research problem. The design science research approach was used to guide this study. The study’s theoretical foundation includes three theories. The Shannon entropy formula was used to calculate the strength of passwords, passphrases and keystroke dynamics. The chunking theory assisted in assessing password and passphrase memorisation issues and the keystroke-level model was used to assess password and passphrase typing issues. Two primary data collection methods were used to evaluate the findings and to ensure that gaps in the research were filled. A login assessment experiment collected data on user authentication and user-system interaction for passwords and passphrases. Plus, an expert review was conducted to verify findings and assess the research artefact in the form of a model. The model can be used to assist with the implementation of a two-tier user authentication solution which involves passphrases and keystroke dynamics. There are a number of components that need to be considered to realise the benefits of this solution and ensure successful implementation