The purpose of this prototype is to demonstrate the feasibility of text entry via detection of the surface myoelectric signals on user's body. Our system is capable to detect the movement of two fingers and the entire palm. The detector produces discrete signals as well as continuous quantifications of the exerted force. Two mappings of the signals on text entry were implemented, Scanning LetterWise and 2-FOCL, in two modes, discrete and continuous.

Touch-screen interfaces on smart devices became ubiquitous in our everyday lives. In specific contextual situations, capacitive touch interfaces used on current mobile devices are not accessible when, for example, wearing gloves during a cold winter. Although the market has responded by providing capacitive styluses or touchscreen-compatible gloves, these solutions are not widely accepted and appropriate in such particular situations. Using the nose instead of fingers is an easy way to overcome this problem. In this paper, we present in-depth results of a user study on nose-based interaction. The study was complemented by an online survey to elaborate the potential and acceptance of the nose-based interaction style. Based on the insights gained in the study, we identify the main challenges of nose-based interaction and contribute to the state of the art of design principles for this interaction style by adding two new design principles and refining one already existing principle. In addition, we investigated in the emotional effect of nose-based interaction based on the user experiences evolved during the user study.

The study presented in this paper is aimed at identifying text editing actions that are routinely performed by the users when composing a text document and that are not directly supported by common word processors. The results of this study will help a design of a novel word processing interface controlled by device with a limited number of input signals, operated by people with certain motor disabilities.

When applying the Wizard of Oz (WOz) method to mobile and ubiquitous computing studies, the task of the wizard becomes more difficult as observing the user requires the wizard to be in the context. We address this problem through the ConWIZ system that allows not only to control a specific prototype but also to control parameters included in the contextual settings. In order to evaluate our approach, we setup a study with eight human wizards where we evaluated the applicability, appropriateness and usability of the ConWIZ system for mobile and UbiComp environments. Each wizard had to simulate a navigation system and control contextual parameters like simulation of wind by switching a fan on and off, and tactile feedback mechanism using the ConWIZ system. All wizards stated that the tool is definitely applicable and appropriate for supporting a mobile WOz study which allows the wizard to be hidden also if he resides in the study context. Regarding the applicability of the system, we found out that high workload may hinder the wizard from doing additional tasks such as note taking.

Nonverbal vocal interaction (NVVI) is an input modality by means of which users control the computer by producing sounds other than speech. Previous research in this field has focused mainly on studying isolated instances of NVVI (such as mouse cursor control in computer games) and their performance. This paper presents a study with 36 elderly users in which basic NVVI vocal gestures (commands) were ranked by their perceived fatigue, satisfaction, and efficiency. The results of this study inspired a set of NVVI gesture design guidelines that are also presented in this paper.

This paper presents Humsher -- a novel text entry method operated by the non-verbal vocal input, specifically the sound of humming. The method utilizes an adaptive language model for text prediction. Four different user interfaces are presented and compared. Three of them use dynamic layout in which n-grams of characters are presented to the user to choose from according to their probability in given context. The last interface utilizes static layout, in which the characters are displayed alphabetically and a modified binary search algorithm is used for an efficient selection of a character. All interfaces were compared and evaluated in a user study involving 17 able-bodied subjects. Case studies with four disabled people were also performed in order to validate the potential of the method for motor-impaired users. The average speed of the fastest interface was 14 characters per minute, while the fastest user reached 30 characters per minute. Disabled participants were able to type at 14 -- 22 characters per minute after seven sessions.

This paper introduces a text entry application for users with physical disabilities who cannot utilize a manual keyboard. The system allows the user to enter text hands-free, with the help of "Non-verbal Vocal Input" (e.g., humming or whistling). To keep the number of input sounds small, an ambiguous keyboard is used. As the user makes a sequence of sounds, each representing a subset of the alphabet, the program searches for matches in a dictionary. As a model for the system, the scanning-based application QANTI was redesigned and adapted to accept the alternative input signals. The usability of the software was investigated in an international longitudinal study done at locations in the Czech Republic, Germany, and the United States. Eight test users were recruited from the target community. The users differed in the level of speech impairment. Three users did not complete the study due to the severity of their impairment. By the end of the experiment, the users were able to enter text at rates between 10 and 15 characters per minute.