Sayan Sarcar

Designing Mid-Air TV Gestures for Blind People Using User- and Choice-Based Elicitation Approaches

Mid-air gestures enable intuitive and natural interactions. However, few studies have investigated the use of mid-air gestures for blind people. TV interactions are one promising use of mid-air gestures for blind people, as listening to TV is one of their most common activities. Thus, we investigated mid-air TV gestures for blind people through two studies. Study 1 used a user-elicitation approach where blind people were asked to define gestures given a set of commands. Then, we present a classification of gesture types and the frequency of body parts usage. Nevertheless, our participants had difficulty imagining gestures for some commands. Thus, we conducted Study 2 that used a choice-based elicitation approach where the participants selected their favorite gesture from a predefined list of choices. We found that providing choices help guide users to discover suitable gestures for unfamiliar commands. We discuss concrete design guidelines for mid-air TV gestures for blind people.

Towards Ability-Based Optimization for Aging Users

This paper addresses the design of user interfaces for aging adults. Older people differ vastly in how aging affects their perceptual, motor, and cognitive abilities. When it comes to interface design for aging users, the one design for all approach fails. We present first results from attempts to extend ability-based design to the aging population. We describe a novel approach using age-related differences as the principle of optimizing interactive tasks. We argue that, to be successful, predictive models must take into account how users adapt their behavioral strategies as a function of their abilities. When combined with design optimization, such models allow us to investigate optimal designs more broadly, examining trade-offs among several design factors. We present first results on optimizing text entry methods for user groups with different age-related declines.

Modelling Learning of New Keyboard Layouts

Predicting how users learn new or changed interfaces is a long-standing objective in HCI research. This paper contributes to understanding of visual search and learning in text entry. With a goal of explaining variance in novices typing performance that is attributable to visual search, a model was designed to predict how users learn to locate keys on a keyboard: initially relying on visual short-term memory but then transitioning to recall-based search. This allows predicting search times and visual search patterns for completely and partially new layouts. The model complements models of motor performance and learning in text entry by predicting change in visual search patterns over time. Practitioners can use it for estimating how long it takes to reach the desired level of performance with a given layout.

Rethinking Mobile Interfaces for Older Adults

This SIG advances the study of mobile user interfaces for the aging population. The topic is timely, as the mobile device has become the most widely used computer terminal and at the same time the number of older people will soon exceed the number of children worldwide. However, most HCI research addresses younger adults and has had little impact on older adults. Some design trends, like the mantra smaller is smarter, contradict the needs of older users. Developments like this may diminish their ability to access information and participate in society. This can lead to further isolation (social and physical) of older adults and increased widening of the digital divide. This SIG aims to discuss mobile interfaces for older adults. The SIG has three goals: (i) to map the state-of-art, (ii) to build a community gathering experts from related areas, and (iii) to raise awareness within the SIGCHI community. The SIG will be open to all at CHI.

EV-Pen: Leveraging Electrovibration Haptic Feedback in Pen Interaction

This paper presents an Electrovibration Pen (EV-Pen) which incorporates electrovibration technology into pen interactions. The EV-Pen has two unique characteristics: precise interaction and pen-on-paper feeling. We conducted four experiments for evaluating the EV-Pen. Experiment 1 was to determine preliminary characteristics of the EV-Pen. Experiments 2 and 3 were to evaluate precise interaction task performance through a steering task and a tracing task. We compared user performance between the EV-Pen, a mechanical-vibration pen, a normal pen without feedback and electrovibration-based finger interaction. Experimental results indicated that the EV-Pen outperformed the other devices in precise task interactions. Experiment 4 tested pen-on-paper feeling in drawing and handwriting tasks, and it was observed that the EV-Pen significantly enhances user experience. Based on the experimental results, we discuss implications and potential benefits for the design of the EV-Pen.

Designing Mobile Interactions for the Ageing Populations

We are concurrently witnessing two significant shifts: mobiles are becoming the most used computing device; and older people are becoming the largest demographic group. However, despite the recent increase in related CHI publication, older adults continue to be underrepresented in HCI research as well as commercially, further widening the digital divide they face and hampering their social participation. This workshop aims to increase the momentum for such research within CHI and related fields such as gerontechnology. We plan to create a space for discussing and sharing principles and strategies to design and evaluate mobile user interfaces for the aging population. We thus welcome contributions to empirical studies, theories, design and evaluation of mobile interfaces for older adults.

Designing Interactions for the Ageing Populations

We are experiencing two revolutions: ubiquitous digital technology and world-wide population aging: digital devices are becoming ubiquitous, and older people are becoming the largest demographic group. However, despite the recent increase in related CHI publication, older adults continue to be underrepresented in HCI research as well as commercially, further widening the digital divide they face and hampering their social participation. Therefore, the overarching aim of this workshop is to increase the momentum for such research within CHI and related fields such as gerontechnology. For this, we plan to create a space for discussing and sharing principles and strategies to design interactions and evaluate user interfaces for the aging population. We thus welcome contributions to empirical studies, theories, design and evaluation of user interfaces for older adults. Concretely, we aim to: map the state-of-art of senior-centred interaction research, build a multidisciplinary community of experts, and raise the profile of this research within SIGCHI.

Approaching Engagement towards Human-Engaged Computing

Debates regarding the nature and role of HCI research and practice have intensified in recent years, given the ever increasingly intertwined relations between humans and technologies. The framework of Human-Engaged Computing (HEC) was proposed and developed over a series of scholarly workshops to complement mainstream HCI models by leveraging synergy between humans and computers with its key notion of engagement. Previous workshop meetings found engagement to be a constructive and extendable notion through which to investigate synergized human-computer relationships, but many aspects concerning the core concept remain underexplored. This SIG aims to tackle the notion of engagement considered through discussions of four thematic threads. It will bring together HCI practitioners and researchers from different disciplines including Humanities, Design, Positive Psychology, Communication and Media Studies, Neuroscience, Philosophy and Eastern Studies, to share and discuss relevant knowledge and insights and identify new research opportunities and future directions.

Ability-Based Optimization of Touchscreen Interactions

Ability-based optimization is a computational approach for improving interface designs for users with sensorimotor and cognitive impairments. Designs are created by an optimizer, evaluated against task-specific cognitive models, and adapted to individual abilities. The approach does not necessitate extensive data collection and could be applied both automatically and manually by users, designers, or caretakers. As a first step, the authors present optimized touchscreen layouts for users with tremor and dyslexia that potentially improve text-entry speed and reduce error.

Ability-Based Optimization: Designing Smartphone Text Entry Interface for Older Adults.

Beside decreasing the abilities, individual difference prevails among older adults, as some individuals are completely healthy at the age 90 while some are not at even 60. In context of touchscreen interface design, it is critical to understand the design space as a function of abilities. In this work, we articulate a better understanding of the effects of ageing and examine their HCI task performing capabilities in terms of interfaces design. We design a text-entry interface in particular, as ageing users often achieve slow text entry performance, thus proving to be a bottleneck for technology use. Our developed text entry interface is tuned based on the parameter values for Elderly having finger tremor. We present initial study results showing the improvement of the accuracy of touch typing in smartphone over the baseline Qwerty keyboard. By carefully considering other sensorimotor abilities, we believe that the current smartphone text-entry interface designs will become more usable to the ageing populations.