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Information technology (IT) has great potential to be an effective and empowering means of communication for people with communication difficulties. Getting IT explores how IT can help such people increase their independence, communicate in more direct ways and express themselves as part of society. Authors Dinah Murray and Ann Aspinall examine common problems faced by people with learning and communication difficulties - being judged on appearances, encountering impatience from communication partners, problems identifying and understanding key information and difficulties communicating decisions. They show how IT can help solve these problems: for example internet search tools for accessing information at home, typing and email as socially neutral, universally acceptable modes of expression, anonymous, non-judgmental internet chatrooms and discussion forums. Three central case studies illustrate how IT improved the lives of Kumar who is on the autism spectrum, Marie who has dementia and Irene who is almost completely nonverbal. The book also provides practical guidance on how to use common IT programs including Powerpoint and gives an overview of the technology available for people with specific difficulties. Useful resources and organisations are supplied at the end of the book. Getting IT shows the power of IT to help people with communication difficulties satisfy the universal human need to communicate. This book will inspire carers, teachers, psychologists, parents and other professionals to use IT with people with communication difficulties, and will expand the skills and knowledge of those who already do.

The revolution in accessible computer technology was fueled by disability activism, the interactive nature of personal computers, and changing public policy. In 1974, not long after developing the first universal optical character recognition technology, Raymond Kurzweil struck up a conversation with a blind man on a flight. Kurzweil explained that he was searching for a use for his new software. The blind man expressed interest: One of the frustrating obstacles that blind people grappled with, he said, was that no computer program could translate text into speech. Inspired by this chance meeting, Kurzweil decided that he must put his new innovation to work to \"overcome this principal handicap of blindness.\" By 1976, he had built a working prototype, which he dubbed the Kurzweil Reading Machine. This type of innovation demonstrated the possibilities of computers to dramatically improve the lives of people living with disabilities. In Making Computers Accessible, Elizabeth R. Petrick tells the compelling story of how computer engineers and corporations gradually became aware of the need to make computers accessible for all people. Motivated by user feedback and prompted by legislation such as the Americans with Disabilities Act, which offered the promise of equal rights via technological accommodation, companies developed sophisticated computerized devices and software to bridge the accessibility gap. People with disabilities, Petrick argues, are paradigmatic computer users, demonstrating the personal computer's potential to augment human abilities and provide for new forms of social, professional, and political participation. Bridging the history of technology, science and technology studies, and disability studies, this book traces the psychological, cultural, and economic evolution of a consumer culture aimed at individuals with disabilities, who increasingly rely on personal computers to make their lives richer and more interconnected.

Ensuring Digital Accessibility through Process and Policy provides readers with a must-have resource to digital accessibility from both a technical and policy perspective.Inaccessible digital interfaces and content often lead to forms of societal discrimination that may be illegal under various laws.

Exoskeletons are robots that closely interact with humans and that are increasingly used for different purposes, such as rehabilitation, assistance in the activities of daily living (ADLs), performance augmentation or as haptic devices. In the last few decades, the research activity on these robots has grown exponentially, and sensors and actuation technologies are two fundamental research themes for their development. In this review, an in-depth study of the works related to exoskeletons and specifically to these two main aspects is carried out. A preliminary phase investigates the temporal distribution of scientific publications to capture the interest in studying and developing novel ideas, methods or solutions for exoskeleton design, actuation and sensors. The distribution of the works is also analyzed with respect to the device purpose, body part to which the device is dedicated, operation mode and design methods. Subsequently, actuation and sensing solutions for the exoskeletons described by the studies in literature are analyzed in detail, highlighting the main trends in their development and spread. The results are presented with a schematic approach, and cross analyses among taxonomies are also proposed to emphasize emerging peculiarities.

Assistive technology is becoming increasingly accessible and affordable for supporting people with dementia and their care partners living at home, with strong potential for technology-based prompting to assist with initiation and tracking of complex, multistep activities of daily living. However, there is limited direct comparison of different prompt features to guide optimal technology design. Across 3 experiments, we investigated the features of tablet-based prompts that best support people with dementia to complete activities of daily living at home, measuring prompt effectiveness and gaining feedback from people with dementia and their care partners about their experiences. Across experiments, we developed a specialized iPad app to enable data collection with people with dementia at home over an extended experimental period. In experiment 1, we varied the prompts in a 3 (visual type: text instruction, iconic image, and photographic image) × 3 (audio type: no sound, symbolic sound, and verbal instruction) experimental design using repeated measures across multiple testing sessions involving single-step activities. In experiment 2, we tested the most effective prompt breakdown for complex multistep tasks comparing 3 conditions (1-prompt, 3-prompt, and 7-prompt conditions). In experiment 3, we compared initiation and maintenance alerts that involved either an auditory tone or an auditory tone combined with a verbal instruction. Throughout, we asked people with dementia and their care partners to reflect on the usefulness of prompting technology in their everyday lives and what could be developed to better meet their needs. First, our results showed that audible verbal instructions were more useful for task completion than either tone-based or visual prompts. Second, a more granular breakdown of tasks was generally more useful and increased independent use, but this varied across individuals. Third, while a voice or text maintenance alert enabled people with dementia to persist with a multistep task for longer when it was more frequent, task initiation still frequently required support from a care partner. These findings can help inform developers of assistive technology about the design features that promote the usefulness of home prompting systems for people with dementia as well as the preferences and insights of people with dementia and their care partners regarding assistive technology design.

The design of “Serious games” that use game components (e.g., storyline, long-term goals, rewards) to create engaging learning experiences has increased in recent years. We examine of the core principles of serious game design and examine the current use of these principles in computer-based interventions for individuals with autism. Participants who undergo these computer-based interventions often show little evidence of the ability to generalize such learning to novel, everyday social communicative interactions. This lack of generalized learning may result, in part, from the limited use of fundamental elements of serious game design that are known to maximize learning. We suggest that future computer-based interventions should consider the full range of serious game design principles that promote generalization of learning.

Purpose The development of assistive technologies that support people in social interactions has attracted increased attention in HCI. This paper presents a systematic review of studies of Socially Assistive Systems targeted at older adults and people with disabilities. The purpose is threefold: (1) Characterizing related assistive systems with a special focus on the system design, primarily including HCI technologies used and user-involvement approach taken; (2) Examining their ways of system evaluation; (3) Reflecting on insights for future design research. Methods A systematic literature search was conducted using the keywords “social interactions” and “assistive technologies” within the following databases: Scopus, Web of Science, ACM, Science Direct, PubMed, and IEEE Xplore. Results Sixty-five papers met the inclusion criteria and were further analyzed. Our results showed that there were 11 types of HCI technologies that supported social interactions for target users. The most common was cognitive and meaning understanding technologies, often applied with wearable devices for compensating users’ sensory loss; 33.85% of studies involved end-users and stakeholders in the design phase; Four types of evaluation methods were identified. The majority of studies adopted laboratory experiments to measure user-system interaction and system validation. Proxy users were used in system evaluation, especially in initial experiments; 42.46% of evaluations were conducted in field settings, primarily including the participants’ own homes and institutions. Conclusion We contribute an overview of Socially Assistive Systems that support social interactions for older adults and people with disabilities, as well as illustrate emerging technologies and research opportunities for future work.

Throughout our lives, we interact daily in conversations with our friends and family, covering a wide range of topics, known as open-domain dialogue. As we age, these interactions may diminish due to changes in social and personal relationships, leading to loneliness in older adults. Conversational companion robots can alleviate this issue by providing daily social support. Large language models (LLMs) offer flexibility for enabling open-domain dialogue in these robots. However, LLMs are typically trained and evaluated on textual data, while robots introduce additional complexity through multi-modal interactions, which has not been explored in prior studies. Moreover, it is crucial to involve older adults in the development of robots to ensure alignment with their needs and expectations. Correspondingly, using iterative participatory design approaches, this paper exposes the challenges of integrating LLMs into conversational robots, deriving from 34 Swedish-speaking older adults’ (one-to-one) interactions with a personalized companion robot, built on Furhat robot with GPT - 3.5. These challenges encompass disruptions in conversations, including frequent interruptions, slow, repetitive, superficial, incoherent, and disengaging responses, language barriers, hallucinations, and outdated information, leading to frustration, confusion, and worry among older adults. Drawing on insights from these challenges, we offer recommendations to enhance the integration of LLMs into conversational robots, encompassing both general suggestions and those tailored to companion robots for older adults.

Robot teleoperation systems face a common set of challenges including latency, low-dimensional user commands, and asymmetric control inputs. User control with Brain–Computer Interfaces (BCIs) exacerbates these problems through especially noisy and erratic low-dimensional motion commands due to the difficulty in decoding neural activity. We introduce a general framework to address these challenges through a combination of computer vision, user intent inference, and arbitration between the human input and autonomous control schemes. Adjustable levels of assistance allow the system to balance the operators capabilities and their perception of control authority. Additionally, a custom servo controller design allow for safe interactions of the robotic arm with the environment. We present experimental results demonstrating significant performance improvement using our shared-control assistance framework on adapted rehabilitation benchmarks with two subjects at various timepoints relative to their implantation with intracortical BCIs. Our results indicate that shared assistance mitigates perceived user difficulty in using a seven-degree of freedom robotic arm as a prosthetic and enables successful performance on previously infeasible tasks. We showcase the extensibility of our architecture with applications to quality-of-life tasks such as opening a door, pouring liquids from containers, and manipulation with objects previously unknown to the system in densely cluttered environments.

According to the World Health Organization, about 15% of the world’s population has some form of disability. Assistive Technology, in this context, contributes directly to the overcoming of difficulties encountered by people with disabilities in their daily lives, allowing them to receive education and become part of the labor market and society in a worthy manner. Assistive Technology has made great advances in its integration with Artificial Intelligence of Things (AIoT) devices. AIoT processes and analyzes the large amount of data generated by Internet of Things (IoT) devices and applies Artificial Intelligence models, specifically, machine learning, to discover patterns for generating insights and assisting in decision making. Based on a systematic literature review, this article aims to identify the machine-learning models used across different research on Artificial Intelligence of Things applied to Assistive Technology. The survey of the topics approached in this article also highlights the context of such research, their application, the IoT devices used, and gaps and opportunities for further development. The survey results show that 50% of the analyzed research address visual impairment, and, for this reason, most of the topics cover issues related to computational vision. Portable devices, wearables, and smartphones constitute the majority of IoT devices. Deep neural networks represent 81% of the machine-learning models applied in the reviewed research.