Brain-Computer Interfaces for augmented communication: Asynchronous and adaptive algorithms and evaluation with end users

This thesis aimed at addressing some of the issues that, at the state of the art, avoid the P300-based brain computer interface (BCI) systems to move from research laboratories to end users’ home. An innovative asynchronous classifier has been defined and validated. It relies on the introduction of a set of thresholds in the classifier, and such thresholds have been assessed considering the distributions of score values relating to target, non-target stimuli and epochs of voluntary no-control. With the asynchronous classifier, a P300-based BCI system can adapt its speed to the current state of the user and can automatically suspend the control when the user diverts his attention from the stimulation interface. Since EEG signals are non-stationary and show inherent variability, in order to make long-term use of BCI possible, it is important to track changes in ongoing EEG activity and to adapt BCI model parameters accordingly. To this aim, the asynchronous classifier has been subsequently improved by introducing a self-calibration algorithm for the continuous and unsupervised recalibration of the subjective control parameters. Finally an index for the online monitoring of the EEG quality has been defined and validated in order to detect potential problems and system failures. This thesis ends with the description of a translational work involving end users (people with amyotrophic lateral sclerosis-ALS). Focusing on the concepts of the user centered design approach, the phases relating to the design, the development and the validation of an innovative assistive device have been described. The proposed assistive technology (AT) has been specifically designed to meet the needs of people with ALS during the different phases of the disease (i.e. the degree of motor abilities impairment). Indeed, the AT can be accessed with several input devices either conventional (mouse, touchscreen) or alterative (switches, headtracker) up to a P300-based BCI.

A web-based non-intrusive ambient system to measure and classify activities of daily living.

BACKGROUND The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). OBJECTIVE We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. METHODS The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. RESULTS In this study, 10 healthy participants (6 women, 4 men; mean age 48.8 years; SD 20.0 years; age range 28-79 years) were included. For explorative purposes, one female Alzheimer patient (Montreal Cognitive Assessment score=23, Timed Up and Go=19.8 seconds, Trail Making Test A=84.3 seconds, Trail Making Test B=146 seconds) was measured in parallel with the healthy subjects. In total, 1317 ADL were performed by the participants, 1211 ADL were classified correctly, and 106 ADL were missed. This led to an overall sensitivity of 91.27% and a specificity of 92.52%. Each subject performed an average of 134.8 ADL (SD 75). CONCLUSIONS The non-intrusive wireless sensor system can acquire environmental data essential for the classification of activities of daily living. By analyzing retrieved data, it is possible to distinguish and assign data patterns to subjects' specific activities and to identify eight different activities in daily living. The Web-based technology allows the system to improve care and provides valuable information about the patient in real-time.

Adapting a driving simulator to study pedestrians' street-crossing decisions: A feasibility study

The decision when to cross a street safely is a challenging task that poses high demands on perception and cognition. Both can be affected by normal aging, neurodegenerative disorder, and brain injury, and there is an increasing interest in studying street-crossing decisions. In this article, we describe how driving simulators can be modified to study pedestrians' street-crossing decisions. The driving simulator's projection system and the virtual driving environment were used to present street-crossing scenarios to the participants. New sensors were added to measure when the test person starts to cross the street. Outcome measures were feasibility, usability, task performance, and visual exploration behavior, and were measured in 15 younger persons, 15 older persons, and 5 post-stroke patients. The experiments showed that the test is feasible and usable, and the selected difficulty level was appropriate. Significant differences in the number of crashes between young participants and patients (p = .001) as well as between healthy older participants and patients (p = .003) were found. When the approaching vehicle's speed is high, significant differences between younger and older participants were found as well (p = .038). Overall, the new test setup was well accepted, and we demonstrated that driving simulators can be used to study pedestrians' street-crossing decisions.

Processing of speech signals for physical and sensory disabilities.

Assistive technology involving voice communication is used primarily by people who are deaf, hard of hearing, or who have speech and/or language disabilities. It is also used to a lesser extent by people with visual or motor disabilities. A very wide range of devices has been developed for people with hearing loss. These devices can be categorized not only by the modality of stimulation [i.e., auditory, visual, tactile, or direct electrical stimulation of the auditory nerve (auditory-neural)] but also in terms of the degree of speech processing that is used. At least four such categories can be distinguished: assistive devices (a) that are not designed specifically for speech, (b) that take the average characteristics of speech into account, (c) that process articulatory or phonetic characteristics of speech, and (d) that embody some degree of automatic speech recognition. Assistive devices for people with speech and/or language disabilities typically involve some form of speech synthesis or symbol generation for severe forms of language disability. Speech synthesis is also used in text-to-speech systems for sightless persons. Other applications of assistive technology involving voice communication include voice control of wheelchairs and other devices for people with mobility disabilities.

Modulação autonômica cardíaca na distrofia muscular de Duchenne durante tarefa no computador

Introdução: A Distrofia Muscular de Duchenne (DMD) é caracterizada como uma fraqueza muscular progressiva que leva à incapacidade. Devido às dificuldades funcionais enfrentadas pelos indivíduos com DMD, o uso da tecnologia assistiva é essencial para proporcionar ou promover habilidades funcionais. Na DMD, além do comprometimento musculoesquelético, uma disfunção autonômica cardíaca também tem sido relatada. Assim, visamos investigar as respostas autonômicas agudas de indivíduos com DMD durante a realização de uma tarefa no computador. Método: A variabilidade da frequência cardíaca foi avaliada através de métodos lineares e não lineares, utilizando uma cinta torácica com equipamento de monitoramento de eletrocardiograma (ECG). Assim, 45 indivíduos foram incluídos no grupo com DMD e 45 no grupo de desenvolvimento típico (controle), avaliados for 20 minutos em repouso sentado e 5 minutos com a realização de uma tarefa no computador. Resultados: Os indivíduos com DMD apresentaram menor modulação cardíaca parassimpática durante o repouso, que diminuiu ainda mais durante a tarefa no computador. Conclusão: Indivíduos com DMD exibiram respostas autonômicas cardíacas mais intensas durante a tarefa no computador

ALEX®: a mobile Adult Literacy Experiential Learning application

An alarmingly high number of adults in the world's most developed countries are linguistically functionally illiterate. The research presented in this paper describes ALEX©, an ongoing attempt to successfully develop an innovative assistive, mobile, experiential language-learning application to support the daily literacy education and needs of such adults, anywhere, anytime. We introduce a set of guidelines we have collated to inform the design of mobile assistive technologies, introduce our application and describe the design activities to date that have led to the development of our current application. We present this overview in the hope that it is useful to others working in the fledgling domains of mobile assistive technology design and/or mobile experiential language-learning technologies.

Designing mobile technologies for individuals with disabilities

While mobile devices offer many innovative possibilities to help increase the standard of living for individuals with disabilities and other special needs, the process of developing assistive technology, such that it will be effective across a group of individuals with a particular disability, can be extremely challenging. This chapter discusses key issues and trends related to designing and evaluating mobile assistive technology for individuals with disabilities. Following an overview of general design process issues, we argue (based on current research trends) that individuals with disabilities and domain experts be involved throughout the development process. While this, in itself, presents its own set of challenges, many strategies have successfully been used to overcome the difficulties and maximize the contributions of users and experts alike. Guidelines based on these strategies are discussed and are illustrated with real examples from one of our active research projects.

Designing mobile technologies for individuals with disabilities

While mobile devices offer many innovative possibilities to help increase the standard of living for individuals with disabilities and other special needs, the process of developing assistive technology, such that it will be effective across a group of individuals with a particular disability, can be extremely challenging. This chapter discusses key issues and trends related to designing and evaluating mobile assistive technology for individuals with disabilities. Following an overview of general design process issues, we argue (based on current research trends) that individuals with disabilities and domain experts be involved throughout the development process. While this, in itself, presents its own set of challenges, many strategies have successfully been used to overcome the difficulties and maximize the contributions of users and experts alike. Guidelines based on these strategies are discussed and are illustrated with real examples from one of our active research projects.

Participatory design:how to engage older adults in participatory design activities

Ongoing advances in mobile technologies have the potential to improve independence and quality of life of older adults by supporting the delivery of personalised and ubiquitous healthcare solutions. The authors are actively engaged in participatory, user-focused research to create a mobile assistive healthcare-related intervention for persons with age-related macular degeneration (AMD): the authors report here on our participatory research in which participatory design (PD) has been positively adopted and adapted for the design of our mobile assistive technology. The authors discuss their work as a case study in order to outline the practicalities and highlight the benefits of participatory research for the design of technology for (and importantly with) older adults. The authors argue it is largely impossible to achieve informed and effective design and development of healthcare-related technologies without employing participatory approaches, and outline recommendations for engaging in participatory design with older adults (with impairments) based on practical experience.

An update on the characteristics of patients attending the Kooyong Low Vision Clinic

BACKGROUND: Since 1972, the Australian College of Optometry has worked in partnership with Vision Australia to provide multidisciplinary low-vision care at the Kooyong Low Vision Clinic. In 1999, Wolffsohn and Cochrane reported on the demographic characteristics of patients attending Kooyong. Sixteen years on, the aim of this study is to review the demographics of the Kooyong patient cohort and prescribing patterns. METHODS: Records of all new patients (n = 155) attending the Kooyong Low Vision Clinic for optometry services between April and September 2012 were retrospectively reviewed. RESULTS: Median age was 84.3 years (range 7.7 to 98.1 years) with 59 per cent female. The majority of patients presented with late-onset degenerative pathology, 49 per cent with a primary diagnosis of age-related macular degeneration. Many (47.1 per cent) lived with their families. Mean distance visual acuity was 0.57 ± 0.47 logMAR or approximately 6/24. The median spectacle-corrected near visual acuity was N8 (range N3 to worse than N80). Fifty patients (32.3 per cent) were prescribed new spectacles, 51 (32.9 per cent) low vision aids and five (8.3 per cent) were prescribed electronic magnification devices. Almost two-thirds (63.9 per cent) were referred for occupational therapy management and 12.3 per cent for orientation and mobility services. CONCLUSIONS: The profile of patients presenting for low-vision services at Kooyong is broadly similar to that identified in 1999. Outcomes appear to be similar, aside from an expected increase in electronic devices and technological solutions; however, the nature of services is changing, as treatments for ocular diseases advance and assistive technology develops and becomes more accessible. Alongside the aging population and age-related ocular disease being the predominant cause of low vision in Australia, the health-funding landscape is becoming more restrictive. The challenge for the future will be to provide timely, high-quality care in an economically efficient model.

The effects of word prediction and text-to-speech technologies on the narrative writing skills of students with specific learning disabilities

This study investigated the effects of word prediction and text-to-speech on the narrative composition writing skills of 6, fifth-grade Hispanic boys with specific learning disabilities (SLD). A multiple baseline design across subjects was used to explore the efficacy of word prediction and text-to-speech alone and in combination on four dependent variables: writing fluency (words per minute), syntax (T-units), spelling accuracy, and overall organization (holistic scoring rubric). Data were collected and analyzed during baseline, assistive technology interventions, and at 2-, 4-, and 6-week maintenance probes. ^ Participants were equally divided into Cohorts A and B, and two separate but related studies were conducted. Throughout all phases of the study, participants wrote narrative compositions for 15-minute sessions. During baseline, participants used word processing only. During the assistive technology intervention condition, Cohort A participants used word prediction followed by word prediction with text-to-speech. Concurrently, Cohort B participants used text-to-speech followed by text-to-speech with word prediction. ^ The results of this study indicate that word prediction alone or in combination with text-to-speech has a positive effect on the narrative writing compositions of students with SLD. Overall, participants in Cohorts A and B wrote more words, more T-units, and spelled more words correctly. A sign test indicated that these perceived effects were not likely due to chance. Additionally, the quality of writing improved as measured by holistic rubric scores. When participants in Cohort B used text-to-speech alone, with the exception of spelling accuracy, inconsequential results were observed on all dependent variables. ^ This study demonstrated that word prediction alone or in combination assists students with SLD to write longer, improved-quality, narrative compositions. These results suggest that word prediction or word prediction with text-to-speech be considered as a writing support to facilitate the production of a first draft of a narrative composition. However, caution should be given to the use of text-to-speech alone as its effectiveness has not been established. Recommendations for future research include investigating the use of these technologies in other phases of the writing process, with other student populations, and with other writing styles. Further, these technologies should be investigated while integrated into classroom composition instruction. ^

Interface para tecnologia assistiva baseada em eletrooculografia

We propose in this work, a new method of conceptual organization of areas involving assistive technology, categorizing them in a logical and simple manner; Furthermore, we also propose the implementation of an interface based on electroculography, able to generate high-level commands, to trigger robotic, computer and electromechanical devices. To validate the eye interface, was developed an electronic circuit associated with a computer program that captured the signals generated by eye movements of users, generating high-level commands, able to trigger an active bracing and many other electromechanical systems. The results showed that it was possible to control many electromechanical systems through only eye movements. The interface is presented as a viable way to perform the proposed task and can be improved in the signals analysis in the the digital level. The diagrammatic model developed, presented as a tool easy to use and understand, providing the conceptual organization needs of assistive technology

Personal Storytelling : Using Natural Language Generation for Children with Complex Communication Needs, in the Wild...

Acknowledgements The authors thank the children, their parents and school staff, who participated in this research, and who so willingly gave us their time, help and support. They also thank Steven Knox and Alan Clelland for their work on programming the mobile phone application. Additional thanks to DynaVox Inc. for supplying the Vmax communication devices to run our system on and Sensory Software Ltd for supplying us with their AAC software. This research was supported by the Research Council UKs Digittal Economy Programme and EPSRC (Grant numbers EP/F067151/1, EP/F066880/1, EP/E011764/1, EP/H022376/1, and EP/H022570 /1).

A Haptic System for Depicting Mathematical Graphics for Students with Visual Impairments

When teaching students with visual impairments educators generally rely on tactile tools to depict visual mathematical topics. Tactile media, such as embossed paper and simple manipulable materials, are typically used to convey graphical information. Although these tools are easy to use and relatively inexpensive, they are solely tactile and are not modifiable. Dynamic and interactive technologies such as pin matrices and haptic pens are also commercially available, but tend to be more expensive and less intuitive. This study aims to bridge the gap between easy-to-use tactile tools and dynamic, interactive technologies in order to facilitate the haptic learning of mathematical concepts. We developed an haptic assistive device using a Tanvas electrostatic touchscreen that provides the user with multimodal (haptic, auditory, and visual) output. Three methodological steps comprise this research: 1) a systematic literature review of the state of the art in the design and testing of tactile and haptic assistive devices, 2) a user-centered system design, and 3) testing of the system’s effectiveness via a usability study. The electrostatic touchscreen exhibits promise as an assistive device for displaying visual mathematical elements via the haptic modality.