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This paper presents the design and usability evaluation of an Arabic keyboard for applications that predominantly use single-pointer input device. Such applications are particularly used in mobile devices like Portable Data Assistants (PDAs) and smartphones. They are also valuable in gaze-controlled interfaces that constitute a growing mode of communication and that particularly empower people with mobility impairments. A special focus is given to the optimization of the key arrangement based on the movement time and character transition frequencies. An optimization model as well as a Simulated Annealing algorithm are presented. Then, the performance of the optimized layout is assessed showing that it outperforms the commonly used Arabic keyboard in terms of the estimated typing speed. However, the main limitation that the new layout might face is that a new arrangement of keys may not be adopted by users, even if the currently used layouts are not optimum. Therefore, a usability evaluation of the optimized layouts was conducted using eye-tracking and task-based testing involving the end-users and considering both objective and subjective measures of usability. Implications for the design are also discussed.

In this research, we aim to gain deep insights into information behavior when discussing epidemics on Twitter. We are more specifically interested in identifying misinformation spread regarding epidemics around the world and in particular, in Saudi Arabia. We are also interested in understanding the effects of governmental laws as a way to prevent the spread of misinformation.Questions to be answered include: Which types of misinformation spread the most in pandemics? How does misinformation evolve over time? What is the effect of governmental laws in the spread of misinformation? We propose a mixed method study to determine if information-exchanging behaviors can be used to minimize the effects of emergent misinformation. To do this, Twitter data was collected for the period beginning in December 2019 to the present day of April 10, 2020 using several keywords related to the pandemic in Arabic.In addition to twitter data, we also created a short survey to collect rumors and fake news that spread in the community. To study the effect of governmental Saudi laws in the spread of misinformation, the misinformation laws were collected.&nbsp

COVID-19 has had broad disruptive effects on economies, healthcare systems, governments, societies, and individuals. Uncertainty concerning the scale of this crisis has given rise to countless rumors, hoaxes, and misinformation. Much of this type of conversation and misinformation about the pandemic now occurs online and in particular on social media platforms like Twitter. This study analysis incorporated a data-driven approach to map the contours of misinformation and contextualize the COVID-19 pandemic with regards to socio-religious-political information. This work consists of a combined system bridging quantitative and qualitative methodologies to assess how information-exchanging behaviors can be used to minimize the effects of emergent misinformation. The study revealed that the social media platforms detected the most significant source of rumors in transmitting information rapidly in the community. It showed that WhatsApp users made up about 46% of the source of rumors in online platforms, while, through Twitter, it demonstrated a declining trend of rumors by 41%. Moreover, the results indicate the second-most common type of misinformation was provided by pharmaceutical companies, however, a prevalent type of misinformation spreading in the world during this pandemic has to do with the biological war. In this combined retrospective analysis of the study, social media with varying approaches in public discourse contributes to efficient public health responses.

This paper explores good practices as exemplified by emerging strategies for co-design of assistive technology (AT) for persons with disabilities (PWDs). Designed not as a thorough study, but as a small set of grassroots exemplars that can inspire and instruct designers, developers, caregivers, service providers, and policy makers, the study examines three co-design projects. The three projects utilize the Humanistic Co-Design approach to designing assistive devices tailored to the needs of those with visual, mobility, and speech and language impairments. Implications for the design of AT in open innovation models are discussed, as well as potential real-world implementations.

Students tend to have difficulties in learning without applying what they have learned. Recent advances in computing science education methods have emphasized team-based and project-based learning to develop the students' problem-solving skills. This study provides insights from an experience report on project-based learning (PBL) conducted in the context of a collegiate course for Human-Computer Interaction (HCI). PBL models have been applied in HCI education contexts [1] with findings that suggest potential for increased levels of engagement, more creative design solutions, and potential for more rigorous user acceptance testing (UAT) as noted in [2] and [3]. The novelty in this particular case study is introducing students to iterative prototyping for an ongoing real-world project in an R&D center that is involved in localizing a platform for Arabic-speaking populations [4].

In this paper, we describe a time-bound health hackathon that brought together multidisciplinary teams to collaborate intensely over a short period of time to define a problem, devise a solution, and design a working prototype. Insights from a case study of diverse teams working together to rapidly validate clinical needs and develop solutions are highlighted. Reflections on how the hackathon contributed towards energizing and connecting the best minds across the health ecosystem to solve healthcare's most significant challenges and develop healthcare entrepreneurship and digital strategies to scale medicine are discussed.

Autism Spectrum Disorder (ASD) is a mental disorder characterized by difficulties with socializing, repetitive behaviors, speech and non-verbal communication. It is diagnosed within the first three years of life. The earlier the diagnoses, the sooner the intervention can start. Previous studies showed that early interventions for ASD children result in higher success rate. Thus, early diagnosis is an important research goal. Clinical instruments currently used for measuring ASD signs and symptoms are time consuming and highly influenced by subjective observations. These limitations delayed diagnosis and further intervention. Therefore, scientists found that atypical gaze movement is among the earliest biomarkers for ASD. Accordingly, in our research, we are aiming to speed up diagnoses by combining gaze-based screening with intelligent methods such as machine learning which would act as a transformative step for identifying ASD at early stages. In this research we used Support Vector Machine (SVM) algorithm to examine the performance in terms of four different measures which are accuracy, sensitivity, specificity and Area under the curve (AUC). Results revealed that SVM accomplished high classification performance when applied on our collected eye movement data set.

This study describes the design iteration in the localization process of Nasa’s Eyes on the Earth which was aligned with co-creation. The paper provides insights from an experience report on project-based learning (PBL) conducted in the context of a collegiate course for Human-Computer Interaction (HCI). We will highlight how co-creation and collaborative work on an existing real-world project was aligned with increased levels of students’ engagement and markedly improved interaction design in prototypes. The implications of the co-creation and design shift for the education of designers and researchers in HCI will be discussed.

Within the human–computer interaction (HCI) community, there is a wide range of experience and approaches to integrating user research in the software-development life cycle. Independent HCI consulting and contracting is becoming a more prevalent mode of user research globally, but our understanding of the local context in some regions is limited. This paper reports the results of a survey of 65 practitioners working in software-development environments in Saudi Arabia. The survey was conducted in January 2018 and covered a range of aspects: profiles of respondents and their organizations, their perception of usability, user experience and user-centered design, assessment of current HCI activities, and motivation for and obstacles to adopting HCI practice in software-development environments. The results revealed recognition of HCI practices was greater than expected. The adoption of HCI practices in the industry and private sector was greater than in government organizations. The findings also suggested that the most-used HCI activities were prototyping and stakeholder meetings for requirements elicitation. The degree of importance of decision factors for adopting HCI practices and the frequency of obstacles to adoption of the practices varied slightly among government, private, and semi-government organizations. The study results also provided basic information for HCI practitioners and researchers who are interested in appropriating HCI methods to meet local needs. Here, we discuss the results and provide implications for advancing HCI practice in software-development environments in Saudi Arabia.

Being a leading cause of death and serious long-term disability across the world, stroke and cerebrovascular diseases became a major burden on health and social care. However, research has shown that early therapy intervention with stroke patients has the potential for significant improvements in terms of cognitive and motor abilities. Integration of technology into rehabilitation such as the robot-assisted therapy, virtual reality applications, and telecare systems have changed the way rehabilitation programs are being delivered and it overcame some of the limitations and challenges that come with conventional therapy programs. Understanding the target audience and their behavior is of crucial importance to be considered in an early design phase especially with this kind of systems that have tedious nature and involve multiple groups of users (patients, therapists, and caregivers). In this study, we aim to adopt a participatory design approach that engages users and stakeholders in developing stroke rehabilitation technologies aligned with behavioral archetypes that are modeled around their behavioral perspectives. We believe that using archetypes in user research gives us a better view of behavior in interaction design of rehabilitation systems and provide developers with a model to validate interactive elements in stroke rehabilitation systems and user flows at a macro level. In this paper, a user study was designed to be conducted to validate behavioral archetypes of these groups through interviews and focus group sessions with different physicians, therapists and caregivers in rehabilitation centers.

This study will shed light on the opportunities for improvements in the function of interaction between Interactive art installations and the spectators. Where a synthesis of the analysis and evaluation of sensory, cognitive and perceptual human and socio-cultural factors in various research studies and an undergoing case study will be presented. The main goal of this study is to enhance the user experience and bring it to a higher level by considering the human factors in the interactivity aspect, as we human beings have different levels of cognition and perception that will compose our experience with the IMAI.

Human factors contribute significantly to the information visualization design considerations and usability evaluation process, and have been shown to play an important role in the design, development and quality assurance of bioinformatics tools. Despite the technological advances in bioinformatics computational methods, humans are an indispensable part of the data mining and decision making process. The complexity of biology data visualization can make perception and analysis a complex cognitive activity for professionals in the bioinformatics domain. Information Visualization (InfoVis) can provide valuable assistance for data analysis in bioinformatics by visually depicting sequences, genomes, alignments, and macromolecular structures. InfoVis coupled with interaction modalities of bioinformatics tools also impact the efficiency and effectiveness of decision-making tasks in applied bioinformatics computing. However, the way people perceive and interact with bioinformatics tools can strongly influence their understanding of the complex data as well as the perceived usability and accessibility of these systems. In this paper, we present a synthesis of research studies and initiatives that have recently examined human factors in interaction and visualization for bioinformatics tools, particularly in perception-based design. Although bioinformatics’ visualization and interaction design research that involves human factors is considered in its infancy, a plethora of potentially promising areas have yet to be explored. The aims of this paper are to review current human factors research in interaction, usability and visualization within bioinformatics tools to provide a basis for future investigations in systems and software engineering of bioinformatics tools, and to identify promising areas for future research directions in interaction design of bioinformatics tools.

Understanding and reacting to the affective state of users is increasingly becoming important in the field of human–computer interaction (HCI) research and practice. Recent developments in brain–computer interface (BCI) technology has facilitated improved accuracy in human emotion detection and classification. In this paper, we investigate the possibility of using electroencephalogram (EEG) for the detection of four affective states based on a dimensional model (valence and arousal) of emotions. We conduct rigorous offline analysis for investigating the deep neural network (DNN) classification method in emotion detection. We also compare our classification performance with a random forest (RF) classifier and support vector machine (SVM). The data analysis results revealed that the proposed DNN-based classifier method outperformed the methods based on the SVM and RF classifiers.

Theories of semiotics and how they relate to the use of web interfaces have been a topic of research for decades. However, little attention has been paid to the perception of semiotics from the perspective of technology users in the Arabic speaking populations. In this paper, we delve into interpretations of semiotics in icons used in open government data (OGD) portals from the perspective of native Arabic speakers in the Arab Gulf. We consider how semiotics are used and understood in technology-mediated OGD environments among this population, paying particular attention to the role of social and cultural norms in the visual design of symbols and semiotics. We then offer culturally sensitive design principles and suggestions for future research that incorporates previously unexplored characteristics of semiotics, which play a role in how users perceive icon-based navigation schemes in open data portals. Implications for the design of intelligent OGD portals, and translation of applied semiotics into technological innovations for intelligent navigation in complex OGD portals are discussed.

A key problem in the field of search interfaces is dyslexic users interaction with the UI. Dyslexia is a widespread specific learning difficult (SpLD) (10% of any population is estimated to have this cognitive disability) which is under researched in the field of information retrieval. The focus here is an analysis of the User Interface (UI) for search, using visual analytical methods on eye tracking data to examine the difference between control and dyslexic searchers. We use a number of visual analytic methods including path similarity analysis (PSA) and clustering of time intervals to demonstrate both similarities and differences between the user groups. Observations of videos are used to augment the visualizations. Results demonstrate a clear difference between the user groups, and a clear memory effect on the user of search interfaces is shown -- this is a key contribution of this paper. We examine the results using of theories of dyslexia, contributing also to the field of dyslexia and search.

In the natural human computer interaction filed, researchers started to consider the other interaction modalities for diversity of applications. Among these modalities are the speech interaction systems, eye gaze interaction systems and recently Brain Computer Interfacing (BCI) systems. In BCI systems, the tools are deployed to manipulate the brain activity to produce signals that can be used to control computers or communication devices. Implementing this technology in real life varies from: entertainment systems to control layers through the user thoughts, to disability assistive devices to reduce care given. Currently the BCI technologies are developed for the purposes of boosting the disability assistive devices especially in the command controlled systems. In addition, the currently demanding research emphasis is to use brain signals for personal identifications and verification; known as biometric verification. Biometric verification was first used in as an authentication technique for systems operating devices in real environment. At that time, authentication was based on unimodal biometric identity verification systems, which compare only one trait or biometrical feature (such as voice, iris, or fingerprint) to a previous sample. However, the performance of such modals varies depending on the presence of outside factors such as background noises in a speech recognition system, or the illumination problems for a face recognition system. Another cause of pitfalls in these models is their dependency on the health of the authenticated user. In order to overcome the weaknesses of the unimodal biometric system, a multimodal biometric system was introduced.

Estimation of human emotions from Electroencephalogram (EEG) signals plays a vital role in developing robust Brain-Computer Interface (BCI) systems. In our research, we used Deep Neural Network (DNN) to address EEG-based emotion recognition. This was motivated by the recent advances in accuracy and efficiency from applying deep learning techniques in pattern recognition and classification applications. We adapted DNN to identify human emotions of a given EEG signal (DEAP dataset) from power spectral density (PSD) and frontal asymmetry features. The proposed approach is compared to state-of-the-art emotion detection systems on the same dataset. Results show how EEG based emotion recognition can greatly benefit from using DNNs, especially when a large amount of training data is available.

In Saudi Arabia, gender shapes cities in a way that is not commonly found in other cities due to Saudi Arabia’s imposed gender segregation. This segregation policy drives both genders to different areas of the city in different ways, influencing the emergence of gendered spaces. In this paper, we utilize social media data to better understand gendered spaces throughout the city of Riyadh. For our analysis, we developed an algorithm to perform gender annotation based on users’ first names. The method, optimized for English and Arabic language names, was applied to a sample of over 120,000 geotagged tweets between November 2016 and January 2017. The customer demographics of Foursquare venues were estimated based on the gender ratio of reviewers. Areas with a high degree of gender concentration in these datasets were used to identify gendered spaces. The correlation between gendered space identified from tweets and Foursquare venues was used to examine the link between amenities and gender-specific mobility habits in Riyadh. Throughout our analysis, we aim to identify ways in which government policies and the organization of businesses and services with similar customer demographics impact the mobility patterns of women and men and lead to the emergence of gendered spaces in Riyadh.

Hackathons are poised to accelerate technological progress and redefine the technology innovation lifecycle. Time-bounded events have spawned a raw form of creativity that is rarely seen elsewhere in the digital innovation landscape. Efficient monitoring and analysis of data emerging from time-bounded events - and trends in the technology innovation process that emerge from encouraging developers, designers and entrepreneurs to go from the drawing board to a working demo - is of interest to both professional analysts and the general public. This research identifies the distinguishing characteristics of hackathons in the MENA region. It also introduces a visual analytics platform for uniquely identifying the technical, socio-cultural and contextual differences that define hackathon practices and the emerging hacking communities in the MENA region. The benefit of such understanding not only supports the continued growth of such activities in these countries, it also helps to disambiguate hackathon activities from other productive practices for software development, entrepreneurship and computing education.

Analyzing and accessing information related to coupled urban socio-technical systems can provide insights into social subcultures, mobility patterns and behavior that are critical to decision making systems at an urban scale. In this paper, we examine the question of how can urban analytics provide a classification of subcultures or urban tribes for the context of Saudi Arabia. Data analytics and classification methodology of urban tribes will be used to guide the discussion, and computational challenges and directions for future research will be discussed.

Diary studies in human-computer interaction (HCI) design are qualitative methods for collecting data about users’ behavior and insights while going through an experience or interacting with a certain system. This paper examines the efficacy of using this method in exploring the design process for complex engineering systems. An online diary study was conducted to capture data from designers working on an interactive visualization platform for large-scale data sets. Design implications and insights for practitioners and developers are discussed.

Purpose To estimate ethnic-specific all-cause mortality risk following ischemic stroke and to compare mortality risk by ethnicity. Methods DATA from the Brain Attack Surveillance in Corpus Christi Project, a population-based stroke surveillance study, were used. Stroke cases between January 1, 2000 and December 31, 2002 were identified from emergency department (ED) and hospital sources ( n = 1,234). Deaths for the same period were identified from the surveillance of stroke cases, the Texas Department of Health, the coroner, and the Social Security Death Index. Ethnic-specific all-cause cumulative mortality risk was estimated at 28 days and 36 months using Kaplan Meier analysis. Cox proportional hazards regression was used to compare mortality risk by ethnicity. Results Cumulative 28-day all-cause mortality risk for Mexican Americans (MAs) was 7.8% and for non-Hispanic whites (NHWs) was 13.5%. Cumulative 36-month all-cause mortality risk was 31.3% in MAs and 47.2% in NHWs. MAs had lower 28-day (RR = 0.58; 95% CI: 0.41, 0.84) and 36-month all-cause mortality risk (RR = 0.79, 95% CI: 0.64, 0.98) compared with NHWs, adjusted for confounders. Conclusions Better survival after stroke in MAs is surprising considering their similar stroke subtype and severity compared with NHWs. Social or psychological factors, which may explain this difference, should be explored.

This paper describes an assistive technology designed for longitudinal monitoring of memory decline for people with Alzheimer’s Disease (AD). While there are systems designed for rehabilitation of people with AD, supporting caregivers, and psychosocial intervention, there is a lack in technology support that provides quantitative measures of progressive memory decline that can assist physicians in clinical settings. An interactive autobiographical memory repository of images and sound recordings was developed to facilitate measuring memory recall and recognition. The system functionality and the user-centered design approach of involving geriatric psychiatry specialists and caregivers are described.

We studied whether a computer algorithm or abstractor could diagnose stroke as well as a fellowship-trained stroke neurologist. As part of an ongoing prospective, community-based stroke surveillance project, a diagnostic algorithm was developed, and patients' neurologic signs and symptoms were collected in a computerized database. The abstractors were blinded to the results of this algorithm and were asked to verify whether the patient had a stroke. The separate results of the computer and abstractor were compared with the final diagnosis given by the blinded neurologist. From 1 January through 31 July 2000, 3418 cases were screened. The abstractors yielded sensitivity 91%, specificity 97%, positive predictive value (PPV) 85%, and negative predictive value (NPV) 99%. Three computer algorithms were evaluated. The sensitivities ranged from 83% to 96%, specificity ranged from 88% to 97%, PPV ranged from 54% to 81%, and NPV ranged from 97% to 99%. The use of computer verification or abstractors may obviate the need for physician stroke verification and may greatly improve study efficiency.

This paper describes Tawasol, a multimedia system offering an innovative and engaging learning experience for people with hearing impairments. Tawasol is a project developed in collaboration between a university-based research group and a charitable foundation. We describe the novel system features specific to Arabic interfaces and signing conventions. Challenges that were faced in the design and development of the software are discussed.

In this paper, we synthesize research on the different emerging Ambient Assisted Living (AAL) sensor-based technologies and examine the spatial parameters that are used in these systems. Different lenses in examining the AAL literature are considered, such as the chronological development in sensor-based AAL and the human factors in the design of sensor-based AAL in various contexts. Relevant metrics and standards in AAL design are highlighted. A comparative prospective of these metrics and how they are applied in recent studies and systems are also discussed. The paper presents a categorization of those technologies based on their selection of the spatial information to obtain a clearer understanding of the relationship between spatial modeling and the accuracy of these technologies. Implications for the design of AAL and situated interaction in AAL contexts are discussed.

To study the variation in emotional responses to stimuli, different methods have been developed to elicit emotions in a replicable way. Using video clips has been shown to be the most effective stimuli. However, the differences in cultural backgrounds lead to different emotional responses to the same stimuli. Therefore, we compared the emotional response to a commonly used emotion eliciting video clips from the Western culture on Saudi culture with an initial selection of emotion eliciting Arabic video clips. We analysed skin physiological signals in response to video clips from 29 Saudi participants. The results of the validated English video clips and the initial Arabic video clips are comparable, which suggest that a universal capability of the English set to elicit target emotions in Saudi sample, and that a refined selection of Arabic emotion elicitation clips would improve the capability of inducing the target emotions with higher levels of intensity.

A rapid growth in the ambient assisted living technologies (AALTs) is being witnessed due to the aging society. Evidence suggests that AALTs empower the elderly’s involvement with their surroundings, and hence; improves the quality of their living. Therefore, public service organizations (e.g. The Saudi Alzheimer’s Disease Association (ALZ)) have been established with the aim to raise awareness about AD, in order to reach a comfortable lifestyle for all elders with AD. Moreover, this fact is the motivation behind addressing our problem in the paper. Each AALT has its own special requirements in usage, care, extensibility, reusability, scalability and adaptability. More importantly, there are many other factors that have great influence on those requirements. In this paper we will investigate some of these factors, such as: the environment, the caregiver’s experience, and the elder’s age, culture, and social structure. Furthermore, adaptability and cultural factors are the pivots of our study, to show their influence on designing AALT and specifying their requirements.

The design and development of Brain Computer Interface (BCI) technologies for clinical applications is a steadily growing area of research. Applications of BCI technologies in rehabilitation contexts is often impeded by the cumbersome setup and computational complexity in BCI data analytics, which consequently leads to challenges in integrating these technologies in clinical contexts. This paper describes a framework for a novel BCI system designed for clinical settings in speech-language rehabilitation. It presents an overview of the technology involved, the applied context and the system design approach. Moreover, an exploratory study was conducted to understand the functional requirements of BCI systems in speech-language rehabilitation contexts of use.

With the growing complexity in Tangible User Interfaces (TUIs) and their integration in the decision-making process, user acceptance of these TUI systems continues to be an important issue. Drawing upon recent findings in computer-mediated communication, human computer interaction, computer-supported-cooperative work, and social psychology, the present research extends the coding schemes for observational video analysis by incorporating the variables of communication and collaboration in the context of systems designed for urban planning and modeling.

This paper reports on insights gained from investigating multilingual user interfaces designed for banking systems in the Arab Region. In this region, Arabic is the native language; however a plethora of expatriates reside in the region who speak different languages. Three modes of banking interactions are examined in the local context; internet banking, automatic teller machines (ATMs), and mobile banking (MB). Reflections on interaction design for the three modes of banking illuminates the culture-orientated design considerations for banking interactions and demonstrates how users, in this case bank customers, shape technological changes and influence interface design. The contribution of this research is threefold. Firstly, gain an insight into socio-cultural design requirements for banking interfaces; secondly, an exploratory survey of interface design considerations in the three modes of banking with a focus on multilingual aspects of the design; and finally, distil the findings into design recommendations for socio-cultural aspects that are relevant to the context of banking interactions in the Arab Region.

This paper reports on a comprehensive survey of mobile applications offered by higher education institutions in Saudi Arabia. In this study, we examine the accessibility, User Experience (UX) design, and usability of services offered by these applications. In recent years, research has shown growing trends in mobile application adoption and usage in the context of higher education in Saudi Arabia. Evidence from the local context suggests that mobile applications have potential to increase retention of students, enhance teaching and learning, and facilitate the provision of services. Our understanding of mobile application services offered by public and private higher education institutions in Saudi Arabia is inadequate. Therefore, we present a synthesis of mobile applications and a categorization of types, platforms, target users, and examine their usability. The study included mobile applications and services offered by twenty six public universities and nine private universities. Design implications of our usability review for these mobile applications that are offered by higher education institutes for students, faculty and administration are discussed.

Emerging technologies are beginning to find their way in different health care centers and clinics worldwide for the purpose of assessment and rehabilitation for people with attention deficit disorders. And due to the variation in the practitioners and patients’ requirements and preferences for using these technologies, understanding the usability issues has become essential for further development in this domain. In particular, addressing issues of selecting usability evaluation methods and their effectiveness in identifying usability problems. A bespoke heuristic set for the context of intervention programs for developing sustained attention is proposed and tested. In this study, we conducted usability heuristic evaluations on three sustained attention assessment and rehabilitation programs that involve emerging technologies; which are Neurofeedback and eye tracking. The heuristic evaluation was conducted by five evaluators, and the results showed that the proposed heuristic inspection evaluation method was effective in finding major usability problems in programs designed for sustained attention assessment and rehabilitation. Moreover, recommendations were presented regarding the evaluators’ experience with the evaluated interactive programs, the contexts of usage, target user communities, and the technical background knowledge of the interaction modalities.

To provide a scientific rationale for choosing an optimal stroke surveillance method, the authors compared active surveillance with passive surveillance. The methods involved ascertaining cerebrovascular events that occurred in Nueces County, Texas, during calendar year 2000. Active methods utilized screening of hospital and emergency department logs and routine visiting of hospital wards and out-of-hospital sources. Passive means relied on International Classification of Diseases, Ninth Revision (ICD-9), discharge codes for case ascertainment. Cases were validated by fellowship-trained stroke neurologists on the basis of published criteria. The results showed that, of the 6,236 events identified through both active and passive surveillance, 802 were validated to be cerebrovascular events. When passive surveillance alone was used, 209 (26.1%) cases were missed, including 73 (9.1%) cases involving hospital admission and 136 (17.0%) out-of-hospital strokes. Through active surveillance alone, 57 (7.1%) cases were missed. The positive predictive value of active surveillance was 12.2%. Among the 2,099 patients admitted to a hospital, passive surveillance using ICD-9 codes missed 73 cases of cerebrovascular disease and mistakenly included 222 noncases. There were 57 admitted hospital cases missed by active surveillance, including 13 not recognized because of human error. This study provided a quantitative means of assessing the utility of active and passive surveillance for cerebrovascular disease. More uniform surveillance methods would allow comparisons across studies and communities.

Recent developments and studies in brain-computer interface (BCI) technologies have facilitated emotion detection and classification. Many BCI studies have sought to investigate, detect, and recognize participants’ emotional affective states. The applied domains for these studies are varied, and include such fields as communication, education, entertainment, and medicine. To understand trends in electroencephalography (EEG)-based emotion recognition system research and to provide practitioners and researchers with insights into and future directions for emotion recognition systems, this study set out to review published articles on emotion detection, recognition, and classification. The study also reviews current and future trends and discusses how these trends may impact researchers and practitioners alike. We reviewed 285 articles, of which 160 were refereed journal articles that were published since the inception of affective computing research. The articles were classified based on a scheme consisting of two categories: research orientation and domains/applications. Our results show considerable growth of EEG-based emotion detection journal publications. This growth reflects an increased research interest in EEG-based emotion detection as a salient and legitimate research area. Such factors as the proliferation of wireless EEG devices, advances in computational intelligence techniques, and machine learning spurred this growth.

This paper presents a systematic review of technologies designed and developed for urban and architectural planning. The usability and user experiences of urban planning systems designed with mixed reality, virtual reality, tangible interaction, and direct manipulation tabletop interfaces are examined. Emphasis in this review is on the design implications of different interaction modalities in supporting decision making in applied scenarios of urban planning. The human factors engineering process for urban planning decision support systems takes into account the perceptive space, comfort, and productivity of planners and decision makers. Tactile fusion of human perception and action is examined in urban planning decision support systems that are designed with virtual and tangible interaction. Case studies describing applied scenarios of urban planning are reviewed with a critique of navigation design, human perception, collaboration support, and visualization of decision scenarios. The human factors for designing systems that support clear representations of urban planning states across all sensory modalities are reported.

In this paper, we introduce a decision support system (DSS) platform (City Schema) that is designed to connect a tangible interface within a 3D modeling environment (City Form) with a simulation engine for analyzing the data of the urban, transportation, energy and water systems of the city (City Analytics) to support collaborative city planning. This DSS connects two completely independent systems into one integrated system. The first system is a physical 3D model of a city with a tangible user interface that supports interactive and collaborative activities and provides users with direct manipulation interaction and intuitive interfaces. The second system is an urban modeling design tool which is a simulation engine that has several simulation modules such as operational energy, mobility, daylight, transportation and others. The DSS we present here can be used to describe a real world problem and identify possible solutions to the modeled problem through the computation of many scenarios/alternatives so that users of the DSS can evaluate, compare and select a potential solution. Our City Schema DSS consists of: database management component, simulation modules management component, and an interactive user interface with dynamic visualization and decision scenario simulations. Human factors for supporting multi-user co-located collaboration to assist decision makers in making better decisions are examined. Design implications of different interaction modalities for decision support systems and their impact on providing intuitive and engaging user experiences are discussed.

Multimedia surveillance systems have evolved in recent years to capture, process and analyze multimedia data coming from heterogeneous sensors in the context of the annual pilgrimage to Mecca in Hajj. Systems in these contexts are often designed to support decision making, such as responding to alerts triggered by sensors and incidents detected by surveillance systems as well as to provide useful information for monitoring and emergency-response teams concerned with health and public safety. Various tools and techniques from different fields such as operations research, computer vision, image and video processing, pattern recognition, and multimedia fusion have contributed to the proliferation of such systems in the context of Hajj. In this paper, a systematic review and synthesis of the representative works that have been done in the field of multimedia surveillance for event detection in Hajj is presented. Observations and reflections on these works are discussed in the context of Hajj rituals' distinctive characteristics, crowd-management challenges, and multimedia issues related to event detection and surveillance systems in Hajj.

The automatic detection of human affective states has been of great interest lately for its applications not only in the field of Human-Computer Interaction, but also for its applications in physiological, neurobiological and sociological studies. Several standardized techniques to elicit emotions have been used, with emotion eliciting movie clips being the most popular. To date, there are only four studies that have been carried out to validate emotional movie clips using three different languages (English, French, Spanish) and cultures (French, Italian, British / American). The context of language and culture is an underexplored area in affective computing. Considering cultural and language differences between Western and Arab countries, it is possible that some of the validated clips, even when dubbed, will not achieve similar results. Given the unique and conservative cultures of the Arab countries, a standardized and validated framework for affect studies is needed in order to be comparable with current studies of different cultures and languages. In this paper, we describe a framework and its prerequisites for eliciting emotions that could be used for affect studies on an Arab population. We present some aspects of Arab culture values that might affect the selection and acceptance of emotion eliciting video clips. Methods for rating and validating Arab emotional clips are presented to derive at a list of clips that could be used in the proposed emotion elicitation framework. A pilot study was conducted to evaluate a basic version of our framework, which showed great potential to succeed in eliciting emotions.

This paper reports on insights gained from collaborations between multi-disciplinary research teams and practitioners in a Disability Service Center in King Saud University (KSU) in Saudi Arabia. Projects were conducted in the context of designing, developing and evaluating different assistive technologies in the university’s Software and Knowledge Engineering Research Group. In these projects, methodological considerations have been reported for effectively involving domain specialists in research and development projects for assistive technologies. Subject Matter Experts (SMEs) are often involved in the technology design cycles of these projects in various roles (e.g. design partners, design informants, testers). This paper highlights the human factors relevant for the design and evaluation of interactive systems for SpLDs that were synthesized from these collaborative contexts. We also shed light on issues to consider in the design partnerships between researchers and practitioners for requirements engineering and user acceptance testing phases of system development. Implications for the design and development of systems for SpLDs in other languages and cultural contexts are discussed.

In this paper, we synthesize research on the type of cognitive commands that have been examined for controlling Brain Computer Interface (BCI) wheelchairs and the human factors that have been reported for the selection of different protocols of BCI commands for an individual user. Moreover, we investigate how different researchers have considered the necessity of sustained movement from a single thought/command, having an emergency stop, and the commands necessary for assisting users with a particular disability. We then highlight how these human factors and ergonomics’ considerations were applied in the design and development of an EEG-controlled motorized wheelchair, aiming to emphasize users’ requirements for people with severe physical disabilities. In this case study, we propose a brain controlled wheelchair navigation system that can help the user travel to a desired destination, without having to personally drive the wheelchair and frequently change the movement directions along the path to the destination. The user can choose the desired destination from a map of the environment, using his/her brain signals only. The user can navigate through the map using BCI cognitivecommands. The system processes the brain signals, determines the required destination on the map, and constructs an optimized movement path from the source to the intended destination. To construct an obstacle-free path with the shortest possible distance and minimum number of turns, a path planning optimization problem is solved using a simple Simulated Annealing (SA) algorithm. The resulting optimized path will be translated into movement directions that are sent to the microcontroller to move the wheelchair to the desired destination.

In this paper, we describe the User Interface (UI) design issues for serious games aimed at developing phonological processing skills of people with specific learning difficulties such as dyslexia. These games are designed with Brain-Computer Interfaces (BCI) which take the compelling and creative aspects of traditional computer games designed for Arabic interfaces and apply them for cognitive skills’ development purposes. Immersion and engagement in the games are sought with novel interaction methods; the interaction mode for these games involved mind-control coupled with cursor-based selection. We describe the conceptual design of these serious games and an overview of the BCI software development framework.

Brain computer interfaces have become one of the growing areas for human computer interaction research. Various research studies were conducted to control graphical user interfaces using brain computer interface methods. Furthermore, eye tracking was another input modality that has been examined for controlling interactive systems. In this paper we investigate object selection using P300 brain signals and eye tracking across consistently design graphical user interface. We conducted several experiments on each approach on able-bodied subjects. The aim of these experiments was to evaluate and compare the accuracy and time to complete the task for both approaches. Experimental results indicated that the accuracy of eye tracking as an input modality was 92.5% on average, with 80% of participants reaching 100% accuracy. In contrast, P300 was found to produce low accuracy and efficiency results compared to eye tracking with average accuracy 32% among 20 participants.

This paper describes the research conducted to design the Arabic Brain Communicator (ABC), which is a brain-controlled typing system designed to facilitate communication for people with severe motor disabilities in Arabic. A user centered design was adopted; it included empirical investigations and meetings with Subject-Matter Experts and possible users. Activities conducted in the analysis and design of the system are discussed.

Sada is an interactive multimedia program for auditory discrimination therapy in the Arabic Language. Sada was designed to extend speech therapy beyond clinical settings and provide patients with a computer-based therapy system which can be used between sessions with speech therapists; at school or at home on an ’on-demand’ basis. The program provides local Arabic dialects and a configurable knowledge-base which allows for extending the therapy and customizing the pronunciation of words for different Arabic-speaking populations. The Sada architecture and its interaction design are described and the advantages of computer-based therapy for auditory perceptual problems are discussed.

This paper describes an eye-controlled game designed for behavioral therapy of ADHD. A user-centered design approach was adopted in the development cycle of these games in close collaboration with domain experts and target user populations. The games have an Arabic language interface and include multimodal interaction. Game scenarios were designed with increasing complexity depicted in visual design, dwell time for controlling elements within the games, and combinations of key presses with eye-control at higher levels of attention training. The visual design, interaction design and the system’s conceptual designs are discussed.

In this paper we describe an exploratory experiment conducted in the early stages of the design and development of a screening program for non-communicative individuals. The system incorporates eye-tracking and biosensor technologies for objectively measuring affective states by combining measures of ElectroDermal Activity (EDA), temperature and eye gaze metrics of pupil dilation. The objective is to provide individuals with cognitive disabilities who experience difficulties in expressing their feelings with an alternate form of communicating their emotional states in clinical screening and occupational therapy sessions. The interactive computer-based screening program is comprised of stimuli-sets designed to elicit emotional response from viewers with a trend analysis component designed with an interface for health care providers. The focus of this paper is the feasibility of including pupil dilation as a measure reflecting affective states of individuals in the overall emotional intelligence screening system.

This paper presents the findings of an exploratory study comparing two of Brain-Computer Interface approaches, P300 and Motor Imagery, with EEG signals acquired using the Emotiv Neuroheadset. It was conducted to determine the most suitable approach for typing applications based on BCI. Results show that while selection accuracy is similar for both, with mean of 50%, the speed varies greatly, with the former approach being approximately 2 times more efficient in typing. Implications presented in this document are useful for BCI researchers who seek to build brain-controlled Augmentative and Alternative Communication technologies.