18 research outputs found

    Usability and performance measure of a consumer-grade brain computer interface system for environmental control by neurological patients

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    With the increasing incidence and prevalence of chronic brain injury patients and the current financial constraints in healthcare budgets, there is a need for a more intelligent way to realise the current practice of neuro-rehabilitation service provision. Brain-computer Interface (BCI) systems have the potential to address this issue to a certain extent only if carefully designed research can demonstrate that these systems are accurate, safe, cost-effective, are able to increase patient/carer satisfaction and enhance their quality of life. Therefore, one of the objectives of the proposed study was to examine whether participants (patients with brain injury and a sample of reference population) were able to use a low cost BCI system (Emotiv EPOC) to interact with a computer and to communicate via spelling words. Patients participated in the study did not have prior experience in using BCI headsets so as to measure the user experience in the first-exposure to BCI training. To measure emotional arousal of participants we used an ElectroDermal Activity Sensor (Qsensor by Affectiva). For the signal processing and feature extraction of imagery controls the Cognitive Suite of Emotiv's Control Panel was used. Our study reports the key findings based on data obtained from a group of patients and a sample reference population and presents the implications for the design and development of a BCI system for communication and control. The study also evaluates the performance of the system when used practically in context of an acute clinical environment

    Excess stroke in Mexican Americans compared with non-Hispanic Whites: the Brain Attack Surveillance in Corpus Christi Project.

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    Mexican Americans are the largest subgroup of Hispanics, the largest minority population in the United States. Stroke is the leading cause of disability and third leading cause of death. The authors compared stroke incidence among Mexican Americans and non-Hispanic Whites in a population-based study. Stroke cases were ascertained in Nueces County, Texas, utilizing concomitant active and passive surveillance. Cases were validated on the basis of source documentation by board-certified neurologists masked to subjects\u27 ethnicity. From January 2000 to December 2002, 2,350 cerebrovascular events occurred. Of the completed strokes, 53% were in Mexican Americans. The crude cumulative incidence was 168/10,000 in Mexican Americans and 136/10,000 in non-Hispanic Whites. Mexican Americans had a higher cumulative incidence for ischemic stroke (ages 45-59 years: risk ratio = 2.04, 95% confidence interval: 1.55, 2.69; ages 60-74 years: risk ratio = 1.58, 95% confidence interval: 1.31, 1.91; ages \u3eor=75 years: risk ratio = 1.12, 95% confidence interval: 0.94, 1.32). Intracerebral hemorrhage was more common in Mexican Americans (age-adjusted risk ratio = 1.63, 95% confidence interval: 1.24, 2.16). The subarachnoid hemorrhage age-adjusted risk ratio was 1.57 (95% confidence interval: 0.86, 2.89). Mexican Americans experience a substantially greater ischemic stroke and intracerebral hemorrhage incidence compared with non-Hispanic Whites. As the Mexican-American population grows and ages, measures to target this population for stroke prevention are critical

    Usability Evaluation of Optimized Single-Pointer Arabic Keyboards Using Eye Tracking

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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

    Developing a New Framework for Evaluating Arabic Dyslexia Training Tools

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    Improving Efficiency of Stroke Research: The Brain Attack Surveillance in Corpus Christi Study

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    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\u27 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

    Usability and Performance Measure of a Consumer-grade Brain Computer Interface System for Environmental Control by Neurological Patients

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    With the increasing incidence and prevalence of chronic brain injury patients and the current financial constraints in healthcare budgets, there is a need for a more intelligent way to realise the current practice of neuro-rehabilitation service provision. Brain-computer Interface (BCI) systems have the potential to address this issue to a certain extent only if carefully designed research can demonstrate that these systems are accurate, safe, cost-effective, are able to increase patient/carer satisfaction and enhance their quality of life. Therefore, one of the objectives of the proposed study was to examine whether participants (patients with brain injury and a sample of reference population) were able to use a low cost BCI system (Emotiv EPOC) to interact with a computer and to communicate via spelling words. Patients participated in the study did not have prior experience in using BCI headsets so as to measure the user experience in the first-exposure to BCI training. To measure emotional arousal of participants we used an ElectroDermal Activity Sensor (Qsensor by Affectiva). For the signal processing and feature extraction of imagery controls the Cognitive Suite of Emotiv's Control Panel was used. Our study reports the key findings based on data obtained from a group of patients and a sample reference population and presents the implications for the design and development of a BCI system for communication and control. The study also evaluates the performance of the system when used practically in context of an acute clinical environment
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