Support vector machines to detect physiological patterns for EEG and EMG-based human-computer interaction:a review

Support Vector Machines (SVMs) are widely used classifiers for detecting physiological patterns in Human-Computer Interaction (HCI). Their success is due to their versatility, robustness and large availability of free dedicated toolboxes. Frequently in the literature, insufficient details about the SVM implementation and/or parameters selection are reported, making it impossible to reproduce study analysis and results. In order to perform an optimized classification and report a proper description of the results, it is necessary to have a comprehensive critical overview of the application of SVM. The aim of this paper is to provide a review of the usage of SVM in the determination of brain and muscle patterns for HCI, by focusing on electroencephalography (EEG) and electromyography (EMG) techniques. In particular, an overview of the basic principles of SVM theory is outlined, together with a description of several relevant literature implementations. Furthermore, details concerning reviewed papers are listed in tables, and statistics of SVM use in the literature are presented. Suitability of SVM for HCI is discussed and critical comparisons with other classifiers are reported.

Using Research Methods in Human Computer Interaction to Design Technology for Resilience

Research in human computer interaction (HCI) covers both technological and human behavioural concerns. As a consequence, the contributions made in HCI research tend to be aware to either engineering or the social sciences. In HCI the purpose of practical research contributions is to reveal unknown insights about human behaviour and its relationship to technology. Practical research methods normally used in HCI include formal experiments, field experiments, field studies, interviews, focus groups, surveys, usability tests, case studies, diary studies, ethnography, contextual inquiry, experience sampling, and automated data collection. In this paper, we report on our experience using the evaluation methods focus groups, surveys and interviews and how we adopted these methods to develop artefacts: either interface’s design or information and technological systems. Four projects are examples of the different methods application to gather information about user’s wants, habits, practices, concerns and preferences. The goal was to build an understanding of the attitudes and satisfaction of the people who might interact with a technological artefact or information system. Conversely, we intended to design for information systems and technological applications, to promote resilience in organisations (a set of routines that allow to recover from obstacles) and user’s experiences. Organisations can here also be viewed within a system approach, which means that the system perturbations even failures could be characterized and improved. The term resilience has been applied to everything from the real estate, to the economy, sports, events, business, psychology, and more. In this study, we highlight that resilience is also made up of a number of different skills and abilities (self-awareness, creating meaning from other experiences, self-efficacy, optimism, and building strong relationships) that are a few foundational ingredients, which people should use along with the process of enhancing an organisation’s resilience. Resilience enhances knowledge of resources available to people confronting existing problems.

Data, Software, and Advanced Computational Usage of University of Washington Research Leaders

Scientific research is increasingly data-intensive, relying more and more upon advanced computational resources to be able to answer the questions most pressing to our society at large. This report presents findings from a brief descriptive survey sent to a sample of 342 leading researchers at the University of Washington (UW), Seattle, Washington in 2010 and 2011 as the first stage of the larger National Science Foundation project “Interacting with Cyberinfrastructure in the Face of Changing Science.” This survey assesses these researcher’s use of advanced computational resources, data, and software in their research. We present high-level findings that describe UW researchers’: demographics, interdisciplinarity, research groups, data use, software and computational use—including software development and use, data storage and transfer activities, and collaboration tools, and computing resources. These findings offer insights into the state of computational resources in use during this time period as well as offering a look at the data intensiveness of UW researchers.

Designing for learner engagement with computer-based testing

The issues influencing student engagement with high-stakes computer-based exams were investigated, drawing on feedback from two cohorts of international MA Education students encountering this assessment method for the first time. Qualitative data from surveys and focus groups on the students’ examination experience were analysed, leading to the identification of engagement issues in the delivery of high-stakes computer-based assessments.The exam combined short-answer open-response questions with multiple-choice-style items to assess knowledge and understanding of research methods. The findings suggest that engagement with computer-based testing depends, to a lesser extent, on students’ general levels of digital literacy and, to a greater extent, on their information technology (IT) proficiency for assessment and their ability to adapt their test-taking strategies, including organisational and cognitive strategies, to the online assessment environment. The socialisation and preparation of students for computer-based testing therefore emerge as key responsibilities for instructors to address, with students requesting increased opportunities for practice and training to develop the IT skills and test-taking strategies necessary to succeed in computer-based examinations. These findings and their implications in terms of instructional responsibilities form the basis of a proposal for a framework for Learner Engagement with e-Assessment Practices.

Dietary Supplement Usage And Motivation In Brazilian Road Runners.

The consumption of dietary supplements is highest among athletes and it can represent potential a health risk for consumers. The aim of this study was to determine the prevalence of consumption of dietary supplements by road runners. We interviewed 817 volunteers from four road races in the Brazilian running calendar. The sample consisted of 671 male and 146 female runners with a mean age of 37.9 ± 12.4 years. Of the sample, 28.33% reported having used some type of dietary supplement. The main motivation for this consumption is to increase in stamina and improve performance. The probability of consuming dietary supplements increased 4.67 times when the runners were guided by coaches. The consumption of supplements was strongly correlated (r = 0.97) with weekly running distance, and also highly correlated (r = 0.86) with the number of years the sport had been practiced. The longer the runner had practiced the sport, the higher the training volume and the greater the intake of supplements. The five most frequently cited reasons for consumption were: energy enhancement (29.5%), performance improvement (17.1%), increased level of endurance (10.3%), nutrient replacement (11.1%), and avoidance of fatigue (10.3%). About 30% of the consumers declared more than one reason for taking dietary supplements. The most consumed supplements were: carbohydrates (52.17%), vitamins (28.70%), and proteins (13.48%). Supplement consumption by road runners in Brazil appeared to be guided by the energy boosting properties of the supplement, the influence of coaches, and the experience of the user. The amount of supplement intake seemed to be lower among road runners than for athletes of other sports. We recommend that coaches and nutritionists emphasise that a balanced diet can meet the needs of physically active people.

Categorization skills and recall in brain damaged children: a multiple case study

During development, children become capable of categorically associating stimuli and of using these relationships for memory recall. Brain damage in childhood can interfere with this development. This study investigated categorical association of stimuli and recall in four children with brain damages. The etiology, topography and timing of the lesions were diverse. Tasks included naming and immediate recall of 30 perceptually and semantically related figures, free sorting, delayed recall, and cued recall of the same material. Traditional neuropsychological tests were also employed. Two children with brain damage sustained in middle childhood relied on perceptual rather than on categorical associations in making associations between figures and showed deficits in delayed or cued recall, in contrast to those with perinatal lesions. One child exhibited normal performance in recall despite categorical association deficits. The present results suggest that brain damaged children show deficits in categorization and recall that are not usually identified in traditional neuropsychological tests.

ScriptLattes: an open-source knowledge extraction system from the Lattes platform

The Lattes platform is the major scientific information system maintained by the National Council for Scientific and Technological Development (CNPq). This platform allows to manage the curricular information of researchers and institutions working in Brazil based on the so called Lattes Curriculum. However, the public information is individually available for each researcher, not providing the automatic creation of reports of several scientific productions for research groups. It is thus difficult to extract and to summarize useful knowledge for medium to large size groups of researchers. This paper describes the design, implementation and experiences with scriptLattes: an open-source system to create academic reports of groups based on curricula of the Lattes Database. The scriptLattes system is composed by the following modules: (a) data selection, (b) data preprocessing, (c) redundancy treatment, (d) collaboration graph generation among group members, (e) research map generation based on geographical information, and (f) automatic report creation of bibliographical, technical and artistic production, and academic supervisions. The system has been extensively tested for a large variety of research groups of Brazilian institutions, and the generated reports have shown an alternative to easily extract knowledge from data in the context of Lattes platform. The source code, usage instructions and examples are available at http://scriptlattes.sourceforge.net/.

Architecture for machining process and production monitoring based in open computer numerical control

This paper proposes an architecture for machining process and production monitoring to be applied in machine tools with open Computer numerical control (CNC). A brief description of the advantages of using open CNC for machining process and production monitoring is presented with an emphasis on the CNC architecture using a personal computer (PC)-based human-machine interface. The proposed architecture uses the CNC data and sensors to gather information about the machining process and production. It allows the development of different levels of monitoring systems with mininium investment, minimum need for sensor installation, and low intrusiveness to the process. Successful examples of the utilization of this architecture in a laboratory environment are briefly described. As a Conclusion, it is shown that a wide range of monitoring solutions can be implemented in production processes using the proposed architecture.

Dynamical models for computer viruses propagation

Nowadays, digital computer systems and networks are the main engineering tools, being used in planning, design, operation, and control of all sizes of building, transportation, machinery, business, and life maintaining devices. Consequently, computer viruses became one of the most important sources of uncertainty, contributing to decrease the reliability of vital activities. A lot of antivirus programs have been developed, but they are limited to detecting and removing infections, based on previous knowledge of the virus code. In spite of having good adaptation capability, these programs work just as vaccines against diseases and are not able to prevent new infections based on the network state. Here, a trial on modeling computer viruses propagation dynamics relates it to other notable events occurring in the network permitting to establish preventive policies in the network management. Data from three different viruses are collected in the Internet and two different identification techniques, autoregressive and Fourier analyses, are applied showing that it is possible to forecast the dynamics of a new virus propagation by using the data collected from other viruses that formerly infected the network. Copyright (c) 2008 J. R. C. Piqueira and F. B. Cesar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Does Training Laparoscopic Skills in a Virtual Reality Simulator Improve Surgical Performance?

Background and Purpose: Several different methods of teaching laparoscopic skills have been advocated, with virtual reality surgical simulation (VRSS) being the most popular. Its effectiveness in improving surgical performance is not a consensus yet, however. The purpose of this study was to determine whether practicing surgical skills in a virtual reality simulator results in improved surgical performance. Materials and Methods: Fifteen medical students recruited for the study were divided into three groups. Group I (control) did not receive any VRSS training. For 10 weeks, group II trained basic laparoscopic skills (camera handling, cutting skill, peg transfer skill, and clipping skill) in a VRSS laparoscopic skills simulator. Group III practiced the same skills and, in addition, performed a simulated cholecystectomy. All students then performed a cholecystectomy in a swine model. Their performance was reviewed by two experienced surgeons. The following parameters were evaluated: Gallbladder pedicle dissection time, clipping time, time for cutting the pedicle, gallbladder removal time, total procedure time, and blood loss. Results: With practice, there was improvement in most of the evaluated parameters by each of the individuals. There were no statistical differences in any of evaluated parameters between those who did and did not undergo VRSS training, however. Conclusion: VRSS training is assumed to be an effective tool for learning and practicing laparoscopic skills. In this study, we could not demonstrate that VRSS training resulted in improved surgical performance. It may be useful, however, in familiarizing surgeons with laparoscopic surgery. More effective methods of teaching laparoscopic skills should be evaluated to help in improving surgical performance.

Elderly online: Effects of a digital inclusion program in cognitive performance

There is little empirical data about the impact of digital inclusion on cognition among older adults. This paper aimed at investigating the effects of a digital inclusion program in the cognitive performance of older individuals who participated in a computer learning workshop named ""Idosos On-Line`` (Elderly Online). Forty-two aged individuals participated in the research study: 22 completed the computer training workshop and 20 constituted the control group. All subjects answered a sociodemographic questionnaire and completed the Addenbrooke`s cognitive examination, revised (ACE-R), which examines five cognitive domains: orientation and attention, memory, verbal fluency, language, and visuo-spatial skills. It was noted that the experimental group`s cognitive performance significantly improved after the program, particularly in the language and memory domains, when compared to the control group. These findings suggest that the acquisition of new knowledge and the use of a new tool, that makes it possible to access the Internet, may bring gains to cognition. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Anthropometric characteristics and motor skills in talent selection and development in indoor soccer

Kick performance, anthropometric characteristics, slalom, and linear running were assessed in 49 (24 elite, 25 nonelite) postpubertal indoor soccer players in order to (a) verify whether anthropometric characteristics and physical and technical capacities can distinguish players of different competitive levels, (b) compare the kicking kinematics of these groups, with and without a defined target, and (c) compare results on the assessments and coaches` subjective rankings of the players. Thigh circumference and specific technical capacities differentiated the players by level of play; cluster analysis correctly classified 77.5% of the players. The correlation between players` standardized measures and the coaches` rankings was 0.29. Anthropometric characteristics and physical capacities do not necessarily differentiate players at post-pubertal stages and should not be overvalued during early development. Considering the coaches` rankings, performance measures outside the specific game conditions may not be useful in identification of talented players.

A Taxonomy for Locality Algorithms on Peer-to-Peer Networks

The continuous growth of peer-to-peer networks has made them responsible for a considerable portion of the current Internet traffic. For this reason, improvements in P2P network resources usage are of central importance. One effective approach for addressing this issue is the deployment of locality algorithms, which allow the system to optimize the peers` selection policy for different network situations and, thus, maximize performance. To date, several locality algorithms have been proposed for use in P2P networks. However, they usually adopt heterogeneous criteria for measuring the proximity between peers, which hinders a coherent comparison between the different solutions. In this paper, we develop a thoroughly review of popular locality algorithms, based on three main characteristics: the adopted network architecture, distance metric, and resulting peer selection algorithm. As result of this study, we propose a novel and generic taxonomy for locality algorithms in peer-to-peer networks, aiming to enable a better and more coherent evaluation of any individual locality algorithm.