310 resultados para HCI


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Interaction is increasingly a public affair, taking place in our theatres, galleries, museums, exhibitions and on the city streets. This raises a new design challenge for HCI, questioning how a performer s interaction with a computer experienced is by spectators. We examine examples from art, performance and exhibition design, comparing them according to the extent to which they hide, partially reveal, transform, reveal or even amplify a performerts manipulations. We also examine the effects of these manipulations including movements, gestures and utterances that take place around direct input and output. This comparison reveals four broad design strategies: `secretive,' where manipulations and effects are largely hidden; `expressive,' where they are revealed, enabling the spectator to fully appreciate the performer's interaction; `magical,' where effects are revealed but the manipulations that caused them are hidden; and finally `suspenseful,' where manipulations are apparent, but effects only get revealed when the spectator takes their turn.

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Betalains are plant derived natural pigments that are presently gaining popularity for use as natural colorants in food industry. Although being betalains from red beetroot already used as food colorant (E- 162), these compounds are not as well studied as compared to other natural pigments such as anthocyanins, carotenoids or chlorophylls (I]. Since food additives are on the focus of public interest, it is becoming increasingly important to meet consumers' expectations for natural and healthy products. Hence, the search for new plant-derived colorants for the food industry is still necessary [2]. Betalains were originally called 'nitrogenous anthocyanins', which incorrectly implied structural similarities between the two pigment classes. There are two structurally different types of betalains: the yellow/orange betaxanthins which are the condensation products of betalamic acid and assorted amino compounds, and the red betacyanins which are formed by glycosylation and acylation of cyclo-DOPA [3]. Looking at the chemical structure of the pigment, the addition of an acid to the extraction solvent will increase the affinity of the pigment with the solvent. The aim of this study was to use Gomphrena globosa L. flowers, as an alternative plant source to obtain these pigments and to evaluate the best acid to be used within the extraction procedure. For that purpose three different acids (acetic, hydrochloric and phosphoric acids, all ofthem allowed by the food industry), adjusted at the same pH, were tested during a maceration extraction procedure. After the extraction a purification through C18 column was performed in order to obtain a more concentrate extract in betacyanins. The results were analysed by HPLC-PDA-MSIESI. The betacyanin profile allowed the identification of gomphrenin IIJIII and isogomphrenin IIIIII and the best results were achieved by performing the extraction procedure using hydrochloric acid (6.6 mg/g extract), while phosphoric acid only presented trace amounts of these compounds. When acetic acid was used, the pigment extracted was 6.8 times less (0.97 mg/g extract) when compared to HCI. In conclusion hydrochloric acid can be considered the most suitable acid to be applied in the extraction procedure of these pigments.

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[EN] Therefore the understanding and proper evaluation of the flow and mixing behaviour at microscale becomes a very important issue. In this study, the diffusion behaviour of two reacting solutions of HCI and NaOH were directly observed in a glass/polydimethylsiloxane microfluidic device using adaptive coatings based on the conductive polymer polyaniline that are covalently attached to the microchannel walls. The two liquid streams were combined at the junction of a Y-shaped microchannel, and allowed to diffuse into each other and react. The results showed excellent correlation between optical observation of the diffusion process and the numerical results. A numerical model which is based on finite volume method (FVM) discretisation of steady Navier-Stokes (fluid flow) equations and mass transport equations without reactions was used to calculate the flow variables at discrete points in the finite volume mesh element. The high correlation between theory and practical data indicates the potential of such coatings to monitor diffusion processes and mixing behaviour inside microfluidic channels in a dye free environment.

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In the past few years, human facial age estimation has drawn a lot of attention in the computer vision and pattern recognition communities because of its important applications in age-based image retrieval, security control and surveillance, biomet- rics, human-computer interaction (HCI) and social robotics. In connection with these investigations, estimating the age of a person from the numerical analysis of his/her face image is a relatively new topic. Also, in problems such as Image Classification the Deep Neural Networks have given the best results in some areas including age estimation. In this work we use three hand-crafted features as well as five deep features that can be obtained from pre-trained deep convolutional neural networks. We do a comparative study of the obtained age estimation results with these features.

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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.

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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.

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Background: The enduring aging of the world population and prospective increase of age-related chronic diseases urge the implementation of new models for healthcare delivery. One strategy relies on ICT (Information and Communications Technology) home-based solutions allowing clients to pursue their treatments without institutionalization. Stroke survivors are a particular population that could strongly benefit from such solutions, but is not yet clear what the best approach is for bringing forth an adequate and sustainable usage of home-based rehabilitation systems. Here we explore two possible approaches: coaching and gaming. Methods: We performed trials with 20 healthy participants and 5 chronic stroke survivors to study and compare execution of an elbow flexion and extension task when performed within a coaching mode that provides encouragement or within a gaming mode. For each mode we analyzed compliance, arm movement kinematics and task scores. In addition, we assessed the usability and acceptance of the proposed modes through a customized self-report questionnaire. Results: In the healthy participants sample, 13/20 preferred the gaming mode and rated it as being significantly more fun (p < .05), but the feedback delivered by the coaching mode was subjectively perceived as being more useful (p < .01). In addition, the activity level (number of repetitions and total movement of the end effector) was significantly higher (p <.001) during coaching. However, the quality of movements was superior in gaming with a trend towards shorter movement duration (p=.074), significantly shorter travel distance (p <.001), higher movement efficiency (p <.001) and higher performance scores (p <.001). Stroke survivors also showed a trend towards higher activity levels in coaching, but with more movement quality during gaming. Finally, both training modes showed overall high acceptance. Conclusions: Gaming led to higher enjoyment and increased quality in movement execution in healthy participants. However, we observed that game mechanics strongly determined user behavior and limited activity levels. In contrast, coaching generated higher activity levels. Hence, the purpose of treatment and profile of end-users has to be considered when deciding on the most adequate approach for home based stroke rehabilitation.

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User Quality of Experience (QoE) is a subjective entity and difficult to measure. One important aspect of it, User Experience (UX), corresponds to the sensory and emotional state of a user. For a user interacting through a User Interface (UI), precise information on how they are using the UI can contribute to understanding their UX, and thereby understanding their QoE. As well as a user’s use of the UI such as clicking, scrolling, touching, or selecting, other real-time digital information about the user such as from smart phone sensors (e.g. accelerometer, light level) and physiological sensors (e.g. heart rate, ECG, EEG) could contribute to understanding UX. Baran is a framework that is designed to capture, record, manage and analyse the User Digital Imprint (UDI) which, is the data structure containing all user context information. Baran simplifies the process of collecting experimental information in Human and Computer Interaction (HCI) studies, by recording comprehensive real-time data for any UI experiment, and making the data available as a standard UDI data structure. This paper presents an overview of the Baran framework, and provides an example of its use to record user interaction and perform some basic analysis of the interaction.

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This work revisits established user classifications and aims to characterise a historically unspecified user category, the Occasional User (OU). Three user categories, novice, intermediate and expert, have dominated the work of user interface (UI) designers, researchers and educators for decades. These categories were created to conceptualise user's needs, strategies and goals around the 80s. Since then, UI paradigm shifts, such as direct manipulation and touch, along with other advances in technology, gave new access to people with little computer knowledge. This fact produced a diversification of the existing user categories not observed in the literature review of traditional classification of users. The findings of this work include a new characterisation of the occasional user, distinguished by user's uncertainty of repetitive use of an interface and little knowledge about its functioning. In addition, the specification of the OU, together with principles and recommendations will help UI community to informatively design for users without requiring a prospective use and previous knowledge of the UI. The OU is an essential type of user to apply user-centred design approach to understand the interaction with technology as universal, accessible and transparent for the user, independently of accumulated experience and technological era that users live in.

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Background: The enduring aging of the world population and prospective increase of age-related chronic diseases urge the implementation of new models for healthcare delivery. One strategy relies on ICT (Information and Communications Technology) home-based solutions allowing clients to pursue their treatments without institutionalization. Stroke survivors are a particular population that could strongly benefit from such solutions, but is not yet clear what the best approach is for bringing forth an adequate and sustainable usage of home-based rehabilitation systems. Here we explore two possible approaches: coaching and gaming. Methods: We performed trials with 20 healthy participants and 5 chronic stroke survivors to study and compare execution of an elbow flexion and extension task when performed within a coaching mode that provides encouragement or within a gaming mode. For each mode we analyzed compliance, arm movement kinematics and task scores. In addition, we assessed the usability and acceptance of the proposed modes through a customized self-report questionnaire. Results: In the healthy participants sample, 13/20 preferred the gaming mode and rated it as being significantly more fun (p < .05), but the feedback delivered by the coaching mode was subjectively perceived as being more useful (p < .01). In addition, the activity level (number of repetitions and total movement of the end effector) was significantly higher (p <.001) during coaching. However, the quality of movements was superior in gaming with a trend towards shorter movement duration (p=.074), significantly shorter travel distance (p <.001), higher movement efficiency (p <.001) and higher performance scores (p <.001). Stroke survivors also showed a trend towards higher activity levels in coaching, but with more movement quality during gaming. Finally, both training modes showed overall high acceptance. Conclusions: Gaming led to higher enjoyment and increased quality in movement execution in healthy participants. However, we observed that game mechanics strongly determined user behavior and limited activity levels. In contrast, coaching generated higher activity levels. Hence, the purpose of treatment and profile of end-users has to be considered when deciding on the most adequate approach for home based stroke rehabilitation.