Past, Present, and Future of EEG-Based BCI Applications

An electroencephalography (EEG)-based brain–computer interface (BCI) is a system that provides a pathway between the brain and external devices by interpreting EEG. EEG-based BCI applications have initially been developed for medical purposes, with the aim of facilitating the return of patients to normal life. In addition to the initial aim, EEG-based BCI applications have also gained increasing significance in the non-medical domain, improving the life of healthy people, for instance, by making it more efficient, collaborative and helping develop themselves. The objective of this review is to give a systematic overview of the literature on EEG-based BCI applications from the period of 2009 until 2019. The systematic literature review has been prepared based on three databases PubMed, Web of Science and Scopus. This review was conducted following the PRISMA model. In this review, 202 publications were selected based on specific eligibility criteria. The distribution of the research between the medical and non-medical domain has been analyzed and further categorized into fields of research within the reviewed domains. In this review, the equipment used for gathering EEG data and signal processing methods have also been reviewed. Additionally, current challenges in the field and possibilities for the future have been analyzed

Making defeating CAPTCHAs harder for bots

For a number of years, many websites have used CAPTCHAs to filter out interactions by bots. However, attackers have found ways to circumvent CAPTCHAs by programming bots to solve or bypass them, or even relay them for humans to solve. In order to reduce the chances of success of such attacks, CAPTCHAs can be strengthened by the addition of certain safeguards. In this paper, we discuss seven existing safeguards as well as five novel safeguards designed to make circumventing CAPTCHAs harder. These safeguards are not mutually exclusive and can add multiple layers of protection to a CAPTCHA. We further provide a high-level comparison of their effectiveness in addressing the threat posed by CAPTCHA-defeating techniques. In order to focus on safeguards that are usable, we restrict our attention to those which have minimal adverse effect on the user experience

Measuring perceived helpfulness of computerized decision aid for youth

The nature of a decision aid is to provide assistance to the users.The assistance should be evaluated from two different perspectives, as human decision making models are mostly based on two approaches: process oriented and outcome oriented. Hence, the property of providing useful assistance (i.e., helpfulness) through a decision aid needs to consider both process and outcome factors.This study explores the constructs of measuring helpfulness through a systematic process which result in four dimensions being identified: reliability, decision making effort, decision process awareness, and confidence.A quantitative validation was also reported on measuring perceived helpfulness of a computerized decision aid for youth, known as YouthPDA

Modeling Caricature Expressions by 3D Blendshape and Dynamic Texture

The problem of deforming an artist-drawn caricature according to a given normal face expression is of interest in applications such as social media, animation and entertainment. This paper presents a solution to the problem, with an emphasis on enhancing the ability to create desired expressions and meanwhile preserve the identity exaggeration style of the caricature, which imposes challenges due to the complicated nature of caricatures. The key of our solution is a novel method to model caricature expression, which extends traditional 3DMM representation to caricature domain. The method consists of shape modelling and texture generation for caricatures. Geometric optimization is developed to create identity-preserving blendshapes for reconstructing accurate and stable geometric shape, and a conditional generative adversarial network (cGAN) is designed for generating dynamic textures under target expressions. The combination of both shape and texture components makes the non-trivial expressions of a caricature be effectively defined by the extension of the popular 3DMM representation and a caricature can thus be flexibly deformed into arbitrary expressions with good results visually in both shape and color spaces. The experiments demonstrate the effectiveness of the proposed method.Comment: Accepted by the 28th ACM International Conference on Multimedia (ACM MM 2020

The body beyond movement: (Missed) opportunities to engage with contemporary dance in HCI

This paper argues that a significant paradigm change in contemporary dance can offer further opportunities for HCI researchers interested in embodied interaction and interactive system design. Based on the analysis of 42 HCI papers in our data set, resulting from searches in two computing research libraries, we suggest seven thematic categories that reflect how HCI researchers have been engaging with contemporary dance. Moreover, we propose a standardized usage of contemporary dance terminology in HCI literature, and discuss the current state of engagement with publications from the field of performance theory. We identify three opportunities for HCI, which can arise through further engagement with the knowledge produced in contemporary dance and performance: to engage with the field of embodied interaction from the perspective of performance research and theory; to employ contemporary dance methods and practices in HCI research; and to integrate contemporary dance choreographers and performers as researchers in interdisciplinary projects

Conceptual Design Model of Computerized Personal-Decision AID (ComPDA)

To date, the attentions given to the improvement of decision support at organizational level has been enormous. On the contrary, academic research in improving the performance of computerized decision aid (CDA) for personal decision is lacking, in which some are dated. Nowadays, the existence of CDA which handles personal decision is mushrooming and progressively getting attention from users. Despite that, users’ perceptions of the suitable decision strategy and technique for CDA have not been subjected to systematic investigation. Literature reviews also indicate that most users do not go for complex mathematical techniques despite the fact that these techniques are better at handling the risks and uncertainties in decisions. In fact, more often than not, the development process of CDAs does not seem to adhere to any conceptual and theoretical model. In view of that, this study aims to propose a conceptual design model for computerized personal-decision aid (ComPDA). The following objectives are outlined to support the general aim: (i) to identify appropriate decision strategy and technique for ComPDA, (ii) to incorporate identified strategy and technique in the construction of conceptual design model for ComPDA (iii) to validate the conceptual design model in different situations via prototyping method and (iv) to measure the users’ perceived helpfulness of the ComPDA prototypes. Participatory design method was implemented in order to achieve objective i and ii. The findings were incorporated into the construction of the conceptual design model of ComPDA. In achieving objective iii, the conceptual design model was validated in two different case studies via prototyping: A- choosing development methodology in mobile computing course (md-Matrix); and B- purchasing a mobile phone (ep-Matrix). In achieving objective iv, an instrument (named as Q-HELP) was developed to measure the helpfulness (HLP) of the prototypes. This study identified four relevant constructs pertinent to helpfulness; reliability (REL), decision making effort (EFF), confidence (CON), and decision awareness (AWR). Altogether, 122 respondents participated where 63 were from case study A and 59 from case study B. Eight hypotheses were formulated comprising testing for correlation between all the constructs in Q-HELP with helpfulness, testing the average time spent to make a selection with and without the proposed ComPDA and testing if the mean score of helpfulness of the proposed ComPDA is high. Paired Samples t Test, Pearson Correlation analyses and descriptive analyses were utilized to validate the hypotheses. The results show that: REL and HLP are significantly correlated, EFF and HLP are significantly correlated, CON and HLP are significantly correlated, AWR and HLP are significantly correlated, the use of md-Matrix and ep-Matrix significantly reduces the time spent to make selection, mean score of helpfulness of md-Matrix is fairly high and mean score of helpfulness of ep-Matrix is high. However, it is concluded that the overall results exhibit sufficient indication that md-Matrix and ep-Matrix were found helpful to users in terms of reliability, lessening the decision making effort, increasing confidence and also awareness in decision making. This study has produced the following outcomes, along with achieving all of its objectives: (i) a conceptual design model for ComPDA which incorporates suitable decision strategies and techniques identified via systematic investigations; (ii) two functional ComPDA prototypes to validate the conceptual design model and to demonstrate its applicability in different situations, (iii) an instrument for measuring helpfulness which includes dimensions from outcome and process aspects; and (iv) comparative analyses of decision models, strategies and techniques which provide basis for future studies.

A multimodal emotion detection system during human-robot interaction

In this paper, a multimodal user-emotion detection system for social robots is presented. This system is intended to be used during human-robot interaction, and it is integrated as part of the overall interaction system of the robot: the Robotics Dialog System (RDS). Two modes are used to detect emotions: the voice and face expression analysis. In order to analyze the voice of the user, a new component has been developed: Gender and Emotion Voice Analysis (GEVA), which is written using the Chuck language. For emotion detection in facial expressions, the system, Gender and Emotion Facial Analysis (GEFA), has been also developed. This last system integrates two third-party solutions: Sophisticated High-speed Object Recognition Engine (SHORE) and Computer Expression Recognition Toolbox (CERT). Once these new components (GEVA and GEFA) give their results, a decision rule is applied in order to combine the information given by both of them. The result of this rule, the detected emotion, is integrated into the dialog system through communicative acts. Hence, each communicative act gives, among other things, the detected emotion of the user to the RDS so it can adapt its strategy in order to get a greater satisfaction degree during the human-robot dialog. Each of the new components, GEVA and GEFA, can also be used individually. Moreover, they are integrated with the robotic control platform ROS (Robot Operating System). Several experiments with real users were performed to determine the accuracy of each component and to set the final decision rule. The results obtained from applying this decision rule in these experiments show a high success rate in automatic user emotion recognition, improving the results given by the two information channels (audio and visual) separately.The authors gratefully acknowledge the funds provided by the Spanish MICINN (Ministry of Science and Innovation) through the project “Aplicaciones de los robots sociales”, DPI2011-26980 from the Spanish Ministry of Economy and Competitiveness. Moreover, the research leading to these results has received funding from the RoboCity2030-II-CM project (S2009/DPI-1559), funded by Programas de Actividades I+D en la Comunidad de Madrid and cofunded by Structural Funds of the EU