Background: Mainly due to an increase in stress-related health problems and driven by recent technological advances in biosensors, microelectronics, computing platform, and human-computer interaction, ubiquitous physiological information will potentially transform the role of biofeedback in clinical treatment. Such technology is also likely to provide a useful tool for stress management in everyday life. The aim of this systematic review is to: (1) Classify biofeedback systems for stress management, with a special focus on biosensing techniques, bio-data computing approaches, biofeedback protocol, and feedback modality. (2) Review ways of evaluating approaches to biofeedback applications in terms of their effectiveness in stress management. Method: A systematic literature search was conducted using keywords for "Biofeedback" and "Stress" within the following databases: PubMed, IEEE Xplore, ACM, and Scopus. Two independent reviewers were involved in selecting articles. Results: We identified 103 studies published between 1990 and 2016, 46 of which met our inclusion criteria and were further analyzed. Based on the evidence reviewed, HRV, multimodal biofeedback, RSP, HR, and GSR appear to be the most common techniques for alleviating stress. Traditional screen-based visual displays remain the most common devices used for biofeedback display. Biofeedback applications are usually assessed by making both physiological and psychological measurements. Conclusions: This review reveals several challenges related to biofeedback for everyday stress management, such as facilitating user's perception and interpretating the biofeedback information, the demand of ubiquitous biosensing and display technologies, and field evaluation in order to understand the use of biofeedback in everyday environments. We expect that various emerging HCI technologies could be used to address these challenges. New interaction designs as well as biofeedback paradigms can be further explored in order to improve the accessibility, usability, comfort, engagement with, and user experience of biofeedback in everyday use.
The CHI conference has grown rapidly over the last 26 years. We present a quantitative analysis on the countries and organizations that contribute to its success. Only 7.8 percent of the countries are responsible for 80 percent of the papers in the CHI proceedings, and the USA is clearly the country with most papers. But the success of a country or organization does not depend only on the number of accepted papers, but also on their quality. We present a ranking of countries and organizations based on the h-index, an indicator that tries to balance the quantity and quality of scientific output based on a bibliometric analysis. The bibliometric analysis also allowed us to demonstrate the difficulty of judging quality. The papers acknowledged by the best paper award committee were not cited more often than a random sample of papers from the same years. The merit of the award is therefore unclear, and it might be worthwhile to allow the visitor to the conference to vote for the best paper.
Robots have been introduced into our society, but their social role is still unclear. A critical issue is whether the robot's exhibition of intelligent behaviour leads to the users' perception of the robot as being a social actor, similar to the way in which people treat computers and media as social actors. The first experiment mimicked Stanley Milgram's obedience experiment, but on a robot. The participants were asked to administer electric shocks to a robot, and the results show that people have fewer concerns about abusing robots than about abusing other people. We refined the methodology for the second experiment by intensifying the social dilemma of the users. The participants were asked to kill the robot. In this experiment, the intelligence of the robot and the gender of the participants were the independent variables, and the users' destructive behaviour towards the robot the dependent variable. Several practical and methodological problems compromised the acquired data, but we can conclude that the robot's intelligence had a significant influence on the users' destructive behaviour. We discuss the encountered problems and suggest improvements. We also speculate on whether the users' perception of the robot as being "sort of alive" may have influenced the participants' abusive behaviour.
An increasing amount of research has recently focused on representing affective states as continuous numerical values on multiple dimensions, such as the valence-arousal (VA) space. Compared to the categorical approach that represents affective states as several classes (e.g., positive and negative), the dimensional approach can provide more finegrained sentiment analysis. However, affective resources with valence-arousal ratings are still very rare, especially for the Chinese language. Therefore, this study builds 1) an affective lexicon called Chinese valence-arousal words (CVAW) containing 1,653 words, and 2) an affective corpus called Chinese valencearousal text (CVAT) containing 2,009 sentences extracted from web texts. To improve the annotation quality, a corpus cleanup procedure is used to remove outlier ratings and improper texts. Experiments using CVAW words to predict the VA ratings of the CVAT corpus show results comparable to those obtained using English affective resources.
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