Natural User Interfaces for Meditative Health Games

2022 ◽  
pp. 207-234
Author(s):  
Ifeoluwapo Fashoro ◽  
Sithembile Ncube

The psychological health outcomes of video games are drawing increasing interest around the world. There is growing interest in video games as an accessible health intervention for depression and anxiety, both of which are rising health concerns globally. New interaction techniques for video games are becoming increasingly popular, with natural user interfaces (NUIs) becoming more commonplace in game systems. This chapter explores the design of a meditative game, a subgenre of casual games that intends for players to become calm and relaxed, and the evaluation of the NUIs for the game. The purpose of the chapter is to ascertain which NUI is most suitable for meditative games. A meditative fishpond game was designed that accepts two NUIs: touch and eye-tracking. The game was evaluated using a Positive and Negative Affect Schedule. The study found the eye-tracking interface reported a higher positive affect score from users and is therefore most suitable for meditative games.

Author(s):  
Kunal Parikh ◽  
Tanvi Makadia ◽  
Harshil Patel

Dengue is unquestionably one of the biggest health concerns in India and for many other developing countries. Unfortunately, many people have lost their lives because of it. Every year, approximately 390 million dengue infections occur around the world among which 500,000 people are seriously infected and 25,000 people have died annually. Many factors could cause dengue such as temperature, humidity, precipitation, inadequate public health, and many others. In this paper, we are proposing a method to perform predictive analytics on dengue’s dataset using KNN: a machine-learning algorithm. This analysis would help in the prediction of future cases and we could save the lives of many.


Author(s):  
Andrea Zammitti ◽  
Chiara Imbrogliera ◽  
Angela Russo ◽  
Rita Zarbo ◽  
Paola Magnano

Italy was quickly hit hard by the coronavirus. ‘Lockdown’ has significantly impacted the psychological health, personal wellbeing and quality of life of the people. The study aims to explore the relationship between positive and negative affect, as well as positive (spiritual well-being and flourishing) and negative outcomes (psychological distress caused by a traumatic life event in terms of perception of PTSD symptoms) on Italian adults during the lockdown period. Data was collected between April and May 2020. The participants were 281 Italian adults aged between 18 and 73 years. The survey was composed of the following measures: Flourishing Scale, Jarel Spiritual Well-Being scale, Positive and Negative Affect Schedule, Impact of Event Scale—Revised, Fear of COVID-19. The mediational analysis shows that fear of COVID-19 fully mediates the relationship between negative affect and spiritual well-being and flourishing; fear of COVID-19 partially mediates the relationship between negative affect and PTSD symptoms; the positive affect shows only direct effects on positive outcomes. Therefore, fear of COVID-19 does not play any mediation role. Implications for psychological interventions and future research will be discussed.


2021 ◽  
Vol 1 ◽  
pp. 283-292
Author(s):  
Jakob Harlan ◽  
Benjamin Schleich ◽  
Sandro Wartzack

AbstractThe increased availability of affordable virtual reality hardware in the last years boosted research and development of such systems for many fields of application. While extended reality systems are well established for visualization of product data, immersive authoring tools that can create and modify that data are yet to see widespread productive use. Making use of building blocks, we see the possibility that such tools allow quick expression of spatial concepts, even for non-expert users. Optical hand-tracking technology allows the implementation of this immersive modeling using natural user interfaces. Here the users manipulated the virtual objects with their bare hands. In this work, we present a systematic collection of natural interactions suited for immersive building-block-based modeling systems. The interactions are conceptually described and categorized by the task they fulfil.


2015 ◽  
Vol 25 (1) ◽  
pp. 17-34 ◽  
Author(s):  
Juan-Fernando Martin-SanJose ◽  
M.-Carmen Juan ◽  
Ramón Mollá ◽  
Roberto Vivó

Author(s):  
Shannon K. T. Bailey ◽  
Daphne E. Whitmer ◽  
Bradford L. Schroeder ◽  
Valerie K. Sims

Human-computer interfaces are changing to meet the evolving needs of users and overcome limitations of previous generations of computer systems. The current state of computers consists largely of graphical user interfaces (GUI) that incorporate windows, icons, menus, and pointers (WIMPs) as visual representations of computer interactions controlled via user input on a mouse and keyboard. Although this model of interface has dominated human-computer interaction for decades, WIMPs require an extra step between the user’s intent and the computer action, imposing both limitations on the interaction and introducing cognitive demands (van Dam, 1997). Alternatively, natural user interfaces (NUI) employ input methods such as speech, touch, and gesture commands. With NUIs, users can interact directly with the computer without using an intermediary device (e.g., mouse, keyboard). Using the body as an input device may be more “natural” because it allows the user to apply existing knowledge of how to interact with the world (Roupé, Bosch-Sijtsema, & Johansson, 2014). To utilize the potential of natural interfaces, research must first determine what interactions can be considered natural. For the purpose of this paper, we focus on the naturalness of gesture-based interfaces. The purpose of this study was to determine how people perform natural gesture-based computer actions. To answer this question, we first narrowed down potential gestures that would be considered natural for an action. In a previous study, participants ( n=17) were asked how they would gesture to interact with a computer to complete a series of actions. After narrowing down the potential natural gestures by calculating the most frequently performed gestures for each action, we asked participants ( n=188) to rate the naturalness of the gestures in the current study. Participants each watched 26 videos of gestures (3-5 seconds each) and were asked how natural or arbitrary they interpreted each gesture for the series of computer commands (e.g., move object left, shrink object, select object, etc.). The gestures in these videos included the 17 gestures that were most often performed in the previous study in which participants were asked what gesture they would naturally use to complete the computer actions. Nine gestures were also included that were created arbitrarily to act as a comparison to the natural gestures. By analyzing the ratings on a continuum from “Completely Arbitrary” to “Completely Natural,” we found that the natural gestures people produced in the first study were also interpreted as the intended action by this separate sample of participants. All the gestures that were rated as either “Mostly Natural” or “Completely Natural” by participants corresponded to how the object manipulation would be performed physically. For example, the gesture video that depicts a fist closing was rated as “natural” by participants for the action of “selecting an object.” All of the gestures that were created arbitrarily were interpreted as “arbitrary” when they did not correspond to the physical action. Determining how people naturally gesture computer commands and how people interpret those gestures is useful because it can inform the development of NUIs and contributes to the literature on what makes gestures seem “natural.”


2021 ◽  
Author(s):  
Andrea Wen-Yi Wang ◽  
Jo-Yu Lan ◽  
Ming-Hung Wang ◽  
Chihhao Yu

BACKGROUND In 2020, the COVID-19 pandemic put the world in crisis on both physical and psychological health. Simultaneously, a myriad of unverified information flowed on social media and online outlets. The situation was so severe that the World Health Organization identified it an infodemic on February 2020. OBJECTIVE We want to study the propagation patterns and textual transformation of COVID-19 related rumors on a closed-platform. METHODS We obtained a dataset of 114 thousand suspicious text messages collected on Taiwan’s most popular instant messaging platform, LINE. We also proposed an algorithm that efficiently cluster text messages into groups, where each group contains text messages within limited difference in content. Each group then represents a rumor and elements in each group is a message about the rumor. RESULTS 114 thousand messages were separated into 937 groups with at least 10 elements. Of the 936 rumors, 44.5% (417) were related to COVID-19. By studying 3 popular false COVID-19 rumors, we identified that key authoritative figures, mostly medical personnel, were often quoted in the messages. Also, rumors resurfaced multiple times after being fact-checked, and the resurfacing pattern were influenced by major societal events and successful content alterations, such as changing whom to quote in a message. CONCLUSIONS To fight infodemic, it is crucial that we first understand why and how a rumor becomes popular. While social media gives rise to unprecedented number of unverified rumors, it also provides a unique opportunity for us to study rumor propagations and the interactions with society. Therefore, we must put more effort in the areas.


2021 ◽  
Vol 229 (1) ◽  
pp. 24-37 ◽  
Author(s):  
Nadine Wedderhoff ◽  
Timo Gnambs ◽  
Oliver Wedderhoff ◽  
Tanja Burgard ◽  
Michael Bošnjak

Abstract. The Positive and Negative Affect Schedule (PANAS; Watson et al., 1988 ) is a popular self-report questionnaire that is administered all over the world. Though originally developed to measure two independent factors, different models have been proposed in the literature. Comparisons among alternative models as well as analyses concerning their robustness in cross-national research have left an inconclusive picture. Therefore, the present study evaluates the dimensionality of the PANAS and differences between English and translated versions of the PANAS using a meta-analytic structural equation modeling approach. Correlation matrices from 57 independent samples ( N = 54,043) were pooled across subsamples. For both English and non-English samples, a correlated two-factor model including correlated uniquenesses provided the best fit. However, measurement invariance analyses indicated differences in factor loadings between subsamples. Thus, cross-national application of the PANAS might only be justified if measurement equivalence was explicitly tested for the countries at hand.


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