User Experience With Dynamic Difficulty Adjustment Methods for an Affective Exergame: Comparative Laboratory-Based Study

Background In affective exergames, game difficulty is dynamically adjusted to match the user’s physical and psychological state. Such an adjustment is commonly made based on a combination of performance measures (eg, in-game scores) and physiological measurements, which provide insight into the player’s psychological state. However, although many prototypes of affective games have been presented and many studies have shown that physiological measurements allow more accurate classification of the player’s psychological state than performance measures, few studies have examined whether dynamic difficulty adjustment (DDA) based on physiological measurements (which requires additional sensors) results in a better user experience than performance-based DDA or manual difficulty adjustment. Objective This study aims to compare five DDA methods in an affective exergame: manual (player-controlled), random, performance-based, personality-performance–based, and physiology-personality-performance–based (all-data). Methods A total of 50 participants (N=50) were divided into five groups, corresponding to the five DDA methods. They played an exergame version of Pong for 18 minutes, starting at a medium difficulty; every 2 minutes, two game difficulty parameters (ball speed and paddle size) were adjusted using the participant’s assigned DDA method. The DDA rules for the performance-based, personality-performance–based, and all-data groups were developed based on data from a previous open-loop study. Seven physiological responses were recorded throughout the sessions, and participants self-reported their preferred changes to difficulty every 2 minutes. After playing the game, participants reported their in-game experience using two questionnaires: the Intrinsic Motivation Inventory and the Flow Experience Measure. Results Although the all-data method resulted in the most accurate changes to ball speed and paddle size (defined as the percentage match between DDA choice and participants’ preference), no significant differences between DDA methods were found on the Intrinsic Motivation Inventory and Flow Experience Measure. When the data from all four automated DDA methods were pooled together, the accuracy of changes in ball speed was significantly correlated with players’ enjoyment (r=0.38) and pressure (r=0.43). Conclusions Although our study is limited by the use of a between-subjects design and may not generalize to other exergame designs, the results do not currently support the inclusion of physiological measurements in affective exergames, as they did not result in an improved user experience. As the accuracy of difficulty changes is correlated with user experience, the results support the development of more effective DDA methods. However, they show that the inclusion of physiological measurements does not guarantee a better user experience even if it yields promising results in offline cross-validation.

User Experience With Dynamic Difficulty Adjustment Methods for an Affective Exergame: Comparative Laboratory-Based Study (Preprint)

BACKGROUND In affective exergames, game difficulty is dynamically adjusted to match the user’s physical and psychological state. Such an adjustment is commonly made based on a combination of performance measures (eg, in-game scores) and physiological measurements, which provide insight into the player’s psychological state. However, although many prototypes of affective games have been presented and many studies have shown that physiological measurements allow more accurate classification of the player’s psychological state than performance measures, few studies have examined whether dynamic difficulty adjustment (DDA) based on physiological measurements (which requires additional sensors) results in a better user experience than performance-based DDA or manual difficulty adjustment. OBJECTIVE This study aims to compare five DDA methods in an affective exergame: manual (player-controlled), random, performance-based, personality-performance–based, and physiology-personality-performance–based (all-data). METHODS A total of 50 participants (N=50) were divided into five groups, corresponding to the five DDA methods. They played an exergame version of Pong for 18 minutes, starting at a medium difficulty; every 2 minutes, two game difficulty parameters (ball speed and paddle size) were adjusted using the participant’s assigned DDA method. The DDA rules for the performance-based, personality-performance–based, and all-data groups were developed based on data from a previous open-loop study. Seven physiological responses were recorded throughout the sessions, and participants self-reported their preferred changes to difficulty every 2 minutes. After playing the game, participants reported their in-game experience using two questionnaires: the Intrinsic Motivation Inventory and the Flow Experience Measure. RESULTS Although the all-data method resulted in the most accurate changes to ball speed and paddle size (defined as the percentage match between DDA choice and participants’ preference), no significant differences between DDA methods were found on the Intrinsic Motivation Inventory and Flow Experience Measure. When the data from all four automated DDA methods were pooled together, the accuracy of changes in ball speed was significantly correlated with players’ enjoyment (<i>r</i>=0.38) and pressure (<i>r</i>=0.43). CONCLUSIONS Although our study is limited by the use of a between-subjects design and may not generalize to other exergame designs, the results do not currently support the inclusion of physiological measurements in affective exergames, as they did not result in an improved user experience. As the accuracy of difficulty changes is correlated with user experience, the results support the development of more effective DDA methods. However, they show that the inclusion of physiological measurements does not guarantee a better user experience even if it yields promising results in offline cross-validation. CLINICALTRIAL

Regarding Revoke of the Paper “A Distributed Autonomous Approach to Developing a Disaster Evacuation Assist System,” Published in the JDR

As an issue was raised with respect to the following paper published in the Journal of Disaster Research (JDR), we conducted an investigation. A) Paper published in the JDR Yasuki Iizuka, Katsuya Kinoshita, and Kayo Iizuka, “A Distributed Autonomous Approach to Developing a Disaster Evacuation Assist System,” J. Disaster Res., Vol.10, No.6, pp. 1081-1090, 2015. (Received: July 31, 2015, Accepted: October 21, 2015, Published: December 1, 2015) B) Paper compared Yasuki IIZUKA, Katsuya KINOSHITA, Kayo IIZUKA, “Agent Based Disaster Evacuation Assistance System,” Information Engineering Express International Journal, Vol.1, No.2, pp. 41-50 (2015). (Published: June 30, 2015) 1. Results of Investigation – The texts of the two papers were compared, whereupon a percentage match exceeding 47 percent was found in terms of the number of words. When the comparison was made with the initially submitted manuscript, that is, the manuscript before it was revised based on peer reviews, the percentage match with paper B was 58 percent. – When the conclusions of the two papers were compared, they were found to be nearly identical, from which we conclude that paper A does not display sufficient novelty. – Paper B is not cited as a reference in paper A, and when the same figure appears in the two documents, its source is not cited. – It was found that, during the period from manuscript submission to publication, the authors failed to submit paper B as a previously published paper, as stipulated in Article 11.2 of the JDR Instructions to Authors (Japanese version), or otherwise submit any documentation that refers to the existence of paper B. 2. Decision As a result of the above investigation, the JDR editorial board concludes that paper A constitutes a duplicate submission and is in violation of the JDR Instructions to Authors (Japanese version). Its acceptance is thereby revoked, and it has been duly removed from the JDR official website. Any inquiries regarding this matter should be made to this office: JDR Editorial Office, Fuji Technology Press Ltd. Unizo Uchikanda 1-Chome Bldg. 2F 1-15-7 Uchikanda, Chiyoda-ku, Tokyo 101-0047, Japan TEL: 03-5577-3851 FAX: 03-5577-3861 E-mail: [email protected]

WeRSort: Preliminary Results from a New Method of Remote Collaboration Facilitated by Fully Immersive Virtual Reality

Fully immersive virtual reality, with the unique ability to replicate the real world, could potentially aid in real-time communication. Geographically separated teams can collaborate using virtual reality. To test the viability of using virtual reality for remote collaboration, we designed a system called “WeRSort” where teams sorted cards in a virtual environment. Participants performed the task as a team of 2 in one of three conditions-controls-only condition, generic embodiment and full embodiment. Objective measures of performance, time and percentage match with master cards showed no significant difference. Subjective measures of presence and system usability also showed no statistical significance. However, overall work-load obtained from NASA-TLX showed that fully immersive virtual reality resulted in lower workload in comparison with the other two. Qualitative data was collected and analyzed to understand collaboration using the awareness evaluation model.

Automated generation of ‘good enough’ transcripts as a first step to transcription of audio-recorded data

In the last decade, automated captioning services have appeared in mainstream technology use. Until now, the focus of these services have been on the technical aspects, supporting pupils with special educational needs and supporting teaching and learning of second language students. Only limited explorations have been attempted regarding its use for research purposes: transcription of audio recordings. This article presents a proof-of-concept exploration utilising three examples of automated transcription of audio recordings from different contexts; an interview, a public hearing and a classroom setting, and compares them against ‘manual’ transcription techniques in each case. It begins with an overview of literature on automated captioning and the use of voice recognition tools for the purposes of transcription. An account is provided of the specific processes and tools used for the generation of the automated captions followed by some basic processing of the captions to produce automated transcripts. Originality checking software was used to determine a percentage match between the automated transcript and a manual version as a basic measure of the potential usability of each of the automated transcripts. Some analysis of the more common and persistent mismatches observed between automated and manual transcripts is provided, revealing that the majority of mismatches would be easily identified and rectified in a review and edit of the automated transcript. Finally, some of the challenges and limitations of the approach are considered. These limitations notwithstanding, we conclude that this form of automated transcription provides ‘good enough’ transcription for first versions of transcripts. The time and cost advantages of this could be considerable, even for the production of summary or gisted transcripts.

Automated generation of “good enough” transcripts as a first step to transcription of audio-recorded data

In the last decade automated captioning services have appeared in mainstream technology use. Until now the focus of these services have been on the technical aspects, supporting pupils with special educational needs and supporting teaching and learning of second language students. Only limited explorations have been attempted regarding its use for research purposes: transcription of audio recordings. This paper presents a proof-of-concept exploration utilising three examples of automated transcription of audio recordings from different contexts; an interview, a public hearing and a classroom setting, and compares them against ‘manual’ transcription techniques in each case. It begins with an overview of literature on automated captioning and the use of voice recognition tools for the purposes of transcription. An account is provided of the specific processes and tools used for the generation of the automated captions followed by some basic processing of the captions to produce automated transcripts. Originality checking software was used to determine a percentage match between the automated transcript and a manual version as a basic measure of the potential usability of each of the automated transcripts. Some analysis of the more common and persistent mismatches observed between automated and manual transcripts is provided, revealing that the majority of mismatches would be easily identified and rectified in a review and edit of the automated transcript. Finally, some of the challenges and limitations of the approach are considered. These limitations notwithstanding, we conclude that this form of automated transcription provides ‘good enough’ transcription for first versions of transcripts. The time and cost advantages of this could be considerable, even for the production of summary or gisted transcripts.

Evaluation of Real-Time Mortality Surveillance Based on Media Reports

ObjectiveWe evaluated the usefulness and accuracy of media-reported data for active disaster-related mortality surveillance.MethodsFrom October 29 through November 5, 2012, epidemiologists from the Centers for Disease Control and Prevention (CDC) tracked online media reports for Hurricane Sandy–related deaths by use of a keyword search. To evaluate the media-reported data, vital statistics records of Sandy-related deaths were compared to corresponding media-reported deaths and assessed for percentage match. Sensitivity, positive predictive value (PPV), and timeliness of the media reports for detecting Sandy-related deaths were calculated.ResultsNinety-nine media-reported deaths were identified and compared with the 90 vital statistics death records sent to the CDC by New York City (NYC) and the 5 states that agreed to participate in this study. Seventy-five (76%) of the media reports matched with vital statistics records. Only NYC was able to actively track Sandy-related deaths during the event. Moderate sensitivity (83%) and PPV (83%) were calculated for the matching media-reported deaths for NYC.ConclusionsDuring Hurricane Sandy, the media-reported information was moderately sensitive, and percentage match with vital statistics records was also moderate. The results indicate that online media-reported deaths can be useful as a supplemental source of information for situational awareness and immediate public health decision-making during the initial response stage of a disaster. (Disaster Med Public Health Preparedness. 2017;11:460–466)

Evaluation of Web-based Dietary Assessment Software for Children: comparing reported fruit, juice and vegetable intakes with plasma carotenoid concentration and school lunch observations

Web-based Dietary Assessment Software for Children (WebDASC) was developed to estimate dietary intake in a school meal intervention study among 8- to 11-year-old Danish children. The present study validates self-reported fruit, juice and vegetable (FJV) intakes in 8- to 11-year-old children by comparing intake with plasma carotenoid concentration, and by comparing the reported FJV intake to actually eaten FJV, as observed by a photographic method. A total of eighty-one children, assisted by parents, reported their diet for seven consecutive days. For the same five schooldays as they reported their diet, the children's school lunch was photographed and weighed before and after eating. In the week after the diet reporting, fasting blood samples were taken. Self-reported intake of FJV and estimated intake of carotenoids were compared with plasma carotenoid concentration. Accuracy of self-reported food and FJV consumption at school lunch was measured in terms of matches, intrusion, omission and faults, when compared with images and weights of lunch intake. Self-reported intake of FJV was significantly correlated with the total carotenoid concentration (0·58) (P< 0·01). Fruit and juice consumption showed higher correlations than vegetables with plasma carotenoid concentration (0·38 and 0·42 v. 0·33) (P< 0·01). A total of 82 % of the participants fell into the same or adjacent quartiles when cross-classified by FJV intake and carotenoids biomarkers. WebDASC attained 82 % reporting matches overall and a higher percentage match for reporting fruits compared with beverages. The present study indicated that WebDASC can be used to rank 8- to 11-year-old Danish children according to their intake of FJV overall and at school meals.