Software Support for Skeleton Recognition and Monitoring People with Privacy

In this research, we have developed an open source software tool which makes it easy for a user to get skeleton information of people in a live image by use of Kinect for Windows V2. Our tool is a set of library software which provides users with easy coding to get body information and face recognition. The tool has been distributed widely and used by several users already for their research work such as robotics. In this paper, we propose possible use cases such as a remote monitor system for elderly care with privacy as well as a monitor system for shelters at disaster

Why I Retweet? Exploring User’s Perspective on Decision-Making of Information Spreading during Disasters

The extensive use of social media during disasters raises an important issue concerning use of social media to spread information, including misinformation. This study explores the underlying behavioral context of disaster information sharing by Twitter users. We conducted a web survey with 999 respondents in Japan to determine what makes people retweet disaster information in disaster situations. As a result of factor analysis, four factors were identified from 36 questions, namely: 1) Willingness to provide relevant and updated information because the information is believable, 2) Want people to know the information they perceive as important, 3) Retweeter subjective feelings and interests, and 4) Want to get feedback and alert other people. The results suggest that two of the factors influenced different groups of people in the community differently; however, everybody can play their role to reduce the negative impact of social media used for future disaster. Based on the findings, we discuss practical and design implications of social media use during disasters

Gesture Recognition with non-contact sensor for Natural User Interface in the COVID-19 era

COBID-19, an infectious disease transmitted by droplet and contact, is prevalent. In order to reduce the risk of contact infection, various operations should be performed in silence and non-contact. A user interface using non-contact sensors is effective in such an environment. Among them, Natural User Interface based on Gesture Recognition using non-contact sensors are useful, we think. We have developed our NUI system in which the user instructs the computer in a full-body gesture. In this paper, we discuss several methods available for gesture recognition based on skeleton recognition. And, for some of the gesture recognition systems we have implemented with the combination of such methods, the design policy and experimental results of each are presented

Introduction to Emerging Issues in Distributed Group Decision-Making: Opportunities and Challenges Minitrack

N/

Designing Warning Interfaces causing Discomfort for Awareness of Risks: Revisited

Making users aware of the risk by giving them a sense of discomfort and helping them not to access dangerous sites is crucial. Thus, we focus on developing a warning interface, causing discomfort, allowing smartphone users to be aware of danger and risks. We studied discomfort feelings while using smartphones and extracted five discomfort factors from a questionnaire survey and factor analysis. We implemented a prototype of warning interfaces for web browsing on a smartphone considering five factors. In the experiments, we have found that three factors out of the five, namely, “Unintended operation or display,” “Sudden changes,” and “Understanding of the application,” are significant for risk awareness, while the other two are not. This paper reports on the findings of the study

How to promote the stockpiling of medication for disaster preparedness among Parkinson’s disease patients receiving home care services

The purpose of this study was to identify factors, using the Health Belief Model (HBM) associated with Parkinson’s disease (PD) medication stockpiling for disaster preparedness among PD patients receiving home care services. The survey was conducted through an anonymous, self-administered postal questionnaire between March and September 2013, targeting all 1,398 members of Japan Parkinson’s Disease Association in nine prefectures in East Japan including the Hokuriku region. The analysis included 571 valid responses (40.8%). The results of a binary logistic regression analysis indicated that three of the modifying factors in the HBM, “possession of a disability certificate,” “bringing a medicine notebook or information sheet when going out,” and “awareness of the possibility of a future disaster” were significantly associated with stockpiling behavior. The “Cues to Action” factor (“encouragement from others or information promoting the stockpiling of medication”) was also significantly associated. However, the other constructs in the HBM, “Susceptibility,” “Severity,” “Perceived Threat,” “Barriers,” and “Benefits,” did not show significant association. We concluded that encouragement of stockpiling behavior from healthcare professionals and the PD Association, making a habit of always bringing a medicine notebook when going out, and raising awareness of the possibility of a disaster are useful in promoting medication stockpiling among PD patients