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Objectives This study analyzed the health technology trends and sentiments of users using Twitter data in an attempt to examine the public's opinions and identify their needs. Methods Twitter data related to health technology, from January 2010 to October 2016, were collected. An ontology related to health technology was developed. Frequently occurring keywords were analyzed and visualized with the word cloud technique. The keywords were then reclassified and analyzed using the developed ontology and sentiment dictionary. Python and the R program were used for crawling, natural language processing, and sentiment analysis. Results In the developed ontology, the keywords are divided into ‘health technology‘ and ‘health information‘. Under health technology, there are are six subcategories, namely, health technology, wearable technology, biotechnology, mobile health, medical technology, and telemedicine. Under health information, there are four subcategories, namely, health information, privacy, clinical informatics, and consumer health informatics. The number of tweets about health technology has consistently increased since 2010; the number of posts in 2014 was double that in 2010, which was about 150 thousand posts. Posts about mHealth accounted for the majority, and the dominant words were ‘care‘, ‘new‘, ‘mental‘, and ‘fitness‘. Sentiment analysis by subcategory showed that most of the posts in nearly all subcategories had a positive tone with a positive score. Conclusions Interests in mHealth have risen recently, and consequently, posts about mHealth were the most frequent. Examining social media users' responses to new health technology can be a useful method to understand the trends in rapidly evolving fields.

This study aimed to investigate the constructive preferences and needs of children and guardians in a child obesity management application, and to suggest and visualize the key features of its design. To reflect users’ preferences and needs, the questionnaires used in this study were developed in four stages: draft, validity test, review, and final version. The survey was conducted with fifth and sixth grade children who are overweight or obese and their guardians. Differences were observed by gender and between children and guardians with respect to children’s perceived body shape, technology experience and preferences, preferred obesity management method, application design, exercise and diet-related features, preferred partner for obesity management, and preferred reward after mission completion. Our study suggests and visualizes the key features of a child obesity management application for both children and guardians based on their preferences and needs, which can be utilized by both application developers and researchers.

Robotic systems are used to support inpatients and healthcare professionals and to improve the efficiency and quality of nursing. There is a lack of scientific literature on how applied robotic systems can be used to support inpatients. This study uses surveys and focus group interviews to identify the necessary aspects and functions of bedside robots for inpatients. A total of 90 healthcare professionals and 108 inpatients completed the questionnaire, and four physicians and five nurses participated in the focus group interviews. The most highly desired functionalities were related to patient care and monitoring, including alerting staff, measuring vital signs, and sensing falls. Nurses and physicians reported different needs for human-robot interaction. Nurses valued robotic functions such as nonverbal expression recognition, automatic movement, content suggestion, and emotional expressions. The results of the patients' open-ended questions and healthcare professionals' focus groups indicate that the purpose of the robots should primarily be treatment and nursing. Participants believe bedside robots would be helpful but have concerns regarding safety and utility. This study attempts to determine which aspects of robots may increase their acceptance. Our findings suggest that if robots are used in healthcare institutions, they may improve the effectiveness of care.