We proposed a model that represents health checkup data in binary according to data structure of the Specific Health Checkup and visually represents the state transition of health conditions. Each of four inspection factors (body type, blood sugar, lipids, and blood pressure) were expressed as binary variable using reference values in the Specific Health Checkup, yielding 16 health condition states, (0000) through (1111). The state transition probability (256 transitions x 4 age ranges) for each of four age groups were calculated. We then constructed a health state-transition model using two cubic lattices with eight vertices. We built our models each age groups and compared these models, and could show by those how people with certain health conditions are likely to continue to change in future. Our health state transition model provides an easy visual demonstration of the health state of examinees, as well as indicating direction of the state transition.
Many studies have reported method to detect car driver drowsiness by heartbeat interval signals, but it is hard to record stable signals while driving in a way that does not burden the drivers. We examined whether the driver’s drowsiness can be detected from respiration signal. In 9 healthy subjects (seven males and two females; age, 45 ± 9 y), respiration, electrocardiogram, and acceleration signals were recoded for a total of 2,359 min (137-468 min per subject) of driving with a smart shirt biometric sensor (Hexoskin). Minute-to-minute respiratory rate, heart rate, and their variability were analyzed by complex demodulation. The sleepiness of drivers was assessed by subjective reports and by a surrogate maker of Dip & Waves, which is known to be a characteristic R-R interval pattern associated with driver drowsiness. Although respiratory rate showed no significant changes associated with Dip & Wave, respiratory rate variability increased progressively from 4 min before, peaked at Dip & Waves, and decreased immediately thereafter. No such definite trend was observed in any time- or frequency domain indices of heart rate variability. The findings of this study not only show the possibility of smart-shirt sensor as a device to detect driver drowsiness but also suggest that respiration signals may provide useful clues to predict driver drowsiness, which is unique from those provided by heart rate variability.
In this study, we used 6 different fragrances to better understand the tendency of scents to elicit a sense of omotenashi (hospitality) in elderly people. To first understand how elderly people perceive scents associated with feelings of omotenashi we performed an impression evaluation using SD method of 22 adjective pairs. We then analyzed the results taken from a questionnaire survey we conducted on 51 elderly Japanese men and women using a factor analysis, and extracted the factors that represent sensations of scents which produced a sense of omotenashi. Our subsequent examination of the main underlying factors indicated that scents with sensations of freshness, adulthood and pleasure hinted a sense of omotenashi in scents for elderly people. We also noted differences in the way the scent was perceived compared to young people.
Entrepreneurship education programs in universities are flourishing. The programs in Europe provide practical knowledge and skills on top of learning an entrepreneurial attitude. On the other hand, in the U.S., programs just provide practical knowledge and skills. In Japan, the programs provide practical knowledge and skills in the US style. However, it is very unlikely that students who will launch their business immediately after completing the program. In order to actually start a business, it is essential to develop “Entrepreneurial intentions,” but all program participants do not necessarily foster entrepreneurial intentions. In this paper, we define the preliminaries of entrepreneurial intentions as the willingness of students participating in the program to actively engage in PBL activities. As a means of fostering the preliminaries of entrepreneurship intentions, a series of methodologies is proposed as the VIA model using the SECI model’s conceptual framework as a means to verify its effectiveness.
Chinese characters developed for the writing of Chinese and have adapted for a number of Asian languages. Basically, the simplified forms of Chinese characters are used in mainland China, Singapore, and Malaysia. The corresponding traditional characters are used in Taiwan, Hong Kong, and Macau. They also remain a key component of Japanese known as kanji. In this study, we arrange the information about the development of Chinese characters and the evolution of typical typefaces in Chinese and Japanese. To explore the relationships between emotions and Chinese characters, 20 simplified types and 20 traditional types of Chinese were extracted and the kansei evaluation experiment was conducted for the people in mainland China and Taiwan. Besides, we collected the emotional evaluation data of Japanese typefaces to explore the emotional difference between Chinese and Japanese. Particularly, it is found that for the widely used types Heiti, Songti, and Kaiti, the people in mainland China and Taiwan have opposite feelings of classic and contemporary. The emotional response for these types is generally consistent between the people in Taiwan and the people in Japan.
This paper experimentally clarifies differences and similarities of the impression of sound clips among Japanese males, Chinese males, and Chinese females. It is shown that the factor of brightness commonly appears in the impression factors of Japanese males, Chinese males, and Chinese females, while the other factors do not always appear. The factors of Japanese males may be similar to those of Chinese females. This similarity is quantitatively clarified. It is also shown that this tendency appears for pictures.
Drawing is an important skill, but it is difficult for people who are weak in visual or spatial perception. In this study, we aim at utilizing computer support to assist people’s visual perception during their drawing practice. To this end, we propose to use AI technology based on CNN (convolutional neural network) model to recognize what people draw, and then output CG (computer graphics) according the recognition result. We apply this proposed solution to support the practice in creating design patterns like the tessellation. Our work includes four contributions in-below. (1) recognition of the user’s original drawing based on our trained AI model; (2) generation of new visual design by incorporating the result of recognition into the pattern called tessellation; (3) a digital interface to interactively provide the drawing recognition and tessellation generation; (4) our work is the first trial to realize the innovation tetra proposed by Dr. H. Shiizuka. A cross validation shows the theoretically accuracy of the train AI model. The result of a questionnaire-based evaluation shows the practical usability of the support system, and also advise us future improvement to reach various user requirements.
A model that estimates emotion types from bio-signals obtained by wearable monitoring systems was developed. A total of 470 events of strongly conscious emotions (happy, relaxed, sad, and angry) during work hours were recorded in 11 office workers under a total of 911 days of continuous monitoring of pulse rate, pulse rate variability (PRV), skin temperature, body motion, and conversation time with a bracelet-shape wearable sensor. When the four emotion types were developed on the two-dimensional plane consisted of valence and arousal axes, the former axis was composed of the coefficient of variation of high-frequency PRV amplitude and skin temperature, while the latter axis was composed of the frequency variability of PRV respiratory peak and conversation time. Among office workers, two emotional coordinates comprising the Russel’s Circumplex model may be estimated by bio-signals obtained by a wearable watch device.
In this study, we created two N-back task tasks - a verbal working memory (VWM) task and a spatial working memory (SWM) task. We compared the reaction with numerical working memory (NWM). In the experiment, we utilized NWM, VWM, and SWM 3- and 1-back tasks. We employed near-infrared spectroscopy to measure the response of oxyhemoglobin during the working memory tasks. In the analysis, we used changes in oxyhemoglobin of NWM, VWM, and SWM, activation frequency, and accuracy rate. The results showed that VWM and SWM performed the same measurement as NWM. We obtained no relationship between the correct answer rate and activation of the prefrontal cortex in the 1-back task, but the activity frequency was low. The 3-back task had a lower correct answer rate than 1-back but a higher activation frequency. It means that moderate difficulty can encourage activation.
To increase affective value of living space, we’ve been approaching to clarify the emotions and those emotional triggers while dressing at a powder room. From analyzing online interview data of 8 women, we externalized the difference between emotional causal relationship of “Dressing to see someone” like family outing and that of “Dressing without any purpose to see someone”. Construe the frequency of seeing someone as “sociality”, we made a discussion about its influence on the emotional causal relationship, referring to the change of sociality through Covid-19.