Previous studies have indicated that many patients with eye diseases are not adherent to eyedrops due to the difficulty in administration. The purpose of using eyedrop compliance aids is to help patients who have difficulties in administering eyedrops. However, this method has not been well recognized and accepted.

This study aimed to upgrade eyedrop compliance aids so that the adherence of eyedrop users could be improved. Among the research methods employed in this study, the analytic hierarchy process (AHP) helped in proposing the best function sequence of the device, and a questionnaire based on the Kano model helped understand the degree of satisfaction with the existing products, as well as discover the appealing factors of their functions and examine their functional relationships. Finally, the results of the two methods were discussed and compared, and the results were used to identify the basic appealing factors influencing consumer satisfaction as well as provide the element attributes and significant features to be weighed in the design of eyedrops. This study suggested that in the design of eyedrops, both the physical and psychological needs of users should be taken into consideration, and reference indexes for aids design that may effectively improve user adherence to eyedrops should be proposed.

Falls are one of the major health risks that affect the quality of life among elderly peoples, but the elderly do not like to wear anti-falling clothing in their daily life as the anti-falling clothing are inconvenient, uncomfortable and not beautiful for the elderly to wear. The elderly clothing and anti-falling function have not been perfectly integrated. To prevent the elderly from being injured by falling and meet their pursuit of clothing, there is a need to integrate anti-falling function into elderly clothing with high satisfaction. This study aims to identify the integration strategies can meet the dressing effect that the elderly pursues in different scenarios using Kansei Engineering Type I. The design strategies for the elderly clothing with anti-falling function will be determined. A framework of integrating anti-falling function for elderly clothing with high satisfaction will be constructed. The results of this study can support the improvement of elderly clothing performance.

A method for estimating health conditions is required to monitor daily health conditions. Various types of data have been used in healthcare studies; however, imaging data are superior because they allow quick and remote measurements. Thermal face images can be measured safely and economically using infrared thermography. Many physiological and psychological states have been evaluated based on the data from these images. A previous study, using short-term experiments, confirmed that an anomaly detection model constructed using a variational autoencoder enables the detection of anomalous states of thermal face images. A long-term experiment is essential to estimate long-term fluctuating human states, such as health conditions. The purpose of this study is to construct a facial skin temperature-based anomaly detection model for human health conditions. The authors obtained thermal face images with health condition questionnaires for approximately a year. Based on the questionnaire responses, the thermal images in good and poor health conditions were labeled “normal state” and “anomaly state,” respectively. The facial skin temperature-based anomaly detection model for health conditions was constructed using a variational autoencoder with only thermal face images in the normal state. The AUC, which represents anomaly detection performance, was 0.70. In addition, an increasing trend of the performance of the model by learning a wider area of skin temperature was confirmed.

Many assumptions were made about people's dissatisfaction with their daily lives, such as debt burden, social problems, unstable economic conditions, health problems, cost of living, lack of job opportunities, lack of educational support, and so on. The positive or negative emotional experience is distinctive between individuals or groups of people who share similar life experiences. Thus, the purpose of this study was to explore the emotional responses of a specific population to daily obstacles that may be related to the mentioned scenarios. The Lokman's Emotion and Importance Quadrant (LEIQ)^TM, which was built on axes of emotion vs. importance, was used in this study to discover the importance of the identified indicators to the people’s happiness. The model is based on the idea that accurate strategies to improve people's quality of life can be devised by classifying indicators that contribute to people's emotions and understanding their importance to the people who interact with the stimuli. The findings of this study will eventually enable the identification of indicators that significantly influence people's positive or negative emotional states, which can then be used by stakeholders to devise effective strategies for future improvements.