## 1 Introduction  
In an aged society, technology can facilitate the provision of healthcare to older adults [1; 2; 3]. The role of artificial intelligence (AI) and machine learning technologies is growing and is expected to be used across the entire healthcare ecosystem [4; 5; 6; 7]. A majority of consumers are willing to consider AI technologies for managing their health, including monitoring heart condition (e.g., pulse, blood pressure, electrocardiography, etc.), providing customized advice for health based on their personal preferences and health records [7; 8]. Furthermore, people are becoming more and more involved in managing their personal health using the internet of things (IoT) and wearable devices [9; 10].  
Wearable devices are becoming increasingly prevalent amidst perpetual component miniaturization and cost reduction. According to consumer data research, the healthcare wearables market is expected to reach $14.4 billion by 2022 [11; 12]. These devices have enabled older users to track and manage their health information anytime, anywhere. In addition, as the voice user interfaces, such as Apple's Siri and Amazon's Alexa, becomes standard on wearables devices, these interactions increase ease of use for healthcare management [13; 14]. In today's market, developers are constantly launching new health management applications (apps), providing more opportunities for older adults to use health information interfaces.  
Wearable devices serve as both accessories and trackers of personal information. This information can be simultaneously transferred to the wearer and relevant parties. Wearable devices must be compatible with the user and their environment. Therefore, they are complex microdevices that facilitate human-computer interaction. With the evolution and innovation of new technology for this interaction, the design of visual display for older adults' health information was concerned in this study. Considering how older adults' physical and mental functions deteriorate with age, questions have arisen as to whether existing app interface designs are suitable for older adults and whether the perceived usability of these app interfaces differs for younger users and older adults. Many scholars asserted that products become more acceptable to users when they are able to incite positive emotions [15; 16; 17]. Therefore, it is important to elucidate how visual health information interfaces incite affective valence and arouse older adults. This study analyzed the display formats of health information on wearable interfaces to determine perceived usability and emotional reactions, with the goal of improving healthcare for older adults.  
A literature review and a sample analysis were performed to identify four different interface formats, namely text, diagram, image, and animation, and a questionnaire was conducted to test them. This study examined the differences in how the four interfaces are used by younger users and older adults, and highlighted the advantages and disadvantages of the interfaces. Several design suggestions are presented based on the research findings.  
The objectives of this study were as follows:  
1. To analyze the display formats for visualizing health information and test the usability of these formats.
2. To investigate users' acceptance and comprehension of the display formats and determine the affective valence and arousal elicited by these formats.
3. To compare the responses of younger users and older users to the different formats.  
This research, however, is subject to several limitations. Providing sound feedback can enhance the user interface design. Furthermore, applying the technology of voice user interfaces to assist communication is growing as the rapid development of AI [18; 19]. This research only focuses on different types of visual interfaces and regards sound/voice as a controlled variable. Therefore, as with the majority of studies, the findings of this study have to be seen in light of some limitations.