Improving Sleep Health Through The Design Of Smartwatch-Based Self-Tracking With Self-Regulation Techniques

Sleep-related problems are increasingly prevalent in the world and can seriously affect people's health and life. Meanwhile, smartwatch-based self-tracking holds great promise for empowering individuals to manage and improve their sleep health, yet there is a lack of understanding on the effects of self-tracking on user attitudes and behaviors, as well as optimized design strategies that can motivate real behavioral change. This study investigated the sleep data of users for two weeks in the field through smartwatch-based self-tracking, and analyzed their behaviors, preferences and needs related to the process, which provided the empirical basis for smart design solutions incorporating self-regulation techniques. Results suggested that sleep self-tracking can increase health awareness and promote behavioral adjustments, but the self-tracking process and data presentation need to be improved, such as setting clear goals, mining valuable information behind the data and providing useful feedback. Therefore, we proposed optimization and visualization strategies, by combining self-regulation techniques and user-centered perspectives to improve the design of smartwatch-based sleep self-tracking.