Data-enabled design (2024-2025)

This study focuses on a core design question: how can design interventions help users reduce non-sleep activities in bed, thereby enhancing their sleep satisfaction and overall sleep experience? The research background highlights that sleep problems have become a global public health challenge. Traditional research has largely focused on improving sleep quality by enhancing objective indicators such as ‘sleep efficiency’; however, recent studies suggest that ‘sleep satisfaction’ has a more significant and lasting impact on daily mood and long-term health. Nevertheless, there remains a lack of clear strategies on how to effectively enhance users’ sleep satisfaction through design. To this end, following two rounds of iterative probe development, this study ultimately resulted in the creation of a light-feedback sleep probe named ‘Lumi Alarm’. The first-round prototype integrated a PIR motion sensor, a microphone, a light sensor and an LCD screen to collect data on ambient noise, lighting and movement in real-life domestic settings. Combined with sleep diaries and interviews, the findings revealed that users’ sleep satisfaction was highly correlated with ‘non-sleep activities in bed’ (particularly mobile phone use), a phenomenon that was particularly pronounced among users living in studio flats due to the blurred boundaries between functional zones. The second-generation prototype shifted the design focus from ‘environmental adjustment’ to ‘behavioural guidance’. Using pressure sensors and a button placed under the pillow, it recorded users’ actual bedtimes and times of getting out of bed. It calculated sleep efficiency based on users’ preset target bedtimes and provided physical feedback via LED lighting: warm light indicated the duration spent in bed, whilst cool light signalled when the user was out of bed. This subtle ‘pressure’ through light colour encouraged users to reduce mobile phone use and fall asleep earlier. The accompanying app also offers a ranking feature to incentivise users to maintain good habits. Preliminary user testing over a single night showed that participants reduced their mobile phone usage whilst in bed, improved their sleep efficiency, and reported higher satisfaction with their sleep activities. The core contribution of this design lies in validating the effectiveness of the ‘mild discomfort induction’ light feedback strategy in reducing non-sleep activities in bed, and revealing the separability of ‘sleep quality satisfaction’ from ‘sleep activity satisfaction’—the former relying on physiological experience, whilst the latter is more influenced by a sense of behavioural control. This provides a new paradigm for the design of future sleep health products, shifting the focus from ‘improving the environment’ to ‘shaping behaviour’, whilst also demonstrating the unique value of data visualisation as a tool for behavioural guidance.