Recently in the Netherlands, researchers have found that sleep duration and quality were suboptimal in the hospital. Evidence proved that many modifiable hospitalrelated factors negatively associate with patients' sleep (JAMA Internal Medicine, 2018). The sound factor is the most significant sleep disturbance in the hospital. In this graduation project, collaborating with Reiner de Graaf hospital and Critical Alarms lab, an information exchange system was proposed to raise awareness of sound as sleep disturbance. The system captures the sound-producing events and visualizes them with visually attractive graphics. In this system, we use the smartphone as the sound captor. The recorded sounds are processed locally on the phone and converted into information such as sound level and the category it belongs to (alarm, speech, incidental sounds, or snore). Fitbit is implemented in the system to collect sleep information. To both patients and medical staff, The Doplor sleep system presents the influence of sound on sleep in a friendly and comprehensive way. During this project, a functioning prototype was developed. We have tested its functionality and user experience with the potential users.

Hospitalized patients were found to sleep significantly worse in the hospital than at home. The lack of quality sleep can cause serious health problems and affect patients’ health recovery. Music as a low-cost sleep aid is a promising way to improve patients’ sleep. However, most available sleep music playlists are limited to generic, soothing songs. People’s personal preferences in relation to the effects of music are not well-considered and under-researched. Therefore, this project aims to explore how to design and deliver music that fits with patients’ sleep and music preferences with a profile-based personalization approach. Literature research was first carried out to understand sleep knowledge, how and why music aid sleep, practices in music therapy and profile-based personalization. Through generative research, people’s preference data was collected and lead to four sleep music profiles: explorer, diver, hunter, observer. A design direction was proposed based on insights from the research activities. In the design phase, two brainstorming sessions were carried out and resulted in a feasible system concept. After two iterations, the final design DREAMe was proposed. DREAMe is personalized music modular system, including profile generation and music delivery. The profile generation logic allows the system to predict which profile users are based on a list of questions. Each profile comes with a sleep music module. To evaluate the music effects, sleep music samples were made under a summarized music design guideline. The music melodies of users’ favourite music come from instrumental covers of the songs participants provided. The resources downloaded online were used fairly and only for this evaluation purpose. In project evaluation, results suggest that the product and profile experience are logical, intuitive, and easy to use. The four profiles can reflect people’s preferences, but they may not be stable. An eight-day evaluation was conducted to test the music effects on sleep. DREAMe music was found to reduce sleep onset latency and improve sleep quality. People could fall asleep more easily and feel more relaxed after two days’ music listening. The music design delivers a relaxing, enjoyable and immersive music experience.