设计师 Yiling Liu 的作品 Doplor Sleep 睡眠监测移动应用程序荣获了极具声望的 2021 A' Design Award 铁奖，竞赛类别为移动技术、应用与软件设计。

铁移动· 2021

Doplor Sleep 睡眠监测移动应用程序

设计师： Yiling Liu

客户: Reinier de Graaf Gasthuis

移动类别A' Design Award 铁奖获奖者

10,713

已验证的获奖者

验证 #114626 的获奖状态

访问网站在A' Design Award上查看新闻稿获奖徽章

色彩

设计作品

关于 Doplor Sleep 睡眠监测移动应用程序

Doplor Sleep是一款专为医院环境打造的睡眠监测应用程序。该应用通过智能手机的麦克风采集环境声音，随后由算法将每种声音归类为医疗警报声、人声交谈、偶发噪音及鼾声等类别。应用同时从相连的睡眠追踪设备获取睡眠数据，并将其与声音数据整合生成每日报告。简洁直观的图示将声音强度与睡眠阶段呈现在同一条时间轴上。其目标在于让患者与医护人员意识到，噪音正是导致医院内睡眠质量不佳的重要原因。

荣誉认可

关于A' Design Award 铁奖

Doplor Sleep 睡眠监测移动应用程序是 A' Design Award 铁奖得主，这是授予满足人们对设计精良的创作所期待的专业与工业要求的优良设计的声望认可。铁奖得主展现出其创作者的高超技艺、高度专业化、专家级的理解力和创造能力。预计Doplor Sleep 睡眠监测移动应用程序将成为一件备受推崇、令人钦佩且被珍爱的创作，既实用又创新。这件赢得 A' Design Award 铁奖的设计整合了行业最佳实践，并拥有与专业知识和才华相结合的称职技术特性。Doplor Sleep 睡眠监测移动应用程序因其严谨而受到尊重，旨在提供有助于让世界变得更美好的生活品质改善。

设计幕后

媒体资料包

由设计师提供的致谢、团队成员及技术详情。

独特属性: Doplor Sleep is a bedtime monitoring application that provides insights into sound disturbances in the hospital. It captures the environmental sounds using the microphone of the smartphone, and the implemented algorithms directed classify the data recorded into different sound source categories, such as medical alarms, speech, incidental sounds, and snoring sounds. Doplor sleep is connected with the Fitbit sleep tracker and retrieves data from Fitbit API to form daily sleep-sound quality reports. As for the UI, we used friendly-looking illustrations to present the data and information, and a creative way of interaction to let users view the dynamic of their sleep status and the acoustical environment throughout the night.
尺寸与包装: The mobile application currently operates on Android devices, such as Android phones and devices.
标签: Soundscape, Sleep, Sleep hygiene, Sleep quality, Hospital, sleep deprivation.
生产技术: The whole system is built with the Android Studio IDE and used the Fitbit API for retrieving sleep data.
设计挑战: The first challenge is how to design a sound classification algorithm that could accurately classify the sounds of the hospital. The second one is to investigate how can we present the sound data and sleep data on the same timeline in a user-friendly way.
研究: Recently in the Netherlands, researchers have found
that sleep duration and quality were suboptimal in the
hospital. Evidence proved that many modifiable hospital-related
factors negatively associated 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
the 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.
灵感: Sleep deprivation caused by environmental factors can be fatal to critically ill patients. For example, various noises caused by false medical alarms, activities of hospital staff, conversations, etc. can cause delirium in patients with brain diseases. When it happens, patients are in a state of mental confusion and emotional disruption, which prolongs their hospital stay and, like a vicious circle, disturbs the rest of the other patients. A first-step solution can be creating awareness.
项目周期: The project started in March 2020 and ends in October 2020 in Delft, the Netherlands.
操作流程: Before going to bed, the user presses the ship-icon button to start recording the environmental sounds. The next morning, the user presses the ship-icon again to stop recording. Then a sleep summary page occurs with information displayed such as sleep quality and sound quality. By Swiping to the left, the next screen occurs and the user sees more details about sees the presence of sounds (loudness levels and classifications) and sleep stages (wake, Light sleep, REM, and Deep sleep) during the whole by moving the boat forward along the river. Here we used boats as a time indicator and a representation of the sleeper, and the river indicating the timeline. The color blocks on the river represent the sleep stages. The icons of picnic, flashlight, rocks, and nose bubble indicate different sound classifications (speech, medical alarms, incidental sounds, and snores). Finally, by swiping to the left again, the user could fill in a short survey on their subjective feelings about sleep quality. The data will then be sent to the medical staff.
团队成员: Yiling Liu
Elif Özcan
‪Jered Vroon
Daan Kamphuis
图片版权: Image #1: Illustrator Yiling Liu, Doplor Sleep Mockup, 2020.
Image #2: Illustrator Yiling Liu, Doplor Sleep Phone Mockup, 2020.
Image # 3: Illustrator Yiling Liu, Doplor Sleep Tablet Mockup, 2020.
Image #4: Creator Yiling Liu, Doplor Sleep Phone Mockup, 2020.
Image #5: Creator Yiling Liu, Doplor Sleep Phone Mockup, 2020.
Video Credits: Creator Yiling Liu, Doplor Sleep Showcase, 2020