Doplor Sleep 수면 모니터링 모바일 애플리케이션 by Yiling Liu

Doplor Sleep 수면 모니터링 모바일 애플리케이션 by Yiling Liu is a highly esteemed winner of the very prestigious 2021 A' Design Award 철상 in 모바일 기술, 애플리케이션 및 소프트웨어 디자인 Competition Category.

철모바일· 2021

Doplor Sleep 수면 모니터링 모바일 애플리케이션

by Yiling Liu

Client: Reinier de Graaf Gasthuis

A' Design Award 철상 Winner in 모바일 Category

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The Design

About Doplor Sleep 수면 모니터링 모바일 애플리케이션

Doplor Sleep은 병원에서 사용하도록 개발된 수면 모니터링 애플리케이션입니다. 이 애플리케이션은 스마트폰의 마이크를 통해 주변 환경음을 녹음합니다. 이후 알고리즘이 각 소리를 의료 기기 알람, 대화 소리, 우발적인 소음, 코골이 등의 범주로 분류합니다. 수면 데이터는 연동된 수면 트래커를 통해 수집되며, 소리 데이터와 결합되어 일일 리포트로 제공됩니다. 간결한 일러스트레이션이 하나의 타임라인 위에 소음 수준과 수면 단계를 함께 보여줍니다. 이 디자인의 목적은 환자와 의료진이 병원 내 수면의 질을 저하시키는 원인으로서의 소음을 인식하도록 하는 데 있습니다.

The Recognition

About the A' Design Award 철상

Doplor Sleep 수면 모니터링 모바일 애플리케이션, 이 작품은 A' Design Award 철상 수상작으로, 잘 디자인된 창작물에 기대되는 전문적·산업적 요건을 충족하는 좋은 디자인에 수여되는 권위 있는 인정입니다. 철상 수상작은 창작자의 뛰어난 기술, 높은 전문성, 전문가다운 이해, 창의적 역량을 보여 줍니다. Doplor Sleep 수면 모니터링 모바일 애플리케이션, 이 작품은 높이 평가받고 감탄과 사랑을 받는 창작물로서 실용적이고 혁신적일 것으로 기대됩니다. 이 철상 수상 디자인은 업계 모범 사례를 통합하며 노하우와 재능으로 연결된 유능한 기술적 특성을 갖추고 있습니다. Doplor Sleep 수면 모니터링 모바일 애플리케이션, 이 작품은 철저함으로 존중받으며 삶의 질을 개선하여 세상을 더 나은 곳으로 만들도록 디자인되었습니다.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: 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.
Dimensions & Packaging: The mobile application currently operates on Android devices, such as Android phones and devices.
Tags: Soundscape, Sleep, Sleep hygiene, Sleep quality, Hospital, sleep deprivation.
Production Technology: The whole system is built with the Android Studio IDE and used the Fitbit API for retrieving sleep data.
Design Challenge: 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.
Research: 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.
Inspiration: 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.
Project Duration: The project started in March 2020 and ends in October 2020 in Delft, the Netherlands.
Operation Flow: 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.
Team Members: Yiling Liu
Elif Özcan
‪Jered Vroon
Daan Kamphuis
Image Credits: 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