Doplor Sleep Slaapmonitering Mobiele Toepassing by Yiling Liu

Doplor Sleep Slaapmonitering Mobiele Toepassing by Yiling Liu is a highly esteemed winner of the very prestigious 2021 A' Design Award in Yster in Mobiele Tegnologieë, Toepassings en Sagteware Ontwerp Competition Category.

YsterMobiel· 2021

Doplor Sleep Slaapmonitering Mobiele Toepassing

by Yiling Liu

Client: Reinier de Graaf Gasthuis

A' Design Award in Yster Winner in Mobiel Category

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Verified Award Winner
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Colors

The Design

About Doplor Sleep Slaapmonitering Mobiele Toepassing

Doplor Sleep is 'n slaapmoniteringstoepassing vir hospitaalgebruik. Die toepassing neem omgewingsklanke op met die mikrofoon van 'n slimfoon. Algoritmes klassifiseer dan elke klank in kategorieë soos mediese alarms, spraak, bykomstige geluide en snork. Slaapdata word ingesamel vanaf 'n gekoppelde slaaptoezicht-toestel en gekombineer met die klankdata in 'n daaglikse verslag. Eenvoudige illustrasies toon klankvlakke en slaapfases op een tydlyn. Die doel is om pasiënte en mediese personeel bewus te maak van geraas as 'n oorsaak van swak slaap in hospitale.

The Recognition

About the A' Design Award in Yster

Doplor Sleep Slaapmonitering Mobiele Toepassing is 'n wenner van die A' Design Award in Yster, 'n prestigieuse erkenning wat toegeken word aan goeie ontwerpe wat voldoen aan die professionele en industriële vereistes wat van goed ontwerpte skeppings verwag word. Wenners in Yster toon groot vaardigheid, hoë spesialisasie, kundige begrip en die kreatiewe vermoë van hul skeppers. Daar word verwag dat Doplor Sleep Slaapmonitering Mobiele Toepassing 'n hoog aangeskrewe, bewonderde en gekoesterde skepping is wat prakties en innoverend is. Hierdie ontwerp wat die A' Design Award in Yster gewen het, integreer die beste praktyke in die bedryf en het bekwame tegniese kenmerke gekoppel aan kundigheid en talent. Doplor Sleep Slaapmonitering Mobiele Toepassing word gerespekteer vir sy deeglikheid en is ontwerp om verbeterings in lewensgehalte te bied wat help om die wêreld 'n beter plek te maak.

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