Doplor Sleep Aplikasyon Mobil pou Siveye Somèy pa Yiling Liu

Dizayn Doplor Sleep Aplikasyon Mobil pou Siveye Somèy pa Yiling Liu se yon gayan ki gen anpil estim nan konpetisyon trè prestijye 2021 A' Design Award Fè nan Kategori Konpetisyon Mobil.

FèMobil· 2021

Doplor Sleep Aplikasyon Mobil pou Siveye Somèy

pa Yiling Liu

Kliyan: Reinier de Graaf Gasthuis

Gayan A' Design Award Fè nan Kategori Mobil

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Gayan Pri Verifye

Verifye Estati Pri pou #114626

Vizite Sit la Gade sou A' Design Award Kominike Laprès Badj Prim

Koulè

Konsepsyon an

Konsènan Doplor Sleep Aplikasyon Mobil pou Siveye Somèy

Doplor Sleep se yon aplikasyon siveyans somèy ki fèt pou itilizasyon lopital. Aplikasyon an anrejistre son anviwònman an avèk mikwofòn yon smartphone. Apre sa, algoritm klase chak son nan kategori tankou alam medikal, pawòl, son aksidantèl ak wonfle. Done somèy yo kolekte soti nan yon aparèy swivi somèy konekte epi yo konbine ak done son yo nan yon rapò chak jou. Ti ilistrasyon senp montre nivo son ak etap somèy yo sou yon sèl liy tan. Objektif la se fè pasyan yo ak pèsonèl medikal yo pi konsyan de bri kòm yon kòz ki fè moun pa dòmi byen nan lopital yo.

Rekonesans lan

Konsènan A' Design Award Fè

Doplor Sleep Aplikasyon Mobil pou Siveye Somèy se yon ganyan A' Design Award Fè, yon rekonesans ki gen prestij yo bay bon design ki satisfè egzijans pwofesyonèl ak endistriyèl yo atann de kreyasyon ki byen fèt. Ganyan Fè yo montre gwo konpetans, espesyalizasyon wo, konpreyansyon ekspè ak kapasite kreyatif kreyatè yo. Yo atann Doplor Sleep Aplikasyon Mobil pou Siveye Somèy pou se yon kreyasyon anpil moun estime, admire e renmen ki pratik e inovatè. Design sa a ki ganyen A' Design Award Fè entegre pi bon pratik sektè a e li gen karakteristik teknik konpetan ki lye ak konnesans pratik ak talan. Yo respekte Doplor Sleep Aplikasyon Mobil pou Siveye Somèy pou jèntan li e li fèt pou bay amelyorasyon kalite lavi ki ede fè mond lan vin yon pi bon kote.

Dèyè Konsepsyon an

Dosye Laprès

Kredi, manm ekip ak detay teknik konseptè a bay.

Pwopriyete Inik: 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.
Dimansyon & Anbalaj: The mobile application currently operates on Android devices, such as Android phones and devices.
Etikèt: Soundscape, Sleep, Sleep hygiene, Sleep quality, Hospital, sleep deprivation.
Teknoloji Pwodiksyon: The whole system is built with the Android Studio IDE and used the Fitbit API for retrieving sleep data.
Defi Dizayn: 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.
Rechèch: 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.
Enspirasyon: 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.
Dire Pwojè: The project started in March 2020 and ends in October 2020 in Delft, the Netherlands.
Fliks Operasyon: 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.
Manm Ekip: Yiling Liu
Elif Özcan
‪Jered Vroon
Daan Kamphuis
Kredi Imaj: 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