Doplor Sleep Cymhwysiad Symudol Monitro Cwsg gan Yiling Liu

Mae Doplor Sleep Cymhwysiad Symudol Monitro Cwsg gan Yiling Liu yn enillydd uchel ei barch o'r 2021 Gwobr Haearn A' Design Award mawreddog iawn yng Nghategori Cystadleuaeth Symudol.

HaearnSymudol· 2021

Doplor Sleep Cymhwysiad Symudol Monitro Cwsg

gan Yiling Liu

Cleient: Reinier de Graaf Gasthuis

Enillydd Gwobr Haearn A' Design Award yn y Categori Symudol

10,713

Enillydd Gwobr Wedi'i Wirio

Gwirio Statws Gwobr ar gyfer #114626

Ymweld â'r Wefan Gweld yn A' Design Award Datganiad i'r Wasg Bathodyn Gwobr

Lliwiau

Y Dyluniad

Am Doplor Sleep Cymhwysiad Symudol Monitro Cwsg

Mae Doplor Sleep yn gymhwysiad monitro cwsg ar gyfer defnydd ysbytai. Mae'r cymhwysiad yn recordio synau amgylcheddol gyda meicroffon ffôn clyfar. Yna mae algorithmau'n dosbarthu pob sain i gategorïau megis larymau meddygol, lleferydd, synau achlysurol a chwyrnu. Casglir data cwsg o draciwr cwsg cysylltiedig a'i gyfuno â'r data sain mewn adroddiad dyddiol. Mae darluniau syml yn dangos lefelau sain a chamau cwsg ar un llinell amser. Y nod yw gwneud cleifion a staff meddygol yn ymwybodol o sŵn fel achos o gwsg gwael mewn ysbytai.

Y Gydnabyddiaeth

Am y Gwobr Haearn A' Design Award

Mae Doplor Sleep Cymhwysiad Symudol Monitro Cwsg yn enillydd Gwobr Haearn A' Design Award, cydnabyddiaeth fawreddog a roddir i ddyluniadau da sydd yn bodloni'r gofynion proffesiynol a diwydiannol a ddisgwylir gan greadigaethau wedi'u dylunio'n dda. Mae enillwyr Haearn yn dangos medrusrwydd mawr, arbenigedd uchel, dealltwriaeth arbenigol a gallu creadigol eu crewyr. Disgwylir i Doplor Sleep Cymhwysiad Symudol Monitro Cwsg fod yn greadigaeth uchel ei bri, a edmygir ac a anwylir, sydd yn ymarferol ac yn arloesol. Mae'r dyluniad buddugol hwn o Wobr Haearn A' Design Award yn integreiddio arferion gorau'r diwydiant ac mae ganddo nodweddion technegol cymwys wedi'u cysylltu â gwybodaeth ymarferol a dawn. Parchir Doplor Sleep Cymhwysiad Symudol Monitro Cwsg am ei drylwyredd ac fe'i dyluniwyd i ddarparu gwelliannau ansawdd bywyd sydd yn helpu i wneud y byd yn lle gwell.

Y Tu Ôl i'r Dyluniad

Pecyn i'r Wasg

Credydau, aelodau tîm a manylion technegol a ddarparwyd gan y dylunydd.

Priodweddau Unigryw: 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.
Dimensiynau a Phecynnu: The mobile application currently operates on Android devices, such as Android phones and devices.
Tagiau: Soundscape, Sleep, Sleep hygiene, Sleep quality, Hospital, sleep deprivation.
Technoleg Cynhyrchu: The whole system is built with the Android Studio IDE and used the Fitbit API for retrieving sleep data.
Her Dylunio: 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.
Ymchwil: 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.
Ysbrydoliaeth: 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.
Hyd y Prosiect: The project started in March 2020 and ends in October 2020 in Delft, the Netherlands.
Llif Gweithrediad: 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.
Aelodau'r Tîm: Yiling Liu
Elif Özcan
‪Jered Vroon
Daan Kamphuis
Cydnabyddiaeth Delweddau: 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