Sistem pemantau postur tidur pengidap obstructive sleep apnea dan primary snoring berbasis sensor IMU = Sleep posture monitoring system on subjects with obstructive sleep apnea and primary snoring based on IMU sensors

Priscilia, Kayleen (2021) Sistem pemantau postur tidur pengidap obstructive sleep apnea dan primary snoring berbasis sensor IMU = Sleep posture monitoring system on subjects with obstructive sleep apnea and primary snoring based on IMU sensors. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Obstructive Sleep Apnea (OSA) dan Primary Snoring (PS) merupakan gangguan tidur yang cukup serius dan dapat mengakibatkan beberapa masalah kesehatan, seperti masalah mental dan medis yang dapat dialami di kemudian hari. Beberapa penelitian sebelumnya mengatakan bahwa kedua gangguan tidur tersebut memiliki koneksi dengan postur tidur, yang hanya mencakup postur badan dimana postur badan yang telentang dapat berdampak pada tingkat keparahan PS dan OSA. Adanya hubungan tersebut memungkinkan untuk dirancangnya suatu sistem yang dapat memantau posisi tidur yang lebih rinci dengan memantau postur badan dan kepala dengan harapan bahwa subjek dapat menghindari postur tidur tertentu yang dianggap dapat meningkatkan keparahan gangguan tidur, seperti PS dan OSA. Tujuan dari penelitian ini adalah untuk mencari tahu hubungan antara postur tidur, yang tidak hanya melibatkan postur badan, tetapi juga postur kepala dan inklinasi kepala dengan dibuatnya sistem pemantau postur tidur pengidap OSA dan PS berbasis sensor IMU. Adapun perangkat lain yang digunakan, seperti EKG untuk mendapatkan sinyal jantung, serta mikrofon agar didapatkan sinyal suara dari subjek. Subjek yang diteliti adalah 2 subjek sehat, 2 subjek pengidap PS dan 1 subjek pengidap OSA. Suara dengkuran ditentukan dengan menggunakan machine learning dengan model Neural Network. Episode OSA diklasifikasi dengan menggunakan model Le-Net-5 yang telah dimodifikasi. Klasifikasi dari postur badan, kepala dan inklinasi kepala dengan sensor IMU menggunakan metode penentuan nilai batas. Hasil percobaan menunjukkan bahwa terdapat hubungan antara postur tidur degan tingkat keparahan dengkuran, dimana subjek pengidap PS dengan postur badan dan postur kepala yang telentang dengan inklinasi kepala normal pada saat tidur mengeluarkan suara dengkuran yang lebih keras. Terdapat degradasi pada intensitas dengkuran serta amplitudo dengkuran pada saat subjek berada dalam postur badan dan kepala balik kiri/kanan, serta inklinasi kepala normal. Hal tersebut berbeda dengan subjek pengidap OSA yang menunjukkan tidak terdapat perbedaan yang signifikan pada kerasnya suara dengkuran maupun intensitas dengkuran pada masing-masing posisi tidur. Namun, terdapat penurunan pada jumlah episode OSA pada saat subjek sedang berada dalam postur badan dan kepala balik kiri/kanan pada saat inklinasi kepala normal dibandingkan dengan postur badan dan kepala telentang pada saat inklinasi kepala normal. / Obstructive Sleep Apnea (OSA) and Primary Snoring (PS) are sleep disorders that are quite serious and can lead to several health problems, such as mental and medical problems that can be experienced later in life. Several previous studies said that the two sleep disorders have a connection with sleep posture, which only covers body posture, where supine body posture can have an impact on the severity of PS and OSA. The existence of this relationship makes it possible to design a system that can monitor a more detailed sleeping position by monitoring body and head posture in the hope that subjects can avoid certain body and head postures that are considered to increase the severity of sleep disorders, such as OSA and PS. The purpose of this study was to find out the relationship between sleep posture, which involves not only body posture, but also head posture and head inclination by developing a sleep posture monitoring system for people with OSA and PS based on IMU sensors. There are other devices used, such as an ECG to get a heart signal, and a microphone to get a sound signal from the subject. The types of subjects studied were 2 healthy subjects, 2 subjects with PS and 1 subject with OSA. The sound of snoring is determined using machine learning with the Neural Network model. OSA episodes were classified using the modified Le-Net-5 model. Body posture, head postur and head inclination is classified by using IMU sensor with thresholding method. According to the results obtained from this system, it was found that there is a relationship between sleep posture and the severity of snoring, where subjects with PS with body posture and head posture that are supine with normal head inclination during sleep make louder snoring sounds. There is degradation in the intensity of snoring and the amplitude of snoring when the subject is in the lateral body and head posture, and the head inclination is normal. It is in contrast to subjects with OSA, where there is no significant difference in the loudness of snoring and the intensity of snoring in each sleeping position. However, there is a decrease in the number of OSA episodes when the subject is in lateral body and head posture at the normal head inclination compared to the supine body head posture at the normal head inclination.

Item Type: Thesis (Bachelor)
Creators:
CreatorsNIMEmail
Priscilia, KayleenNIM01082170009kayleenpriscilia@gmail.com
Contributors:
ContributionContributorsNIDN/NIDKEmail
Thesis advisorSutrisno, SutrisnoNIDN0331126201sutrisno.fik@uph.edu
Thesis advisorTjahyadi, HendraNIDN0410076901hendra.tjahyadi@uph.edu
Uncontrolled Keywords: obstructive sleep apnea ; primary snoring ; postur tidur ; sensor IMU ; EKG ; machine learning
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: University Subject > Current > Faculty/School - UPH Karawaci > School of Information Science and Technology > Informatics
Current > Faculty/School - UPH Karawaci > School of Information Science and Technology > Informatics
Depositing User: Users 9586 not found.
Date Deposited: 02 Aug 2021 01:07
Last Modified: 16 Mar 2022 09:39
URI: http://repository.uph.edu/id/eprint/40939

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