Deteksi Dini Level Keparahan Gangguan Spektrum Austisme Menggunakan Data Sensor Imu Serta Kalman Filtering Berbasis Fuzzy Decision Support System

Fatmasari, Kunthi (2023) Deteksi Dini Level Keparahan Gangguan Spektrum Austisme Menggunakan Data Sensor Imu Serta Kalman Filtering Berbasis Fuzzy Decision Support System. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Gangguan Spektrum Autisme adalah suatu kondisi seseorang mengalami kesulitan dalam berkomunikasi, bersosialisasi dan berperilaku. Tanda awal seseorang mengalami autisme ditandai dengan kurangnya atau keterlambatan berbahasa lisan, penggunaan bahasa yang berulang-ulang serta memainkan permainan yang itu-itu saja, menghindari kontak mata, dan tidak ada minat berinteraksi dengan teman-teman sebaya. Gangguan autisme biasanya muncul pada individu sebelum usia 3 tahun hingga usia 7 tahun. Namun, banyak orang tua yang terlambat mengenali dan menyadari kemunculan gejala gangguan spectrum austisme tersebut, sehingga menyebabkan kesalahan penanganan dan memicu peningkatan jumlah penderita autisme. Untuk mendeteksi secara dini tingkat keparahan gangguan spektrum autisme tersebut, dirancang sebuah system perangkat menggunakan wearable sensors berupa sensor inertial measurement units yang terdiri dari akselerometer dan giroskop serta menggunakan kalman filter yang berfungsi untuk mendeteksi indikasi adanya repetitive behaviours berupa gerakan flapping hand pada penderita gangguan spektrum autism.Kalman filter berfungsi untuk mengurangi noise dan menggabungkan output yang dihasilkan oleh akselerometer dan giroskop. Selain pendeteksian melalui gerakan getaran tangan, system ini dilengkapi dengan form assessment seputar keadaan individu kepada orang tua sebagai pendukung dalam deteksi dari modul deteksi gangguan spectrum autism. Hasil penelitian menunjukkan bahwa penggunaan form assesment M-CHART-R terbukti cukup akurat dalam mendeteksi kondisi awal subjek. Selain itu, sensor deteksi flapping hand yang digunakan mampu mengenali gerakan yang muncul pada pergerakan tangan subjek. Hasil Form DDST dinilai cukup membarikan informasi tambahan perkembangan subjek. Saran pengembangan lebih lanjut, penelitian ini dapat terintegrasi dengan database system sehingga dapat memberikan wawasan yang lebih mendalam tentang efektivitas sistem deteksi yang dikembangkan dalam mengidentifikasi tingkat keparahan ASD pada populasi yang relevan.
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Autism Spectrum Disorder is a condition in which a person experiences difficulties in communicating, socializing and behaving. Early signs of someone experiencing autism are marked by a lack or delay of spoken language, the use of language that is repeated and playing the same games, avoiding eye contact, and no interest in interacting with peers. Autism disorder usually appears in individuals before the age of 3 years until the age of 7 years. However, many parents are late in recognizing and realizing the appearance of the symptoms of autism spectrum disorder, causing mishandling and triggering an increase in the number of people with autism. To detect early the severity of the autism spectrum disorder, a device system is designed using wearable sensors in the form of sensors inertial measurement units consisting of accelerometers and gyroscopes and using a Kalman filter which functions to detect indications of repetitive behaviors in the form of flapping hand movements in sufferers of autism spectrum disorders. Kalman filter serves to reduce noise and combine the output generated by the accelerometer and gyroscope. In addition to detection through handshaking movements, this system is equipped with an assessment form regarding individual circumstances to parents as a support in the detection of the autism spectrum disorder detection module. The results showed that the use of the MCHART-R assessment form proved to be quite accurate in detecting the subject's initial condition. In addition, the flapping hand detection sensor used is able to recognize movements that appear in the subject's hand movements. The results of the DDST Form are considered sufficient to provide additional information on the subject's development. Suggestions for further development, this research can be integrated with the database system so that it can provide deeper insight into the effectiveness of the detection system developed in identifying the severity of ASD in the relevant population.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Gangguan Spektrum Autisme, Flapping hand, Kalman Filtering, Fuzzy Decision Support System Autism Spectrum Disorder, Flapping Hand, Kalman Filtering, Fuzzy Decision Support System
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7878 Electronic instruments
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Biomedical Engineering > 11410-(S1) Undergraduate Thesis
Depositing User:	Kunthi Fatmasari
Date Deposited:	08 Aug 2023 08:50
Last Modified:	08 Aug 2023 08:50
URI:	http://repository.its.ac.id/id/eprint/104278

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