TY - GEN
T1 - Autism Spectrum Disorder Detection in Children Using Fuzzy Detection Support System
AU - Amanda, Patricia
AU - Arifin, Achmad
AU - Hikmah, Nada Fitrievatul
AU - Nuh, Mohammad
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Autism Spectrum Disorder (ASD) is a developmental disability caused by differences in the brain. Autism disorders usually appear in children before the age of three to seven years. However, ASD in children is only detected after the age of ten years old. In this study, a detection system based on fuzzy logic decision support was designed to detect the severity of ASD in children. The detection process was carried out by asking parents questions about the child's condition as a detection reference taken from the ASD detection module. This system was also equipped with instrumentation in the form of wearable sensors in the form of accelerometers and gyroscopes that function to read flapping hand movement signals in children as an indication of repetitive behaviors suffered by ASD children. The results showed that the assessment form used, namely M-CHART - R, proved to be quite accurate in detecting the initial condition of the subject. The flapping hand detection sensor detected flapping hands that appeared on the subject with an average error of 0.356133 for sensor module 1 and 0.30866 for sensor module 2. The system has 83.3% accuracy. Future development can be addressed to hardware and software development as an embedded system so that the entire system can work in real-time using IoT.
AB - Autism Spectrum Disorder (ASD) is a developmental disability caused by differences in the brain. Autism disorders usually appear in children before the age of three to seven years. However, ASD in children is only detected after the age of ten years old. In this study, a detection system based on fuzzy logic decision support was designed to detect the severity of ASD in children. The detection process was carried out by asking parents questions about the child's condition as a detection reference taken from the ASD detection module. This system was also equipped with instrumentation in the form of wearable sensors in the form of accelerometers and gyroscopes that function to read flapping hand movement signals in children as an indication of repetitive behaviors suffered by ASD children. The results showed that the assessment form used, namely M-CHART - R, proved to be quite accurate in detecting the initial condition of the subject. The flapping hand detection sensor detected flapping hands that appeared on the subject with an average error of 0.356133 for sensor module 1 and 0.30866 for sensor module 2. The system has 83.3% accuracy. Future development can be addressed to hardware and software development as an embedded system so that the entire system can work in real-time using IoT.
KW - Autism Spectrum Disorder (ASD)
KW - Flapping Hand
KW - Fuzzy Logic
KW - Repetitive Behaviours
KW - Wearable Sensors
UR - http://www.scopus.com/inward/record.url?scp=85149123396&partnerID=8YFLogxK
U2 - 10.1109/CENIM56801.2022.10037404
DO - 10.1109/CENIM56801.2022.10037404
M3 - Conference contribution
AN - SCOPUS:85149123396
T3 - Proceeding of the International Conference on Computer Engineering, Network and Intelligent Multimedia, CENIM 2022
SP - 14
EP - 19
BT - Proceeding of the International Conference on Computer Engineering, Network and Intelligent Multimedia, CENIM 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 International Conference on Computer Engineering, Network and Intelligent Multimedia, CENIM 2022
Y2 - 22 November 2022 through 23 November 2022
ER -