An IoT-Belief Rule Base Smart System to Assess Autism

An Internet-of-Things (IoT)-Belief Rule Base (BRB) based hybrid system is introduced to assess Autism spectrum disorder (ASD). This smart system can automatically collect sign and symptom data of various autistic children in real-time and classify the autistic children. The BRB subsystem incorporate...

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Bibliographic Details
Published in2018 4th International Conference on Electrical Engineering and Information & Communication Technology (iCEEiCT) pp. 672 - 676
Main Authors Alam, Md. Eftekhar, Kaiser, M. Shamim, Hossain, Mohammad Shahadat, Andersson, Karl
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2018
SeriesInternational Conference on Electrical Engineering and Information Communication Technology
Subjects
Autism
Distribuerade datorsystem
Electromyography
Expert systems
Heart rate
Microphones
Pervasive Mobile Computing
Uncertainty
Wireless sensor networks
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Summary:An Internet-of-Things (IoT)-Belief Rule Base (BRB) based hybrid system is introduced to assess Autism spectrum disorder (ASD). This smart system can automatically collect sign and symptom data of various autistic children in real-time and classify the autistic children. The BRB subsystem incorporates knowledge representation parameters such as rule weight, attribute weight and degree of belief. The IoT-BRB system classifies the children having autism based on the sign and symptom collected by the pervasive sensing nodes. The classification results obtained from the proposed IoT-BRB smart system is compared with fuzzy and expert based system. The proposed system outperformed the state-of-the-art fuzzy system and expert system.
ISBN:9781538682791
9781538682807
1538682796
153868280X
DOI:10.1109/CEEICT.2018.8628131