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An IoT-belief rule base smart system to assess autism
Electrical Electronic Engineering, International Islamic University, Chittagong, Bangladesh.
Institute of Information Technology, Jahangirnagar University, Dhaka, Bangladesh.
Computer Science Engineering, University of Chittagong, Chittagong, Bangladesh.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-0244-3561
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
IEEE, 2018.
Keywords [en]
Autism, Expert systems, Heart rate, Uncertainty, Electromyography, Microphones, Wireless sensor networks
National Category
Computer Sciences
Research subject
Pervasive Mobile Computing
Identifiers
URN: urn:nbn:se:ltu:diva-73492DOI: 10.1109/CEEICT.2018.8628131Scopus ID: 2-s2.0-85062777292OAI: oai:DiVA.org:ltu-73492DiVA, id: diva2:1302965
Conference
4th International Conference on Electrical Engineering and Information and Communication Technology, iCEEiCT 2018, Dhaka, Bangladesh, 13-15 September 2018
Available from: 2019-04-08 Created: 2019-04-08 Last updated: 2019-04-08

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Andersson, Karl

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