fASSERT: A Fuzzy Assistive System for Children with Autism Using Internet of Things

  • Anjum Ismail Sumi
  • Most. Fatematuz Zohora
  • Maliha Mahjabeen
  • Tasnova Jahan Faria
  • Mufti MahmudEmail author
  • M. Shamim KaiserEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11309)


This work presents an assistive system for child with autism spectrum disorder (C-ASD). The main objective of this system is to reduce dependency on the caregiver and parent and thereby assisting them to make independent. Fuzzy logic based expert system is designed for the assisting system which will help in intervention strategies. The system collects data from four different sensors, such as GPS, heart beat, accelerometer and sound, and generates required notification for the parent, caregiver and C-ASD. The wearables-specifically smart watches- can be used to implement such system. A case study shows the proposed expert system is able to help the C-ASD to restore dysfunction.


Fuzzy set Knowledge base Wearable devices Caregiver Brain disorder 


  1. 1.
    Ahmed, I.U., Hassan, N., Rashid, H.: Solar powered smart wearable health monitoring and tracking device based on GPS and GSM technology for children with autism. In: Proceedings of ICAEE, pp. 111–116 (2017)Google Scholar
  2. 2.
    Alwakeel, S., Alhalabi, B., Aggoune, H., Alwakeel, M.: A machine learning based WSN system for autism activity recognition. In: Proceedings of ICMLA, pp. 771–776 (2015)Google Scholar
  3. 3.
    Goel, I., Kumar, D.: Design and implementation of android based wearable smart locator band for people with autism, dementia, and alzheimer. Adv. Electr. 2015, 1–8 (2015)CrossRefGoogle Scholar
  4. 4.
    Kaiser, M.S., et al.: A neuro-fuzzy control system based on feature extraction of surface electromyogram signal for solar-powered wheelchair. Cogn. Comput. 8(5), 946–954 (2016)CrossRefGoogle Scholar
  5. 5.
    Mahmud, M., et al.: Applications of deep learning and reinforcement learning to biological data. IEEE Trans. Neural Netw. Learn. Syst. 29(6), 2063–2079 (2018)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Mahmud, M., et al.: A brain-inspired trust management model to assure security in a cloud based IoT framework for neuroscience applications. [ePub ahead of print]CrossRefGoogle Scholar
  7. 7.
    Min, C.: Automatic detection and labeling of self-stimulatory behavioral patterns in children with autism. In: Proceedings of IEEE-EMBC, pp. 279–282 (2017)Google Scholar
  8. 8.
    Min, C.H., Tewfik, A.: Automatic characterization and detection of behavioral patterns using linear predictive coding of accelerometer sensor data. In: Proceedings of IEEE-EMBC, pp. 220–2233 (2010)Google Scholar
  9. 9.
    Santos, B.R., et al.: A method for automatic fuzzy set generation using sensor data. Intell. Autom. Soft Comput. 14(3), 279–294 (2008)CrossRefGoogle Scholar
  10. 10.
    Sula, A., Spaho, E.: Using assistive technologies in autism care centers to support children develop communication and language skills. A case study: Albania. Acad. J. Interdiscip. Stud. 3(1), 203–212 (2014)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Anjum Ismail Sumi
    • 1
  • Most. Fatematuz Zohora
    • 1
  • Maliha Mahjabeen
    • 1
  • Tasnova Jahan Faria
    • 1
  • Mufti Mahmud
    • 2
    Email author
  • M. Shamim Kaiser
    • 1
    Email author
  1. 1.Institute of Information TechnologyJahangirnagar UniversitySavar, DhakaBangladesh
  2. 2.Computing and Technology, School of Science and TechnologyNottingham Trent UniversityNottinghamUK

Personalised recommendations