ASD children adaption behaviour assessment via hand movement properties: a RoadMap

Dinghuang Zhang; Carrie Miriam Toptan; Shuwen Zhao; Gongyue Zhang; Honghai Liu

doi:10.1007/978-3-030-87094-2_42

ASD children adaption behaviour assessment via hand movement properties: a RoadMap

Dinghuang Zhang, Carrie Miriam Toptan, Shuwen Zhao, Gongyue Zhang, Honghai Liu

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Adaptive behavioural assessments are useful in the diagnosis of autism. This research proposes a strategy of assessing autistic children’s adaption skills through the change of hand behaviour complexity based on deep learning and complex systems. Specifically, we implement a sparse representation of high-dimensional features of hand movements utilize convolutional neural network (CNN) and Bag of Word model (BoW) and explain in detail how two quantify measurements (complexity and diversity) reflect adaption behavioural capacity. This paper introduces our ongoing projects and demonstrates the preliminary experimental setups and motion protocol design. Future work includes improving the interaction scenarios, establishing a data set, and enhancing the interpretability of the results of the adaption behaviour skill measurements.

Original language	English
Title of host publication	Advances in Computational Intelligence Systems
Subtitle of host publication	Contributions Presented at the 20th UK Workshop on Computational Intelligence, September 8-10, 2021, Aberystwyth, Wales, UK
Editors	Thomas Jansen, Richard Jensen, Neil Mac Parthaláin, Chih-Min Lin
Publisher	Springer
Pages	475–480
Number of pages	6
Volume	1409
ISBN (Electronic)	9783030870942
DOIs	https://doi.org/10.1007/978-3-030-87094-2_42
Publication status	Published - 18 Nov 2021

Publication series

Name	Advances in Intelligent Systems and Computing
Publisher	Springer
Volume	1409
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Keywords

ASD diagnose
Adaption skill assessment
CNN
Computer vision

Access to Document

10.1007/978-3-030-87094-2_42

Cite this

Zhang, D., Toptan, C. M., Zhao, S., Zhang, G., & Liu, H. (2021). ASD children adaption behaviour assessment via hand movement properties: a RoadMap. In T. Jansen, R. Jensen, N. M. Parthaláin, & C.-M. Lin (Eds.), Advances in Computational Intelligence Systems: Contributions Presented at the 20th UK Workshop on Computational Intelligence, September 8-10, 2021, Aberystwyth, Wales, UK (Vol. 1409 , pp. 475–480). (Advances in Intelligent Systems and Computing; Vol. 1409). Springer. https://doi.org/10.1007/978-3-030-87094-2_42

Zhang, Dinghuang ; Toptan, Carrie Miriam ; Zhao, Shuwen et al. / ASD children adaption behaviour assessment via hand movement properties: a RoadMap. Advances in Computational Intelligence Systems: Contributions Presented at the 20th UK Workshop on Computational Intelligence, September 8-10, 2021, Aberystwyth, Wales, UK. editor / Thomas Jansen ; Richard Jensen ; Neil Mac Parthaláin ; Chih-Min Lin. Vol. 1409 Springer, 2021. pp. 475–480 (Advances in Intelligent Systems and Computing).

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title = "ASD children adaption behaviour assessment via hand movement properties: a RoadMap",

abstract = "Adaptive behavioural assessments are useful in the diagnosis of autism. This research proposes a strategy of assessing autistic children{\textquoteright}s adaption skills through the change of hand behaviour complexity based on deep learning and complex systems. Specifically, we implement a sparse representation of high-dimensional features of hand movements utilize convolutional neural network (CNN) and Bag of Word model (BoW) and explain in detail how two quantify measurements (complexity and diversity) reflect adaption behavioural capacity. This paper introduces our ongoing projects and demonstrates the preliminary experimental setups and motion protocol design. Future work includes improving the interaction scenarios, establishing a data set, and enhancing the interpretability of the results of the adaption behaviour skill measurements.",

keywords = "ASD diagnose, Adaption skill assessment, CNN, Computer vision",

author = "Dinghuang Zhang and Toptan, {Carrie Miriam} and Shuwen Zhao and Gongyue Zhang and Honghai Liu",

year = "2021",

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doi = "10.1007/978-3-030-87094-2_42",

language = "English",

volume = "1409 ",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer",

pages = "475–480",

editor = "Thomas Jansen and Richard Jensen and Parthal{\'a}in, {Neil Mac} and Chih-Min Lin",

booktitle = "Advances in Computational Intelligence Systems",

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Zhang, D, Toptan, CM, Zhao, S, Zhang, G & Liu, H 2021, ASD children adaption behaviour assessment via hand movement properties: a RoadMap. in T Jansen, R Jensen, NM Parthaláin & C-M Lin (eds), Advances in Computational Intelligence Systems: Contributions Presented at the 20th UK Workshop on Computational Intelligence, September 8-10, 2021, Aberystwyth, Wales, UK. vol. 1409 , Advances in Intelligent Systems and Computing, vol. 1409, Springer, pp. 475–480. https://doi.org/10.1007/978-3-030-87094-2_42

ASD children adaption behaviour assessment via hand movement properties: a RoadMap. / Zhang, Dinghuang; Toptan, Carrie Miriam; Zhao, Shuwen et al.
Advances in Computational Intelligence Systems: Contributions Presented at the 20th UK Workshop on Computational Intelligence, September 8-10, 2021, Aberystwyth, Wales, UK. ed. / Thomas Jansen; Richard Jensen; Neil Mac Parthaláin; Chih-Min Lin. Vol. 1409 Springer, 2021. p. 475–480 (Advances in Intelligent Systems and Computing; Vol. 1409).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - Adaptive behavioural assessments are useful in the diagnosis of autism. This research proposes a strategy of assessing autistic children’s adaption skills through the change of hand behaviour complexity based on deep learning and complex systems. Specifically, we implement a sparse representation of high-dimensional features of hand movements utilize convolutional neural network (CNN) and Bag of Word model (BoW) and explain in detail how two quantify measurements (complexity and diversity) reflect adaption behavioural capacity. This paper introduces our ongoing projects and demonstrates the preliminary experimental setups and motion protocol design. Future work includes improving the interaction scenarios, establishing a data set, and enhancing the interpretability of the results of the adaption behaviour skill measurements.

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Zhang D, Toptan CM, Zhao S, Zhang G, Liu H. ASD children adaption behaviour assessment via hand movement properties: a RoadMap. In Jansen T, Jensen R, Parthaláin NM, Lin CM, editors, Advances in Computational Intelligence Systems: Contributions Presented at the 20th UK Workshop on Computational Intelligence, September 8-10, 2021, Aberystwyth, Wales, UK. Vol. 1409 . Springer. 2021. p. 475–480. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-87094-2_42

ASD children adaption behaviour assessment via hand movement properties: a RoadMap

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