Skip to main content

Assessment System for Imitative Ability for Children with Autism Spectrum Disorder Based on Human Pose Estimation

  • Conference paper
  • First Online:
Intelligent Robotics and Applications (ICIRA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13455))

Included in the following conference series:

  • 2503 Accesses

Abstract

Autism spectrum disorders is a range of neurodevelopmental conditions primarily characterized by difficulties in social interactions, differences in communication, and presentations of rigid and repetitive behavior. The evidence shows that the functional social behavior of children with autism can be enhanced by early intervention. However, traditional intervention methods meet problems, e.g., assessment results are varied from one clinician to another while sometimes children are lack of interest in intervention. To address these problems, we design a computer-aided motion imitation assessment system based on human pose estimation in this paper. The system is implemented by Unity3D. We recruit 10 people (5 people with imitation ability defect and 5 people without imitation ability defect) participated in the experiment, and the result shows that the system can effectively evaluate the motion imitation ability. Finally, three future development directions of the system are further discussed for better application in autistic early intervention.

Supported by Peng Cheng Laboratory.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bailey, A., et al.: A clinicopathological study of autism. Brain J. Neurol. 121(5), 889–905 (1998)

    Google Scholar 

  2. Chauhan, A., et al.: Prevalence of autism spectrum disorder in Indian children: a systematic review and meta-analysis. Neurol. India 67(1), 100 (2019)

    Article  Google Scholar 

  3. Chen, H., Feng, R., Wu, S., Xu, H., Zhou, F., Liu, Z.: 2D human pose estimation: a survey, April 2022

    Google Scholar 

  4. Choe, M., Yoo, J., Lee, G., Baek, W., Kang, U., Shin, K.: Deep learning-based human pose estimation: a survey (2 2022)

    Google Scholar 

  5. Fang, H.S., Xie, S., Tai, Y.W., Lu, C.: RMPE: regional multi-person pose estimation, November 2016

    Google Scholar 

  6. He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 770–778 (2016)

    Google Scholar 

  7. Jaliaawala, M.S., Khan, R.A.: Can autism be catered with artificial intelligence-assisted intervention technology? A comprehensive survey. Artif. Intell. Rev. 53(2), 1039–1069 (2020)

    Article  Google Scholar 

  8. Liu, J., et al.: Early screening of autism in toddlers via response-to-instructions protocol. IEEE Trans. Cybern. 1–11 (9 2020)

    Google Scholar 

  9. Liu, X., Wu, Q., Zhao, W., Luo, X.: Technology-facilitated diagnosis and treatment of individuals with autism spectrum disorder: an engineering perspective. Appl. Sci. 7(10), 1051 (2017)

    Article  Google Scholar 

  10. Pavllo, D., Feichtenhofer, C., Grangier, D., Auli, M.: 3D human pose estimation in video with temporal convolutions and semi-supervised training. In: CVPR, November 2019

    Google Scholar 

  11. Qin, H., et al.: Vision-based pointing estimation and evaluation in toddlers for autism screening. In: Liu, X.-J., Nie, Z., Yu, J., Xie, F., Song, R. (eds.) ICIRA 2021. LNCS (LNAI), vol. 13015, pp. 177–185. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-89134-3_17

    Chapter  Google Scholar 

  12. Scassellati, B., Admoni, H., Matarić, M.: Robots for use in autism research. Annu. Rev. Biomed. Eng. 14, 275–294 (2012)

    Article  Google Scholar 

  13. Stone, W.L., Ousley, O.Y., Littleford, C.D.: Motor imitation in young children with autism: what’s the object? J. Abnorm. Child Psychol. 25(6), 475–485 (1997)

    Article  Google Scholar 

  14. Sun, K., Xiao, B., Liu, D., Wang, J.: Deep high-resolution representation learning for human pose estimation (2019)

    Google Scholar 

  15. Wang, Z., Liu, J., He, K., Xu, Q., Xu, X., Liu, H.: Screening early children with autism spectrum disorder via response-to-name protocol. IEEE Trans. Industr. Inform. 17, 587–595 (2021)

    Google Scholar 

  16. Zheng, C., Zhu, S., Mendieta, M., Yang, T., Chen, C., Ding, Z.: 3D human pose estimation with spatial and temporal transformers. In: IEEE/CVF International Conference on Computer Vision, pp. 11656–11665 (2021)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Honghai Liu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ma, H. et al. (2022). Assessment System for Imitative Ability for Children with Autism Spectrum Disorder Based on Human Pose Estimation. In: Liu, H., et al. Intelligent Robotics and Applications. ICIRA 2022. Lecture Notes in Computer Science(), vol 13455. Springer, Cham. https://doi.org/10.1007/978-3-031-13844-7_35

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-13844-7_35

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-13843-0

  • Online ISBN: 978-3-031-13844-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics