Towards Explainable Abnormal Infant Movements Identification: A Body-part Based Prediction and Visualisation Framework

Kevin McCay, Edmond S. L. Ho*, Dimitrios Sakkos, Wai Lok Woo, Claire Marcroft, Patricia Dulson, Nicholas D. Embleton

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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Abstract

Providing early diagnosis of cerebral palsy (CP) is key to enhancing the developmental outcomes for those affected. Diagnostic tools such as the General Movements Assessment (GMA), have produced promising results in early diagnosis, however these manual methods can be laborious.

In this paper, we propose a new framework for the automated classification of infant body movements, based upon the GMA, which unlike previous methods, also incorporates a visualization framework to aid with interpretability. Our proposed framework segments extracted features to detect the presence of Fidgety Movements (FMs) associated with the GMA spatiotemporally. These features are then used to identify the body-parts with the greatest contribution towards a classification decision and highlight the related body-part segment providing visual feedback to the user.

We quantitatively compare the proposed framework's classification performance with several other methods from the literature and qualitatively evaluate the visualization's veracity. Our experimental results show that the proposed method performs more robustly than comparable techniques in this setting whilst simultaneously providing relevant visual interpretability.
Original languageEnglish
Title of host publication2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)
Place of PublicationPiscataway
PublisherIEEE
Number of pages4
ISBN (Electronic)9781665447706
ISBN (Print)9781665403580
DOIs
Publication statusPublished - 27 Jul 2021
EventIEEE International Conference on Biomedical and Health Informatics (BHI) : Reshaping healthcare through advanced AI-enabled health informatics for a better quality of life - Virtual
Duration: 27 Jul 202130 Jul 2021
https://www.bhi-bsn-2021.org/?page_id=2336

Publication series

NameIEEE EMBS International Conference on Biomedical and Health Informatics
PublisherIEEE
ISSN (Print)2641-3590
ISSN (Electronic)2641-3604

Conference

ConferenceIEEE International Conference on Biomedical and Health Informatics (BHI)
Abbreviated titleIEEE BHI 2021
Period27/07/2130/07/21
Internet address

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