Prakash, VG and Kohli, M and Prathosh, AP and Juneja, M and Gupta, M and Sairam, S and Sitaraman, S and Bangalore, AS and Kommu, JVS and Saini, L and Utage, PR and Goyal, N (2023) Video-based real-time assessment and diagnosis of autism spectrum disorder using deep neural networks. In: Expert Systems .
Full text not available from this repository. (Request a copy)Abstract
Human action recognition (HAR) in untrimmed videos can make insightful predictions of human behaviour. Previous work on HAR-included models trained on spatial and temporal annotations and could classify limited actions from trimmed videos. These methods reported limitations such as (1) performance degradation due to the lack of precision temporal regions proposal and (2) poor adaptability of the models in the clinical domain because of unrelated actions of interest. We propose an innovative method that could analyse untrimmed behavioural videos to recommend actions of interest leading to diagnostic and functional assessments for children with Autism Spectrum Disorder (ASD). Our method entails end-to-end behaviour action recognition (BAR) pipeline, including child detection, temporal action localization, and actions of interest identification and classification. The model trained on the data of 400 ASD children and 125 with other developmental delays (ODD) accurately identified ASD, ODD, and Neurotypical children with 79.7, 77.2, and 80.8 accuracy, respectively. The model's performance on an independent benchmark Self-Stimulatory Behaviour Dataset (SSBD) reported top-1 accuracy of 78.57 for combined localization with action recognition, significantly higher than the earlier reported outcomes. © 2023 John Wiley & Sons Ltd.
| Item Type: | Journal Article |
|---|---|
| Publication: | Expert Systems |
| Publisher: | John Wiley and Sons Inc |
| Additional Information: | The copyright for this article belongs to John Wiley and Sons Inc. |
| Keywords: | Behavioral research; Benchmarking; Diseases, Action recognition; Autism; Autism spectrum disorders; Developmental delay; Human behaviors; Human-action recognition; Localisation; Real-time assessment; Real-time diagnosis; Temporal action localization, Deep neural networks |
| Department/Centre: | Division of Electrical Sciences > Electrical Communication Engineering |
| Date Deposited: | 25 Apr 2023 06:37 |
| Last Modified: | 25 Apr 2023 06:37 |
| URI: | https://eprints.iisc.ac.in/id/eprint/81269 |
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