Abstract:
Strange Situation Procedure (SSP) is commonly used to assess the patterns of attachment behaviours by observing and categorising child's reactions to a series of separations and reunions, clarifying them into specific attachment categories. However, conducting SSP requires the dedication of trained professionals to administer the procedures of assessment, demanding expertise in attachment theory with proficiency in coding and analysing collected data. This study aims to use machine learning models to automatically analyse the patterns of attachment behaviours, utilising audio-visual features extracted from SSP videos.
About the speaker:
Zeijan Feng is a visiting PhD student from Behavioural-AI Lab, School of Computing Science, University of Glasgow. His research interest is primarily focusing on utilising machine learning models to detect neurodevelopmental disorders through the integration of visual and audio data modalities.
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