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While standardized assessments exist, identifying subtle communication deficits, especially during multimodal interactions, remains time-consuming and prone to human error. To address this, we propose an automated behavior analysis framework that aims to support clinicians by accurately detecting both verbal and non-verbal communication markers. Specifically, we put forth a composite artificial intelligence framework that integrates various deep learning algorithms to analyze information from body and hand poses, object detection, tracking and manipulation, and speech. By combining these features with a rule-based system, we can identify events within the Autism Diagnostic Observation Schedule second edition, Construction Task, where participants initiate requests. These requests can be verbal, non-verbal or a combination of both resulting in multimodal interactions. Building on our prior work, this paper introduces a smart glass technology component, integrating gaze and blinking analysis, which are challenging for clinicians to monitor, given the multi-task nature of their role. These additions enable the detection of eye contact, a crucial social cue. Our approach allows us to recognize gestures, identify hand object manipulations, detect eye contact, and understand the natural language in clinician-participant interactions. We achieve 94% and 73% <jats:italic>F<\/jats:italic>-1 score, on verbal and non-verbal request detection, respectively, which may improve, as deep learning advances.<\/jats:p>","DOI":"10.1007\/s12559-025-10481-7","type":"journal-article","created":{"date-parts":[[2025,8,14]],"date-time":"2025-08-14T08:12:10Z","timestamp":1755159130000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Multimodal Framework for Automatic Behavior Analysis of Children with Autism During ADOS-2"],"prefix":"10.1007","volume":"17","author":[{"given":"Bruno Carlos","family":"Dos Santos Mel\u00edcio","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaan","family":"Karak\u00f6se","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"\u00c1d\u00e1m","family":"Fodor","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linyun","family":"Xiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Viktor","family":"Varga","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Latha","family":"Soorya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emily","family":"Dillon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"P\u00e9ter","family":"Kun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andr\u00e1s","family":"S\u00e1rk\u00e1ny","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohamed","family":"Chetouani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kristian","family":"Fenech","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andr\u00e1s","family":"L\u0151rincz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,8,14]]},"reference":[{"key":"10481_CR1","doi-asserted-by":"crossref","unstructured":"Maenner MJ, Warren Z, Williams AR, al et. 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