Screening Tools for Early Autism Detection using Voice and Gesture Analysis - Farrukh, Riffat; Ashraf, Ahmad Bilal; Kumar, Akash; Shamraz, Hinza; Mushtaq, Asma; Mushtaq, Laiba (Indus Journal of Bioscience Research, 2025)
Background: For maximizing outcomes of treatment, timely and precise condition analysis, and screening, are necessary. For example, using ASD Screening combines clinical and observational assessments. The objective of the study assessed the aim of Voice Automated Technology, and an objective multi- modality detection tool integrates gesture to analyze the phenomena of children. Methods: Eighty-two young children referred for developmental evaluation were included in this observational study and were separated into two groups, ASD (n=41) and non-ASD (n=41), according to the Modified Checklist for Autism in Toddlers (M-CHAT). Samples of the participants' voices were examined to measure dimensions of atypicality (total fundamental frequency, jitter, speech rate), while the processed, structured video recordings were analyzed with motion-tracking software to measure the frequencies of gesture expression, duration of mutual visual attention, and eye fixation, thus resulting in an overall score for gesture atypicality. Sensitivity, specificity, accuracy, and area under the curve (AUC) were employed in examining both the separate and the combined models. Results: Variations between the ASD and non-ASD populations were apparent regarding all parameters in the other acoustic and gesture parameters combined. The Combined Voice + Gesture Model achieved significantly higher performance (p