Analyzing Social Communication Deficits in Autism Using Wearable Sensors and Real-Time Affective Computing Systems (2025)

Status: pending Scraped: 2026-08-12 Source: semantic_scholar Relevance: Direct

Authors: Paul Okugo Imoh, Joy Onma Enyejo

Citation: Paul Okugo Imoh, Joy Onma Enyejo (2025), Analyzing Social Communication Deficits in Autism Using Wearable Sensors and Real-Time Affective Computing Systems, semantic_scholar. Type: Determine after review

Abstract

Social communication deficits are a hallmark characteristic of Autism Spectrum Disorder (ASD), often manifesting as challenges in interpreting and expressing emotions, maintaining eye contact, and engaging in reciprocal interactions. Traditional diagnostic and intervention methods, while valuable, c…

Key Contribution

Review and expand.

Design

Review and expand.

Key Results

Review and expand.

Impact

Review and expand.

Linked To

Add cross-references after review.

Data Quality Assessment

Field	Assessment
Subject selection	How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
Data acquisition	How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar, dedicated sensor), sampling rate, placement, firmware version.
Acquisition context	From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based? Naturalistic or controlled?
Gold standard labels	How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation, chart review? Inter-rater reliability reported?
Data validation	How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, manual inspection, automated QC pipeline?
Missingness	n=X subjects — do all have complete data? Missing at random, missing completely at random, or missing not at random? Is missingness correlated with outcome?