Integrating Artificial Intelligence, Internet of Things, and Sensor-Based Technologies: A Systematic Review of Methodologies in Autism Spectrum Disorder Detection (2025)

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

Authors: Georgios Bouchouras, Konstantinos Kotis

Citation: Georgios Bouchouras, Konstantinos Kotis (2025), Integrating Artificial Intelligence, Internet of Things, and Sensor-Based Technologies: A Systematic Review of Methodologies in Autism Spectrum Disorder Detection, semantic_scholar. Type: Determine after review

Abstract

This paper presents a systematic review of the emerging applications of artificial intelligence (AI), Internet of Things (IoT), and sensor-based technologies in the diagnosis of autism spectrum disorder (ASD). The integration of these technologies has led to promising advances in identifying unique …

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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?