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Using Wearable Technology to Predict the Occurrence of Severe Behavior Problems among Neurodiverse Individuals: A
Patrick W Romani1,2,3, Sidney K D'Mello4, Robert M Moulder4
1Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO USA.
Perspectives on Behavior Science
|June 5, 2026
Summary
Wearable sensors and AI may help predict severe behavior problems (SBPs) in individuals with neurodevelopmental disabilities (NDD). However, current research shows methodological concerns, limiting the accuracy of these early predictions.
Area of Science:
- Behavioral science
- Biomedical engineering
- Artificial intelligence
Background:
- Severe behavior problems (SBPs) in individuals with neurodevelopmental disabilities (NDD) pose significant risks.
- Effective behavioral analysis methods exist, but high-risk situations persist.
- Advances in wearable sensing and AI offer new avenues for support.
Purpose of the Study:
- To systematically review studies examining the predictive relationship between biometrics and SBPs.
- To identify commonalities, differences, and limitations in current research.
- To propose future research directions.
Main Methods:
- Systematic literature review of 13 peer-reviewed articles.
- Analysis of studies investigating physiological and behavioral signals (biometrics) for SBP prediction.
- Evaluation of methodological rigor and claims of predictive accuracy.
Main Results:
- Some studies claim to predict SBPs over 30 seconds in advance.
- Methodological concerns were identified, reducing the confidence in these predictive claims.
- Biometric data shows potential but requires further validation.
Conclusions:
- Current research on biometric prediction of SBPs in NDD populations has limitations.
- Further research is needed to improve the accuracy and reliability of predictive models.
- Future studies should address methodological concerns to advance the field.
