Open AccessObjective Measurement of Hyperactivity Using Mobile Sensing and Machine Learning: Pilot Study
Author(s) -
Oliver Lindhiem,
Mayank Goel,
Sam Shaaban,
Kristie Mak,
Prerna Chikersal,
Jamie Feldman,
Jordan L. Harris
Publication year - 2022
Publication title -
jmir formative research
Language(s) - English
Resource type - Journals
ISSN - 2561-326X
DOI - 10.2196/35803
Subject(s) - attention deficit hyperactivity disorder , smartwatch , wearable computer , presentation (obstetrics) , usability , motion sensors , smartphone application , artificial intelligence , machine learning , psychology , computer science , medicine , audiology , human–computer interaction , multimedia , clinical psychology , embedded system , radiology
Background Although hyperactivity is a core symptom of attention-deficit/hyperactivity disorder (ADHD), there are no objective measures that are widely used in clinical settings. Objective We describe the development of a smartwatch app to measure hyperactivity in school-age children. The LemurDx prototype is a software system for smartwatches that uses wearable sensor technology and machine learning to measure hyperactivity. The goal is to differentiate children with ADHD combined presentation (a combination of inattentive and hyperactive/impulsive presentations) or predominantly hyperactive/impulsive presentation from children with typical levels of activity. Methods In this pilot study, we recruited 30 children, aged 6 to 11 years, to wear a smartwatch with the LemurDx app for 2 days. Parents also provided activity labels for 30-minute intervals to help train the algorithm. Half of the participants had ADHD combined presentation or predominantly hyperactive/impulsive presentation (n=15), and half were in the healthy control group (n=15). Results The results indicated high usability scores and an overall diagnostic accuracy of 0.89 (sensitivity=0.93; specificity=0.86) when the motion sensor output was paired with the activity labels. Conclusions State-of-the-art sensors and machine learning may provide a promising avenue for the objective measurement of hyperactivity.