Automated and scalable Computerized Assessment of Motor Imitation (CAMI) in children with Autism Spectrum Disorder using a single 2D camera: A pilot study

Abstract

BackgroundMotor imitation difficulties are pervasive in children with Autism Spectrum Disorder (ASD). Previous research demonstrated the validity and reliability of an algorithm called Computerized Assessment of Motor Imitation (CAMI) using 3D depth cameras. However, incorporating CAMI into serious games and making it accessible in clinic and home settings requires a more scalable approach that uses “off-the-shelf” 2D cameras. MethodIn a brief (one-minute) task, children (23 ASD, 17 typically developing [TD]) imitated a model’s dance movements while simultaneously being recorded using Kinect Xbox motion tracking technology (Kinect 3D) and a single 2D camera. Pose-estimation software (OpenPose 2D) was used on the 2D camera video to fit a skeleton to the imitating child. Motor imitation scores computed from the fully automated OpenPose 2D CAMI method were compared to scores computed from the Kinect 3D CAMI and Human Observation Coding (HOC) methods. ResultsMotor imitation scores obtained from the OpenPose 2D CAMI method were significantly correlated with scores obtained from the Kinect 3D CAMI method (r40 = 0.82, p < 0.001) and the HOC method (r40 = 0.80, p < 0.001). Both 2D and 3D CAMI methods showed better discriminative ability than the HOC, with the Kinect 3D CAMI method outperforming the OpenPose 2D CAMI method (area under ROC curve (AUC): AUCHOC = 0.799, AUC2D-CAMI = 0.876, AUC3D-CAMI = 0.94). Finally, all motor imitation scores were significantly associated with the social-communication impairment (all p ≤ 0.003). ConclusionsThis pilot-study demonstrated that motor imitation can be automatically quantified using a single 2D camera.