An Adaptive Multi-Robot Therapy for Improving Joint Attention and Imitation of ASD Children

Abstract

Robot-mediated therapies for autism spectrum disorder (ASD) have shown promising results in the past. We have proposed a novel mathematical model based on an adaptive multi-robot therapy of ASD children focusing on two main impairments in autism: 1) joint attention and 2) imitation. Joint attention intervention is based on three different least-to-most (LTM) cues, whereas the adaptive imitation module uses joint attention for activation of the robot. The proposed model uses a multi-robot system as a therapist without any external stimuli (from the environment) to improve the skills of the ASD child. Another novel aspect of this paper is the deployment of a multi-robot system for introducing the ASD child to the concept of multi-person communication. This is particularly useful as, unlike humans, robots can be more consistent and relatively immune to fatigue. Two different therapies of human–robot interaction (i.e., with and without inter-robot communication) have been conducted. The model has been tested on 12 ASD children, eight sessions for each intervention over a period of six months. The effectiveness of the model is validated by analyzing the cognitive state of the brain before and after the intervention with electroencephalogram (EEG) neuroheadsets. Moreover, results obtained using the childhood autism rating scale (CARS) to measure the effectiveness of therapy also support the conclusions firmly. The statistical results with the p-value = 3.79E-07 3.28 show reliability and significance of the data. The results strongly indicate significant improvements in both modules, along with a notable improvement in multi-communication skills of the participating children.