Behavioral and Autonomic Responses in Treating Children with High-Functioning Autism Spectrum Disorder: Clinical and Phenomenological Insights from Two Case Reports

A Scoping Review of Research Evaluating Physiological Information for Individuals With Developmental Disabilities: Augmentative and Alternative Communication Research Considerations

PURPOSE

Today, an ever-increasing number of technological advancements are becoming mainstream. As the availability of technological innovations increases, so do opportunities for evaluating any benefits of those innovations in augmentative and alternative communication (AAC) research for individuals with developmental disabilities. One innovation that has become mainstream is the use of noninvasive wearable technology to provide physiological information (e.g., heart rate, skin conductance). Such information could be valuable in AAC research, but more information about its potential feasibility and utility is needed.

METHOD

A scoping review was conducted to review and report on existing research that has evaluated (a) physiological information as a communication intervention tool for individuals with developmental disabilities and (b) the relationship between physiological information from individuals with developmental disabilities and behavioral and/or environmental information in real time.

RESULTS

Results revealed that, while little communication intervention research has been completed, descriptive research demonstrates that physiological information from individuals with developmental disabilities gathered using wearable technology corresponds meaningfully to observable environmental and behavioral events.

CONCLUSIONS

Future AAC research incorporating wearable technology to gather physiological information is warranted. Such research could evaluate potential benefits such as preempting challenging behavior with communication opportunities, signaling readiness for language learning, indicating AAC feature preferences, and expanding methodological approaches.

Towards Robot-Assisted Therapy for Children With Autism—The Ontological Knowledge Models and Reinforcement Learning-Based Algorithms

Robots are more and more present in our lives, particularly in the health sector. In therapeutic centers, some therapists are beginning to explore various tools like video games, Internet exchanges, and robot-assisted therapy. These tools will be at the disposal of these professionals as additional resources that can support them to assist their patients intuitively and remotely. The humanoid robot can capture young children’s attention and then attract the attention of researchers. It can be considered as a play partner and can directly interact with children or without a third party’s presence. It can equally perform repetitive tasks that humans cannot achieve in the same way. Moreover, humanoid robots can assist a therapist by allowing him to teleoperated and interact from a distance. In this context, our research focuses on robot-assisted therapy and introduces a humanoid social robot in a pediatric hospital care unit. That will be performed by analyzing many aspects of the child’s behavior, such as verbal interactions, gestures and facial expressions, etc. Consequently, the robot can reproduce consistent experiences and actions for children with communication capacity restrictions. This work is done by applying a novel approach based on deep learning and reinforcement learning algorithms supported by an ontological knowledge base that contains relevant information and knowledge about patients, screening tests, and therapies. In this study, we realized a humanoid robot that will assist a therapist by equipping the robot NAO: 1) to detect whether a child is autistic or not using a convolutional neural network, 2) to recommend a set of therapies based on a selection algorithm using a correspondence matrix between screening test and therapies, and 2) to assist and monitor autistic children by executing tasks that require those therapies.

The Challenging Heterogeneity of Autism: Editorial for Brain Sciences Special Issue "Advances in Autism Research"

My personal experience as Guest Editor of the Special Issue (SI) entitled "Advances in Autism Research" began with a nice correspondence with Andrew Meltzoff, from the University of Washington, Seattle (WA, USA), which, in hindsight, I consider as a good omen for the success of this Special Issue: "Dear Antonio… [...].