Mobile Application to identify and recognize emotions for children with autism: A systematic review

Abstract

IntroductionEmotions are a vital component of human interaction. Children with Autism Spectrum Disorder (ASD) face severe difficulties in sensing and interpreting the emotions of others, as well as responding emotionally appropriately. Developers are producing many mobile applications to assist ASD children in improving their facial expression detection and reaction abilities and increasing their independence.ObjectiveThis systematic review aims to explore the mobile application in helping children with ASD to identify and express their feeling.MethodsThe inclusion and exclusion articles for our analysis were mapped using the PRISMA Preferred Reporting Items for Systematic Reviews and Meta-Analysis diagram. The studies were retrieved from the following four databases: Google Scholar, Scopus, Association for Computing Machinery (ACM), and Institute of Electrical and Electronics Engineers (IEEE). Additionally, two screening processes were used to determine relevant literature. Reading the title and abstract was the initial step, followed by reading the complete content. Finally, the authors display the results using a narrative synthesis.ResultsFrom four electronic databases, we retrieved 659 articles. six studies that met our inclusion criteria were included in the systematic review. More details about inclusion and exclusion criteria can be found in the Eligibility criteria.ConclusionThis systematic review sheds light on current research that employed mobile applications to improve emotion detection and expression in children with ASD. This smartphone application has the potential to empower autistic children by assisting them in expressing their emotions and enhancing their ability to recognize emotions. However, it is currently deemed essential to assess the effectiveness of mobile applications for remediation through more rigorous methodological research. For example, most included studies were quantitative and focused on statical measurements. However, there is an immediate need for more incredible research in this area to include qualitative research and to consider large samples, control groups and placebo, prolonged treatment durations, and follow-up to see whether improvements are sustainable and to ensure the effectiveness of applications.