Features of Mobile Apps for People with Autism in a Post COVID-19 Scenario: Current Status and Recommendations for Apps Using AI.
Ikram Ur RehmanDrishty D SobnathMoustafa M NasrallaMaria WinnettAamir AnwarWaqar AsifHafiz Husnain Raza SheraziPublished in: Diagnostics (Basel, Switzerland) (2021)
The new 'normal' defined during the COVID-19 pandemic has forced us to re-assess how people with special needs thrive in these unprecedented conditions, such as those with Autism Spectrum Disorder (ASD). These changing/challenging conditions have instigated us to revisit the usage of telehealth services to improve the quality of life for people with ASD. This study aims to identify mobile applications that suit the needs of such individuals. This work focuses on identifying features of a number of highly-rated mobile applications (apps) that are designed to assist people with ASD, specifically those features that use Artificial Intelligence (AI) technologies. In this study, 250 mobile apps have been retrieved using keywords such as autism, autism AI, and autistic. Among 250 apps, 46 were identified after filtering out irrelevant apps based on defined elimination criteria such as ASD common users, medical staff, and non-medically trained people interacting with people with ASD. In order to review common functionalities and features, 25 apps were downloaded and analysed based on eye tracking, facial expression analysis, use of 3D cartoons, haptic feedback, engaging interface, text-to-speech, use of Applied Behaviour Analysis therapy, Augmentative and Alternative Communication techniques, among others were also deconstructed. As a result, software developers and healthcare professionals can consider the identified features in designing future support tools for autistic people. This study hypothesises that by studying these current features, further recommendations of how existing applications for ASD people could be enhanced using AI for (1) progress tracking, (2) personalised content delivery, (3) automated reasoning, (4) image recognition, and (5) Natural Language Processing (NLP). This paper follows the PRISMA methodology, which involves a set of recommendations for reporting systematic reviews and meta-analyses.
Keyphrases
- autism spectrum disorder
- artificial intelligence
- intellectual disability
- attention deficit hyperactivity disorder
- deep learning
- machine learning
- meta analyses
- healthcare
- systematic review
- coronavirus disease
- sars cov
- stem cells
- randomized controlled trial
- big data
- clinical practice
- high throughput
- smoking cessation
- cell therapy
- genome wide identification
- transcription factor
- soft tissue
- health insurance
- respiratory syndrome coronavirus