Features of Mobile Apps for People with Autism in a Post COVID-19 Scenario: Current Status and Recommendations for Apps Using AI

Ikram Ur Rehman; Drishty Sobnath; Moustafa M. Nasralla; Maria Winnett; Aamir Anwar; Waqar Asif; Hafiz Husnain Raza Sherazi

doi:10.3390/diagnostics11101923

Diagnostics (Oct 2021)

Features of Mobile Apps for People with Autism in a Post COVID-19 Scenario: Current Status and Recommendations for Apps Using AI

Ikram Ur Rehman,
Drishty Sobnath,
Moustafa M. Nasralla,
Maria Winnett,
Aamir Anwar,
Waqar Asif,
Hafiz Husnain Raza Sherazi

Affiliations

Ikram Ur Rehman: School of Computing and Engineering, University of West London, London W5 5RF, UK
Drishty Sobnath: Faculty of Business, Law and Digital Technologies, Solent University, Southampton SO14 0YN, UK
Moustafa M. Nasralla: Department of Communications and Networks Engineering, Prince Sultan University, Riyadh 11586, Saudi Arabia
Maria Winnett: School of Computing and Engineering, University of West London, London W5 5RF, UK
Aamir Anwar: School of Computing and Engineering, University of West London, London W5 5RF, UK
Waqar Asif: School of Computing and Engineering, University of West London, London W5 5RF, UK
Hafiz Husnain Raza Sherazi: School of Computing and Engineering, University of West London, London W5 5RF, UK

DOI: https://doi.org/10.3390/diagnostics11101923
Journal volume & issue: Vol. 11, no. 10
p. 1923

Abstract

Read online

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.

Published in Diagnostics

ISSN: 2075-4418 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Medicine: Medicine (General)
Website: http://www.mdpi.com/journal/diagnostics

About the journal

Abstract

Keywords