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• W4310398382 abstract "<sec> <title>BACKGROUND</title> The proliferation of mobile devices is altering how we interact with and understand the world. Nowadays, it's not uncommon for smartphones and tablets to have facial recognition software, and wireless biosensors can assess factors like a person's alertness, focus, or even meditation. With these enhanced capacities, developers now have the chance to make a wide variety of emotional-intelligence apps [1]. Children with Autism Spectrum Disorder (ASD) are a population that would benefit significantly from emotion-aware apps, whereas smartphones and tablets can identify their facial expressions, and wireless biosensors can assess their degrees of alertness, focus, and relaxation. [1]. Autism spectrum disorder (ASD) is a term used to describe a group of symptoms that include difficulties with social communication and repetitive sensory-motor behaviors that manifest at an early age and have both a significant genetic component and other factors [2]. Autistic Disorder, Asperger's Disorder, and Atypical Autism are the three primary subtypes of ASD. People with Asperger's Disorder and Atypical Autism share similar symptoms, and they are both considered mild versions of the autistic spectrum [3]. Despite cultural, racial, ethnic, and socioeconomic differences, children with ASD share essential traits in two areas: social communication and confined, repetitive sensory-motor behaviors [2]. In addition, a variety of symptoms, including cognitive, behavioral, emotional, and sensory problems, are reported. Sleeping deprivation and eating disorders, synesthesia, emotional instability, and challenges with initiating, thinking, and organizing are frequently observed in people with autism [4]. Hyperactivity and attention deficits (such as attention-deficit/hyperactivity disorder (ADHD)), anxiety, depression, and seizures are quite common co-occurring mental or neurological illnesses among people with autism, along with these core symptoms [2]. On a global scale, ASD affects roughly one in every hundred children [5]. ASD has a masculine preponderance of more than four to one occurrence worldwide [6]. As many as 47% of children diagnosed with ASD in 2005 also suffered from another diagnosis; attention deficit or hyperactivity constituted the most common (30%) [7]. 83% of children with ASD at age eight had a co-occurring developmental diagnosis, 16% a co-occurring neurologic condition, and 10% a co-occurring psychiatric diagnosis [8]. Since co-occurring conditions/symptoms often lead to a greater level of impairment, and increased demand for services, especially medications and emergency room visits for accidents, the quality of life of children with ASD and their families is negatively impacted [9]. In this paper, we conduct a systematic review to examine the available studies on the use of mobile applications to aid children with ASD in identifying and expressing their emotions. This study aims to assess the state of emotion recognition mobile apps for children with ASD and to identify existing tools, promising developments, and unmet needs in the field. </sec> <sec> <title>OBJECTIVE</title> This systematic review aims to explore the mobile application in helping children with ASD to identify and express their feeling. </sec> <sec> <title>METHODS</title> The 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 author displays the results using a narrative synthesis. </sec> <sec> <title>RESULTS</title> From the electronic databases, we retrieved 659 articles. After removing the duplicate research, 593 articles remained. A total of 537 studies were discarded after an initial screening of titles and abstracts, whereas 306 studies were excluded because of irrelevancy, 70 studies were removed due to measuring different outcomes, 45 articles were eliminated due to using irrelevant intervention, 35 articles were rejected because were book chapters, 33 studies were excluded because they conduct their studies in a different population, 28 articles were rejected because were reviews, 16 studies were removed because they don’t have participants, 2 articles were excluded because we don’t have access, one study was removed because it was written in a foreign language, and one study was rejected because it was abstract only. </sec> <sec> <title>CONCLUSIONS</title> This systematic review seeks to shed light on the most 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 youngsters by assisting them in expressing their emotions and enhancing their ability to recognize emotions. However, it is currently deemed important to assess the effectiveness of mobile applications for remediation through more rigorous methodological research that include large samples, control groups and placebo, prolonged treatment durations, and follow-up to see whether improvements are sustainable. </sec> <sec> <title>CLINICALTRIAL</title> systematic review </sec>" @default.
• W4310398382 created "2022-12-10" @default.
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• W4310398382 date "2022-11-24" @default.
• W4310398382 modified "2023-09-27" @default.
• W4310398382 title "Mobile Application to identify and recognize emotions for children with autism in research and practice. (Preprint)" @default.
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• W4310398382 doi "https://doi.org/10.2196/preprints.44563" @default.
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