Digital Attention-Related Augmented-Reality Game: Significant Correlation between Student Game Performance and Validated Clinical Measures of Attention-Deficit/Hyperactivity Disorder (ADHD)

Feasibility and Usability of an Artificial Intelligence-Powered Gamification Intervention for Enhancing Physical Activity Among College Students: Quasi-Experimental Study

Background

Physical activity (PA) is vital for physical and mental health, but many college students fail to meet recommended levels. Artificial intelligence (AI)-powered gamification interventions through mobile app have the potential to improve PA levels among Chinese college students.

Objective

This study aimed to assess the feasibility and usability of an AI-powered gamification intervention.

Methods

A quasi-experimental study spanning 2 months was conducted on a sample of college students aged 18 to 25 years old from 18 universities in Beijing. PA data were recorded using the ShouTi Fitness app, and participant engagement was evaluated through surveys. User satisfaction was gauged through the System Usability Scale, while the intervention's feasibility was assessed through Spearman rank correlation analysis, Mann-Whitney tests, and additional descriptive analyses.

Results

As of July 2023, we enrolled 456 college students. In total, 18,073 PA sessions were recorded, with men completing 8068 sessions and women completing 10,055 sessions. The average PA intensity was 7 metabolic equivalent of energy (MET)s per session. Most participants preferred afternoon sessions and favored short-duration sessions, with men averaging 66 seconds per session and women 42 seconds. The System Usability Scale score for the intervention based on app is 65.2. Users responded positively to the integration of AI and gamification elements, including personalized recommendations, action recognition, smart grouping, dynamic management, collaborative, and competition. Specifically, 341 users (75%) found the AI features very interesting, 365 (80%) were motivated by the gamification elements, 364 (80%) reported that the intervention supported their fitness goals, and 365 (80%) considered the intervention reliable. A significant positive correlation was observed between the duration of individual PA and intervention duration for men (ρ=0.510, P<.001), although the correlation was weaker for women (ρ=0.258, P=.046). However, the frequency of PA declined after 35 days.

Conclusions

This study provides pioneering evidence of the feasibility and usability of the AI-powered gamification intervention. While adherence was successfully demonstrated, further studies or interventions are needed to directly assess the impact on PA levels and focus on optimizing long-term adherence strategies and evaluating health outcomes.

Integrating AI and Assistive Technologies in Healthcare: Insights from a Narrative Review of Reviews

The integration of artificial intelligence (AI) into assistive technologies is an emerging field with transformative potential, aimed at enhancing autonomy and quality of life for individuals with disabilities and aging populations. This overview of reviews, utilizing a standardized checklist and quality control procedures, examines recent advancements and future implications in this domain. The search for articles for the review was finalized by 15 December 2024. Nineteen review studies were selected through a systematic process identifying prevailing themes, opportunities, challenges, and recommendations regarding the integration of AI in assistive technologies. First, AI is increasingly central to improving mobility, healthcare diagnostics, and cognitive support, enabling personalized and adaptive solutions for users. The integration of AI into traditional assistive technologies, such as smart wheelchairs and exoskeletons, enhances their performance, creating more intuitive and responsive devices. Additionally, AI is improving the inclusion of children with autism spectrum disorders, promoting social interaction and cognitive development through innovative devices. The review also identifies significant opportunities and challenges. AI-powered assistive technologies offer enormous potential to increase independence, reduce reliance on external support, and improve communication for individuals with cognitive disorders. However, challenges such as personalization, digital literacy among the elderly, and privacy concerns in healthcare contexts need to be addressed. Notably, AI itself is expanding the concept of assistive technology, shifting from traditional tools to intelligent systems capable of learning and adapting to individual needs. This evolution represents a fundamental change in assistive technology, emphasizing dynamic, adaptive systems over static solutions. Finally, the study emphasizes the growing economic investment in this sector, forecasting significant market growth, with AI-driven assistive devices poised to transform the landscape. Despite challenges such as high development costs and regulatory hurdles, opportunities for innovation and affordability remain. This review underscores the importance of addressing challenges related to standardization, accessibility, and ethical considerations to ensure the successful integration of AI into assistive technologies, fostering greater inclusivity and improved quality of life for users globally.

Automated Detection of Neurodevelopmental Disorders Using Face-to-Face Mobile Technology Among Typically Developing Greek Children: Randomized Controlled Trial

BACKGROUND

Neurodevelopmental disorders (NDs) are characterized by heterogeneity, complexity, and interactions among multiple domains with long-lasting effects in adulthood. Early and accurate identification of children at risk for NDs is crucial for timely intervention, yet many cases remain undiagnosed, leading to missed opportunities for effective interventions. Digital tools can help clinicians assist and identify NDs. The concept of using serious games to enhance health care has gained attention among a growing group of scientists, entrepreneurs, and clinicians.

OBJECTIVE

This study aims to explore the core principles of automated mobile detection of NDs in typically developing Greek children, using a serious game developed within the SmartSpeech project, designed to evaluate multiple developmental domains through principal component analysis (PCA).

METHODS

A total of 229 typically developing children aged 4 to 12 years participated in the study. The recruitment process involved open calls through public and private health and educational institutions across Greece. Parents were thoroughly informed about the study's objectives and procedures, and written consent was obtained. Children engaged under the clinician's face-to-face supervision with the serious game "Apsou," which assesses 18 developmental domains, including speech, language, psychomotor, cognitive, psychoemotional, and hearing abilities. Data from the children's interactions were analyzed using PCA to identify key components and underlying principles of ND detection.

RESULTS

A sample of 229 typically developing preschoolers and early school-aged children played the Apsou mobile serious game for automated detection of NDs. Performing a PCA, the findings identified 5 main components accounting for about 80% of the data variability that potentially have significant prognostic implications for a safe diagnosis of NDs. Varimax rotation explained 61.44% of the total variance. The results underscore key theoretical principles crucial for the automated detection of NDs. These principles encompass communication skills, speech and language development, vocal processing, cognitive skills and sensory functions, and visual-spatial skills. These components align with the theoretical principles of child development and provide a robust framework for automated ND detection.

CONCLUSIONS

The study highlights the feasibility and effectiveness of using serious games for early ND detection in children. The identified principal components offer valuable insights into critical developmental domains, paving the way for the development of advanced machine learning applications to support highly accurate predictions and classifications for automated screening, diagnosis, prognosis, or intervention planning in ND clinical decision-making. Future research should focus on validating these findings across diverse populations integrating additional features such as biometric data and longitudinal tracking to enhance the accuracy and reliability of automated detection systems.

TRIAL REGISTRATION

ClinicalTrials.gov NCT06633874; https://clinicaltrials.gov/study/NCT06633874.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-https://doi.org/10.3390/signals4020021.

The Role of AI in Serious Games and Gamification for Health: Scoping Review

BACKGROUND

Artificial intelligence (AI) and game-based methods such as serious games or gamification are both emerging technologies and methodologies in health care. The merging of the two could provide greater advantages, particularly in the field of therapeutic interventions in medicine.

OBJECTIVE

This scoping review sought to generate an overview of the currently existing literature on the connection of AI and game-based approaches in health care. The primary objectives were to cluster studies by disease and health topic addressed, level of care, and AI or games technology.

METHODS

For this scoping review, the databases PubMed, Scopus, IEEE Xplore, Cochrane Library, and PubPsych were comprehensively searched on February 2, 2022. Two independent authors conducted the screening process using Rayyan software (Rayyan Systems Inc). Only original studies published in English since 1992 were eligible for inclusion. The studies had to involve aspects of therapy or education in medicine and the use of AI in combination with game-based approaches. Each publication was coded for basic characteristics, including the population, intervention, comparison, and outcomes (PICO) criteria; the level of evidence; the disease and health issue; the level of care; the game variant; the AI technology; and the function type. Inductive coding was used to identify the patterns, themes, and categories in the data. Individual codings were analyzed and summarized narratively.

RESULTS

A total of 16 papers met all inclusion criteria. Most of the studies (10/16, 63%) were conducted in disease rehabilitation, tackling motion impairment (eg, after stroke or trauma). Another cluster of studies (3/16, 19%) was found in the detection and rehabilitation of cognitive impairment. Machine learning was the main AI technology applied and serious games the main game-based approach used. However, direct interaction between the technologies occurred only in 3 (19%) of the 16 studies. The included studies all show very limited quality evidence. From the patients' and healthy individuals' perspective, generally high usability, motivation, and satisfaction were found.

CONCLUSIONS

The review shows limited quality of evidence for the combination of AI and games in health care. Most of the included studies were nonrandomized pilot studies with few participants (14/16, 88%). This leads to a high risk for a range of biases and limits overall conclusions. However, the first results present a broad scope of possible applications, especially in motion and cognitive impairment, as well as positive perceptions by patients. In future, the development of adaptive game designs with direct interaction between AI and games seems promising and should be a topic for future reviews.

Breaking Barriers-The Intersection of AI and Assistive Technology in Autism Care: A Narrative Review

(Background) Autism increasingly requires a multidisciplinary approach that can effectively harmonize the realms of diagnosis and therapy, tailoring both to the individual. Assistive technologies (ATs) play an important role in this context and hold significant potential when integrated with artificial intelligence (AI). (Objective) The objective of this study is to analyze the state of integration of AI with ATs in autism through a review. (Methods) A review was conducted on PubMed and Scopus, applying a standard checklist and a qualification process. The outcome reported 22 studies, including 7 reviews. (Key Content and Findings) The results reveal an early yet promising interest in integrating AI into autism assistive technologies. Exciting developments are currently underway at the intersection of AI and robotics, as well as in the creation of wearable automated devices like smart glasses. These innovations offer substantial potential for enhancing communication, interaction, and social engagement for individuals with autism. Presently, researchers are prioritizing innovation over establishing a solid presence within the healthcare domain, where issues such as regulation and acceptance demand increased attention. (Conclusions) As the field continues to evolve, it becomes increasingly clear that AI will play a pivotal role in bridging various domains, and integrated ATs with AI are positioned to act as crucial connectors.

Remote Assessment of ADHD Symptoms Based on Mobile Game Performance in Children with ADHD: A Proof of Concept

The use of game-based digital medicine is gaining increasing interest in helping children with ADHD to improve their attention outside the clinical setting. In this process, it is important to continue monitoring children's responses to the use of digital medicine. In this work, we introduce novel digital markers and an analytic pipeline to estimate ADHD-related symptomatic levels during the self-administration of attention games. The digital markers, capturing the children's characteristics of attention and inattention spans, were extracted and translated into clinically-accepted measures of ADHD symptoms, specifically the ADHD-Rating Scale (ADHD-RS) and Child Behavior Checklist (CBCL). To validate the feasibility of our approach, we collected game-specific performance data from 15 children with ADHD, which was used to train machine learning-based regression models to estimate their corresponding ADHD-RS and CBCL scores. Our experiment results showed mean absolute errors of 5.14 and 4.05 points between the actual and estimated ADHD-RS and CBCL scores respectively. This study enables new clinical and research opportunities for accurate longitudinal assessment of symptomatic levels of ADHD via an interactive means of playing mobile games.

Evaluating attention deficit hyperactivity disorder symptoms in children and adolescents through tracked head movements in a virtual reality classroom: The effect of social cues with different sensory modalities

Background

Attention deficit hyperactivity disorder (ADHD) is clinically diagnosed; however, quantitative analysis to statistically analyze the symptom severity of children with ADHD via the measurement of head movement is still in progress. Studies focusing on the cues that may influence the attention of children with ADHD in classroom settings, where children spend a considerable amount of time, are relatively scarce. Virtual reality allows real-life simulation of classroom environments and thus provides an opportunity to test a range of theories in a naturalistic and controlled manner. The objective of this study was to investigate the correlation between participants’ head movements and their reports of inattention and hyperactivity, and to investigate how their head movements are affected by different social cues of different sensory modalities.

Methods

Thirty-seven children and adolescents with (n = 20) and without (n = 17) ADHD were recruited for this study. All participants were assessed for diagnoses, clinical symptoms, and self-reported symptoms. A virtual reality-continuous performance test (VR-CPT) was conducted under four conditions: (1) control, (2) no-cue, (3) visual cue, and (4) visual/audio cue. A quantitativecomparison of the participants’ head movements was conducted in three dimensions (pitch [head nods], yaw [head turns], and roll [lateral head inclinations]) using a head-mounted display (HMD) in a VR classroom environment. Task-irrelevant head movements were analyzed separately, considering the dimension of movement needed to perform the VR-CPT.

Results

The magnitude of head movement, especially task-irrelevant head movement, significantly correlated with the current standard of clinical assessment in the ADHD group. Regarding the four conditions, head movement showed changes according to the complexity of social cues in both the ADHD and healthy control (HC) groups.

Conclusion

Children and adolescents with ADHD showed decreasing task-irrelevant movements in the presence of social stimuli toward the intended orientation. As a proof-of-concept study, this study preliminarily identifies the potential of VR as a tool to understand and investigate the classroom behavior of children with ADHD in a controlled, systematic manner.

The Utilization of Augmented Reality Technology for Sustainable Skill Development for People with Special Needs: A Systematic Literature Review

New technologies such as Augmented Reality can be used to enhance the possibility of obtaining new experiences to assist people with special needs. However, in the literature, there are not enough studies conducted on the use of Augmented Reality as an assistive technology, especially for people with special needs. The purpose of this study is to highlight the use of Augmented Reality technology on people with special needs for skill development. This systematic literature review includes recent and high-quality articles from chosen prestige databases between the years 2010 and 2020. The selected studies which fitted the eligibility selection criteria have been analyzed and synthesized. The study findings reveal the importance of using AR technology to assist individuals with special needs in their skill development process, to help them become more independent. We hope this study will enlighten researchers and the developers of AR tools. It has been recommended that more studies be done on the sustainable use of AR as an assistive technology, particularly for children with special needs, to make their life easier.

Mobile Augmented Reality Technologies for Autism Spectrum Disorder Interventions: A Systematic Literature Review

Over the past decade, enhanced computing capabilities and mobile technologies have begotten the upsurge of innovative mobile health (mHealth) solutions, and many research efforts have occurred recently in the area of technology-based interventions (TBI) for autism spectrum disorders (ASD). Mobile augmented reality (MAR) refers to AR systems that use the handheld mobile device medium (mobile phones, tablets or smart glasses). This article reports the results of a systematic review undertaken on the use of MAR for ASD-related skills learning from the year 2010. It aims to provide an insight into the current state of research on MAR interventions and to provide guidance to relevant designers and researchers. We searched seven databases and retrieved 625 articles initially. After exclusion and screening, 36 articles were reviewed reporting on using MAR to improve various skills of children and adolescents with ASD, and 10 research questions related to PICO (P: Population, I: Intervention, C: Comparison, O: Outcomes) were addressed. This study identifies challenges that still exist in the research efforts towards the development of applications exploiting the MAR for ASD interventions: technology issues, research design consideration, subjective assessment etc. The studies examined suggest researchers should focus on users and improve the quality of the MAR app. In addition, more effective research methods and evaluation methods could be involved in future studies to facilitate the development of MAR intervention applications.

Effectiveness of Virtual Reality-Based Interventions for Children and Adolescents with ADHD: A Systematic Review and Meta-Analysis

This review aims to evaluate the effectiveness of virtual reality-based interventions (VR-based interventions) on cognitive deficits in children with attention deficit hyperactivity disorder (ADHD). A systematic review and meta-analysis were performed according to the PRISMA statement and the Cochrane Handbook guidelines for conducting meta-analyses. The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) was used to assess the quality of the evidence. Clinical trials published up to 29 October 2020, were included. The meta-analysis included four studies, with a population of 125 participants with ADHD. The magnitude of the effect was large for omissions (SMD = −1.38; p = 0.009), correct hits (SMD = −1.50; p = 0.004), and perceptual sensitivity (SMD = −1.07; p = 0.01); and moderate for commissions (SMD = −0.62; p = 0.002) and reaction time (SMD = −0.67; p = 0.03). The use of VR-based interventions for cognitive rehabilitation in children with ADHD is limited. The results showed that VR-based interventions are more effective in improving sustained attention. Improvements were observed in attentional vigilance measures, increasing the number of correct responses and decreasing the number of errors of omission. No improvements were observed in impulsivity responses.

Self-Regulation in Children with Neurodevelopmental Disorders "SR-MRehab: Un Colegio Emocionante": A Protocol Study

Self-regulation refers to the ability to control and modulate behavior, and it can include both emotional and cognitive modulation. Children with neurodevelopmental disorders may show difficulties in self-regulation. The main objective of this study is to improve self-regulation skills in children between 6 and 11 years of age with neurodevelopmental disorders. Methodology: A randomized controlled trial will be conducted with the use of “SR-MRehab: Un colegio emocionante”, based on a non-immersive virtual reality system where virtual objects can be managed by children in a natural way using their hands. Children will be recruited from several schools of Granada (Spain) and they will be randomly allocated to two groups. An assessment will be conducted before and after the intervention and 24 weeks after the end of the intervention process. The experimental group will receive the intervention using virtual reality. The control group will receive a standard self-regulation program. Both interventions will be performed once a week for a total of 10 sessions. Changes in self-regulation, as well as the acceptability of technology with the use of SR-MRehab, will be evaluated. The results will be published and will provide evidence regarding the use of this type of intervention in children with neurodevelopmental disorders. Trial registration: Registered with code NCT04418921.