A systematic review on the application of machine learning models in psychometric questionnaires for the diagnosis of attention deficit hyperactivity disorder.

Attention deficit hyperactivity disorder is one of the most prevalent neurodevelopmental disorders worldwide. Recent studies show that machine learning has great potential for the diagnosis of attention deficit hyperactivity disorder. The aim of the present article is to systematically review the scientific literature on machine learning studies for the diagnosis of attention deficit hyperactivity disorder, focusing on psychometric questionnaire tools. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines were adopted. The review protocol was registered in the PROSPERO database. A search was conducted in three databases-Web of Science Core Collection, Scopus and Pubmed-with the aim of identifying studies that apply ML techniques to support the diagnosis of attention deficit hyperactivity disorder. A total of 17 empirical studies were found that met the established inclusion criteria. The results showed that machine learning can be used to increase the accuracy of attention deficit hyperactivity disorder diagnosis. Machine learning techniques are useful and effective strategies that can complement traditional diagnostics in patients with attention deficit hyperactivity disorder.

Effectiveness of a Serious Video Game (MOON) for Attention Deficit Hyperactivity Disorder: Protocol for a Randomized Clinical Trial.

BACKGROUND: Attention deficit hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder in childhood and adolescence, with a prevalence of 5% and associated difficulties and worse prognosis if undetected. Multimodal treatment is the treatment of choice. However, sometimes treatment can be insufficient or have drawbacks. OBJECTIVE: This study protocol aims to demonstrate the effectiveness of cognitive training through the serious video game The Secret Trail of Moon (MOON) in improving emotional regulation in people with ADHD. METHODS: This is a prospective, unicenter, randomized, unblinded, pre- and postintervention study. The groups will be randomized (MOON vs control) via an electronic case report form. The MOON intervention will be performed 2 times per week for 10 weeks (30 minutes per session). The first 5 weeks (10 sessions) will be conducted face-to-face at the Puerta de Hierro University Hospital, and the remaining weeks will be conducted via the internet at the participants' homes. The total sample consists of 152 patients aged between 7 and 18 years. All participants have a clinical diagnosis of ADHD under pharmacological treatment. Data collection will be used to obtain demographic and clinical data. The data will be recorded using REDCap. Measures will be made through clinical scales for parents and objective tests of cognitive functioning in patients. Additional information on academic performance will be collected. The study has a power greater than 80% to detect differences. Student t test, 2-factor analysis of variance (ANOVA), and Mann-Whitney analyses will be performed according to each variable's characteristics. RESULTS: The study was approved by the Research Ethics Committee of the Puerta de Hierro University Hospital on December 14, 2022. As of September 26, 2023, we have enrolled 62 participants, and 31 participants have completed the study. This clinical trial was funded by the Comunidad de Madrid (IND2020/BMD-17544). The approximate completion date is March 2024. CONCLUSIONS: Serious video games such as MOON can be motivational tools that complement multimodal treatment for ADHD. TRIAL REGISTRATION: ClinicalTrials.gov; NCT06006871; https://clinicaltrials.gov/study/NCT06006871. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/53191.

Assessment of ADHD Subtypes Using Motion Tracking Recognition Based on Stroop Color-Word Tests.

Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder known for its significant heterogeneity and varied symptom presentation. Describing the different subtypes as predominantly inattentive (ADHD-I), combined (ADHD-C), and hyperactive-impulsive (ADHD-H) relies primarily on clinical observations, which can be subjective. To address the need for more objective diagnostic methods, this pilot study implemented a Microsoft Kinect-based Stroop Color-Word Test (KSWCT) with the objective of investigating the potential differences in executive function and motor control between different subtypes in a group of children and adolescents with ADHD. A series of linear mixture modeling were used to encompass the performance accuracy, reaction times, and extraneous movements during the tests. Our findings suggested that age plays a critical role, and older subjects showed improvements in KSWCT performance; however, no significant divergence in activity level between the subtypes (ADHD-I and ADHD-H/C) was established. Patients with ADHD-H/C showed tendencies toward deficits in motor planning and executive control, exhibited by shorter reaction times for incorrect responses and more difficulty suppressing erroneous responses. This study provides preliminary evidence of unique executive characteristics among ADHD subtypes, advances our understanding of the heterogeneity of the disorder, and lays the foundation for the development of refined and objective diagnostic tools for ADHD.

Adherence, frequency, and long-term follow-up of video game-based treatments in patients with attention-deficit/hyperactivity disorder: A systematic review.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children and adolescents. Recent studies show that video games have great potential for the treatment and rehabilitation of ADHD patients. The aim of the present review is to systematically review the scientific literature on the relationship between video games and ADHD, focusing on adherence to treatment, frequency of the intervention, and the long-term follow-up of video games in children and adolescents with ADHD. METHODS: The preferred reporting items for systematic reviews and meta-analyses guidelines were adopted. The review protocol was registered in PROSPERO database. We searched in three databases, PubMed, Medline, and Web of Science to identify studies examining the association between video game interventions in ADHD patients. RESULTS: A total of 18 empirical studies met the established inclusion criteria. The results showed that video games-based interventions can be used to improve ADHD symptoms and display high adherence to treatment. In addition, in the studies reviewed, the most common intervention frequency is 30 min three to five times per week. However, there is little evidence from studies with video games showing long-term effects in patients with ADHD. CONCLUSION: Video games are useful and effective interventions that can complement traditional treatments in patients with ADHD.

Attention and impulsivity assessment using virtual reality games.

The assessment of cognitive functions is mainly based on standardized neuropsychological tests, widely used in various fields such as personnel recruitment, education, or health. This paper presents a virtual reality game that allows collecting continuous measurements of both the performance and behaviour of the subject in an immersive, controllable, and naturalistic experience. The application registers variables related to the user's eye movements through the use of virtual reality goggles, as well as variables of the game performance. We study how virtual reality can provide data to help predict scores on the Attention Control Scale Test and the Barratt Impulsiveness Scale. We design the application and test it with a pilot group. We build a random forest regressor model to predict the attention and impulsivity scales' total score. When evaluating the performance of the model, we obtain a positive correlation with attention (0.434) and with impulsivity (0.382). In addition, our model identified that the most significant variables are the time spent looking at the target or at distractors, the eye movements variability, the number of blinks and the pupil dilation in both attention and impulsivity. Our results are consistent with previous results in the literature showing that it is possible to use data collected in virtual reality to predict the degree of attention and impulsivity.

Simulation of X-ray projections on GPU: Benchmarking gVirtualXray with clinically realistic phantoms.

BACKGROUND AND OBJECTIVES: This study provides a quantitative comparison of images created using gVirtualXray (gVXR) to both Monte Carlo (MC) and real images of clinically realistic phantoms. gVirtualXray is an open-source framework that relies on the Beer-Lambert law to simulate X-ray images in realtime on a graphics processor unit (GPU) using triangular meshes. METHODS: Images are generated with gVirtualXray and compared with a corresponding ground truth image of an anthropomorphic phantom: (i) an X-ray projection generated using a Monte Carlo simulation code, (ii) real digitally reconstructed radiographs (DRRs), (iii) computed tomography (CT) slices, and (iv) a real radiograph acquired with a clinical X-ray imaging system. When real images are involved, the simulations are used in an image registration framework so that the two images are aligned. RESULTS: The mean absolute percentage error (MAPE) between the images simulated with gVirtualXray and MC is 3.12%, the zero-mean normalised cross-correlation (ZNCC) is 99.96% and the structural similarity index (SSIM) is 0.99. The run-time is 10 days for MC and 23 ms with gVirtualXray. Images simulated using surface models segmented from a CT scan of the Lungman chest phantom were similar to (i) DRRs computed from the CT volume and (ii) an actual digital radiograph. CT slices reconstructed from images simulated with gVirtualXray were comparable to the corresponding slices of the original CT volume. CONCLUSIONS: When scattering can be ignored, accurate images that would take days using MC can be generated in milliseconds with gVirtualXray. This speed of execution enables the use of repetitive simulations with varying parameters, e.g. to generate training data for a deep-learning algorithm, and to minimise the objective function of an optimisation problem in image registration. The use of surface models enables the combination of X-ray simulation with real-time soft-tissue deformation and character animation, which can be deployed in virtual reality applications.

Developing Serious Video Games to Treat Attention Deficit Hyperactivity Disorder: Tutorial Guide.

Video game-based therapeutic interventions have demonstrated some effectiveness in decreasing the symptoms of attention deficit hyperactivity disorder (ADHD). Compared with more traditional strategies within the multimodal treatment of ADHD, video games have certain advantages such as being comfortable, flexible, and cost-efficient. However, establishing the most appropriate type(s) of video games that should be used for this treatment remains a matter of debate, including the commercial existing video games or serious video games that are specifically constructed to target specific disorders. This guide represents a starting point for developing serious video games aimed at treating ADHD. We summarize the key points that need to be addressed to generate an effective and motivating game-based treatment. Following recommendations from the literature to create game-based treatments, we describe the development stages of a serious video game for treating ADHD. Game design should consider the interests of future users; game mechanics should be based on cognitive exercises; and therapeutic mechanisms must include the control of difficulty, engagement, motivation, time constraints, and reinforcement. To elaborate upon this guide, we performed a narrative review focused on the use of video games for the treatment of ADHD, and were inspired by our own experience during the development of the game "The Secret Trail of Moon."

Attention Deficit Hyperactivity Disorder Assessment Based on Patient Behavior Exhibited in a Car Video Game: A Pilot Study.

Symptoms of Attention Deficit Hyperactivity Disorder (ADHD) include excessive activity, difficulty sustaining attention, and inability to act in a reflective manner. Early diagnosis and treatment of ADHD is key but may be influenced by the observation and communication skills of caregivers, and the experience of the medical professional. Attempts to obtain additional measures to support the medical diagnosis, such as reaction time when performing a task, can be found in the literature. We propose an information recording system that allows to study in detail the behavior shown by children already diagnosed with ADHD during a car driving video game. We continuously record the participants' activity throughout the task and calculate the error committed. Studying the trajectory graphs, some children showed uniform patterns, others lost attention from one point onwards, and others alternated attention/inattention intervals. Results show a dependence between the age of the children and their performance. Moreover, by analyzing the positions by age over time using clustering, we show that it is possible to classify children according to their performance. Future studies will examine whether this detailed information about each child's performance pattern can be used to fine-tune treatment.

Automatic Personality Assessment through Movement Analysis.

Obtaining accurate and objective assessments of an individual's personality is vital in many areas including education, medicine, sports and management. Currently, most personality assessments are conducted using scales and questionnaires. Unfortunately, it has been observed that both scales and questionnaires present various drawbacks. Their limitations include the lack of veracity in the answers, limitations in the number of times they can be administered, or cultural biases. To solve these problems, several articles have been published in recent years proposing the use of movements that participants make during their evaluation as personality predictors. In this work, a multiple linear regression model was developed to assess the examinee's personality based on their movements. Movements were captured with the low-cost Microsoft Kinect camera, which facilitates its acceptance and implementation. To evaluate the performance of the proposed system, a pilot study was conducted aimed at assessing the personality traits defined by the Big-Five Personality Model. It was observed that the traits that best fit the model are Extroversion and Conscientiousness. In addition, several patterns that characterize the five personality traits were identified. These results show that it is feasible to assess an individual's personality through his or her movements and open up pathways for several research.

Interactive teaching environment for diagnostic radiography with real-time X-ray simulation and patient positioning.

PURPOSE: Traditional undergraduate radiographer training mixes academic lectures and clinical practice. Our goal is to bridge the current disconnection between theory and practice in a safe environment, avoiding the risk of radiation for both practitioners and patients. To this end, this research proposes a new software to teach diagnostic radiography using real-time interactive X-ray simulation and patient positioning. METHODS: The proposed medical simulator is composed of three main modules. A fast and accurate character animation technique is in charge of simulating the patient positioning phase and adapts their internal anatomy accordingly. gVirtualXRay is an open-source X-ray simulation library and generates the corresponding radiographs in real time. Finally, the courseware allows going through all the diagnostic radiology steps from the patient positioning and the machine configuration to the final image enhancing. RESULTS: A face and content validation study has been conducted; 18 radiology professionals were recruited to evaluate our software using a questionnaire. The results show that our tool is realistic in many ways (72% of the participants agreed that the simulations are visually realistic), useful (67%) and suitable (78%) for teaching X-ray radiography. CONCLUSIONS: The proposed tool allows simulating the most relevant steps of the projectional radiography procedure. The virtual patient posing system and X-ray simulation module execute at interactive rates. These features enable the lectures to show their students the results of good and bad practices in a classroom environment, avoiding radiation risk.

Objective Assessment of Attention-Deficit Hyperactivity Disorder (ADHD) Using an Infinite Runner-Based Computer Game: A Pilot Study.

In the last few years, several computerized tasks have been developed to increase the objectivity of the diagnosis of attention-deficit hyperactivity disorder (ADHD). This article proposes the "running raccoon" video game to assess the severity of inattention in patients diagnosed with ADHD. Unlike existing tests, the proposed tool is a genuine video game in which the patient must make a raccoon avatar jump to avoid falling into different gaps. The distance to the gap is recorded for each jump. To evaluate the proposed game, an experiment was conducted in which 32 children diagnosed with ADHD participated. For each participant, the median and interquartile range of these distances were calculated, along with the number of omissions. Experimental results showed a significant correlation between the participants' inattention (measured by the Attention-Deficit/Hyperactivity Disorder Symptoms and Normal Behavior rating scale (SWAN) inattention subscale) with each of these three measures. In addition to its accuracy, other benefits are its short duration and the possibility of being run on both standard computers and mobile devices. These characteristics facilitate its acceptance in clinical environments or even its telematic use. The obtained results, together with the characteristics of the video game, make it an excellent tool to support clinicians in the diagnosis of ADHD.