Exploring Adaptive Virtual Reality Systems Used in Interventions for Children With Autism Spectrum Disorder: Systematic Review.

BACKGROUND: Adaptive systems serve to personalize interventions or training based on the user's needs and performance. The adaptation techniques rely on an underlying engine responsible for processing incoming data and generating tailored responses. Adaptive virtual reality (VR) systems have proven to be efficient in data monitoring and manipulation, as well as in their ability to transfer learning outcomes to the real world. In recent years, there has been significant interest in applying these systems to improve deficits associated with autism spectrum disorder (ASD). This is driven by the heterogeneity of symptoms among the population affected, highlighting the need for early customized interventions that target each individual's specific symptom configuration. OBJECTIVE: Recognizing these technology-driven therapeutic tools as efficient solutions, this systematic review aims to explore the application of adaptive VR systems in interventions for young individuals with ASD. METHODS: An extensive search was conducted across 3 different databases-PubMed Central, Scopus, and Web of Science-to identify relevant studies from approximately the past decade. Each author independently screened the included studies to assess the risk of bias. Studies satisfying the following inclusion criteria were selected: (1) the experimental tasks were delivered via a VR system, (2) system adaptation was automated, (3) the VR system was designed for intervention or training of ASD symptoms, (4) participants' ages ranged from 6 to 19 years, (5) the sample included at least 1 group with ASD, and (6) the adaptation strategy was thoroughly explained. Relevant information extracted from the studies included the sample size and mean age, the study's objectives, the skill trained, the implemented device, the adaptive strategy used, the engine techniques, and the signal used to adapt the systems. RESULTS: Overall, a total of 10 articles were included, involving 129 participants, 76% of whom had ASD. The studies included level switching (7/10, 70%), adaptive feedback strategies (9/10, 90%), and weighing the choice between a machine learning (ML) adaptive engine (3/10, 30%) and a non-ML adaptive engine (8/10, 80%). Adaptation signals ranged from explicit behavioral indicators (6/10, 60%), such as task performance, to implicit biosignals, such as motor movements, eye gaze, speech, and peripheral physiological responses (7/10, 70%). CONCLUSIONS: The findings reveal promising trends in the field, suggesting that automated VR systems leveraging real-time progression level switching and verbal feedback driven by non-ML techniques using explicit or, better yet, implicit signal processing have the potential to enhance interventions for young individuals with ASD. The limitations discussed mainly stem from the fact that no technological or automated tools were used to handle data, potentially introducing bias due to human error.

Virtual Experience Toolkit: An End-to-End Automated 3D Scene Virtualization Framework Implementing Computer Vision Techniques.

Virtualization plays a critical role in enriching the user experience in Virtual Reality (VR) by offering heightened realism, increased immersion, safer navigation, and newly achievable levels of interaction and personalization, specifically in indoor environments. Traditionally, the creation of virtual content has fallen under one of two broad categories: manual methods crafted by graphic designers, which are labor-intensive and sometimes lack precision; traditional Computer Vision (CV) and Deep Learning (DL) frameworks that frequently result in semi-automatic and complex solutions, lacking a unified framework for both 3D reconstruction and scene understanding, often missing a fully interactive representation of the objects and neglecting their appearance. To address these diverse challenges and limitations, we introduce the Virtual Experience Toolkit (VET), an automated and user-friendly framework that utilizes DL and advanced CV techniques to efficiently and accurately virtualize real-world indoor scenarios. The key features of VET are the use of ScanNotate, a retrieval and alignment tool that enhances the precision and efficiency of its precursor, supported by upgrades such as a preprocessing step to make it fully automatic and a preselection of a reduced list of CAD to speed up the process, and the implementation in a user-friendly and fully automatic Unity3D application that guides the users through the whole pipeline and concludes in a fully interactive and customizable 3D scene. The efficacy of VET is demonstrated using a diversified dataset of virtualized 3D indoor scenarios, supplementing the ScanNet dataset.

Hybrid brain/neural interface and autonomous vision-guided whole-arm exoskeleton control to perform activities of daily living (ADLs).

BACKGROUND: The aging of the population and the progressive increase of life expectancy in developed countries is leading to a high incidence of age-related cerebrovascular diseases, which affect people's motor and cognitive capabilities and might result in the loss of arm and hand functions. Such conditions have a detrimental impact on people's quality of life. Assistive robots have been developed to help people with motor or cognitive disabilities to perform activities of daily living (ADLs) independently. Most of the robotic systems for assisting on ADLs proposed in the state of the art are mainly external manipulators and exoskeletal devices. The main objective of this study is to compare the performance of an hybrid EEG/EOG interface to perform ADLs when the user is controlling an exoskeleton rather than using an external manipulator. METHODS: Ten impaired participants (5 males and 5 females, mean age 52 ± 16 years) were instructed to use both systems to perform a drinking task and a pouring task comprising multiple subtasks. For each device, two modes of operation were studied: synchronous mode (the user received a visual cue indicating the sub-tasks to be performed at each time) and asynchronous mode (the user started and finished each of the sub-tasks independently). Fluent control was assumed when the time for successful initializations ranged below 3 s and a reliable control in case it remained below 5 s. NASA-TLX questionnaire was used to evaluate the task workload. For the trials involving the use of the exoskeleton, a custom Likert-Scale questionnaire was used to evaluate the user's experience in terms of perceived comfort, safety, and reliability. RESULTS: All participants were able to control both systems fluently and reliably. However, results suggest better performances of the exoskeleton over the external manipulator (75% successful initializations remain below 3 s in case of the exoskeleton and bellow 5s in case of the external manipulator). CONCLUSIONS: Although the results of our study in terms of fluency and reliability of EEG control suggest better performances of the exoskeleton over the external manipulator, such results cannot be considered conclusive, due to the heterogeneity of the population under test and the relatively limited number of participants.

Effectiveness of a combined transcranial direct current stimulation and virtual reality-based intervention on upper limb function in chronic individuals post-stroke with persistent severe hemiparesis: a randomized controlled trial.

BACKGROUND: Functional impairments derived from the non-use of severely affected upper limb after stroke have been proposed to be mitigated by action observation and imagination-based techniques, whose effectiveness is enhanced when combined with transcranial direct current stimulation (tDCS). Preliminary studies in mildly impaired individuals in the acute phase post-stroke show intensified effects when action is facilitated by tDCS and mediated by virtual reality (VR) but the effectiveness in cases of severe impairment and chronic stroke is unknown. This study investigated the effectiveness of a combined tDCS and VR-based intervention in the sensorimotor function of chronic individuals post-stroke with persistent severe hemiparesis compared to conventional physical therapy. METHODS: Twenty-nine participants were randomized into an experimental group, who received 30 minutes of the combined tDCS and VR-based therapy and 30 minutes of conventional physical therapy, or a control group, who exclusively received conventional physical therapy focusing on passive and active assistive range of motion exercises. The sensorimotor function of all participants was assessed before and after 25 one-hour sessions, administered three to five times a week, using the upper extremity subscale of the Fugl-Meyer Assessment, the time and ability subscales of the Wolf Motor Function Test, and the Nottingham Sensory Assessment. RESULTS: A clinically meaningful improvement of the upper limb motor function was consistently revealed in all motor measures after the experimental intervention, but not after conventional physical therapy. Similar limited effects were detected in the sensory function in both groups. CONCLUSION: The combined tDCS and VR-based paradigm provided not only greater but also clinically meaningful improvement in the motor function (and similar sensory effects) in comparison to conventional physical therapy.

Emotion Recognition in Immersive Virtual Reality: From Statistics to Affective Computing.

Emotions play a critical role in our daily lives, so the understanding and recognition of emotional responses is crucial for human research. Affective computing research has mostly used non-immersive two-dimensional (2D) images or videos to elicit emotional states. However, immersive virtual reality, which allows researchers to simulate environments in controlled laboratory conditions with high levels of sense of presence and interactivity, is becoming more popular in emotion research. Moreover, its synergy with implicit measurements and machine-learning techniques has the potential to impact transversely in many research areas, opening new opportunities for the scientific community. This paper presents a systematic review of the emotion recognition research undertaken with physiological and behavioural measures using head-mounted displays as elicitation devices. The results highlight the evolution of the field, give a clear perspective using aggregated analysis, reveal the current open issues and provide guidelines for future research.

Development and Calibration of an Eye-Tracking Fixation Identification Algorithm for Immersive Virtual Reality.

Fixation identification is an essential task in the extraction of relevant information from gaze patterns; various algorithms are used in the identification process. However, the thresholds used in the algorithms greatly affect their sensitivity. Moreover, the application of these algorithm to eye-tracking technologies integrated into head-mounted displays, where the subject's head position is unrestricted, is still an open issue. Therefore, the adaptation of eye-tracking algorithms and their thresholds to immersive virtual reality frameworks needs to be validated. This study presents the development of a dispersion-threshold identification algorithm applied to data obtained from an eye-tracking system integrated into a head-mounted display. Rules-based criteria are proposed to calibrate the thresholds of the algorithm through different features, such as number of fixations and the percentage of points which belong to a fixation. The results show that distance-dispersion thresholds between 1-1.6° and time windows between 0.25-0.4 s are the acceptable range parameters, with 1° and 0.25 s being the optimum. The work presents a calibrated algorithm to be applied in future experiments with eye-tracking integrated into head-mounted displays and guidelines for calibrating fixation identification algorithms.

Gait analysis with the Kinect v2: normative study with healthy individuals and comprehensive study of its sensitivity, validity, and reliability in individuals with stroke.

BACKGROUND: Gait is usually assessed by clinical tests, which may have poor accuracy and be biased, or instrumented systems, which potentially solve these limitations at the cost of being time-consuming and expensive. The different versions of the Microsoft Kinect have enabled human motion tracking without using wearable sensors at a low-cost and with acceptable reliability. This study aims: First, to determine the sensitivity of an open-access Kinect v2-based gait analysis system to motor disability and aging; Second, to determine its concurrent validity with standardized clinical tests in individuals with stroke; Third, to quantify its inter and intra-rater reliability, standard error of measurement, minimal detectable change; And, finally, to investigate its ability to identify fall risk after stroke. METHODS: The most widely used spatiotemporal and kinematic gait parameters of 82 individuals post-stroke and 355 healthy subjects were estimated with the Kinect v2-based system. In addition, participants with stroke were assessed with the Dynamic Gait Index, the 1-min Walking Test, and the 10-m Walking Test. RESULTS: The system successfully characterized the performance of both groups. Significant concurrent validity with correlations of variable strength was detected between all clinical tests and gait measures. Excellent inter and intra-rater reliability was evidenced for almost all measures. Minimal detectable change was variable, with poorer results for kinematic parameters. Almost all gait parameters proved to identify fall risk. CONCLUSIONS: Results suggest that although its limited sensitivity to kinematic parameters, the Kinect v2-based gait analysis could be used as a low-cost alternative to laboratory-grade systems to complement gait assessment in clinical settings.

[Use of virtual reality for neurodevelopmental disorders. A review of the state of the art and future agenda]. / Uso de entornos virtuales para trastornos del neurodesarrollo: una revisión del estado del arte y agenda futura.

To date, the diagnostic tools for autism spectrum disorder (ASD) have been mostly based on qualitative criteria from observational information in contexts with low ecological validity. We are witnessing a growing scientific activity that proposes the use of implicit measures for the evaluation and diagnosis of ASD. These measures are based on processes of a biological and unconscious nature, underlying the capacity of human cognition, and are obtained through the acquisition and treatment of brain, physiological and behavioral responses in order to obtain the behavioral structure of the ASD patient facing a stimulus. The complex relationship between physiological responses and the behavioral structure of the ASD patient requires the use of advanced techniques of signal processing based on cognitive computation. Artificial intelligence (AI) techniques, such as machine learning and neurocomputing applied to the analysis of psychophysiological signals, have demonstrated their robustness for the classification of complex cognitive constructs. Virtual reality (VR) is a tool that allows recreating real-life situations with high sensory fidelity, but at the same time individually controlling each of the situations and stimuli that influence human behavior. It also allows the measurement in real time of human reactions to such stimuli. This document analyzes the latest scientific and technological advances relevant to its applications in the diagnosis of ASD. We conclude that VR is a very valuable tool for ASD research, especially for the evaluation and diagnosis of complex skills and competencies.

Hasta ahora las herramientas diagnósticas de los trastornos del espectro autista (TEA) se basan mayoritariamente en criterios cualitativos de información observacional en contextos con baja validez ecológica. Una creciente actividad científica propone medidas implícitas para la evaluación y diagnóstico del TEA. Dichas medidas se basan en procesos de carácter biológico e inconsciente, subyacentes a la capacidad de cognición humana y son obtenidas a través de la adquisición y tratamiento de respuestas cerebrales, fisiológicas y comportamentales, con el objetivo de obtener la estructura comportamental del paciente TEA ante un estímulo. La compleja relación existente entre respuestas fisiológicas y la estructura comportamental del paciente TEA ante un estímulo, obliga a utilizar técnicas avanzadas de tratamiento de la señal basadas en computación cognitiva. Las técnicas de inteligencia artificial, tales como aprendizaje automático (machine learning) y neurocomputación aplicadas al análisis de señales psicofisiológicas, han demostra do su robustez para la clasificación de complejos constructos cognitivos. La realidad virtual (RV) es una herramienta que permite recrear situaciones de la vida real con una alta fidelidad sensorial, pero al mismo tiempo controlar individualmente cada una de las situaciones y estímulos que influyen en el comportamiento humano. También permite la medición en tiempo real de las reacciones humanas ante tales estímulos. Este documento analiza los últimos avances científicos y tecnológicos relevantes para sus aplicaciones en el diagnóstico del TEA. Afirmamos que la RV es una herramienta muy valiosa para la investigación del TEA, especialmente para la evaluación y diagnóstico de habilidades y competencias complejas.

Time since injury limits but does not prevent improvement and maintenance of gains in balance in chronic stroke.

OBJECTIVE: To determine the influence of time since injury on the efficacy and maintenance of gains of rehabilitation of balance after stroke. METHOD: Forty-seven participants were assigned to a least (6-12 months), a moderate (12-24 months), or a most chronic (>24 months) group. Participants trained for 20 one-hour sessions, administered three to five times a week, combining conventional physical therapy and visual feedback-based exercises that trained the ankle and hip strategies. Participants were assessed before, after the intervention, and one month later with a posturography test (Sway Speed and Limits of Stability) and clinical scales. RESULTS: In contrast to other subjects, the most chronic participants failed to improve their sway and to maintain the benefits detected in the Limits of Stability after the intervention. Although all the participants improved in those clinical tests that better matched the trained skills, time since injury limited the improvement, and over all, the maintenance of gains. CONCLUSION: Time since injury limits but does not prevent improvement in chronic stages post-stroke, and this effect appears to be more pronounced with maintaining gains. These findings support that training duration and intensity as well as type of therapy may need to be adjusted based on time post-stroke.

Intelligent Multimodal Framework for Human Assistive Robotics Based on Computer Vision Algorithms.

Assistive technologies help all persons with disabilities to improve their accessibility in all aspects of their life. The AIDE European project contributes to the improvement of current assistive technologies by developing and testing a modular and adaptive multimodal interface customizable to the individual needs of people with disabilities. This paper describes the computer vision algorithms part of the multimodal interface developed inside the AIDE European project. The main contribution of this computer vision part is the integration with the robotic system and with the other sensory systems (electrooculography (EOG) and electroencephalography (EEG)). The technical achievements solved herein are the algorithm for the selection of objects using the gaze, and especially the state-of-the-art algorithm for the efficient detection and pose estimation of textureless objects. These algorithms were tested in real conditions, and were thoroughly evaluated both qualitatively and quantitatively. The experimental results of the object selection algorithm were excellent (object selection over 90%) in less than 12 s. The detection and pose estimation algorithms evaluated using the LINEMOD database were similar to the state-of-the-art method, and were the most computationally efficient.

Combined Transcranial Direct Current Stimulation and Virtual Reality-Based Paradigm for Upper Limb Rehabilitation in Individuals with Restricted Movements. A Feasibility Study with a Chronic Stroke Survivor with Severe Hemiparesis.

Impairments of the upper limb function are a major cause of disability and rehabilitation. Most of the available therapeutic options are based on active exercises and on motor and attentional inclusion of the affected arm in task oriented movements. However, active movements may not be possible after severe impairment of the upper limbs. Different techniques, such as mirror therapy, motor imagery, and non-invasive brain stimulation have been shown to elicit cortical activity in absence of movements, which could be used to preserve the available neural circuits and promote motor learning. We present a virtual reality-based paradigm for upper limb rehabilitation that allows for interaction of individuals with restricted movements from active responses triggered when they attempt to perform a movement. The experimental system also provides multisensory stimulation in the visual, auditory, and tactile channels, and transcranial direct current stimulation coherent to the observed movements. A feasibility study with a chronic stroke survivor with severe hemiparesis who seemed to reach a rehabilitation plateau after two years of its inclusion in a physical therapy program showed clinically meaningful improvement of the upper limb function after the experimental intervention and maintenance of gains in both the body function and activity. The experimental intervention also was reported to be usable and motivating. Although very preliminary, these results could highlight the potential of this intervention to promote functional recovery in severe impairments of the upper limb.

Feasibility of a walking virtual reality system for rehabilitation: objective and subjective parameters.

BACKGROUND: Even though virtual reality (VR) is increasingly used in rehabilitation, the implementation of walking navigation in VR still poses a technological challenge for current motion tracking systems. Different metaphors simulate locomotion without involving real gait kinematics, which can affect presence, orientation, spatial memory and cognition, and even performance. All these factors can dissuade their use in rehabilitation. We hypothesize that a marker-based head tracking solution would allow walking in VR with high sense of presence and without causing sickness. The objectives of this study were to determine the accuracy, the jitter, and the lag of the tracking system and its elicited sickness and presence in comparison of a CAVE system. METHODS: The accuracy and the jitter around the working area at three different heights and the lag of the head tracking system were analyzed. In addition, 47 healthy subjects completed a search task that involved navigation in the walking VR system and in the CAVE system. Navigation was enabled by natural locomotion in the walking VR system and through a specific device in the CAVE system. An HMD was used as display in the walking VR system. After interacting with each system, subjects rated their sickness in a seven-point scale and their presence in the Slater-Usoh-Steed Questionnaire and a modified version of the Presence Questionnaire. RESULTS: Better performance was registered at higher heights, where accuracy was less than 0.6 cm and the jitter was about 6 mm. The lag of the system was 120 ms. Participants reported that both systems caused similar low levels of sickness (about 2.4 over 7). However, ratings showed that the walking VR system elicited higher sense of presence than the CAVE system in both the Slater-Usoh-Steed Questionnaire (17.6 ± 0.3 vs 14.6 ± 0.6 over 21, respectively) and the modified Presence Questionnaire (107.4 ± 2.0 vs 93.5 ± 3.2 over 147, respectively). CONCLUSIONS: The marker-based solution provided accurate, robust, and fast head tracking to allow navigation in the VR system by walking without causing relevant sickness and promoting higher sense of presence than CAVE systems, thus enabling natural walking in full-scale environments, which can enhance the ecological validity of VR-based rehabilitation applications.

Effect of a mixed reality-based intervention on arm, hand, and finger function on chronic stroke.

BACKGROUND: Virtual and mixed reality systems have been suggested to promote motor recovery after stroke. Basing on the existing evidence on motor learning, we have developed a portable and low-cost mixed reality tabletop system that transforms a conventional table in a virtual environment for upper limb rehabilitation. The system allows intensive and customized training of a wide range of arm, hand, and finger movements and enables interaction with tangible objects, while providing audiovisual feedback of the participants' performance in gamified tasks. This study evaluates the clinical effectiveness and the acceptance of an experimental intervention with the system in chronic stroke survivors. METHODS: Thirty individuals with stroke were included in a reversal (A-B-A) study. Phase A consisted of 30 sessions of conventional physical therapy. Phase B consisted of 30 training sessions with the experimental system. Both interventions involved flexion and extension of the elbow, wrist, and fingers, and grasping of different objects. Sessions were 45-min long and were administered three to five days a week. The body structures (Modified Ashworth Scale), functions (Motricity Index, Fugl-Meyer Assessment Scale), activities (Manual Function Test, Wolf Motor Function Test, Box and Blocks Test, Nine Hole Peg Test), and participation (Motor Activity Log) were assessed before and after each phase. Acceptance of the system was also assessed after phase B (System Usability Scale, Intrinsic Motivation Inventory). RESULTS: Significant improvement was detected after the intervention with the system in the activity, both in arm function measured by the Wolf Motor Function Test (p < 0.01) and finger dexterity measured by the Box and Blocks Test (p < 0.01) and the Nine Hole Peg Test (p < 0.01); and participation (p < 0.01), which was maintained to the end of the study. The experimental system was reported as highly usable, enjoyable, and motivating. CONCLUSIONS: Our results support the clinical effectiveness of mixed reality interventions that satisfy the motor learning principles for upper limb rehabilitation in chronic stroke survivors. This characteristic, together with the low cost of the system, its portability, and its acceptance could promote the integration of these systems in the clinical practice as an alternative to more expensive systems, such as robotic instruments.

Effectiveness, usability, and cost-benefit of a virtual reality-based telerehabilitation program for balance recovery after stroke: a randomized controlled trial.

OBJECTIVES: First, to evaluate the clinical effectiveness of a virtual reality (VR)-based telerehabilitation program in the balance recovery of individuals with hemiparesis after stroke in comparison with an in-clinic program; second, to compare the subjective experiences; and third, to contrast the costs of both programs. DESIGN: Single-blind, randomized, controlled trial. SETTING: Neurorehabilitation unit. PARTICIPANTS: Chronic outpatients with stroke (N=30) with residual hemiparesis. INTERVENTIONS: Twenty 45-minute training sessions with the telerehabilitation system, conducted 3 times a week, in the clinic or in the home. MAIN OUTCOME MEASURES: First, Berg Balance Scale for balance assessment. The Performance-Oriented Mobility Assessment balance and gait subscales, and the Brunel Balance Assessment were secondary outcome measures. Clinical assessments were conducted at baseline, 8 weeks (posttreatment), and 12 weeks (follow-up). Second, the System Usability Scale and the Intrinsic Motivation Inventory for subjective experiences. Third, cost (in dollars). RESULTS: Significant improvement in both groups (in-clinic group [control] and a home-based telerehabilitation group) from the initial to the final assessment in the Berg Balance Scale (ηp(2)=.68; P=.001), in the balance (ηp(2)=.24; P=.006) and gait (ηp(2)=.57, P=.001) subscales of the Tinetti Performance-Oriented Mobility Assessment, and in the Brunel Balance Assessment (control: χ(2)=15.0; P=.002; experimental: χ(2)=21.9; P=.001). No significant differences were found between the groups in any balance scale or in the feedback questionnaires. With regard to subjective experiences, both groups considered the VR system similarly usable and motivating. The in-clinic intervention resulted in more expenses than did the telerehabilitation intervention ($654.72 per person). CONCLUSIONS: First, VR-based telerehabilitation interventions can promote the reacquisition of locomotor skills associated with balance in the same way as do in-clinic interventions, both complemented with a conventional therapy program; second, the usability of and motivation to use the 2 interventions can be similar; and third, telerehabilitation interventions can involve savings that vary depending on each scenario.

Improvement in balance using a virtual reality-based stepping exercise: a randomized controlled trial involving individuals with chronic stroke.

OBJECTIVE: To study the clinical effectiveness and the usability of a virtual reality-based intervention compared with conventional physical therapy in the balance recovery of individuals with chronic stroke. DESIGN: Randomized controlled trial. SETTING: Outpatient neurorehabilitation unit. PARTICIPANTS: A total of 20 individuals with chronic stroke. INTERVENTIONS: The intervention consisted of 20 one-hour sessions, five sessions per week. The experimental group combined 30 minutes with the virtual reality-based intervention with 30 minutes of conventional training. The control group underwent one hour conventional therapy. MAIN MEASURES: Balance performance was assessed at the beginning and at the end of the trial using the Berg Balance Scale, the balance and gait subscales of the Tinetti Performance-Oriented Mobility Assessment, the Brunel Balance Assessment, and the 10-m Walking Test. Subjective data of the virtual reality-based intervention were collected from the experimental group, with a feedback questionnaire at the end of the trial. RESULTS: The results revealed a significant group-by-time interaction in the scores of the Berg Balance Scale (p < 0.05) and in the 10-m Walking Test (p < 0.05). Post-hoc analyses showed greater improvement in the experimental group: 3.8 ±2.6 vs. 1.8 ±1.4 in the Berg Balance Scale, -1.9 ±1.6 seconds vs. 0.0 ±2.3 seconds in the 10-m Walking Test, and also in the number of participants who increased level in the Brunel Balance Assessment (χ(2) = 2.5, p < 0.01). CONCLUSIONS: Virtual reality interventions can be an effective resource to enhance the improvement of balance in individuals with chronic stroke.

Videogame-based group therapy to improve self-awareness and social skills after traumatic brain injury.

BACKGROUND: This study determines the feasibility of different approaches to integrative videogame-based group therapy for improving self-awareness, social skills, and behaviors among traumatic brain injury (TBI) victims and retrieves participant feedback. METHODS: Forty-two adult TBI survivors were included in a longitudinal study with a pre- and post-assessments. The experimental intervention involved weekly one-hour sessions conducted over six months. Participants were assessed using the Self-Awareness Deficits Interview (SADI), Patient Competency Rating Scale (PCRS), the Social Skills Scale (SSS), the Frontal Systems Behavior Scale (FrSBe), the System Usability Scale (SUS). Pearson's chi-squared test (χ (2)) was applied to determine the percentage of participants who had changed their clinical classification in these tests. Feedback of the intervention was collected through the Intrinsic Motivation Inventory (IMI). RESULTS: SADI results showed an improvement in participant perceptions of deficits (χ (2) = 5.25, p < 0.05), of their implications (χ (2) = 4.71, p < 0.05), and of long-term planning (χ (2) = 7.86, p < 0.01). PCRS results confirm these findings (χ (2) = 5.79, p < 0.05). SSS results were also positive with respect to social skills outcomes (χ (2) = 17.52, p < 0.01), and FrSBe results showed behavioral improvements (χ (2) = 34.12, p < 0.01). Participants deemed the system accessible (80.43 ± 8.01 out of 100) and regarded the intervention as interesting and useful (5.74 ± 0.69 out of 7). CONCLUSIONS: Integrative videogame-based group therapy can improve self-awareness, social skills, and behaviors among individuals with chronic TBI, and the approach is considered effective and motivating.

Tracking systems for virtual rehabilitation: objective performance vs. subjective experience. A practical scenario.

Motion tracking systems are commonly used in virtual reality-based interventions to detect movements in the real world and transfer them to the virtual environment. There are different tracking solutions based on different physical principles, which mainly define their performance parameters. However, special requirements have to be considered for rehabilitation purposes. This paper studies and compares the accuracy and jitter of three tracking solutions (optical, electromagnetic, and skeleton tracking) in a practical scenario and analyzes the subjective perceptions of 19 healthy subjects, 22 stroke survivors, and 14 physical therapists. The optical tracking system provided the best accuracy (1.074 ± 0.417 cm) while the electromagnetic device provided the most inaccurate results (11.027 ± 2.364 cm). However, this tracking solution provided the best jitter values (0.324 ± 0.093 cm), in contrast to the skeleton tracking, which had the worst results (1.522 ± 0.858 cm). Healthy individuals and professionals preferred the skeleton tracking solution rather than the optical and electromagnetic solution (in that order). Individuals with stroke chose the optical solution over the other options. Our results show that subjective perceptions and preferences are far from being constant among different populations, thus suggesting that these considerations, together with the performance parameters, should be also taken into account when designing a rehabilitation system.

Competitive active video games: Physiological and psychological responses in children and adolescents.

BACKGROUND: Recent strategies to reduce sedentary behaviour in children include replacing sedentary screen time for active video games. Active video game studies have focused principally on the metabolic consumption of a single player, with physiological and psychological responses of opponent-based multiplayer games to be further evaluated. OBJECTIVE: To determine whether adding a competitive component to playing active video games impacts physiological and psychological responses in players. METHODS: Sixty-two healthy Caucasian children and adolescents, nine to 14 years years of age, completed three conditions (8 min each) in random order: treadmill walking, and single and opponent-based Kinect active video games. Affect, arousal, rate of perceived exertion, heart rate and percentage of heart rate reserve were measured for each participant and condition. RESULTS: Kinect conditions revealed significantly higher heart rate, percentage of heart rate reserve, rate of perceived exertion and arousal when compared with treadmill walking (P<0.001). Opponent-based condition revealed lower values for the rate of perceived exertion (P=0.02) and higher affect (P=0.022) when compared with single play. CONCLUSION: Competitive active video games improved children's psychological responses (affect and rate of perceived exertion) compared with single play, providing a solution that may contribute toward improved adherence to physical activity.

HISTORIQUE: Parmi les récentes stratégies en vue de réduire les comportements sédentaires chez les enfants, soulignons le remplacement du temps d'écran sédentaire par des jeux vidéo actifs. Les études sur ce type de jeux ont surtout porté sur la consommation métabolique en mode solo. Les réponses physiologiques et psychologiques de jeux en mode multijoueur comportant des adversaires n'ont pas encore été évaluées. OBJECTIF: Déterminer si l'ajout d'un élément compétitif aux jeux vidéo actifs influe sur les réponses physiologiques et psychologiques chez les joueurs. MÉTHODOLOGIE: Soixante-deux enfants et adolescents blancs en bonne santé de neuf à 14 ans ont effectué trois conditionnements de huit minutes chacun, dans un ordre aléatoire : marche sur tapis roulant et jeux vidéo actifs Kinect en mode solo et multijoueur (Microsoft Corporation, États-Unis). Les chercheurs ont mesuré l'affect, l'éveil, le taux d'effort perçu, la fréquence cardiaque et le pourcentage de réserve de fréquence cardiaque de chaque participant et de chaque conditionnement. RÉSULTATS: Le conditionnement Kinect a suscité une augmentation significative de la fréquence cardiaque, du pourcentage de réserve de fréquence cardiaque, d'effort perçu et d'éveil par rapport à la marche sur tapis roulant (P<0,001). Le conditionnement contre un adversaire révélait des valeurs plus faibles de taux d'effort perçu (P=0,02) et un affect plus élevé (P=0,022) que le jeu en mode solo. CONCLUSION: Les jeux vidéo actifs compétitifs donnent de meilleures réponses psychologiques chez les enfants (affect et taux d'efforts perçu) que le jeu en mode solo. Cette solution pourrait contribuer à une meilleure adhérence à l'activité physique.

[Virtual reality and digital biomarkers: a clinical tool for early autism diagnosis]. / Realidad virtual y biomarcadores digitales: una herramienta clínica para el diagnóstico del autismo.

INTRODUCTION: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition which traditional assessment procedures encounter certain limitations. The current ASD research field is exploring and endorsing innovative methods to assess the disorder early on, based on the automatic detection of biomarkers. However, many of these procedures lack ecological validity in their measurements. In this context, virtual reality (VR) shows promise for objectively recording biosignals while users experience ecological situations. METHODS: This study outlines a novel and playful VR procedure for the early assessment of ASD, relying on multimodal biosignal recording. During a VR experience featuring 12 virtual scenes, eye gaze, motor skills, electrodermal activity and behavioural performance were measured in 39 children with ASD and 42 control peers. Machine learning models were developed to identify digital biomarkers and classify autism. RESULTS: Biosignals reported varied performance in detecting ASD, while the combined model resulting from the combination of specific-biosignal models demonstrated the ability to identify ASD with an accuracy of 83% (SD = 3%) and an AUC of 0.91 (SD = 0.04). DISCUSSION: This screening tool may support ASD diagnosis by reinforcing the outcomes of traditional assessment procedures.

Introducción: El Trastorno del Espectro Autista (TEA) es un trastorno del neurodesarrollo, y sus procedimientos tradicionales de evaluación encuentran ciertas limitaciones. El actual campo de investigación sobre TEA está explorando y respaldando métodos innovadores para evaluar el trastorno tempranamente, basándose en la detección automática de biomarcadores. Sin embargo, muchos de estos procedimientos carecen de validez ecológica en sus mediciones. En este contexto, la realidad virtual (RV) presenta un prometedor potencial para registrar objetivamente bioseñales mientras los usuarios experimentan situaciones ecológicas. Métodos: Este estudio describe un novedoso y lúdico procedimiento de RV para la evaluación temprana del TEA, basado en la grabación multimodal de bioseñales. Durante una experiencia de RV con 12 escenas virtuales, se midieron la mirada, las habilidades motoras, la actividad electrodermal y el rendimiento conductual en 39 niños con TEA y 42 compañeros de control. Se desarrollaron modelos de aprendizaje automático para identificar biomarcadores digitales y clasificar el autismo. Resultados: Las bioseñales reportaron un rendimiento variado en la detección del TEA, mientras que el modelo resultante de la combinación de los modelos de las bioseñales demostró la capacidad de identificar el TEA con una precisión del 83% (DE = 3%) y un AUC de 0.91 (DE = 0.04). Discusión: Esta herramienta de detección puede respaldar el diagnóstico del TEA al reforzar los resultados de los procedimientos tradicionales de evaluación.

Beyond Reality: Exploring the effect of different virtual reality environments on visual assessment of cakes.

Visual assessment triggers physiological, emotional, and cognitive responses in consumer behavior. This confluence of signals can be influenced by context, which plays a crucial role in eating behavior. The strategies used to evoke scenarios that enhance ecological validity in sensory experiences have evolved in the last years to include immersive technologies and virtual reality (VR) to simulate the complexity of the real world and predict consumer preferences. This study explored VR's effect on visual liking and hedonic responses of five virtual cakes in two virtual contexts designed with advanced 3D modeling and photogrammetry techniques to ensure high realism and immersion. Although the virtual contexts themselves did not impact liking ratings, the variables "context-cake," "age," and "subjective hunger" had a significant effect on the visual liking of cakes. A Check-All-That-Apply (CATA) questionnaire showed significant differences in responses for various terms related to the intrinsic and extrinsic characteristics of the five cakes. Finally, the internal preference map separated two consumer patterns of visual liking: traditional versus innovative.