Background: Motor learning, a primary goal of pediatric rehabilitation, is facilitated when tasks are presented at a "just-right" challenge level-at the edge of the child's current abilities, yet attainable enough to motivate the child in persistent efforts for success. Immersive virtual reality (VR) may be ideally suited for "just-right" task challenges because it enables precise adjustments of task parameters in motivating environments. Rehabilitation-specific VR tasks often use dynamic difficulty algorithms based on task performance to personalize task difficulty. However, these approaches do not consider relevant cognitive processes that could also impact "just-right" challenges, such as attention and engagement. Objective physiological measurement of these cognitive processes using wearable sensors could support their integration within "just-right" challenge detection and prediction algorithms. As a first step, it is important to explore relationships between objectively and subjectively measured psychophysiological states at progressively challenging task difficulty levels.
Objective: This study aims to (1) evaluate the performance of wearable sensors in a novel movement-based motor learning immersive VR task; (2) evaluate changes in physiological data at 3 task difficulty levels; and (3) explore the relationship between physiological data, task performance, and self-reported cognitive processes at each task difficulty level.
Methods: This study uses the within-participant experimental design. Typically developing children and youth aged 8-16 years will be recruited to take part in a single 90-minute data collection session. Physiological sensors include electrodermal activity, heart rate, electroencephalography, and eye-tracking. After collecting physiological data at rest, participants will play a seated unimanual immersive VR task involving bouncing a virtual ball on a virtual racket. They will first play for 3 minutes at a predefined medium level of difficulty to determine their baseline ability level and then at a personalized choice of 3 progressive difficulty levels of 3 minutes each. Following each 3-minute session, participants will complete a short Likert-scale questionnaire evaluating engagement, attention, cognitive workload, physical effort, self-efficacy, and motivation. Data loss and data quality will be calculated for each sensor. Repeated-measures ANOVAs will evaluate changes in physiological response at each difficulty level. Correlation analyses will determine individual relationships between task performance, physiological data, and self-reported data at each difficulty level.
Results: Research ethics board approval has been obtained, and data collection is underway. Data collection was conducted on December 12, 2023, and April 12, 2024, with a total of 15 typically developing children. Data analysis has been completed, and results are expected to be published in the fall of 2024.
Conclusions: Wearable sensors may provide insights into the physiological effects of immersive VR task interaction at progressive difficulty levels in children and youth. Understanding the relationship between physiological and self-reported cognitive processes is a first step in better identifying and predicting "just-right" task challenges during immersive VR motor learning interventions.
International Registered Report Identifier (irrid): DERR1-10.2196/55730.
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http://dx.doi.org/10.2196/55730 | DOI Listing |
J Neuroeng Rehabil
January 2025
Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Vita Stråket 12, Floor 4, 41346, Gothenburg, Sweden.
Background: Myoelectric pattern recognition (MPR) combines multiple surface electromyography channels with a machine learning algorithm to decode motor intention with an aim to enhance upper limb function after stroke. This study aims to determine the feasibility and preliminary effectiveness of a novel intervention combining MPR, virtual reality (VR), and serious gaming to improve upper limb function in people with chronic stroke.
Methods: In this single case experimental A-B-A design study, six individuals with chronic stroke and moderate to severe upper limb impairment completed 18, 2 h sessions, 3 times a week.
Transl Psychiatry
January 2025
Department of Psychology, Goldsmiths University of London, London, UK.
Bipolar disorder (BD) involves altered reward processing and decision-making, with inconsistencies across studies. Here, we integrated hierarchical Bayesian modelling with magnetoencephalography (MEG) to characterise maladaptive belief updating in this condition. First, we determined if previously reported increased learning rates in BD stem from a heightened expectation of environmental changes.
View Article and Find Full Text PDFPhys Ther
January 2025
School of Health and Rehabilitation Sciences, The Ohio State University, Columbus, OH, United States.
Objective: This study aimed to describe the monitoring of treatment fidelity in a pragmatic pediatric rehabilitation trial using the National Institutes of Health Behavior Change Consortium framework, and to identify child and therapist factors that influence treatment fidelity.
Methods: Therapists (n = 28) were trained in the key ingredients (1-on-1, functional, goal-directed, motor learning intervention) and study protocol for a comparative effectiveness trial titled: A Comparison: High Intensity periodic vs. Every week therapy in children with cerebral palsy (ACHIEVE) for children ages 2 to 8 years with cerebral palsy.
Phys Ther
January 2025
Department of Physical Medicine and Rehabilitation.
Research over the past 20 years indicates the amount of task-specific walking practice provided to individuals with stroke, brain injury, or incomplete spinal cord injury can strongly influence walking recovery. However, more recent data suggest that attention towards 2 other training parameters, including the intensity and variability of walking practice, may maximize walking recovery and facilitate gains in non-walking outcomes. The combination of these training parameters represents a stark contrast from traditional strategies, and confusion regarding the potential benefits and perceived risks may limit their implementation in clinical practice.
View Article and Find Full Text PDFArch Rehabil Res Clin Transl
December 2024
Research Centre for Nutrition, Lifestyle and Exercise, School of Physiotherapy, Zuyd University of Applied Sciences, Faculty of Health, Heerlen, The Netherlands.
Objective: To provide a broad overview of the current state of research regarding the effects of 7 commonly used motor learning strategies to improve functional tasks within older neurologic and geriatric populations.
Data Sources: PubMed, CINAHL, and Embase were searched.
Study Selection: A systematic mapping review of randomized controlled trials was conducted regarding the effectiveness of 7 motor learning strategies-errorless learning, analogy learning, observational learning, trial-and-error learning, dual-task learning, discovery learning, and movement imagery-within the geriatric and neurologic population.
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