Effects of a Multimodal Exercise Program for Children With ASD

Overview

Exploring the effects of an exercise program for children ages 6 -26 years old who have been diagnosed with autism spectrum disorder and neurotypical children respond to high-intensity whole body exercise interventions (Group 1), training using a sensory glove and armband (Group 2), no-intervention control (waitlist control) (Group 3). Approximately 50 children and adolescents will volunteer to participate in this program with participants parents' (or legal guardians') permission. This study will be conducted at an off-site pediatric occupational therapy facility Inclusive Sports and Fitness, Inc. (ISF).

The purpose of this study is to explore the effects of a structured high-intensity sensorimotor exercise program on performance skills (cognitive or executive function and functional motor skills) and hand function of children diagnosed with autistic spectrum disorder (ASD) and a neurotypical group and an additional qEEG which will be administered during the 6-12 week period. The investigators would like to recruit 50 participants for this study. The research design consists of a nonequivalent quasi-experimental multi-group (ASD and Neurotypical) pre and post-test group design: Experimental Group 1 (high-intensity whole-body exercise): Pretest - intervention - Post-test; Experimental Group 2 (Sensory glove and armband): Pretest-Intervention-Post-test. The pretest will consist of motor and cognitive testing and a quantitative electroencephalogram (qEEG). The administration of these measures will be conducted on the grounds of the clinical site (ISF). The same measures used at the pretest will be utilized during post-test. The potential benefits from the findings of this study will provide important information as to the efficacy of using multimodal (multisensory) training with exergaming applications on performance skills and abilities. The multisensory feedback will come from a number of sensory-based activities and gaming mechanisms employed in occupational and physical therapy. To our knowledge, there is a limited number of studies in peer-reviewed literature using validated and reliable outcome assessments under scientifically rigorous methods. The children participating in this study will receive the benefits of being in a skill-oriented exercise and functional skills training program that will address their performance skills impairments. These types of programs are not available to this population, particularly for families with limited financial support. Cognitive interventions will address the participants' ability to process various sensory (visual, auditory, haptic, proprioceptive, and vestibular information. The intervention will include a combination of cognitive tasks and sensorimotor activities. The investigators are utilizing a dynamic system approach that integrates sensory, physical, and cognitive processes with wearable technology and gaming. This approach recognizes the plastic nature of the brain and its ability to adapt through skilled interventions. Recent studies have posited that the neural substructures associated with functional impairments in children with ASD are not localized to morphological brain disorders, but rather a connectome issue associated with interneuron network impairments. Disordered connectivity can impair information processing, integration, and application of information from the different "processing nodes" within a functional network. Children with ASD demonstrate poor integration of multisensory information utilizing qEEG. The researchers suggested that interventions that provide multisensory stimuli may help improve neural connections and help them develop strategies for functioning in mainstream environments. In addition to the multisensory interventions to advance interconnectivity in the brain, children will participate in high-intensity physical activity. High-intensity activity has been found to produce neurophysiological and morphological changes in the brain with subsequent cognitive improvements. Test and measures will be administered using the Bruininks-Oseretsky Test of Motor Proficiency (BOT-2). The BOT-2 covers the age range of 4 to 21 years, with a 53-item assessment consisting of eight subtests designed as game-like tasks that measure hand and arm coordination, balance, mobility, and strength. Investigators will be including an assessment that will allow us to measure the quality of movement of the hand. It will also provide feedback to the user to better calibrate and isolate hand movements. The participant will don a glove and arm sleeve with inductive sensors that will measure hand performance. The participants are asked to make a series of hand gestures for numbers 1 to 9 based on the American Sign Language and then follow some patterns of arm movements. The glove will record the kinematic data corresponding to each hand gesture and arm movement using a set of inductive sensors in the form of patches to be attached to the arm, a glove, and/or a pad of inductive sensors. The data will be used to develop machine learning algorithms from the gestures and arm movements made by neurotypical and ASD children and young adults. Machine learning applications will provide user feedback to identify correct hand positions and improve fine motor capabilities. Cognitive Performance Measure The Test of Variables of Attention (TOVA). The TOVA is a culture- and language-free, sufficiently long computerized test that requires no left/right discrimination or sequencing. Responses to visual or auditory stimuli are recorded with a unique, highly accurate (±1 ms) microswitch. The TOVA calculates response time variability (consistency), the response time (speed), commissions (impulsivity), and omissions (focus and vigilance). These calculations are then compared to a large age- and gender-matched normative sample, as well as to a sample population of individuals independently diagnosed with ADHD. Qualitative EEG (qEEG) Those potential participants who meet the eligibility criteria of the screening visit will be invited to participate in the study. As a baseline, qEEG will be a measure and guide in the individualized intervention protocol group. The qEEG is used to study a person's brainwaves via an analytic procedure called "brain mapping." The qEEG is derived by digitally analyzing the EEG to measure the amount of various EEG frequencies at different scalp locations (power analysis) and the connections between different areas (coherence analysis). Quantitative EEG frequencies will be measured at 19 sites on the head. The data obtained at 19 standard sites on the head is compared with data from normal individuals in the Applied Neuroscience, Inc. database. qEEG data will be analyzed to obtain brain maps and Z Scores for each participant. These qEEG analyses will provide a baseline for before/during/after intervention comparison in the individualized intervention group.