Biofeedback-Based, Videogame Balance Training in Autism

Abstract

The present study examined the effects of a visual-based biofeedback training on improving balance challenges in autism spectrum disorder (ASD). Twenty-nine youth with ASD (7-17 years) completed an intensive 6-week biofeedback-based videogame balance training. Participants exhibited training-related balance improvements that significantly accounted for postural-sway improvements outside of training. Participants perceived the training as beneficial and enjoyable. Significant moderators of training included milder stereotyped and ritualistic behaviors and better starting balance. Neither IQ nor BMI moderated training. These results suggest that biofeedback-based balance training is associated with balance improvements in youth with ASD, most robustly in those with less severe repetitive behaviors and better starting balance. The training was perceived as motivating, further suggesting its efficacy and likelihood of use.

Whole-Body Movement during Videogame Play Distinguishes Youth with Autism from Youth with Typical Development

“…The biofeedback-based balance training set up and protocol have been previously detailed 25 . In brief, the study started with an intake session, in which participants completed standardized IQ and motor assessments.…”

“…Therefore, the present study had three aims. Using non-invasive, kinematic tracking of body movements during a biofeedback-based balance training in which participants received visual input regarding their body positioning in order to enhance static balance over time 25 , the first aim of the study was to determine whether whole-body movement and postural stability during balance tasks could reliably distinguish between youth with ASD and youth with TD. In other words, could the way that individuals moved during a biofeedback-based balance training 25 reliably distinguish between the two diagnostic groups?…”

“…Using non-invasive, kinematic tracking of body movements during a biofeedback-based balance training in which participants received visual input regarding their body positioning in order to enhance static balance over time 25 , the first aim of the study was to determine whether whole-body movement and postural stability during balance tasks could reliably distinguish between youth with ASD and youth with TD. In other words, could the way that individuals moved during a biofeedback-based balance training 25 reliably distinguish between the two diagnostic groups? We selected to test this aim with a machine learning (ML) approach rather than traditional null hypothesis testing within each motor domain because of the desire to reduce multiple statistical comparisons, and because of the volume and complexity of the current data set (x,y,z coordinates of 20 joint positions and x-y coordinates of the balance board in multiple training poses across multiple sessions).…”

“…To achieve these aims, kinematic and postural sway data were collected in 39 youth with ASD and 23 age-matched youth with TD (ages 7.0–17.9 years), as part of a biofeedback-based videogame training to enhance balance 25 . Table 1 shows the participant demographics.…”

“…Because of the sensory symptoms in ASD 24 , all kinematic data were collected as non-invasively as possible, without markers placed on the body or wires. Because previous work 25 has demonstrated balance improvements in ASD as a function of this training, training sessions 2–4 (of 18) were used in these analyses to characterize motor skills before the majority of the improvements due to training but after the initial intake assessment (session 1). These data were cleaned, informative features were extracted, and an ensemble of random forest (RF) classifiers were trained.…”