Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Mar 15:12:623200.
doi: 10.3389/fneur.2021.623200. eCollection 2021.

Performance Variability During Motor Learning of a New Balance Task in a Non-immersive Virtual Environment in Children With Hemiplegic Cerebral Palsy and Typically Developing Peers

Affiliations

Performance Variability During Motor Learning of a New Balance Task in a Non-immersive Virtual Environment in Children With Hemiplegic Cerebral Palsy and Typically Developing Peers

Minxin Cheng et al. Front Neurol. .

Abstract

Background: Motor impairments contribute to performance variability in children with cerebral palsy (CP) during motor skill learning. Non-immersive virtual environments (VEs) are popular interventions to promote motor learning in children with hemiplegic CP. Greater understanding of performance variability as compared to typically developing (TD) peers during motor learning in VEs may inform clinical decisions about practice dose and challenge progression. Purpose: (1) To quantify within-child (i.e., across different timepoints) and between-child (i.e., between children at the same timepoint) variability in motor skill acquisition, retention and transfer in a non-immersive VE in children with CP as compared to TD children; and (2) To explore the relationship between the amount of within-child variability during skill acquisition and learning outcomes. Methods: Secondary data analysis of 2 studies in which 13 children with hemiplegic CP and 67 TD children aged 7-14 years undertook repeated trials of a novel standing postural control task in acquisition, retention and transfer sessions. Changes in performance across trials and sessions in children with CP as compared to TD children and between younger (7-10 years) and older (11-14 years) children were assessed using mixed effects models. Raw scores were converted to z-scores to meet model distributional assumptions. Performance variability was quantified as the standard deviation of z-scores. Results: TD children outperformed children with CP and older children outperformed younger children at each session. Older children with CP had the least between-child variability in acquisition and the most in retention, while older TD children demonstrated the opposite pattern. Younger children with CP had consistently high between-child variability, with no difference between sessions. Within-child variability was highest in younger children, regardless of group. Within-child variability was more pronounced in TD children as compared to children with CP. The relationship between the amount of within-child variability in performance and performance outcome at acquisition, retention and transfer sessions was task-specific, with a positive correlation for 1 study and a negative correlation in the other. Conclusions: Findings, though preliminary and limited by small sample size, can inform subsequent research to explore VE-specific causes of performance variability, including differing movement execution requirements and individual characteristics such as motivation, attention and visuospatial abilities.

Keywords: cerebral palsy; children; motor learning; variability; virtual environment; virtual reality.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Displays the Study 1 virtual environment, showing the path emerging in front of the participant (the white dots).
Figure 2
Figure 2
Displays the Study 2 virtual environment, showing the entire path visible to the participant (the blue line).
Figure 3
Figure 3
Mean z-score by group and age group across all trials at each session. Error bars use sdDiff (the standard deviation of the pair-wise trial-to-trial differences). SE is calculated by devising the SD by the square root of the number of subjects in each trial.
Figure 4
Figure 4
Performance score for each individual participant across all trials of the 3 sessions, fit with a quadratic curve.

Similar articles

Cited by

References

    1. Van Naarden Braun K, Doernberg N, Schieve L, Christensen D, Goodman A, Yeargin-Allsopp M. Birth prevalence of cerebral palsy: a population-based study. Pediatrics. (2016) 137:1–9. 10.1542/peds.2015-2872 - DOI - PMC - PubMed
    1. Maenner MJ, Blumberg SJ, Kogan MD, Christensen D, Yeargin-Allsopp M, Schieve LA. Prevalence of cerebral palsy and intellectual disability among children identified in two US National Surveys, 2011–2013. Ann Epidemiol. (2016) 26:222–6. 10.1016/j.annepidem.2016.01.001 - DOI - PMC - PubMed
    1. Pulgar S, Bains S, Gooch J, Chambers H, Noritz GH, Wright E, et al. . Prevalence, patterns, and cost of care for children with cerebral palsy enrolled in medicaid managed care. J Manag Care Special Pharm. (2019) 25:817–22. 10.18553/jmcp.2019.25.7.817 - DOI - PMC - PubMed
    1. Oskoui M, Coutinho F, Dykeman J, Jette N, Pringsheim T. An update on the prevalence of cerebral palsy: a systematic review and meta-analysis. Dev Med Child Neurol. (2013) 55:509–19. 10.1111/dmcn.12080 - DOI - PubMed
    1. Shevell MI, Dagenais L, Hall N. The relationship of cerebral palsy subtype and functional motor impairment: a population-based study. Dev Med Child Neurol. (2009) 51:872–7. 10.1111/j.1469-8749.2009.03269.x - DOI - PubMed

LinkOut - more resources