Presentation Title

Static and Dynamic Assessments of Postural Control Post-Concussion: Logistic Regression Models

Location

Room 2901

Session Format

Paper Presentation

Research Area Topic:

Exercise Science & Human Performance - Biomechanics

Co-Presenters, Co- Authors, Co-Researchers, Mentors, or Faculty Advisors

Anthony Salvatore, PhD

Douglas Powell, PhD

Rebecca Reed-Jones, PhD

Nicholas Murray, PhD

Abstract

Context: Traditional static, quiet stance balance assessments lack the environmental component to adequately assess the health of the postural control system post-concussion. When compared to static assessments, dynamic assessments are more environmentally-relevant, require more functional motor control tasks, and more heavily assess both the feed-back and feed-forward control strategies of the continuous feedback control system.

Objective: To determine whether static or dynamic postural sway assessments of Center of Pressure (CoP) directions could predict a clinically diagnosed concussion.

Methods: 15 collegiate athletes, with a clinical diagnosis of concussion within 24-48 hours, and 20 age-matched healthy collegiate athletes completed static and dynamic balance assessments. The static assessment was performed on a WiiFit board for 60 seconds in both eyes open and eyes closed conditions. The dynamic assessment was performed on a WiiFit board while playing the WiiFit Soccer Heading Game, which lasts about 70 seconds. Under both assessments, the WiiFit board was placed on top of an AMTI force platform, which calculated CoP Peak Velocity in both the anteroposterior (AP) and mediolateral (ML) directions at a frequency of 100 Hz.

Results: The static logistic regression model alone correctly predicted 77.1% of the clinically diagnosed concussions (p=0.014, R2=0.403), whereas the dynamic logistic regression model alone correctly predicted 71.4% of the clinically diagnosed concussions (p=0.005, R2=0.351). The combined logistic regression model correctly predicted 91.4% of the clinical diagnosis of a concussion (p2=0.727).

Conclusions: These results suggest that static and dynamic balance assessments potentially measure different postural control tasks. Combining both static and dynamic assessments together may provide the greatest insight into the health of the postural control system post-concussion and may be the most accurate in making a clinical diagnosis of concussion. This research also supports the merit of both static and dynamic balance assessments as valid methods to determine balance dysfunctions post-concussion.

Keywords

Concussion, MTBI, Balance, Postural control, Force platform, WiiFit, Logistic regression

Presentation Type and Release Option

Presentation (Open Access)

Start Date

4-24-2015 9:30 AM

End Date

4-24-2015 10:30 AM

This document is currently not available here.

Share

COinS
 
Apr 24th, 9:30 AM Apr 24th, 10:30 AM

Static and Dynamic Assessments of Postural Control Post-Concussion: Logistic Regression Models

Room 2901

Context: Traditional static, quiet stance balance assessments lack the environmental component to adequately assess the health of the postural control system post-concussion. When compared to static assessments, dynamic assessments are more environmentally-relevant, require more functional motor control tasks, and more heavily assess both the feed-back and feed-forward control strategies of the continuous feedback control system.

Objective: To determine whether static or dynamic postural sway assessments of Center of Pressure (CoP) directions could predict a clinically diagnosed concussion.

Methods: 15 collegiate athletes, with a clinical diagnosis of concussion within 24-48 hours, and 20 age-matched healthy collegiate athletes completed static and dynamic balance assessments. The static assessment was performed on a WiiFit board for 60 seconds in both eyes open and eyes closed conditions. The dynamic assessment was performed on a WiiFit board while playing the WiiFit Soccer Heading Game, which lasts about 70 seconds. Under both assessments, the WiiFit board was placed on top of an AMTI force platform, which calculated CoP Peak Velocity in both the anteroposterior (AP) and mediolateral (ML) directions at a frequency of 100 Hz.

Results: The static logistic regression model alone correctly predicted 77.1% of the clinically diagnosed concussions (p=0.014, R2=0.403), whereas the dynamic logistic regression model alone correctly predicted 71.4% of the clinically diagnosed concussions (p=0.005, R2=0.351). The combined logistic regression model correctly predicted 91.4% of the clinical diagnosis of a concussion (p2=0.727).

Conclusions: These results suggest that static and dynamic balance assessments potentially measure different postural control tasks. Combining both static and dynamic assessments together may provide the greatest insight into the health of the postural control system post-concussion and may be the most accurate in making a clinical diagnosis of concussion. This research also supports the merit of both static and dynamic balance assessments as valid methods to determine balance dysfunctions post-concussion.