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Automated BESS Test for Diagnosis of Post- Concussive Symptoms using Microsoft Kinect

Automated BESS Test for Diagnosis of Post- Concussive Symptoms using Microsoft Kinect

Abstract

The Balance Error Scoring System (BESS) test is a commonly used tool for assessing static postural stability after concussion that quantifies compensatory arm, eye and trunk movements. However, since it is scored by clinician observation, it is potentially susceptible to biased and inaccurate test scores. It is further limited by the need for properly trained clinicians to simultaneously administer, score and interpret the test. Such personnel may not always be available when concussion testing is needed such as at amateur sporting events or in military field situations. In response, we are creating a system to automatically administer and score the BESS in field conditions. The system is based on the Microsoft Kinect, which is an inexpensive commodity motion capture system originally developed for gaming applications. The Kinect can be interfaced to a custom-programmed laptop computer in order to quantitatively measure patient posture compensations for preventing balance loss such as degree of hip abduction/flexion, heel lift, and hand movement. By (a) removing the need for an adequately trained clinician, and (b) using rugged off-the-shelf system components, it will be possible to administer concussion assessments outside of standard clinical settings. Future work will determine whether the system can reduce score variability between clinicians.

Keywords

Engineering, Bess Test, Autobess, Microsoft Kinect, Automated Administration, Engineering, Biomedical, Electrical Engineering

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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