Quantification of the Balance Error Scoring System with Mobile Technology
The aim of this project was to develop a biomechanically based quantification of the Balance Error Scoring System (BESS) using data derived from the accelerometer and gyroscope of a mobile tablet device. Thirty-two healthy young adults completed the BESS while an iPad was positioned at the sacrum. D...
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Published in | Medicine and science in sports and exercise Vol. 47; no. 10; p. 2233 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
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United States
01.10.2015
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Abstract | The aim of this project was to develop a biomechanically based quantification of the Balance Error Scoring System (BESS) using data derived from the accelerometer and gyroscope of a mobile tablet device.
Thirty-two healthy young adults completed the BESS while an iPad was positioned at the sacrum. Data from the iPad were compared to position data gathered from a three-dimensional motion capture system. Peak-to-peak (P2P), normalized path length (NPL), and root mean squared (RMS) were calculated for each system and compared. Additionally, a 95% ellipsoid volume, iBESS volume, was calculated using center of mass (CoM) movements in the anteroposterior (AP), mediolateral (ML), and trunk rotation planes of movement to provide a comprehensive, 3D metric of postural stability.
Across all kinematic outcomes, data from the iPad were significantly correlated with the same outcomes derived from the motion capture system (rho range, 0.37-0.94; P < 0.05). The iBESS volume metric was able to detect a difference in postural stability across stance and surface, showing a significant increase in volume in increasingly difficult conditions, whereas traditional error scoring was not as sensitive to these factors.
The kinematic data provided by the iPad are of sufficient quality relative to motion capture data to accurately quantify postural stability in healthy young adults. The iBESS volume provides a more sensitive measure of postural stability than error scoring alone, particularly in conditions 1 and 4, which often suffer from floor effects, and condition 5, which can experience ceiling effects. The iBESS metric is ideally suited for clinical and in the field applications in which characterizing postural stability is of interest. |
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AbstractList | The aim of this project was to develop a biomechanically based quantification of the Balance Error Scoring System (BESS) using data derived from the accelerometer and gyroscope of a mobile tablet device.
Thirty-two healthy young adults completed the BESS while an iPad was positioned at the sacrum. Data from the iPad were compared to position data gathered from a three-dimensional motion capture system. Peak-to-peak (P2P), normalized path length (NPL), and root mean squared (RMS) were calculated for each system and compared. Additionally, a 95% ellipsoid volume, iBESS volume, was calculated using center of mass (CoM) movements in the anteroposterior (AP), mediolateral (ML), and trunk rotation planes of movement to provide a comprehensive, 3D metric of postural stability.
Across all kinematic outcomes, data from the iPad were significantly correlated with the same outcomes derived from the motion capture system (rho range, 0.37-0.94; P < 0.05). The iBESS volume metric was able to detect a difference in postural stability across stance and surface, showing a significant increase in volume in increasingly difficult conditions, whereas traditional error scoring was not as sensitive to these factors.
The kinematic data provided by the iPad are of sufficient quality relative to motion capture data to accurately quantify postural stability in healthy young adults. The iBESS volume provides a more sensitive measure of postural stability than error scoring alone, particularly in conditions 1 and 4, which often suffer from floor effects, and condition 5, which can experience ceiling effects. The iBESS metric is ideally suited for clinical and in the field applications in which characterizing postural stability is of interest. |
Author | Schindler, David D Koop, Mandy M Thota, Anil Dey, Tanujit Linder, Susan M Ozinga, Sarah Alberts, Jay L Hirsch, Joshua Burke, Daniel |
Author_xml | – sequence: 1 givenname: Jay L surname: Alberts fullname: Alberts, Jay L organization: 1Department of Biomedical Engineering, Cleveland Clinic, Cleveland, OH; 2Center for Neurological Restoration, Cleveland Clinic, Cleveland, OH; 3Cleveland Clinic Concussion Center, Cleveland Clinic, Cleveland, OH; and 4Qualitative Health Services, Cleveland Clinic, Cleveland, OH – sequence: 2 givenname: Anil surname: Thota fullname: Thota, Anil – sequence: 3 givenname: Joshua surname: Hirsch fullname: Hirsch, Joshua – sequence: 4 givenname: Sarah surname: Ozinga fullname: Ozinga, Sarah – sequence: 5 givenname: Tanujit surname: Dey fullname: Dey, Tanujit – sequence: 6 givenname: David D surname: Schindler fullname: Schindler, David D – sequence: 7 givenname: Mandy M surname: Koop fullname: Koop, Mandy M – sequence: 8 givenname: Daniel surname: Burke fullname: Burke, Daniel – sequence: 9 givenname: Susan M surname: Linder fullname: Linder, Susan M |
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SubjectTerms | Accelerometry - standards Adolescent Adult Athletic Injuries - diagnosis Biomechanical Phenomena - physiology Brain Concussion - diagnosis Computers, Handheld - standards Female Humans Male Postural Balance Reproducibility of Results Time and Motion Studies Young Adult |
Title | Quantification of the Balance Error Scoring System with Mobile Technology |
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