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Comparing Computer-Derived and Human-Observed Scores for the Balance Error Scoring System
Abstract
Context: The Balance Error Scoring System (BESS) is the current standard for assessing postural stability in concussed athletes on the sideline. However, research has questioned the objectivity and validity of the BESS, suggesting that while certain subcategories of the BESS have sufficient reliability to be used in evaluation of postural stability, the total score is not reliable, demonstrating limited interrater and intrarater reliability. Recently, a computerized BESS test was developed to automate scoring. Objective: To compare computerderived BESS scores with those taken from 3 trained human scorers. Design: Interrater reliability study. Setting: Athletic training room. Patients: NCAA Division I student athletes (53 male, 58 female; 19 ± 2 y, 168 ± 41 cm, 69 ± 4 kg). Interventions: Subjects were asked to perform the BESS while standing on the Tekscan (Boston, MA) MobileMat® BESS. The MobileMat BESS software displayed an error score at the end of each trial. Simultaneously, errors were recorded by 3 separate examiners. Errors were counted using the standard BESS scoring criteria. Main Outcome Measures: The number of BESS errors was computed for the 6 stances from the software and each of the 3 human scorers. Interclass correlation coefficients (ICCs) were used to compare errors for each stance scored by the MobileMat BESS software with each of 3 raters individually. The ICC values were converted to Fisher Z scores, averaged, and converted back into ICC values. Results: The double-leg, single-leg, and tandem-firm stances resulted in good agreement with human scorers (ICC = .999, .731, and .648). All foam stances resulted in fair agreement. Conclusions: Our results suggest that the MobileMat BESS is suitable for identifying BESS errors involving each of the 6 stances of the BESS protocol. Because the MobileMat BESS scores consistently and reliably, this system can be used with confidence by clinicians as an effective alternative to scoring the BESS.
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“Although the visual system of humans, with expert knowledge, can interpret and provide relative BFI abundance in SEM images from wound-edge tissue,26 such assessments are primarily subjective, time-intensive, limited by the availability of expert raters, and prone to interobserver variability.27-30”
From SEMTWIST Quantification of Biofilm Infection in Human Chronic Wound Using Scanning Electron Microscopy and Machine Learning (2025) · cites this paper as [27]
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Singh, S., Muniz De Oliveira, F., Wang, C., Kumar, M., Xuan, Y., DeMazumder, D., Sen, C. K., & Roy, S. (2025) · Advances in Wound Care · doi:10.1089/wound.2024.0291 · Cited by 6
Metadata
- Authors
- Caccese, J. B., & Kaminski, T. W.
- Venue
- Journal of Sport Rehabilitation
- Publisher
- Human Kinetics
- Published
- 2016-05
- Volume
- 25
- Issue
- 2
- Pages
- 133-136
- ISSN
- 1056-6716
- 1543-3072
- Cited by
- 15
- References
- 0
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