Glass Stephen M, Napoli Alessandro, Thompson Elizabeth D, Obeid Iyad, Tucker Carole A
1 Department of Physical Therapy, Temple University College of Public Health, Philadelphia, PA.
2 Department of Electrical and Computer Engineering, Temple University College of Engineering, Philadelphia, PA.
J Appl Biomech. 2019 Feb 1;35(1):32–36. doi: 10.1123/jab.2018-0056. Epub 2018 Aug 6.
The Balance Error Scoring System (BESS) is a human-scored, field-based balance test used in cases of suspected concussion. Recently developed instrumented alternatives to human scoring carry substantial advantages over traditional testing, but thus far report relatively abstract outcomes which may not be useful to clinicians or coaches. In contrast, the Automated Assessment of Postural Stability (AAPS) is a computerized system that tabulates error events in accordance with the original description of the BESS. This study compared AAPS and human-based BESS scores. Twenty-five healthy adults performed the modified BESS. Tests were scored twice each by human raters (3) and the computerized system. Interrater (between-human) and inter-method (AAPS vs. human) agreement (ICC) were calculated alongside Bland-Altman limits of agreement (LOA). Interrater analyses were significant (p<0.005) and demonstrated good to excellent agreement. Inter-method agreement analyses were significant (p<0.005), with agreement ranging from poor to excellent. Computerized scores were equivalent across rating occasions. LOA ranges for AAPS vs. the Human Average exceeded the average LOA ranges between human raters. Coaches and clinicians may consider a system such as AAPS to automate balance testing while maintaining the familiarity of human-based scoring, although scores should not yet be considered interchangeable with those of a human rater.
平衡误差评分系统(BESS)是一种用于疑似脑震荡病例的人工评分、基于现场的平衡测试。最近开发的人工评分的仪器替代方法比传统测试具有显著优势,但迄今为止报告的结果相对抽象,可能对临床医生或教练没有用处。相比之下,姿势稳定性自动评估(AAPS)是一种计算机化系统,它根据BESS的原始描述将错误事件制成表格。本研究比较了AAPS和基于人工的BESS评分。25名健康成年人进行了改良的BESS测试。测试由人工评分员(3名)和计算机化系统各评分两次。计算了评分员间(人与人之间)和方法间(AAPS与人工)的一致性(ICC)以及布兰德-奥特曼一致性界限(LOA)。评分员间分析具有显著性(p<0.005),并显示出良好到极好的一致性。方法间一致性分析具有显著性(p<0.005),一致性范围从差到极好。计算机化评分在不同评分场合是等效的。AAPS与人类平均评分的LOA范围超过了人工评分员之间的平均LOA范围。教练和临床医生可以考虑使用AAPS这样的系统来实现平衡测试自动化,同时保持对基于人工评分的熟悉度,尽管目前不应认为这些分数与人工评分员的分数可以互换。