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Reliability and Validity of an Accelerometer-based Balance Assessment for Fall Risk Screening.

机译：基于加速度计的平衡评估用于坠落风险筛选的可靠性和有效性。

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摘要

Postural sway occurs spontaneously during static stance as a result of the unstable properties of the body. In balance dysfunction, often a consequence of the normal aging process, the amplitude and frequency of this sway may exceed the limits of stability and contribute to a fall. Therefore, it is important to develop reliable and valid tools to assess postural sway and fall risk. When compared with force plate center of pressure (COP) measurements (one of the most commonly used postural sway assessment tools), accelerometers have been as good as, or better at discriminating postural sway differences between populations with and without balance deficits and between tasks requiring different levels of balance control.;A wireless tri-axial accelerometer has recently come on the market that is smaller, less expensive, and more sensitive than those previously utilized in postural control studies. However, no reliability or validity studies on this device exist. Therefore, we aimed to assess the new accelerometer's 1) test-retest reliability, 2) ability to discriminate between tasks with differing sensory conditions (i.e., visual and somatosensory), 3) ability to discriminate between individuals who are fallers versus non-fallers , and 4) and its concurrent validity with other fall risk screening tools in older adult populations.;Twenty healthy and independent living older adults (mean age 81+/-4 years; 8 male and 12 female) participated in the reliability and balance task discrimination study. An accelerometer was taped to the lower back of the participant with a gait belt positioned just below. Participants completed three 30-second trials of the four classic Romberg conditions (standing on a firm or compliant surface with eyes open or closed) in random order. Following a 20 minute rest, participants underwent a second block of testing for a total of 24 trials. Raw data was collected at approximately 250 Hz and low-pass filtered at 55Hz. Data were transformed to correct for pelvic tilt and adjust for low frequency. Following processing of raw data, root mean squared (RMS), with the unit gravity (g), for the anterior-posterior (A-P) and mediolateral (M-L) acceleration data was calculated. Intraclass Correlation Coefficients (ICC) were used to test for reliability, while repeated measures analysis of variance (ANOVA) models were used to test for a main effect of balance condition on the A-P and M-L acceleration RMS.;To validate the accelerometer-based balance assessment (ABA) as a fall risk screening tool, we recruited 95 healthy older adults (mean age 86+/-6 years) residing in five different independent living facilities. Participants reported the number of falls they had in the previous six months prior to testing. Participants then completed, in random order, the Berg Balance Scale (BBS), Timed up-and-go (TUG), Activities-specific Balance Confidence (ABC) scale, and the ABA. The ABA consisted of the same four Romberg conditions used in the reliability assessment with and without a cognitive task (counting backward by 3's) for a total of eight balance conditions. The best attempt of two successful trials (the one with the lowest RMS values) for each condition was included in the data analysis. The fall risk discriminative power of various combinations of the TUG, BBS, ABC, and/or the ABA was evaluated using logistic regression and chi-square analyses. Spearman's rank correlation coefficients were used to investigate the relationship between RMS, BBS, and the ABC scale measures. Pearson's product-moment correlation was used to determine the relationship between RMS and TUG scores.;ICCs were all good to excellent with values ranging from 0.736 to 0.972 for trial-to- trial and from 0.760 to 0.954 for block-to-block. There was a significant stepwise increase in A-P and M-L acceleration RMS from conditions 1 to 4. With respect to A-P sway, the mean acceleration RMS increases from conditions 1 to 2, 2 to 3, and 3 to 4 were 0.0031}0.0008g, 0.0035}0.0011g, and 0.0075}0.0022g, respectively. Similarly, the M-L mean acceleration RMS increased significantly from conditions 1 to 2, 2 to 3, and 3 to 4 (0.0025}0.0007g, 0.0068}0.0010g, and 0.0084}0.0018g, respectively). A-P and M-L acceleration RMS were statistically similar when standing on a firm surface. However, M-L acceleration RMS significantly exceeded A-P for condition 3 and condition 4.;For the prediction of fall risk, all prediction models with the ABA, alone or in combination with the TUG, BBS, and ABC scale, had AUC's ≥ 0.80. Models without the ABA had AUC's in the range of 0.45 to 0.75.;In summary, the accelerometer exhibited good to excellent trial-to-trial and block-to- block reliability. The accelerometer was also able to discriminate between visual and supporting surface conditions and acceleration axes. Though not significantly correlated with the clinical tests, the ABA alone was better than the TUG, BBS, and/or ABC at discriminating fallers from non-fallers. (Abstract shortened by UMI.).
机译：由于身体的不稳定特性，在静态姿势期间，姿势摇摆会自发发生。在平衡功能障碍中，通常是正常衰老过程的结果，这种摇摆的幅度和频率可能会超过稳定性极限并导致跌倒。因此，开发可靠且有效的工具以评估姿势摇摆和跌倒风险很重要。与测力板压力中心（COP）测量（最常用的姿势摇动评估工具之一）相比，加速度计在区分有无平衡差和没有平衡差的人群之间以及需要执行的任务之间的姿势摇动差异方面表现出色，甚至更好。不同级别的平衡控制。无线三轴加速度计最近上市，它比以前在姿势控制研究中使用的那些更小，更便宜，更灵敏。但是，不存在对该设备的可靠性或有效性研究。因此，我们旨在评估新的加速度计的性能：1）重测可靠性，2）区分具有不同感官条件（即视觉和体感）的任务的能力，3）区分跌倒者与非跌倒者的能力， 4）及其与其他跌倒风险筛查工具在老年人群中的并发有效性。；二十名健康独立生活的老年人（平均年龄81 +/- 4岁；男性8位，女性12位）参与了可靠性和平衡任务歧视研究。加速度计被绑在参与者的下背部，步态带位于正下方。参与者以随机顺序完成了四个经典Romberg条件（站在坚硬或顺从的表面，睁开或闭着眼睛）的三项30秒试验。休息20分钟后，参与者进行了第二次测试，共进行了24次试验。以大约250 Hz的频率收集原始数据，并以55Hz的频率进行低通滤波。转换数据以校正骨盆倾斜并调整低频。处理原始数据后，计算前后（A-P）和中外侧（M-L）加速度数据的均方根（RMS）和单位重力（g）。使用类内相关系数（ICC）来检验可靠性，同时使用重复测量方差分析（ANOVA）模型来检验平衡条件对AP和ML加速度RMS的主要影响。;以验证基于加速度计的平衡评估（ABA）作为跌落风险筛查工具，我们招募了95位健康的老年人（平均年龄86 +/- 6岁），他们住在五个不同的独立生活设施中。参与者报告了他们在测试前六个月中跌倒的次数。然后，参与者以随机顺序完成了Berg平衡量表（BBS），定时向上（TUG），特定于活动的平衡信心量表（ABC）和ABA。 ABA包括可靠性评估中使用的相同的四个Romberg条件，带有和不带有认知任务（倒数为3），总共八个平衡条件。在每种情况下，两次成功试验（RMS值最低的试验）的最佳尝试包括在数据分析中。使用逻辑回归和卡方分析评估了TUG，BBS，ABC和/或ABA各种组合的跌倒风险判别力。 Spearman等级相关系数用于调查RMS，BBS和ABC量表之间的关系。 Pearson的乘积矩相关性用于确定RMS与TUG得分之间的关​​系。ICC的优劣各异，试验间值范围从0.736至0.972，逐组范围从0.760至0.954。从条件1到4，AP和ML加速度RMS显着逐步增加。相对于AP摇摆，从条件1到2，2至3和3到4的平均加速度RMS分别为0.0031} 0.0008g，0.0035分别为} 0.0011g和0.0075} 0.0022g。同样，M-L平均加速度RMS从条件1到2、2到3和3到4显着增加（分别为0.0025} 0.0007g，0.0068} 0.0010g和0.0084} 0.0018g）。站在坚固的表面上时，A-P和M-L加速度RMS在统计上相似。但是，对于条件3和条件4，M-L加速度RMS显着超过A-P。;对于跌倒风险的预测，所有单独使用ABA或与TUG，BBS和ABC量表结合使用的ABA预测模型的AUC均≥0.80。没有ABA的模型的AUC在0.45至0.75范围内。总而言之，该加速度计表现出良好的试验间和块对块可靠性。加速度计还能够区分视觉和支撑表面状况以及加速度轴。尽管与临床测试无显着相关性，但单独的ABA优于TUG，BBS，和/或ABC区分法人与非法人。 （摘要由UMI缩短。）。

著录项

  • 作者

    Saunders, Nathan William.;

  • 作者单位

    The Ohio State University.;

  • 授予单位 The Ohio State University.;
  • 学科 Biomechanics.;Physical therapy.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 122 p.
  • 总页数 122
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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