Prato Thomas A, Lynall Robert C, Howell David R, Lugade Vipul
UGA Biomechanics Laboratory, Department of Kinesiology, University of Georgia, Athens, GA, USA.
Sports Medicine Center, Department of Orthopedics, University of Colorado Anschutz Medical Campus and Children's Hospital Colorado, Aurora, CO, USA.
J Sport Rehabil. 2024 Nov 18;34(2):177-183. doi: 10.1123/jsr.2024-0072. Print 2025 Feb 1.
Clinical balance assessments vary in reliability due to subjectivity in their scoring. A valid and objective accelerometer-based smartphone evaluation could benefit patients, clinicians, and researchers.
Our objective was to assess the validity and reliability of smartphone-based standing balance.
A repeated-measures study was conducted with 23 healthy young adult participants across 2 sessions ∼7 days apart.
Participants completed 30-second standing trials during tandem-stance eyes-open, tandem-stance eyes-closed, single-leg eyes-open, and single-leg eyes-closed conditions. Android and iOS smartphones were placed vertically on the lower back via a belt with 3 retroreflective markers attached and tracked by an 8-camera motion capture system. Sway path, range, and area were calculated from smartphone accelerometer and marker data. We assessed reliability using intraclass correlation coefficients (ICC[2,k]) and validity using Pearson r correlations between the marker and smartphones from visit 1.
Across eyes-open conditions, Android (ICC = .84-.96), iOS (ICC = .82-.98), and marker-based (ICC = .84-.95) assessments demonstrated good to excellent reliability. Across eyes-closed conditions, Android (ICC = .41-.87), iOS (ICC = .34-.79), and marker-based (ICC = .31-.87) assessments demonstrated poor to good reliability. Correlations between smartphones and the marker data were moderate to very high (r = .56-.97).
The smartphone-based assessment was valid and reliable, indicating that clinicians and researchers can implement this method to measure balance with the opportunity for remote administration and increased patient tracking across various recovery timepoints.
由于临床平衡评估在评分上存在主观性，其可靠性各不相同。基于加速度计的有效且客观的智能手机评估可能会使患者、临床医生和研究人员受益。
我们的目的是评估基于智能手机的站立平衡的有效性和可靠性。
对23名健康的年轻成年参与者进行了重复测量研究，分两个阶段进行，间隔约7天。
参与者在睁眼串联站立、闭眼串联站立、睁眼单腿站立和闭眼单腿站立条件下完成30秒的站立试验。安卓和iOS智能手机通过一条系有3个反光标记的腰带垂直放置在下背部，并由一个8摄像头运动捕捉系统进行跟踪。根据智能手机加速度计和标记数据计算摆动路径、范围和面积。我们使用组内相关系数（ICC[2,k]）评估可靠性，并使用第一次就诊时标记与智能手机之间的Pearson r相关性评估有效性。
在睁眼条件下，安卓（ICC =.84-.96）、iOS（ICC =.82-.98）和基于标记的（ICC =.84-.95）评估显示出良好到优秀的可靠性。在闭眼条件下，安卓（ICC =.41-.87）、iOS（ICC =.34-.79）和基于标记的（ICC =.31-.87）评估显示出较差到良好的可靠性。智能手机与标记数据之间的相关性为中等至非常高（r =.56-.97）。
基于智能手机的评估是有效且可靠的，这表明临床医生和研究人员可以采用这种方法来测量平衡，并且有机会进行远程管理并在不同恢复时间点增加对患者的跟踪。
