Department of Radiologic Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand.
Research Administration, Academic Services and International Relations Section, Faculty of Engineering, Chiang Mai University, Chiang Mai, Thailand.
ScientificWorldJournal. 2022 Jun 22;2022:9483665. doi: 10.1155/2022/9483665. eCollection 2022.
Postural sway indicates controlling stability in response to standing balance perturbations and determines risk of falling. In order to assess balance and postural sway, costly laboratory equipment is required, making it impractical for clinical settings. The study aimed to develop a triaxial inertial sensor and apply machine learning (ML) algorithms for predicting trajectory of the center of pressure (COP) path of postural sway. Fifty-three healthy adults, with a mean age of 46 years, participated. The inertial sensor prototype was investigated for its concurrent validity relative to the COP path length obtained from the force platform measurement. Then, ML was applied to predict the COP path by using sensor-sway metrics as the input. The results of the study revealed that all variables from the sensor prototype demonstrated high concurrent validity against the COP path from the force platform measurement ( > 0.75; < 0.001). The agreement between sway metrics, derived from the sensor and ML algorithms, illustrated good to excellent agreement (ICC; 0.89-0.95) between COP paths from the sensor metrics, with respect to the force plate measurement. This study demonstrated that the inertial sensor, in comparison to the standard tool, would be an option for balance assessment since it is of low-cost, conveniently portable, and comparable to the accuracy of standard force platform measurement.
姿势摆动表示在应对站立平衡干扰时的控制稳定性，并确定跌倒的风险。为了评估平衡和姿势摆动，需要使用昂贵的实验室设备，因此在临床环境中不切实际。本研究旨在开发三轴惯性传感器，并应用机器学习 (ML) 算法来预测姿势摆动的重心 (COP) 轨迹。53 名健康成年人参与了研究，平均年龄为 46 岁。研究了惯性传感器原型，以评估其与力台测量得到的 COP 路径长度的同时效度。然后，应用 ML 通过使用传感器摆动指标作为输入来预测 COP 路径。研究结果表明，传感器原型的所有变量均与力台测量的 COP 路径具有高度的同时效度（>0.75；<0.001）。传感器和 ML 算法得出的摆动指标之间的一致性表明，传感器指标的 COP 路径与力板测量之间具有良好到极好的一致性（ICC；0.89-0.95）。本研究表明，与标准工具相比，惯性传感器将是一种平衡评估的选择，因为它具有低成本、便携且与标准力台测量的准确性相当。
