Digital Health Center, Hasso Plattner Institute, University of Potsdam, 14482 Potsdam, Germany.
NETLAB, Department of Computer Engineering, Bogazici University, 34342 Istanbul, Turkey.
Sensors (Basel). 2020 Jul 22;20(15):4090. doi: 10.3390/s20154090.
Inertial measurement units (IMUs) are commonly used for localization or movement tracking in pervasive healthcare-related studies, and gait analysis is one of the most often studied topics using IMUs. The increasing variety of commercially available IMU devices offers convenience by combining the sensor modalities and simplifies the data collection procedures. However, selecting the most suitable IMU device for a certain use case is increasingly challenging. In this study, guidelines for IMU selection are proposed. In particular, seven IMUs were compared in terms of their specifications, data collection procedures, and raw data quality. Data collected from the IMUs were then analyzed by a gait analysis algorithm. The difference in accuracy of the calculated gait parameters between the IMUs could be used to retrace the issues in raw data, such as acceleration range or sensor calibration. Based on our algorithm, we were able to identify the best-suited IMUs for our needs. This study provides an overview of how to select the IMUs based on the area of study with concrete examples, and gives insights into the features of seven commercial IMUs using real data.
惯性测量单元（IMU）常用于普及医疗保健相关研究中的定位或运动跟踪，而使用 IMU 进行步态分析是最常研究的课题之一。越来越多的商业可用的 IMU 设备通过组合传感器模式提供了便利性，并简化了数据采集过程。然而，为特定用例选择最合适的 IMU 设备变得越来越具有挑战性。在本研究中，提出了 IMU 选择的指南。特别是，从规格、数据采集过程和原始数据质量方面对七台 IMU 进行了比较。然后，通过步态分析算法分析从 IMU 收集的数据。计算出的步态参数之间的差异可以用来追溯原始数据中的问题，例如加速度范围或传感器校准。基于我们的算法，我们能够确定最适合我们需求的 IMU。本研究通过具体示例概述了如何根据研究领域选择 IMU，并使用实际数据深入了解七台商业 IMU 的特点。
