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基于带有漂移校正技术的推算法的单惯性传感器上肢位置跟踪。

Upper Limb Position Tracking with a Single Inertial Sensor Using Dead Reckoning Method with Drift Correction Techniques.

机构信息

School of Computing, Ulster University, Belfast BT15 1ED, UK.

School of Engineering, University of Kent, Canterbury CT2 7NZ, UK.

出版信息

Sensors (Basel). 2022 Dec 29;23(1):360. doi: 10.3390/s23010360.

Abstract

Inertial sensors are widely used in human motion monitoring. Orientation and position are the two most widely used measurements for motion monitoring. Tracking with the use of multiple inertial sensors is based on kinematic modelling which achieves a good level of accuracy when biomechanical constraints are applied. More recently, there is growing interest in tracking motion with a single inertial sensor to simplify the measurement system. The dead reckoning method is commonly used for estimating position from inertial sensors. However, significant errors are generated after applying the dead reckoning method because of the presence of sensor offsets and drift. These errors limit the feasibility of monitoring upper limb motion via a single inertial sensing system. In this paper, error correction methods are evaluated to investigate the feasibility of using a single sensor to track the movement of one upper limb segment. These include zero velocity update, wavelet analysis and high-pass filtering. The experiments were carried out using the nine-hole peg test. The results show that zero velocity update is the most effective method to correct the drift from the dead reckoning-based position tracking. If this method is used, then the use of a single inertial sensor to track the movement of a single limb segment is feasible.

摘要

惯性传感器广泛应用于人体运动监测。在运动监测中,最常用的两个测量指标是方向和位置。使用多个惯性传感器进行跟踪是基于运动学建模的,当应用生物力学约束时,该建模可以达到较高的精度。最近,人们越来越关注使用单个惯性传感器进行跟踪运动,以简化测量系统。惯导方法常用于从惯性传感器估计位置。然而,由于传感器的偏差和漂移,惯导方法应用后会产生较大的误差,这限制了通过单个惯性传感系统监测上肢运动的可行性。本文评估了误差修正方法,以研究使用单个传感器来跟踪一个上肢段运动的可行性。这些方法包括零速度更新、小波分析和高通滤波。实验采用九孔钉测试进行。结果表明,零速度更新是修正基于惯导的位置跟踪漂移最有效的方法。如果使用这种方法,那么使用单个惯性传感器来跟踪单个肢体段的运动是可行的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/456f/9823748/8c228e3a31c8/sensors-23-00360-g001.jpg

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