On the Orientation Error of IMU: Investigating Static and Dynamic Accuracy Targeting Human Motion.

Luca Ricci,Domenico Formica,Fabrizio Taffoni,Christof Markus Aegerter

doi:10.1371/journal.pone.0161940

Abstract

The accuracy in orientation tracking attainable by using inertial measurement units (IMU) when measuring human motion is still an open issue. This study presents a systematic quantification of the accuracy under static conditions and typical human dynamics, simulated by means of a robotic arm. Two sensor fusion algorithms, selected from the classes of the stochastic and complementary methods, are considered. The proposed protocol implements controlled and repeatable experimental conditions and validates accuracy for an extensive set of dynamic movements, that differ in frequency and amplitude of the movement. We found that dynamic performance of the tracking is only slightly dependent on the sensor fusion algorithm. Instead, it is dependent on the amplitude and frequency of the movement and a major contribution to the error derives from the orientation of the rotation axis w.r.t. the gravity vector. Absolute and relative errors upper bounds are found respectively in the range [0.7° ÷ 8.2°] and [1.0° ÷ 10.3°]. Alongside dynamic, static accuracy is thoroughly investigated, also with an emphasis on convergence behavior of the different algorithms. Reported results emphasize critical issues associated with the use of this technology and provide a baseline level of performance for the human motion related application.

Highlights

Human kinematic tracking by means of wearable inertial measurement units (IMU) sensors that are directly attached to the body is emerging as a promising alternative to stereophotogrammetry based systems
This paper presented a systematic study of IMU accuracy in measuring the orientation for a static and a range of dynamic movements with a bandwidth typically found in human motion doi:10.1371/journal.pone.0161940.g007
The protocol we devised exploits the benefits of the first approach by using a robotic platform, which guarantees controlled and repeatable experimental conditions, while selecting dynamic sinusoidal movements in the bandwidth of human motion

Summary

Introduction

Human kinematic tracking by means of wearable IMU sensors that are directly attached to the body is emerging as a promising alternative to stereophotogrammetry based systems (ranked as the gold standard). An IMU comprises tri–axial accelerometers and gyroscopes and is typically coupled with a magnetic flux sensor. Sensor fusion of the IMU readings allow measuring 3D orientation with respect to a fixed system of coordinates [1]. When an IMU is firmly attached to a human body segment, it is possible to obtain an estimate of its absolute orientation. When multiple IMUs are attached to different body segments their relative orientation can be combined to measure human motion [2]. Extensive research effort within this specific field of application has been committed to: the investigation of new sensor

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Conclusion