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用于日常生活中膝关节角度测量的可穿戴测角仪与加速度计传感融合

Wearable Goniometer and Accelerometer Sensory Fusion for Knee Joint Angle Measurement in Daily Life.

作者信息

Tognetti Alessandro, Lorussi Federico, Carbonaro Nicola, de Rossi Danilo

机构信息

Research Center E.Piaggio, University of Pisa, Largo L. Lazzarino 1, 56126 Pisa, Italy.

Information Engineering Department, University of Pisa, Via G. Caruso 16, 56122 Pisa, Italy.

出版信息

Sensors (Basel). 2015 Nov 11;15(11):28435-55. doi: 10.3390/s151128435.

Abstract

Human motion analysis is crucial for a wide range of applications and disciplines. The development and validation of low cost and unobtrusive sensing systems for ambulatory motion detection is still an open issue. Inertial measurement systems and e-textile sensors are emerging as potential technologies for daily life situations. We developed and conducted a preliminary evaluation of an innovative sensing concept that combines e-textiles and tri-axial accelerometers for ambulatory human motion analysis. Our sensory fusion method is based on a Kalman filter technique and combines the outputs of textile electrogoniometers and accelerometers without making any assumptions regarding the initial accelerometer position and orientation. We used our technique to measure the flexion-extension angle of the knee in different motion tasks (monopodalic flexions and walking at different velocities). The estimation technique was benchmarked against a commercial measurement system based on inertial measurement units and performed reliably for all of the various tasks (mean and standard deviation of the root mean square error of 1:96 and 0:96, respectively). In addition, the method showed a notable improvement in angular estimation compared to the estimation derived by the textile goniometer and accelerometer considered separately. In future work, we will extend this method to more complex and multi-degree of freedom joints.

摘要

人体运动分析对于广泛的应用和学科至关重要。开发和验证用于动态运动检测的低成本、非侵入式传感系统仍然是一个未解决的问题。惯性测量系统和电子织物传感器正在成为适用于日常生活场景的潜在技术。我们开发并进行了一项创新传感概念的初步评估,该概念结合了电子织物和三轴加速度计用于动态人体运动分析。我们的传感融合方法基于卡尔曼滤波技术,结合了纺织电子测角仪和加速度计的输出,而无需对加速度计的初始位置和方向做任何假设。我们使用该技术测量不同运动任务(单脚站立弯曲和不同速度行走)中膝盖的屈伸角度。该估计技术以基于惯性测量单元的商业测量系统为基准进行测试,并且在所有各种任务中都可靠运行(均方根误差的均值和标准差分别为1.96和0.96)。此外,与分别考虑纺织测角仪和加速度计得出的估计相比,该方法在角度估计方面有显著改进。在未来的工作中,我们将把这种方法扩展到更复杂和多自由度的关节。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4589/4701288/3cdbfaa58d3d/sensors-15-28435-g001.jpg

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