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

机译:穿戴式测角仪和加速度计感觉融合在日常生活中的膝关节角度测量

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摘要

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.
机译:人体运动分析对于广泛的应用和学科至关重要。低成本和不显眼的动态检测系统的开发和验证仍然是一个未解决的问题。惯性测量系统和电子纺织传感器正在成为日常生活中的潜在技术。我们开发了一种创新的传感概念并对其进行了初步评估,该传感概念将电子纺织物和三轴加速度计结合在一起用于动态人体运动分析。我们的感官融合方法基于卡尔曼滤波技术,并结合了纺织品电动测角仪和加速度计的输出,而无需对初始加速度计的位置和方向进行任何假设。我们使用我们的技术来测量不同运动任务(单足屈曲和以不同速度行走)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,并且可以可靠地执行所有各种任务(均方根误差的均值和标准偏差分别为1.96和0.96 ) 。另外,与分别考虑的纺织品测角仪和加速度计得出的估计相比,该方法在角度估计上显示出显着的改进。在以后的工作中,我们将把这种方法扩展到更复杂和多自由度的关节上。

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