Physical sensor difference-based method and virtual sensor difference-based method for visual and quantitative estimation of lower limb 3D gait posture using accelerometers and magnetometers
Department of Intelligent Mechanical Systems Engineering, Kochi University of Technology, 185 Miyanokuchi, Tosayamada-cho, Kochi 782-8502, Japan.Computer Methods in Biomechanics and Biomedical Engineering (Impact Factor: 1.77). 12/2010; 15(2):203-10. DOI: 10.1080/10255842.2010.522184
An approach using a physical sensor difference-based algorithm and a virtual sensor difference-based algorithm to visually and quantitatively confirm lower limb posture was proposed. Three accelerometers and two MAG(3)s (inertial sensor module) were used to measure the accelerations and magnetic field data for the calculation of flexion/extension (FE) and abduction/adduction (AA) angles of hip joint and FE, AA and internal/external rotation (IE) angles of knee joint; then, the trajectories of knee and ankle joints were obtained with the joint angles and segment lengths. There was no integration of acceleration or angular velocity for the joint rotations and positions, which is an improvement on the previous method in recent literature. Compared with the camera motion capture system, the correlation coefficients in five trials were above 0.91 and 0.92 for the hip FE and AA, respectively, and higher than 0.94, 0.93 and 0.93 for the knee joint FE, AA and IE, respectively.
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ABSTRACT: This paper presents a wearable inertial-sensing-based body sensor network (BSN) composed of two inertial modules that are placed on human upper limb for real-time human motion capture applications. Each inertial module consists of an ARM-based 32-bit microcontroller (MCU), a triaxial accelerometer, a triaxial gyroscope, and a triaxial magnetometer. To estimate shoulder range of motion (ROM), the accelerations, angular velocities, and magnetic signals are collected and processed by a quaternion-based complementary nonlinear filter for minimizing the cumulative errors caused by the intrinsic noise/drift of the inertial sensors. The proposed BSN is a cost-effective tool and can be used anywhere without any external reference device for shoulder ROM. The sensor fusion algorithm can reduce orientation error effectively and thus can assess shoulder joint motions accurately.2013 International Conference on Orange Technologies (ICOT); 03/2013
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