Ambulatory measurement and analysis of the lower limb 3D posture using wearable sensor system
ABSTRACT An original approach for ambulatory measurement and analysis of lower limb 3D gait posture was presented, and a wearable sensor system was developed according to the approach. To explicate the lower limb posture, thigh orientation angles were calculated based on a virtual sensor at the hip joint and double analog inertial sensors (MAG3) on the thigh; Knee joint angle in sagittal plane was calculated with combination of angular accelerations and angular velocities measured by two MAG3 on the thigh and shank on the basis of the virtual-sensor based algorithm. The developed wearable sensor system was evaluated on the lower limb. Without integration of angular acceleration or angular velocity for the thigh orientation angles and the knee joint angle, the calculated result was not distorted by offset and drift. Using virtual sensors at the hip joint and the knee joint were more simple, practical and effective than fixing physical sensors at these joints. Compared with the result from the reference system, the measured result with the developed wearable sensor system was feasible to do gait analysis for the patients in the daily life, and the method can also be used in other conditions such as measuring rigid segment posture with less sensors and high degree of accuracy.
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ABSTRACT: This contribution is concerned with joint angle calculation based on inertial measurement data in the context of human motion analysis. Unlike most robotic devices, the human body lacks even surfaces and right angles. Therefore, we focus on methods that avoid assuming certain orientations in which the sensors are mounted with respect to the body segments. After a review of available methods that may cope with this challenge, we present a set of new methods for: (1) joint axis and position identification; and (2) flexion/extension joint angle measurement. In particular, we propose methods that use only gyroscopes and accelerometers and, therefore, do not rely on a homogeneous magnetic field. We provide results from gait trials of a transfemoral amputee in which we compare the inertial measurement unit (IMU)-based methods to an optical 3D motion capture system. Unlike most authors, we place the optical markers on anatomical landmarks instead of attaching them to the IMUs. Root mean square errors of the knee flexion/extension angles are found to be less than 1° on the prosthesis and about 3° on the human leg. For the plantar/dorsiflexion of the ankle, both deviations are about 1°.Sensors 04/2014; 14(4):6891-909. · 2.05 Impact Factor
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ABSTRACT: We consider 6d inertial measurement units (IMU) attached to rigid bodies, e.g. human limb segments or links of a robotic manipulator, which are connected by hinge joints and spheroidal joints. Novel methods for joint axis estimation and joint position estimation are presented that exploit the kinematic constraints induced by these two types of joints. The presented methods do not require any knowledge about the sensor units' positions or orientations and do not include integration, i.e. they are insensitive to measurement bias. By means of a three-links simulation model, the estimation algorithms are validated and convergence is analyzed. Finally, the algorithms are tested using experimental data from IMU-based human gait analysis.Control Applications (CCA), 2012 IEEE International Conference on; 01/2012
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ABSTRACT: The current trends in wearable sensor technology suggest that, in the next decade or so, garments will commonly include some form of biometric/biopotential measurement system and will be of great value for gathering ambulatory metadata for remote diagnosis. In parallel, the introduction of new powerful mixed-signal devices will enhance the possibility of garments including cost-effective biopotential measurements, over the classical analog signal conditioning configurations. This paper presents the use of a recently introduced ASIC device (ADS1298) for measuring ECG, EEG and EMG data, towards developing a multimodal biopotential measurement system. Two programmable analog filter configurations are tested for comparison. The results show that adjusting the analog filters to accommodate different biopotentials is an unfeasible task in comparison with the ASIC device, which proved useful for measuring common biopotentials: ECG, EMG and EEG, and thus is more suitable for wearable sensor applications.Electronics, Robotics and Automotive Mechanics Conference (CERMA), 2012 IEEE Ninth; 01/2012