scholarly journals Extraction of Parameters for 90-degree Turn Prediction Using the IMU-based Motion Capture System

2021 ◽  
Keyword(s):  
Motion Capture ◽  
Inertial Measurement Unit ◽  
Prediction Method ◽  
Measurement Unit ◽  
Motion Capture System ◽  
Living Space ◽  
Turning Motion ◽  
Home Robot ◽  
And Behavior ◽  
Prediction Parameters

Abstract. Against the increasing number of single households, we have been proposing the “Biofied Building” that provides a safe, secure, and comfortable living space for a resident using a small home robot. The robot can be used for real-time sensing of the resident’s position and behavior. On the other hand, for further use of the robot, such as choosing a path that does not disturb the resident, a phase to predict the resident’s behavior is necessary. Walking, which is one of the most basic activities of daily living, is often targeted in studies of motion prediction. However, most of them deal with steady walking, even though walking in daily life includes unsteady walking such as the turning motion. Therefore, the purpose of this study was to extract the prediction parameters to construct a prediction method for the unsteady 90-degree turn. In this study, we explored the effective prediction parameters for 90-degree turns based on the measured data using the inertial measurement unit (IMU) based motion capture system aiming to introduce the prediction of unsteady walking to the “Biofied Building”.

scholarly journals Quaternion-Based Local Frame Alignment between an Inertial Measurement Unit and a Motion Capture System

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 4003 ◽  
Author(s):  
Jung Keun Lee ◽  
Woo Chang Jung
Keyword(s):  
Angular Velocity ◽  
Motion Capture ◽  
Inertial Measurement Unit ◽  
Least Squares Method ◽  
Measurement Unit ◽  
Motion Capture System ◽  
Inertial Measurement ◽  
Local Frame ◽  
Velocity Transformation ◽  
Frame Alignment

Local frame alignment between an inertial measurement unit (IMU) system and an optical motion capture system (MCS) is necessary to combine the two systems for motion analysis and to validate the accuracy of IMU-based motion data by using references obtained through the MCS. In this study, we propose a new quaternion-based local frame alignment method where equations of angular velocity transformation are used to determine the frame alignment orientation in the form of quaternion. The performance of the proposed method was compared with those of three other methods by using data with different angular velocities, noises, and alignment orientations. Furthermore, the effects of the following three factors on the estimation performance were investigated for the first time: (i) transformation concept, i.e., angular velocity transformation vs. angle transformation; (ii) orientation representations, i.e., quaternion vs. direction cosine matrix (DCM); and (iii) applied solvers, i.e., nonlinear least squares method vs. least squares method through pseudoinverse. Within our limited test data, we obtained the following results: (i) the methods using angular velocity transformation were better than the method using angle transformation; (ii) the quaternion is more suitable than the DCM; and (iii) the applied solvers were not critical in general. The proposed method performed the best among the four methods. We surmise that the fewer number of components and constraints of the quaternion in the proposed method compared to the number of components and constraints of the DCM-based methods may result in better accuracy. Owing to the high accuracy and easy setup, the proposed method can be effectively used for local frame alignment between an IMU and a motion capture system.

scholarly journals Comparison of a New Inertial Sensor Based System with an Optoelectronic Motion Capture System for Motion Analysis of Healthy Human Wrist Joints

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5297 ◽  
Author(s):  
Michael Alexander Wirth ◽  
Gabriella Fischer ◽  
Jorge Verdú ◽  
Lisa Reissner ◽  
Simone Balocco ◽  
...  
Keyword(s):  
Range Of Motion ◽  
Motion Capture ◽  
Inertial Measurement Unit ◽  
Absolute Difference ◽  
Measurement Unit ◽  
Good Precision ◽  
Motion Capture System ◽  
Ulnar Deviation ◽  
Inertial Measurement ◽  
Flexion Extension

This study aims to compare a new inertial measurement unit based system with the highly accurate but complex laboratory gold standard, an optoelectronic motion capture system. Inertial measurement units are sensors based on accelerometers, gyroscopes, and/or magnetometers. Ten healthy subjects were recorded while performing flexion-extension and radial-ulnar deviation movements of their right wrist using inertial sensors and skin markers. Maximum range of motion during these trials and mean absolute difference between the systems were calculated. A difference of 10° ± 5° for flexion-extension and 2° ± 1° for radial-ulnar deviation was found between the two systems with absolute range of motion values of 126° and 50° in the respective axes. A Wilcoxon rank sum test resulted in a no statistical differences between the systems with p-values of 0.24 and 0.62. The observed results are even more precise than reports from previous studies, where differences between 14° and 27° for flexion-extension and differences between 6° and 17° for radial-ulnar deviation were found. Effortless and fast applicability, good precision, and low inter-observer variability make inertial measurement unit based systems applicable to clinical settings.

scholarly journals Estimation of the External Knee Adduction Moment during Gait Using an Inertial Measurement Unit in Patients with Knee Osteoarthritis

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1418
Author(s):  
Yu Iwama ◽  
Kengo Harato ◽  
Shu Kobayashi ◽  
Yasuo Niki ◽  
Naomichi Ogihara ◽  
...  
Keyword(s):  
Knee Osteoarthritis ◽  
Motion Capture ◽  
Inertial Measurement Unit ◽  
Knee Adduction Moment ◽  
Measurement Unit ◽  
Motion Capture System ◽  
Medial Knee ◽  
Inertial Measurement ◽  
Knee Oa ◽  
External Knee Adduction Moment

Although the external knee adduction moment (KAM) during gait was shown to be a quantitative parameter of medial knee osteoarthritis (OA), it requires expensive equipment and a dedicated large space to measure. Therefore, it becomes a major reason to limit KAM measurement in a clinical environment. The purpose of this study was to estimate KAM using a single inertial measurement unit (IMU) during gait in patients with knee OA. A total of 22 medial knee OA patients (44 knee joints) performed conventional gait analysis using three-dimensional (3D) motion capture system. At the same time, we attached commercial IMUs to six body segments (sternum, pelvis, both thighs, and both shanks), and IMU signals during gait were recorded synchronized with the motion capture system. The peak-to-peak difference of acceleration in the lateral/medial axis immediately after heel contact was defined as the thrust acceleration (TA). We hypothesized that TA would represent the lateral thrust of the knee during the stance phase and correlate with the first peak of KAM. The relationship between the peak KAM and TA of pelvis (R = 0.52, p < 0.001), shanks (R = 0.57, p < 0.001) and thighs (R = 0.49, p = 0.001) showed a significant correlation. The root mean square error (RMSE) of linear regression models of pelvis, shanks, and thighs to estimate KAM were 0.082, 0.079, and 0.084 Nm/(kg·m), respectively. Our newly established parameter TA showed a moderate correlation with conventional KAM. The current study confirmed our hypothesis that a single IMU would predict conventional KAM during gait. Since KAM is known as an indicator for prognosis and severity of knee OA, this new parameter has the potential to become an accessible predictor for medial knee OA instead of KAM.

Design and Optimization of a Master-Slave System for Tele-Echography Application

2012 ◽  
Author(s):  
T. Essomba ◽  
M. A. Laribi ◽  
J. P. Gazeau ◽  
G. Poisson ◽  
S. Zeghloul
Keyword(s):  
Motion Capture ◽  
Inertial Measurement Unit ◽  
Control Device ◽  
Measurement Unit ◽  
Motion Capture System ◽  
Design And Optimization ◽  
Real Coded Genetic Algorithm ◽  
Spherical Parallel Mechanism ◽  
Real Patients ◽  
Master Control

This paper introduces the research carried out on the design of a robotized teleechography system. Such a system is composed of a master control device and a slave robotic manipulator. Our objective is to contribute to the French Agence National de Recherche (ANR) project PROSIT by designing both devices. To define the kinematic architecture, we had proposed an approach based on the analysis of the expert gesture as a first step of the design process. We have used a motion capture system to study the ultrasound examination gesture and to define the kinematic specifications for the proposed manipulator. A new kind of architecture was selected: the spherical parallel mechanism (SPM). We have chosen it because it reaches the constraint requirements. The kinematic architecture was synthesized by executing a real-coded genetic algorithm (GA). We integrated optimization criteria in the synthesis of the selected architecture. We have fixed a minimum required workspace and we have chosen to optimized the SPM in terms of dexterity and compacity. Another important part of our research was to design a haptic device to provide a very intuitive control of the tele-operated robot. We have opted for a free hand interface that integrates an active force control and feedback. An Inertial Measurement Unit (IMU) has been integrated. The data collected from the IMU that we integrated are processed by a Kalman Filter. But we have modified this predictor-estimator tool from the state of art to adapt its behavior with respect to the type of motion done by the operator. Experimentations via our motion capture system have demonstrated the accuracy of this orientation control strategy. The final step will be the experimental and clinical validation on real patients.

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