scholarly journals Joint angle tracking with inertial sensors

Author(s):  
Mahmoud El-Gohary ◽  
Sean Pearson ◽  
James McNames
Author(s):  
Vishesh Vikas ◽  
Carl D. Crane

Knowledge of joint angles, angular velocities is essential for control of link mechanisms and robots. The estimation of joint angles and angular velocity is performed using combination of inertial sensors (accelerometers and gyroscopes) which are contactless and flexible at point of application. Different estimation techniques are used to fuse data from different inertial sensors. Bio-inspired sensors using symmetrically placed multiple inertial sensors are capable of instantaneously measuring joint parameters (joint angle, angular velocities and angular acceleration) without use of any estimation techniques. Calibration of inertial sensors is easier and more reliable for accelerometers as compared to gyroscopes. The research presents gyroscope-less, multiple accelerometer and magnetometer based sensors capable of measuring (not estimating) joint parameters. The contribution of the improved sensor are four-fold. Firstly, the inertial sensors are devoid of symmetry constraint unlike the previously researched bio-inspired sensors. However, the accelerometer are non-coplanarly placed. Secondly, the accelerometer-magnetometer combination sensor allows for calculation of a unique rotation matrix between two link joined by any kind of joint. Thirdly, the sensors are easier to calibrate as they consist only of accelerometers. Finally, the sensors allow for calculation of angular velocity and angular acceleration without use of gyroscopes.


2018 ◽  
Vol 10 (02) ◽  
pp. 1840008
Author(s):  
Alberto López-Delis ◽  
Cristiano J. Miosso ◽  
João L. A. Carvalho ◽  
Adson F. da Rocha ◽  
Geovany A. Borges

Information extracted from the surface electromyographic (sEMG) signals can allow for the detection of movement intention in transfemoral prostheses. The sEMG can help estimate the angle between the femur and the tibia in the sagittal plane. However, algorithms based exclusively on sEMG information can lead to inaccurate results. Data captured by inertial-sensors can improve this estimate. We propose three myoelectric algorithms that extract data from sEMG and inertial sensors using Kalman-filters. The proposed fusion-based algorithms showed improved performance compared to methods based exclusively on sEMG data, generating improvements in the accuracy of knee joint angle estimation and reducing estimation artifacts.


Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2975 ◽  
Author(s):  
Chingszu Lin ◽  
Masako Kanai-Pak ◽  
Jukai Maeda ◽  
Yasuko Kitajima ◽  
Mitsuhiro Nakamura ◽  
...  

Currently, due to shortages in the nursing faculty and low access to actual patients, it is difficult for students to receive feedback from teachers and practice with actual patients to obtain clinic experience. Thus, both evaluation systems and simulated patients have become urgent requirements. Accordingly, this study proposes a method to evaluate the nurse’s transfer skill through observation from the patient. After verifying the proposed method, it will be integrated with a robotic patient as a future work. To verify if such an evaluation is practical, a checklist comprising 16 steps with correct and incorrect methods was proposed by the nursing teachers. Further, the evaluation parameters were determined as translational acceleration, rotational speed, and joint angle of patient. Inertial sensors and motion capture were employed to measure the translational acceleration, rotational speed, and joint angle. An experiment was conducted with two nursing teachers, who were asked to carry out both correct and incorrect methods. According to the results, three parameters reveal the difference for a patient under correct/incorrect methods and can further be used to evaluate the nurse’s skill once the thresholds are determined. In addition, the applicability of inertial sensors is confirmed for the use of robot development.


Sign in / Sign up

Export Citation Format

Share Document