Information signaled by sensory fibers in medial articular nerve

1975 ◽  
Vol 38 (6) ◽  
pp. 1464-1472 ◽  
Author(s):  
F. J. Clark
Keyword(s):  
Knee Joint ◽  
Entire Range ◽  
Joint Angle ◽  
Nerve Fibers ◽  
Pacinian Corpuscle ◽  
Joint Angles ◽  
Discharge Characteristics ◽  
Gentle Pressure ◽  
Sensory Fibers ◽  
Deep Pressure

Responses of 331 individual medial articular nerve fibers innervating the cat knee joint were tested to bending the joint over its entire range and to pressing on the tissues of the joint. The 331 fibers were classified into five groups on the basis of their discharge characteristics: slowly adapting (64), phasic (103), Pacinian corpuscle-like (12), weakly activated (39), and nonactivated (113). Five of the slowly adapting and all twelve of the Pacinian corpuscle-like receptors responded at intermediate joint angles. The remainder responded, if at all, only near the extremes of joint bending or twisting. Many of these same receptors could be activated by pressing about the knee. Sometimes gentle pressure on the focus sufficed to produce a vigorous discharge. The properties of these receptors are considered to be consistent with the hypothesis that articular mechanoreceptors do not signal joint angle but are involved in deep-pressure sensations.

Continuous Estimation Prediction of Knee Joint Angles Using Fusion of Electromyographic and Inertial Sensors for Active Transfemoral Leg Prostheses

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
Keyword(s):  
Knee Joint ◽  
Joint Angle ◽  
Inertial Sensors ◽  
Sagittal Plane ◽  
Joint Angles ◽  
Knee Joint Angle ◽  
Improved Performance ◽  
Continuous Estimation ◽  
Movement Intention ◽  
Semg Signals

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.

scholarly journals A model-free control method for estimating the joint angles of the knee exoskeleton

2018 ◽  
Vol 10 (10) ◽  
pp. 168781401880776 ◽  
Author(s):  
Yan Zhang ◽  
Jianzhou Wang ◽  
Wei Li ◽  
Jie Wang ◽  
Peng Yang
Keyword(s):  
Knee Joint ◽  
Joint Angle ◽  
Control Method ◽  
Sliding Mode ◽  
Control Law ◽  
Joint Angles ◽  
Output Data ◽  
Model Free ◽  
Model Free Control ◽  
Discrete Sliding Mode Control

This article describes a model-free adaptive control method for knee joint exoskeleton, which avoids the complexity of human–exoskeleton modeling. An important feature of the proposed controller is that it uses the input and output data of the knee joint angle to control the exoskeleton. Furthermore, discrete sliding mode control law and prior torque are introduced to improve the accuracy and robustness of the system. Prior torque of knee joint is obtained through the walking simulation of human–exoskeleton modeling. Specially, the experiment is carried out by using the co-simulation automatic dynamic analysis of mechanical systems and MATLAB. Data from these assessments indicate that the proposed strategy enables the knee exoskeleton to track the trajectory of angle well and has a good performance on walking assistance.

scholarly journals Knee joint angle estimation by sequential correction of gyroscope bias

2021 ◽  
Author(s):  
AYUKO SAITO ◽  
YUTAKA TANZAWA ◽  
SATORU KIZAWA
Keyword(s):  
Knee Joint ◽  
Medical Care ◽  
Motion Analysis ◽  
Pose Estimation ◽  
Joint Angle ◽  
Angle Measurement ◽  
Motion Sensors ◽  
Joint Angles ◽  
Knee Joint Angle ◽  
Tangential Acceleration

Abstract Compact and lightweight nine-axis motion sensors have come to be used for motion analysis in a variety of fields such as medical care, welfare, and sports. Nine-axis motion sensors include a three-axis gyroscope, a three-axis accelerometer, and a three-axis magnetometer and can estimate joint angles using the gyroscope outputs. However, the bias of the gyroscope is often unstable depending on the measurement environment and the accuracy of the gyroscope itself, causing error to accumulate in the angle obtained by integrating the gyroscope output. Although several sensor fusions have been proposed for pose estimation, such as using an accelerometer and a magnetometer, sequentially estimating and correcting the bias of the gyroscope are desirable for more accurate pose estimation. In addition, considering accelerations other than the acceleration due to gravity is important for a sensor fusion method that utilizes the accelerometer to correct the gyroscope output. Therefore, in this study, an extended Kalman filter algorithm was developed to sequentially correct both the gyroscope bias and the centrifugal and tangential acceleration of an accelerometer. The gait measurement results indicate that the proposed method successfully suppresses drift in the estimated knee joint angle over the entire measurement time of knee angle measurement during gait. The knee joint angles estimated using the proposed method were generally consistent with results obtained from an optical 3D motion analysis system. The proposed method is expected to be useful for estimating motion in medical care and welfare applications.

scholarly journals Genome-Wide Association Studies Based on Equine Joint Angle Measurements Reveal New QTL Affecting the Conformation of Horses

Genes ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 370 ◽  
Author(s):  
Annik Imogen Gmel ◽  
Thomas Druml ◽  
Rudolf von Niederhäusern ◽  
Tosso Leeb ◽  
Markus Neuditschko
Keyword(s):  
Joint Angle ◽  
Association Studies ◽  
Genome Wide Association ◽  
Cranial Morphology ◽  
Genome Wide Association Studies ◽  
Joint Angles ◽  
Mineral Density ◽  
Mixed Effect ◽  
Stifle Joint ◽  
Genome Wide

The evaluation of conformation traits is an important part of selection for breeding stallions and mares. Some of these judged conformation traits involve joint angles that are associated with performance, health, and longevity. To improve our understanding of the genetic background of joint angles in horses, we have objectively measured the angles of the poll, elbow, carpal, fetlock (front and hind), hip, stifle, and hock joints based on one photograph of each of the 300 Franches-Montagnes (FM) and 224 Lipizzan (LIP) horses. After quality control, genome-wide association studies (GWASs) for these traits were performed on 495 horses, using 374,070 genome-wide single nucleotide polymorphisms (SNPs) in a mixed-effect model. We identified two significant quantitative trait loci (QTL) for the poll angle on ECA28 (p = 1.36 × 10−7), 50 kb downstream of the ALX1 gene, involved in cranial morphology, and for the elbow joint on ECA29 (p = 1.69 × 10−7), 49 kb downstream of the RSU1 gene, and 75 kb upstream of the PTER gene. Both genes are associated with bone mineral density in humans. Furthermore, we identified other suggestive QTL associated with the stifle joint on ECA8 (p = 3.10 × 10−7); the poll on ECA1 (p = 6.83 × 10−7); the fetlock joint of the hind limb on ECA27 (p = 5.42 × 10−7); and the carpal joint angle on ECA3 (p = 6.24 × 10−7), ECA4 (p = 6.07 × 10−7), and ECA7 (p = 8.83 × 10−7). The application of angular measurements in genetic studies may increase our understanding of the underlying genetic effects of important traits in equine breeding.

scholarly journals Experimental and Numerical Study of Fracture Behavior of Rock-Like Material Specimens with Single Pre-Set Joint under Dynamic Loading

Materials ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2690
Author(s):  
Bo Pan ◽  
Xuguang Wang ◽  
Zhenyang Xu ◽  
Lianjun Guo ◽  
Xuesong Wang
Keyword(s):  
Crack Initiation ◽  
Crack Propagation ◽  
Joint Angle ◽  
Simulation Software ◽  
Dissipated Energy ◽  
Energy Structure ◽  
Joint Angles ◽  
Crack Penetration ◽  
Before And After ◽  
The Impact

The Split Hopkinson Pressure Bar (SHPB) is an apparatus for testing the dynamic stress-strain response of the cement mortar specimen with pre-set joints at different angles to explore the influence of joint attitudes of underground rock engineering on the failure characteristics of rock mass structure. The nuclear magnetic resonance (NMR) has also been used to measure the pore distribution and internal cracks of the specimen before and after the testing. In combination with numerical analysis, the paper systematically discusses the influence of joint angles on the failure mode of rock-like materials from three aspects of energy dissipation, microscopic damage, and stress field characteristics. The result indicates that the impact energy structure of the SHPB is greatly affected by the pre-set joint angle of the specimen. With the joint angle increasing, the proportion of reflected energy moves in fluctuation, while the ratio of transmitted energy to dissipated energy varies from one to the other. NMR analysis reveals the structural variation of the pores in those cement specimens before and after the impact. Crack propagation direction is correlated with pre-set joint angles of the specimens. With the increase of the pre-set joint angles, the crack initiation angle decreases gradually. When the joint angles are around 30°–75°, the specimens develop obvious cracks. The crushing process of the specimens is simulated by LS-DYNA software. It is concluded that the stresses at the crack initiation time are concentrated between 20 and 40 MPa. The instantaneous stress curve first increases and then decreases with crack propagation, peaking at different times under various joint angles; but most of them occur when the crack penetration ratio reaches 80–90%. With the increment of joint angles in specimens through the simulation software, the changing trend of peak stress is consistent with the test results.

scholarly journals Continuous Estimation of Knee Joint Angle Based on Surface Electromyography Using a Long Short-Term Memory Neural Network and Time-Advanced Feature

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4966
Author(s):  
Xunju Ma ◽  
Yali Liu ◽  
Qiuzhi Song ◽  
Can Wang
Keyword(s):  
Neural Network ◽  
Knee Joint ◽  
Surface Electromyography ◽  
Joint Angle ◽  
Short Term Memory ◽  
Mean Square ◽  
Short Term ◽  
Term Memory ◽  
Knee Joint Angle ◽  
Long Short Term Memory

Continuous joint angle estimation based on a surface electromyography (sEMG) signal can be used to improve the man-machine coordination performance of the exoskeleton. In this study, we proposed a time-advanced feature and utilized long short-term memory (LSTM) with a root mean square (RMS) feature and its time-advanced feature (RMSTAF; collectively referred to as RRTAF) of sEMG to estimate the knee joint angle. To evaluate the effect of joint angle estimation, we used root mean square error (RMSE) and cross-correlation coefficient ρ between the estimated angle and actual angle. We also compared three methods (i.e., LSTM using RMS, BPNN (back propagation neural network) using RRTAF, and BPNN using RMS) with LSTM using RRTAF to highlight its good performance. Five healthy subjects participated in the experiment and their eight muscle (i.e., rectus femoris (RF), biceps femoris (BF), semitendinosus (ST), gracilis (GC), semimembranosus (SM), sartorius (SR), medial gastrocnemius (MG), and tibialis anterior (TA)) sEMG signals were taken as algorithm inputs. Moreover, the knee joint angles were used as target values. The experimental results showed that, compared with LSTM using RMS, BPNN using RRTAF, and BPNN using RMS, the average RMSE values of LSTM using RRTAF were respectively reduced by 8.57%, 46.62%, and 68.69%, whereas the average ρ values were respectively increased by 0.31%, 4.15%, and 18.35%. The results demonstrated that LSTM using RRTAF, which contained the time-advanced feature, had better performance for estimating the knee joint motion.

scholarly journals Evaluating the use of machine learning in the assessment of joint angle using a single inertial sensor

2019 ◽  
Vol 6 ◽  
pp. 205566831986854 ◽  
Author(s):  
Rob Argent ◽  
Sean Drummond ◽  
Alexandria Remus ◽  
Martin O’Reilly ◽  
Brian Caulfield
Keyword(s):  
Machine Learning ◽  
Knee Joint ◽  
Inertial Measurement Unit ◽  
Joint Angle ◽  
Machine Learning Algorithms ◽  
Measurement Unit ◽  
Reference Standard ◽  
Inertial Measurement ◽  
Knee Joint Angle ◽  
Single Sensor

Introduction Joint angle measurement is an important objective marker in rehabilitation. Inertial measurement units may provide an accurate and reliable method of joint angle assessment. The objective of this study was to assess whether a single sensor with the application of machine learning algorithms could accurately measure hip and knee joint angle, and investigate the effect of inertial measurement unit orientation algorithms and person-specific variables on accuracy. Methods Fourteen healthy participants completed eight rehabilitation exercises with kinematic data captured by a 3D motion capture system, used as the reference standard, and a wearable inertial measurement unit. Joint angle was calculated from the single inertial measurement unit using four machine learning models, and was compared to the reference standard to evaluate accuracy. Results Average root-mean-squared error for the best performing algorithms across all exercises was 4.81° (SD = 1.89). The use of an inertial measurement unit orientation algorithm as a pre-processing step improved accuracy; however, the addition of person-specific variables increased error with average RMSE 4.99° (SD = 1.83°). Conclusions Hip and knee joint angle can be measured with a good degree of accuracy from a single inertial measurement unit using machine learning. This offers the ability to monitor and record dynamic joint angle with a single sensor outside of the clinic.

BIOMECHANICAL ANALYSIS OF THE STANDING LONG JUMP

2003 ◽  
Vol 15 (05) ◽  
pp. 186-192 ◽  
Author(s):  
WEN-LAN WU ◽  
JIA-HROUNG WU ◽  
HWAI-TING LIN ◽  
GWO-JAW WANG
Keyword(s):  
Knee Joint ◽  
Motion Analysis ◽  
Joint Angle ◽  
Three Dimensional ◽  
The Body ◽  
Initial Angle ◽  
Knee Joint Angle ◽  
Standing Long Jump ◽  
Long Jump ◽  
Arm Motion

The purposes of the present study were to (1) investigate the effects of the arm movement and initial knee joint angle employed in standing long jump by the ground reaction force analysis and three-dimensional motion analysis; and (2) investigate how the jump performance of the female gender related to the body configuration. Thirty-four healthy adult females performed standing long jump on a force platform with full effort. Body segment and joint angles were analyzed by three-dimensional motion analysis system. Using kinetic and kinematic data, the trajectories on mass center of body, knee joint angle, magnitude of peak takeoff force, and impulse generation in preparing phase were calculated. Average standing long jump performances with free arm motion were +1.5 times above performance with restricted arm motion in both knee initial angles. The performances with knee 90° initial flexion were +1.2 times above performance with knee 45° initial flexion in free and restricted arm motions. Judging by trajectories of the center mass of body (COM), free arm motion improves jump distance by anterior displacement of the COM in starting position. The takeoff velocity with 90° knee initial angle was as much as 11% higher than in with 45° knee initial angle. However, the takeoff angles on the COM trajectory showed no significant differences between each other. It was found that starting jump from 90° bend knee relatively extended the time that the force is applied by the leg muscles. To compare the body configurations and the jumping scores, there were no significant correlations between jump scores and anthropometry data. The greater muscle mass or longer leg did not correlated well with the superior jumping performance.

scholarly journals Human muscle length-dependent changes in blood flow

2012 ◽  
Vol 112 (4) ◽  
pp. 560-565 ◽  
Author(s):  
John McDaniel ◽  
Stephen J. Ives ◽  
Russell S. Richardson
Keyword(s):  
Blood Flow ◽  
Knee Joint ◽  
Joint Angle ◽  
Muscle Blood Flow ◽  
Muscle Length ◽  
Limb Blood Flow ◽  
Knee Joint Angle ◽  
Femoral Blood Flow ◽  
Femoral Blood ◽  
Cyclic Changes

Although a multitude of factors that influence skeletal muscle blood flow have been extensively investigated, the influence of muscle length on limb blood flow has received little attention. Thus the purpose of this investigation was to determine if cyclic changes in muscle length influence resting blood flow. Nine healthy men (28 ± 4 yr of age) underwent a passive knee extension protocol during which the subjects' knee joint was passively extended and flexed through 100–180° knee joint angle at a rate of 1 cycle per 30 s. Femoral blood flow, cardiac output (CO), heart rate (HR), stroke volume (SV), and mean arterial pressure (MAP) were continuously recorded during the entire protocol. These measurements revealed that slow passive changes in knee joint angle did not have a significant influence on HR, SV, MAP, or CO; however, net femoral blood flow demonstrated a curvilinear increase with knee joint angle ( r2 = 0.98) such that blood flow increased by ∼90% (125 ml/min) across the 80° range of motion. This net change in blood flow was due to a constant antegrade blood flow across knee joint angle and negative relationship between retrograde blood flow and knee joint angle ( r2 = 0.98). Thus, despite the absence of central hemodynamic changes and local metabolic factors, blood flow to the leg was altered by changes in muscle length. Therefore, when designing research protocols, researchers need to be cognizant of the fact that joint angle, and ultimately muscle length, influence limb blood flow.

Sign in / Sign up

Export Citation Format

Share Document