Effect of Knee Joint Angle on Regional Hamstrings Activation During Isometric Knee-Flexion Exercise

2020 ◽  
pp. 1-6
Author(s):  
Raki Kawama ◽  
Masamichi Okudaira ◽  
David H. Fukuda ◽  
Hirohiko Maemura ◽  
Satoru Tanigawa
Keyword(s):  
Knee Joint ◽  
Muscle Activity ◽  
Repeated Measures ◽  
Knee Flexion ◽  
Muscle Activation ◽  
Joint Angle ◽  
Motor Nerve ◽  
Activity Level ◽  
Activity Levels ◽  
Knee Joint Angle

Context: Each hamstring muscle is subdivided into several regions by multiple motor nerve branches, which implies each region has different muscle activation properties. However, little is known about the muscle activation of each region with a change in the knee joint angle. Understanding of regional activation of the hamstrings could be helpful for designing rehabilitation and training programs targeted at strengthening a specific region. Objective: To investigate the effect of knee joint angle on the activity level of several regions within the individual hamstring muscles during isometric knee-flexion exercise with maximal effort (MVCKF). Design: Within-subjects repeated measures. Setting: University laboratory. Participants: Sixteen young males with previous participation in sports competition and resistance training experience. Intervention: The participants performed 2 MVCKF trials at each knee joint angle of 30°, 60°, and 90°. Outcome Measures: Surface electromyography was used to measure muscle activity in the proximal, middle, and distal regions of the biceps femoris long head (BFlh), semitendinosus, and semimembranosus of hamstrings at 30°, 60°, and 90° of knee flexion during MVCKF. Results: Muscle activity levels in the proximal and middle regions of the BFlh were higher at 30° and 60° of knee flexion than at 90° during MVCKF (all: P < .05). Meanwhile, the activity levels in the distal region of the BFlh were not different among all of the evaluated knee joint angles. In semitendinosus and semimembranosus, the activity levels were higher at 30° and 60° than at 90°, regardless of region (all: P < .05). Conclusion: These findings suggest that the effect of knee joint angle on muscle activity level differs between regions of the BFlh, whereas that is similar among regions of semitendinosus and semimembranosus during MVCKF.

scholarly journals Influence of Trunk Posture on Knee Joint Angle and Muscle Activity during Single-leg Landing: A Comparison by Gender

2014 ◽  
Vol 29 (6) ◽  
pp. 955-959
Author(s):  
Akira SAITO ◽  
Makoto SASAKI ◽  
Masahiko WAKASA ◽  
Sachiko UEMURA ◽  
Kyoji OKADA
Keyword(s):  
Knee Joint ◽  
Muscle Activity ◽  
Joint Angle ◽  
Knee Joint Angle ◽  
Trunk Posture

scholarly journals Effects of Trunk and Neck Extensor Muscle Activity on the Bridging Exercise According to Knee Joint Angle

2013 ◽  
Vol 25 (4) ◽  
pp. 363-365 ◽  
Author(s):  
Su-Kyoung Lee ◽  
Dong-Chul Moon ◽  
Hyun-Rae Cho ◽  
Tae-Young Kim
Keyword(s):  
Knee Joint ◽  
Muscle Activity ◽  
Joint Angle ◽  
Extensor Muscle ◽  
Knee Joint Angle

scholarly journals Effect of Forefoot Strike on Lower Extremity Muscle Activity and Knee Joint Angle During Cutting in Female Team Handball Players

2016 ◽  
Vol 2 (1) ◽  
Author(s):  
Naruto Yoshida ◽  
Shun Kunugi ◽  
Sonoko Mashimo ◽  
Yoshihiro Okuma ◽  
Akihiko Masunari ◽  
...  
Keyword(s):  
Knee Joint ◽  
Lower Extremity ◽  
Muscle Activity ◽  
Joint Angle ◽  
Knee Joint Angle ◽  
Team Handball ◽  
Lower Extremity Muscle

scholarly journals Use of instrumented spasticity tests in clinical applications. Preliminary results

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Ewa Szczerbik ◽  
Małgorzata Kalinowska ◽  
Krzysztof Graff ◽  
Dorota Olczak-Kowalczyk ◽  
Anna Dąbrowska-Gontarczyk ◽  
...  
Keyword(s):  
Knee Joint ◽  
Muscle Activity ◽  
Joint Angle ◽  
Correlation Coefficients ◽  
Clinical Applications ◽  
Clinical Tests ◽  
Preliminary Results ◽  
Knee Joint Angle ◽  
Dynamic Movement ◽  
Pendulum Test

Summary Study aim: the aim of the study was to evaluate whether the use of instrumented versions of spasticity tests would provide us with clinically more useful information on the patient’s status. Material and methods: the study included 19 children, 8–17 years old: 7 girls and 12 boys. Pendulum, velocity, and popliteal tests were performed using the Vicon system (knee joint angle, 8 muscles EMG). Dynamic movement ranges of the knee joint during velocity and popliteal tests (ROM), indices of the pendulum test, and muscle activity in dependence of velocity of movement (MA, MAST) were calculated. Correlation coefficients between ROM, Vmax, MA, and MAST were calculated to show whether instrumentation of clinical tests can validate the patient’s status more precisely. Results: Vmax value from the pendulum test does not always correlate with ROM. Scores of MA and MAST do not correlate with ROM. Vmax generally does not correlate with MA or MAST. Conclusions: ROM is one of the most important parameters reflecting the level of spasticity but it is not sensitive enough to detect small changes in the patient’s status. In that case, Vmax of the pendulum test and the number of activated muscles in velocity and popliteal tests could become important tools to assess changes in spasticity level, especially when motion systems are more commonly available.

Comparison of balance and Muscle Activity of Normal Male and Female in squats Exercise According to Knee Joint Angle

2019 ◽  
Vol 19 (2) ◽  
pp. 682
Author(s):  
Jun-Hyeok Park ◽  
Dae-ho Yoon ◽  
Hyeon-ji Choi ◽  
Ji-Heon Hong ◽  
Jin-seop Kim ◽  
...  
Keyword(s):  
Knee Joint ◽  
Muscle Activity ◽  
Joint Angle ◽  
Normal Male ◽  
Male And Female ◽  
Knee Joint Angle

scholarly journals Abdominal muscle activity according to knee joint angle during sit-to-stand

2016 ◽  
Vol 28 (6) ◽  
pp. 1849-1851 ◽  
Author(s):  
Juri Eom ◽  
Min-Hyung Rhee ◽  
Laurentius Jongsoon Kim
Keyword(s):  
Knee Joint ◽  
Muscle Activity ◽  
Joint Angle ◽  
Abdominal Muscle ◽  
Knee Joint Angle ◽  
Sit To Stand

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.

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