scholarly journals Surface EMG variability while running on grass, concrete and treadmill

2021 ◽  
pp. 102624
Author(s):  
Morteza Yaserifar ◽  
Anderson Souza Oliveira
Keyword(s):  
Surface Emg

Rectification of surface EMG impairs cortico-muscular coherence estimation

2011 ◽  
Vol 42 (01) ◽  
Author(s):  
Z. Bayraktaroglu ◽  
K. von Carlowitz-Ghori ◽  
F. Losch ◽  
G. Nolte ◽  
G. Curio ◽  
...  
Keyword(s):  
Surface Emg ◽  
Coherence Estimation

Kinematic Analysis of Biathlon Using Surface EMG : Case Study

2018 ◽  
Vol 27 (5) ◽  
pp. 1469-1476
Author(s):  
An-Sik Heo ◽  
Jung-Chul Lee ◽  
Jae-Young Park
Keyword(s):  
Kinematic Analysis ◽  
Surface Emg

scholarly journals Reliability of diaphragmatic motor-evoked potentials induced by transcranial magnetic stimulation

2020 ◽  
Vol 129 (6) ◽  
pp. 1393-1404
Author(s):  
Joseph F. Welch ◽  
Patrick J. Argento ◽  
Gordon S. Mitchell ◽  
Emily J. Fox
Keyword(s):  
Transcranial Magnetic Stimulation ◽  
Evoked Potentials ◽  
Magnetic Stimulation ◽  
Motor Evoked Potentials ◽  
Surface Emg ◽  
Noninvasive Technique ◽  
Large Variability ◽  
Adult Men ◽  
Latency Duration ◽  
Excellent Reproducibility

Transcranial magnetic stimulation (TMS) is a noninvasive technique to assess neural impulse conduction along the cortico-diaphragmatic pathway. The reliability of diaphragm motor-evoked potentials (MEP) induced by TMS is unknown. Notwithstanding large variability in MEP amplitude, we found good-to-excellent reproducibility of all MEP characteristics (latency, duration, amplitude, and area) both within- and between-day in healthy adult men and women. Our findings support the use of TMS and surface EMG to assess diaphragm activation in humans.

Amplitude cancellation reduces the size of motor unit potentials averaged from the surface EMG

2006 ◽  
Vol 100 (6) ◽  
pp. 1928-1937 ◽  
Author(s):  
Kevin G. Keenan ◽  
Dario Farina ◽  
Roberto Merletti ◽  
Roger M. Enoka
Keyword(s):  
Motor Unit ◽  
Conduction Velocity ◽  
Motor Units ◽  
Surface Emg ◽  
Excitation Level ◽  
Bipolar Electrode ◽  
Emg Signal ◽  
Motor Unit Synchronization ◽  
Rate Coding ◽  
Simulated Surface

The purpose of the study was to evaluate the influence of selected physiological parameters on amplitude cancellation in the simulated surface electromyogram (EMG) and the consequences for spike-triggered averages of motor unit potentials derived from the interference and rectified EMG signals. The surface EMG was simulated from prescribed recruitment and rate coding characteristics of a motor unit population. The potentials of the motor units were detected on the skin over a hand muscle with a bipolar electrode configuration. Averages derived from the EMG signal were generated using the discharge times for each of the 24 motor units with lowest recruitment thresholds from a population of 120 across three conditions: 1) excitation level; 2) motor unit conduction velocity; and 3) motor unit synchronization. The area of the surface-detected potential was compared with potentials averaged from the interference, rectified, and no-cancellation EMGs. The no-cancellation EMG comprised motor unit potentials that were rectified before they were summed, thereby preventing cancellation between the opposite phases of the potentials. The percent decrease in area of potentials extracted from the rectified EMG was linearly related to the amount of amplitude cancellation in the interference EMG signal, with the amount of cancellation influenced by variation in excitation level and motor unit conduction velocity. Motor unit synchronization increased potentials derived from both the rectified and interference EMG signals, although cancellation limited the increase in area for both potentials. These findings document the influence of amplitude cancellation on motor unit potentials averaged from the surface EMG and the consequences for using the procedure to characterize motor unit properties.

scholarly journals Association between Oxygen Consumption and Surface Electromyographic Amplitude and Its Variation within Individual Calf Muscles during Walking at Various Speeds

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1748
Author(s):  
Kohei Watanabe ◽  
Shideh Narouei
Keyword(s):  
Oxygen Consumption ◽  
Spatial Variation ◽  
Metabolic Response ◽  
Correlation Coefficients ◽  
Surface Emg ◽  
Medial Gastrocnemius ◽  
Whole Body ◽  
Young Males ◽  
Emg Amplitude ◽  
Calf Muscles

Surface electromyography (EMG) has been used to estimate muscle work and physiological burden of the whole body during human movements. However, there are spatial variations in surface EMG responses within individual muscles. The aim of this study was to investigate the relation between oxygen consumption and surface EMG responses of lower leg muscles during walking at various speeds and to quantify its spatial variation within an individual muscle. Nine young males walked on a treadmill at four speeds: preferred minus 1 km/h, preferred, preferred plus 1 km/h, and preferred plus 2 km/h, and the metabolic response was measured based on the expired gas. High-density surface EMG of the tibialis anterior (TA), medial gastrocnemius (MG), lateral gastrocnemius, and soleus muscles was performed using 64 two-dimensional electrode grids. Correlation coefficients between oxygen consumption and the surface EMG amplitude were calculated across the gait speeds for each channel in the electrode grid and for individual muscles. Mean correlation coefficients across electrodes were 0.69–0.87 for the four individual muscles, and the spatial variation of correlation between the surface EMG amplitude and oxygen consumption within an electrode grid was significantly greater in MG muscle than in TA muscle (Quartile deviations: 0.24 for MG and 0.02 for TA, p < 0.05). These results suggest that the physiological burden of the whole body during gait at various speeds can be estimated from the surface EMG amplitude of calf muscles, but we need to note its spatial distribution within the MG muscle.

scholarly journals Low-cost Active Dry-Contact Surface EMG Sensor for Bionic Arms

2020 ◽  
Author(s):  
Asma M. Naim ◽  
Kithmin Wickramasinghe ◽  
Ashwin De Silva ◽  
Malsha V. Perera ◽  
Thilina Dulantha Lalitharatne ◽  
...  
Keyword(s):  
Contact Surface ◽  
Low Cost ◽  
Surface Emg ◽  
Dry Contact

Thumb Attitude Analysis using High Density Surface EMG: A Preliminary Survey

2021 ◽  
Author(s):  
Muhammad Mukhlis Suhaimi ◽  
Aimi Shazwani Ghazali ◽  
Shahrul Na'im Sidek ◽  
Ahmad Jazlan
Keyword(s):  
Surface Emg ◽  
High Density ◽  
Preliminary Survey ◽  
Density Surface

scholarly journals Surface EMG-Based Instantaneous Hand Gesture Recognition Using Convolutional Neural Network with the Transfer Learning Method

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2540
Author(s):  
Zhipeng Yu ◽  
Jianghai Zhao ◽  
Yucheng Wang ◽  
Linglong He ◽  
Shaonan Wang
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Transfer Learning ◽  
Gesture Recognition ◽  
Recognition System ◽  
Surface Emg ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Training Time ◽  
Generalization Ability

In recent years, surface electromyography (sEMG)-based human–computer interaction has been developed to improve the quality of life for people. Gesture recognition based on the instantaneous values of sEMG has the advantages of accurate prediction and low latency. However, the low generalization ability of the hand gesture recognition method limits its application to new subjects and new hand gestures, and brings a heavy training burden. For this reason, based on a convolutional neural network, a transfer learning (TL) strategy for instantaneous gesture recognition is proposed to improve the generalization performance of the target network. CapgMyo and NinaPro DB1 are used to evaluate the validity of our proposed strategy. Compared with the non-transfer learning (non-TL) strategy, our proposed strategy improves the average accuracy of new subject and new gesture recognition by 18.7% and 8.74%, respectively, when up to three repeated gestures are employed. The TL strategy reduces the training time by a factor of three. Experiments verify the transferability of spatial features and the validity of the proposed strategy in improving the recognition accuracy of new subjects and new gestures, and reducing the training burden. The proposed TL strategy provides an effective way of improving the generalization ability of the gesture recognition system.

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