scholarly journals Processing of EMG Signals with High Impact of Power Line and Cardiac Interferences

2021 ◽  
Vol 11 (10) ◽  
pp. 4625
Author(s):  
Krzysztof Strzecha ◽  
Marek Krakós ◽  
Bogusław Więcek ◽  
Piotr Chudzik ◽  
Karol Tatar ◽  
...  
Keyword(s):  
Signal Processing ◽  
Muscle Activity ◽  
High Impact ◽  
Activity Measurement ◽  
Power Network ◽  
Original Algorithm ◽  
Emg Signal ◽  
Minimal Loss ◽  
Activity Measurements ◽  
The Eu

This work deals with electromyography (EMG) signal processing for the diagnosis and therapy of different muscles. Because the correct muscle activity measurement of strongly noised EMG signals is the major hurdle in medical applications, a raw measured EMG signal should be cleaned of different factors like power network interference and ECG heartbeat. Unfortunately, there are no completed studies showing full multistage signal processing of EMG recordings. In this article, the authors propose an original algorithm to perform muscle activity measurements based on raw measurements. The effectiveness of the proposed algorithm for EMG signal measurement was validated by a portable EMG system developed as a part of the EU research project and EMG raw measurement sets. Examples of removing the parasitic interferences are presented for each stage of signal processing. Finally, it is shown that the proposed processing of EMG signals enables cleaning of the EMG signal with minimal loss of the diagnostic content.

Noise Reduction in Swallowing Muscle Activity Measurement Based on Mixture Gaussian Distribution Model

2017 ◽  
Vol 21 (1) ◽  
pp. 109-118 ◽  
Author(s):  
Nobuyuki Ohmori ◽  
◽  
Chihiro Murasawa ◽  
Jumpei Aizawa ◽  
Hideya Momose ◽  
...  
Keyword(s):  
Muscle Activity ◽  
Measurement Method ◽  
Muscle Group ◽  
Distribution Model ◽  
Activity Measurement ◽  
Specialized Knowledge ◽  
Activity Measurements ◽  
Measurement Results ◽  
Surface Electromyograms ◽  
Gaussian Distribution Model

For the noninvasive measurement of swallowing muscle activity, surface electromyograms and swallowing sounds are used. The electromyogram electrodes can be placed appropriately only by experts with specialized knowledge about the location of the swallowing muscle group. Therefore, these sensors have not been used for measurements in food development, for which there were no experts. In order to develop a simple swallowing muscle measurement method for food development, we proposed a sensor sheet consisting of multiple electromyogram electrodes and observed that different swallowing muscle activities could be measured depending on the type of food. In this work, we study a calculation method for the elimination of noise, which is inevitable in electromyograms, from the sensor sheet measurement results and prove that the method improves the performance of the swallowing muscle activity measurements.

scholarly journals Low-Frequency Oscillations (<0.3 Hz) in the Electromyographic (EMG) Activity of the Human Trapezius Muscle During Sleep

2002 ◽  
Vol 88 (3) ◽  
pp. 1177-1184 ◽  
Author(s):  
R. H. Westgaard ◽  
P. Bonato ◽  
K. A. Holte
Keyword(s):  
Heart Rate ◽  
Muscle Activity ◽  
Activity Pattern ◽  
Sudden Change ◽  
Mean Amplitude ◽  
Activity Level ◽  
Emg Activity ◽  
Similar Frequency ◽  
Emg Signal ◽  
The Mean

The surface electromyographic (EMG) signal from right and left trapezius muscles and the heart rate were recorded over 24 h in 27 healthy female subjects. The root-mean-square (RMS) value of the surface EMG signals and the heartbeat interval time series were calculated with a time resolution of 0.2 s. The EMG activity during sleep showed long periods with stable mean amplitude, modulated by rhythmic components in the frequency range 0.05–0.2 Hz. The ratio between the amplitude of the oscillatory components and the mean amplitude of the EMG signal was approximately constant over the range within which the phenomenon was observed, corresponding to a peak-to-peak oscillatory amplitude of ∼10% of the mean amplitude. The duration of the periods with stable mean amplitude ranged from a few minutes to ∼1 h, usually interrupted by a sudden change in the activity level or by cessation of the muscle activity. Right and left trapezius muscles presented the same pattern of FM. In supplementary experiments, rhythmic muscle activity pattern was also demonstrated in the upper extremity muscles of deltoid, biceps, and forearm flexor muscles. There was no apparent association between the rhythmic components in the muscle activity pattern and the heart rate variability. To our knowledge, this is the first time that the above-described pattern of EMG activity during sleep is documented. On reanalysis of earlier recorded trapezius motor unit firing pattern in experiments on awake subjects in a situation with mental stress, low-FM of firing with similar frequency content was detected. Possible sources of rhythmic excitation of trapezius motoneurons include slow-wave cortical oscillations represented in descending cortico-spinal pathways, and/or activation by monoaminergic pathways originating in the brain stem reticular formation. The analysis of muscle activity patterns may provide an important new tool to study neural mechanisms in human sleep.

scholarly journals Integrated Measurement System of Postural Angle and Electromyography Signal for Manual Materials Handling Assessment

2021 ◽  
Vol 13 (6) ◽  
Author(s):  
Isa Halim ◽  
◽  
Adi Saptari ◽  
Mohd Fairil Abulais ◽  
Vinothini Padmanathan ◽  
...  
Keyword(s):  
Measurement System ◽  
Muscle Activity ◽  
Integrated System ◽  
Body Posture ◽  
Microsoft Kinect ◽  
Industrial Workers ◽  
Materials Handling ◽  
Emg Signal ◽  
Manual Materials Handling ◽  
Effort Assessment

Improper design of manual materials handling (MMH) tasks at workplace can cause musculoskeletal disorders such as muscle strain to industrial workers. To avoid these disorders, ergonomists and engineers require an integrated measurement system which allows them to study the interaction of body posture and muscle effort during performing MMH tasks. However, far too little attention has been paid to develop an integrated measurement system of body posture and muscle activity for assessing MMH tasks. The aim of this study was to develop and test a prototype of integrated system for measuring postural angles and electromyography (EMG) signals of a worker who doing MMH tasks. The Microsoft Visual Studio software, a 3D camera (Microsoft Kinect), Advancer Technologies muscle sensors and a microcontroller (NI DAQ USB-6000) were applied to develop the integrated postural angle and EMG signal measurement system. Additionally, a graphical user interface was created in the system to enable users to perform body posture and muscle effort assessment simultaneously. Based on the testing results, this study concluded that the patterns of EMG signals are depending on the postural angles which consistent with the findings of established works. Further study is required to enhance the validity, reliability and usability of the prototype so that it may facilitate ergonomists and engineers to assess work posture and muscle activity during MMH task.

scholarly journals Motion Calculation for Human Lower Extremities Based on EMG-Signal-Processing and Simple Biomechanical Model

2005 ◽  
pp. 153-161 ◽  
Author(s):  
Christian Fleischer ◽  
Konstantin Kondak ◽  
Christian Reinicke ◽  
Günter Hommel
Keyword(s):  
Signal Processing ◽  
Biomechanical Model ◽  
Lower Extremities ◽  
Emg Signal

Information-based analysis of the relation between human muscle reaction and walking path

2020 ◽  
Vol 28 (6) ◽  
pp. 675-684 ◽  
Author(s):  
Shahul Mujib Kamal ◽  
Norazryana Binti Mat Dawi ◽  
Sue Sim ◽  
Rui Tee ◽  
Visvamba Nathan ◽  
...  
Keyword(s):  
Nervous System ◽  
Information Content ◽  
Muscle Activity ◽  
Human Muscle ◽  
Complex Structures ◽  
Entropy Analysis ◽  
Movement Path ◽  
Leg Muscles ◽  
Emg Signal ◽  
Leg Muscle

BACKGROUND: Walking is one of the important actions of the human body. For this purpose, the human brain communicates with leg muscles through the nervous system. Based on the walking path, leg muscles act differently. Therefore, there should be a relation between the activity of leg muscles and the path of movement. OBJECTIVE: In order to address this issue, we analyzed how leg muscle activity is related to the variations of the path of movement. METHOD: Since the electromyography (EMG) signal is a feature of muscle activity and the movement path has complex structures, we used entropy analysis in order to link their structures. The Shannon entropy of EMG signal and walking path are computed to relate their information content. RESULTS: Based on the obtained results, walking on a path with greater information content causes greater information content in the EMG signal which is supported by statistical analysis results. This allowed us to analyze the relation between muscle activity and walking path. CONCLUSION: The method of analysis employed in this research can be applied to investigate the relation between brain or heart reactions and walking path.

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