Log In Sign up
The largest database of trusted experimental protocols
> Procedures > Diagnostic Procedure > Surface Electromyography

Surface Electromyography

Surface electromyography (sEMG) is a non-invasive technique used to measure the electrical activity generated by skeletal muscles during muscular contraction. sEMG signals are recorded from the surface of the skin using electrodes, providing insights into muscle function and neuromusclar activation.
This modality is widely used in clinical assessment, rehabilitation, ergonomics, and sports science research to evaluate muscle fatigue, coordination, and motor control.
Accurate and reproducible sEMG data collection is crucial for deriving meaningful insights, which can be facilitated by referencing best practices from the published literature.
PubCompare.ai's AI-driven platform helps researchers quickly identify the most appropriate sEMG protocols to optimize their study design and acheive better results.

Most cited protocols related to «Surface Electromyography»

1
EMG Onset Detection Protocol
Before data collection, patients’ skin over the vastus lateralis was shaved, rubbed with abrasive skin prep, and cleaned with alcohol to improve the electrode–skin contact and minimize skin impedance. Bipolar, disposable, pre-gelled Ag/AgCl surface electrodes with 20 mm distance between electrode centers were placed on the belly of the vastus lateralis. The exact placement of the electrodes followed the recommendations by Surface Electromyography for the Non-Invasive Assessment of Muscles (SENIAM 2008 ). The reference electrode was placed over the proximal end of the fibula of the same leg. Signals were analog filtered at 10–500 Hz (with first order filter at lower cutoff frequency and sixth order filter at higher cutoff frequency), amplified 2000× and sampled at 1 kHz using a TeleMyo 900 telemetric hardware system (Noraxon USA, Inc., Scottsdale, AZ, baseline noise < 1 uV RMS, Common Mode Rejection min. 85 dB through 10–500 Hz operating range).
EMG signals were recorded as each of 17 subjects performed one near-maximal voluntary isometric contractions, starting with 1 s of rest interval to establish baseline. The raw signals were visually inspected and the pre-contraction portions of the baseline as well as the steady portions of the EMG burst were identified. The baseline and the EMG burst from each recorded signal was then used to construct 17 reference EMG signals by adjoining the baseline and the burst portion at a known onset time t0 (see Fig. 1). Length of the EMG baseline, EMG burst, and position of the true onset t0 varied for all reference signals. The known, true onset times, t0, were used as a reference to quantify the accuracy of estimated onset times t1 identified by three onset detection methods.

Construction of the reference signal. From the raw signal (top panel), a portion of the baseline and a portion of the EMG burst was selected (middle panel) and re-joined at the known onset time t0 (bottom panel). To demonstrate the importance of signal conditioning, the baseline in this example contains fluctuations in the signal amplitude. These fluctuations were not associated with the muscle contraction

The precise EMG onset was not known in the experimental signals recorded from old adults during gait. In these trials, we determined the onset time, t0, by visual detection because computerized techniques should detect EMG onset close to the onset time selected by individuals with EMG expertise (Staude et al. 2001 (link)).
SNR of the reference signals was calculated to test the influence of signal quality on onset detection accuracy. The SNR of the signals was defined as: where A is RMS amplitude. All data analysis was performed in MATLAB (MathWorks, Natick, MA).
Solnik S., Rider P., Steinweg K., DeVita P, & Hortobágyi T. (2010). Teager–Kaiser energy operator signal conditioning improves EMG onset detection. European Journal of Applied Physiology, 110(3), 489-498.
Publication 2010
Adult Ethanol Fibula Gels Isometric Contraction Muscle Tissue Patients Skin Surface Electromyography Telemetry Vastus Lateralis
2
Evaluating Neuromuscular Control Modes

Protocol full text hidden due to copyright restrictions

Open the protocol to access the free full text link

Publication 2015
Arm, Upper Buttocks Condyle Ethics Committees, Research factor A Femur Generic Drugs Gracilis Muscle Healthy Volunteers Hip Joint Homo sapiens Joints Joints, Ankle Knee Joint Lata, Fascia Lower Extremity Muscle, Gastrocnemius Muscle Contraction Muscle Tissue Nervousness Plant Roots Rectus Femoris Semimembranosus Soleus Muscle Surface Electromyography Tendons Vastus Lateralis Vastus Medialis
3
Biceps Activation in Post-Stroke Hemiparesis

Protocol full text hidden due to copyright restrictions

Open the protocol to access the free full text link

Publication 2014
Action Potentials Arm, Upper Asthenia Cerebrovascular Accident Condyle Contracture Electric Conductivity Electricity Females Fingers Forearm Hemiplegia Hemorrhagic Stroke Homo sapiens Humerus Joints, Elbow Low Vision Males Muscle Contraction Muscle Tissue Nerves, Musculocutaneous Nervousness Shoulder Skeletal Muscles Skin Spastic Stimulations, Electric Supination Surface Electromyography Tendons Torque Transducers Wrist Wrist Joint
4
Extraoperative Video-ECoG Recordings for Seizure Mapping

Protocol full text hidden due to copyright restrictions

Open the protocol to access the free full text link

Publication 2008
Antiepileptic Agents Electrocorticography Electrooculography Fingers Muscles, Deltoid Seizures Surface Electromyography
5
Extraoperative ECoG Recordings for HFOs
Extraoperative video-ECoG recordings were obtained for 3 to 5 days, using a 192-channel Nihon Kohden Neurofax 1100A Digital System (Nihon Kohden America Inc, Foothill Ranch, CA, USA), which has an input impedance of 200 Megaohm, a common mode rejection ratio greater than 110 dB, an A/D conversion of 16 bits, and a sampling frequency selectable from 200 to 10,000 Hz. The sampling rate was set at 1,000 Hz with the amplifier band pass at 0.08 – 300 Hz. This clinical recording system has adequate specifications for recording low-voltage HFOs (Crone et al., 2006 (link); Fukuda et al., 2008 (link); Kobayashi et al., 2010 (link)). The averaged voltage of ECoG signals derived from the fifth and sixth subdural electrodes of the ECoG amplifier (system reference potential) was used as the original reference. ECoG signals were then re-montaged to a common average reference. The advantages and limitations of using a common average reference for measurement of event-related gamma-oscillations were previously discussed (Crone et al., 2001 (link); Asano et al., 2009b (link)). Channels contaminated with large interictal epileptiform discharges or artifacts were excluded from the average reference. No notch filter was used for further analysis in any of the subjects. As part of our routine clinical procedure, surface electromyography (EMG) electrodes were placed on the left and right deltoid muscles, and electrooculography electrodes were placed 2.5 cm below and 2.5 cm lateral to the left and right outer canthi. Antiepileptic medications were discontinued or reduced during ECoG monitoring until a sufficient number of habitual seizures were captured.
Nariai H., Nagasawa T., Juhasz C., Sood S., Chugani H.T, & Asano E. (2010). Statistical mapping of ictal high-frequency oscillations in epileptic spasms. Epilepsia, 52(1), 63-74.
Publication 2010
Antiepileptic Agents Electrocorticography Electrooculography Fingers Gamma Rays Muscles, Deltoid Seizures Subdural Space Surface Electromyography

Most recents protocols related to «Surface Electromyography»

1
Quantifying Upper Limb Tremor: Acceleration and EMG Signals
In order to quantify upper limb tremor for comparison, we collected two continuous tremor signals, which were tremor acceleration and EMG signals, respectively. Before experiment, the tremor type (postural tremor/resting tremor) to record of each subject was decided independently by a physician after patient's enrollment. The main principle of choosing the main tremor type is tremor intensity and stability. Intentional tremor was not considered in our research since it is difficult to standardize motion. For subjects whose main tremor type is resting tremor, we had them seated comfortably with arms fully supported on armrests and recorded their tremor. For the others, postural tremor was inspected with seated subject stretching the whole upper limb forward and maintaining the posture for some time (Zhang et al., 2018 (link)). Additional requirements in recording postural tremor included: (1) fingers closed, (2) palms facing downward, and (3) seated upright.
All data was recorded through a commercial device system named the Biometrics Datalog (Biometrics Inc., the USA), along with a three-axis accelerometer sensor and four surface EMG (sEMG) sensors. The accelerometer sensor was fixed onto the third knuckle of the middle finger on the more affected side. Four sEMG sensors were attached respectively onto the muscle bellies of the flexor carpi radialis (FCR), the flexor carpi ulnaris (FCU), the extensor carpi radialis (ECR) and the extensor carpi ulnaris (ECU). The data of tremor acceleration and EMG signals were both digitized into 1,000 Hz and simultaneously recorded. From each subject, we obtained a 5-min sequential data package comprising tremor acceleration and EMG signals.
Zhang B., Huang F., Liu J, & Zhang D. (2023). Bilateral transcranial direct current stimulation may be a feasible treatment of Parkinsonian tremor. Frontiers in Neuroscience, 17, 1101751.
Full text: Click here
Publication 2023
Acceleration Action Tremor Arecaceae Arm, Upper Continuous Tremor Epistropheus Fingers Medical Devices Metacarpophalangeal Joint Muscle Tissue Physicians Resting Tremor Static Tremor Surface Electromyography Tremor Tremor, Limb Upper Extremity Wrist
2
Robotic Exoskeletons for Gait Rehabilitation
This study is based on analyses as part of a randomized controlled trial (RCT) [29 (link)], conducted at the University Department of Rehabilitation Medicine, Danderyd Hospital and Department of Clinical Sciences at Karolinska Institutet in Stockholm, Sweden. The study was approved by the Swedish Ethical Review Authority (2015/1216-31) as a multicenter trial with the ordinal scale, Functional Ambulation Category, as primary outcome and 54 participants/site to reach statistical power. Before study start, the planned 3 study sites were reduced to 1, due to limited access to robotic suits for gait training. The 6-minute walk test (6MWT) was changed from secondary to primary outcome, to allow more sensitive analyses of changes in walking (48 participants, to reach statistical power, please see the statistics section below). The study was registered with these changes at ClinicalTrials.gov: NCT02545088 prior to study start.
The RCT was single blinded, with an assessor blinded to group allocation. Randomization was performed according to block randomization (prepared by a statistician not otherwise involved in the study, using the SAS system, including the variables: blocks of three, treatment and patient). A nurse not otherwise involved in the study randomized the participants after the baseline testing, by pulling the participant’s ID-number one by one from a prepared envelope and placing them in the order of the block starting at the top of each block. The result of the randomization was photographed and saved in the study file. Participants were randomized into three groups 1) One intervention group received gait training with the exoskeleton Hybrid Assistive Limb (HAL) as well as conventional gait and mobility training (HAL-group), 2) A second intervention group received conventional gait and mobility training (Conventional group), and 3) a control group, continued with their usual activities (Control group). The two intervention groups were dose-matched to out rule any variations in intensity and scheduled three times a week for six weeks, (18 sessions). In the HAL-group each session was scheduled for a maximum of 60 minutes of gait training with HAL, plus a maximum of 30 minutes of conventional gait and mobility training to enhance generalizability of the acquired skills to everyday life activities. The HAL was used on a treadmill with a safety harness including body weight support (pre-set to 9 kg) to unburden the weight of the HAL-suit. HAL can be individually set to support movements of the hip and knee joints and includes a hybrid system with a voluntary mode where the level of assistance is individually adjusted and triggered by muscle contractions detected by surface- electromyography (EMG) [30 (link)]. To optimize training intensity, the level of assistance from the HAL and the walking speed on the treadmill was continuously adjusted, as tolerated by the participant and as the participant improved. In the conventional group, each session was scheduled for a maximum of 90 minutes of gait and mobility training with a physiotherapist. The conventional training included individualized, challenging exercises targeting an improved walking ability, such as overground walking on varying surfaces with and without walking aid, treadmill walking, weightbearing on the paretic leg, motor training of the lower extremity, and mobility tasks.
Bergqvist M., Möller M.C., Björklund M., Borg J, & Palmcrantz S. (2023). The impact of visuospatial and executive function on activity performance and outcome after robotic or conventional gait training, long-term after stroke—as part of a randomized controlled trial. PLOS ONE, 18(3), e0281212.
Full text: Click here
Publication 2023
6-Minute Walk Test Ethical Review Hybrids Knee Joint Lower Extremity Movement Muscle Contraction Nurses Patients Physical Therapist Range of Motion, Articular Safety Surface Electromyography
3
Measuring Muscle Activity in Stroke and Healthy Subjects
In stroke patients and a sub-group (n = 18) of healthy subjects, surface electromyography (EMG) of medial gastrocnemius and soleus muscles was recorded with the NeuroFlexor assessment during the whole passive movement from onset until full ankle dorsiflexion.
For EMG recordings, disposable gelled Ag/AgCl electrodes were used. EMG signals were amplified with a Grass LP511 Ac Amplifier (Grass Technologies, Astro-Med, Inc., West Warwick, RI, USA), sampled at 1 kHz using a CED Power1401 (Cambridge Electronic Designs, Cambridge, UK) and rectified. The root mean square of the EMG signal, with a 50 ms sliding window, was computed to generate the EMG amplitude during the whole NeuroFlexor movement from onset until full dorsiflexion of ankle. Data were acquired with Spike2 software (Version 7.12; CED) and analysed off-line using custom-written programmes in MATLAB R2021a (The MathWorks, Inc., Natick, MA, USA).
PENNATI G.V., CARMENT L., GODBOLT A.K., PLANTIN J., BORG J, & LINDBERG P.G. (2023). VALIDITY, INTRA-RATER RELIABILITY AND NORMATIVE DATA OF THE NEUROFLEXOR™ DEVICE TO MEASURE SPASTICITY OF THE ANKLE PLANTAR FLEXORS AFTER STROKE. Journal of Rehabilitation Medicine, 55, 2067.
Publication 2023
Cerebrovascular Accident Electromyography Gels Healthy Volunteers Joints, Ankle Movement Muscle, Gastrocnemius Passive Range of Motion Patients Poaceae Soleus Muscle Surface Electromyography Tooth Root
4
Respiratory Muscle Electromyography Protocol
Electromyographic activities of the sternocleidomastoid (right and left), external intercostal, diaphragm, and anterior serratus muscles were analyzed using the MyoSystem BR1 P84 portable electromyograph (DataHominis, Uberlândia, Minas Gerais, Brazil). During the electromyographic examination, the environment was kept silent, with the participant seated without shoes on rubber mats asked to remain as calm as possible and breathe slowly. The participant’s head was positioned upright, with the face facing forward and looking towards the horizon. Instructions and necessary explanations were provided, asking the participant to remain calm (Moreto Santos et al., 2020 (link)). The surface electrodes were positioned according to the recommendations of the Surface EMG for Non-Invasive Assessment of Muscles project (Hermens et al., 2000 (link)). Before placing the electrodes, the skin was cleaned with alcohol to reduce impedance (Di Palma et al., 2017 (link)). To determine the placement of the electrodes in collecting the electromyographic signal from the respiratory muscles, a maximum voluntary pressure maneuver was performed during inspiration (MIP) and expiration (MEP) (Xu et al., 2017 (link)). The arrangement of the electrodes for collecting the diaphragm muscle was based on the positioning of the midclavicular line of the 6th intercostal space (Chien et al., 2010 (link)). Electromyographic evaluation was performed with the participant in a seated position, with the upper limbs beside the body, and the lower limbs flexed at a 90° angle. Respiratory function was analyzed at respiratory rest, respiratory cycle (deep inspiration and expiration), and maximum inspiration and expiration, with a 1-min interval between collections. The respiratory muscles of the left side of the body could produce crosstalk owing to cardiac interference in the acquisition of the electromyographic signal; therefore, to avoid impedance when capturing the signal to the external intercostal, serratus anterior, and diaphragm muscles, collection was performed only from the right side of the body (Abbaspour and Fallah, 2014 (link); Hawkes et al., 2007 (link)). The protocol for normalizing the electromyographic recordings of the respiratory muscles was followed using the maximal inspiration maneuver sustained for 4 sec.
Fabrin S.C., Palinkas M., Fioco E.M., Gomes G.G., Regueiro E.M., da Silva G.P., Siéssere S., Verri E.D, & Regalo S.C. (2023). Functional assessment of respiratory muscles and lung capacity of CrossFit athletes. Journal of Exercise Rehabilitation, 19(1), 67-74.
Publication 2023
Alcohols Arecaceae Cross Reactions Electromyography Face Head Heart Human Body Inhalation Intercostal Muscle Lower Extremity Muscle Tissue Pressure Respiration Respiratory Rate Rubber Sitting Skin Surface Electromyography Upper Extremity Vaginal Diaphragm
5
Wireless EMG Analysis of Ankle Kinematics
Noraxon Ultium (Noraxon Inc., Scottsdale, AZ, USA) wireless surface electromyography (EMG) sensors were used to record bilateral muscle activity from the PL, which provides foot eversion and plantarflexion, TA, which provides dorsiflexion and inversion, and SOL, which provides plantarflexion and inversion [13 (link)]. The recording electrodes were placed 20 mm apart with respect to the muscle fiber to be measured, as recommended by the SENIAM [22 ]. Prior to electrode attachment, the skin was prepared by shaving and alcohol swapping. The raw signals were recorded and processed using MR3.18® software (Noraxon Inc., Scottsdale, AZ, USA). EMG data were recorded at a sampling frequency of 2000 Hz, high-pass filtered at 20 Hz, rectified, and low-pass filtered at 50 Hz, following the protocol by Rankin et al. [23 (link)]. The sampling rates of the CoP and vGRF data were 500 Hz. The start and end points of a single step-aside movement are illustrated in the phase and period division sections. For amplitude normalization, the filtered-rectified muscle EMG data of a single step-aside movement were divided by the average of all step-aside movement muscle EMG data in the trial. Time was normalized to 200 data points.
Participants wore a pair of knitted shoes (Natso Knit Jogging Shoes, KeonJong, S-Korea) equipped with the Noraxon Ultium Insole, and total foot pressure (vGRF) and foot CoP displacement data were collected. An increase in CoP displacement represented a shift to the right (medial side of the left foot and lateral side of the right foot) and anterior sides. A decrease in the CoP displacement value indicated the opposite. We conducted a statistical analysis of the differential CoP movement (change in CoP from the initial position) in the mediolateral or anteroposterior direction. CoP displacement was obtained by subtracting the first value from the CoP value of the average report for each participant [15 (link)]. vGRF data were normalized to the body weight of each participant.
Xie L, & Cho S. (2023). Ankle strategies for step-aside movement during quiet standing. PLOS ONE, 18(3), e0281400.
Full text: Click here
Publication 2023
Body Weight Electromyography Ethanol Fibrosis Foot Inversion, Chromosome Movement Muscle Tissue Pressure Skin Strains Surface Electromyography

Top products related to «Surface Electromyography»

1
Trigno by Delsys
Sourced in United States
The Trigno is a wireless electromyography (EMG) system developed by Delsys. It is designed to capture and record muscle activation signals. The Trigno system consists of sensor units that can be attached to the skin over the muscles of interest and transmit the EMG data wirelessly to a receiver unit.
2
Matlab by MathWorks
Sourced in United States, United Kingdom, Germany, Canada, Japan, Sweden, Austria, Morocco, Switzerland, Australia, Belgium, Italy, Netherlands, China, France, Denmark, Norway, Hungary, Malaysia, Israel, Finland, Spain
MATLAB is a high-performance programming language and numerical computing environment used for scientific and engineering calculations, data analysis, and visualization. It provides a comprehensive set of tools for solving complex mathematical and computational problems.
3
Trigno wireless system by Delsys
Sourced in United States
The Trigno Wireless System is a wireless EMG and inertial measurement system developed by Delsys. The system is designed to capture high-quality electromyography (EMG) and motion data wirelessly. It features multiple sensor channels and a compact, lightweight design.
4
Blue sensor n by Ambu
Sourced in Denmark, Malaysia, United States
The Blue Sensor N is a disposable, single-use electrode used for electrocardiography (ECG) monitoring. It is designed to capture high-quality ECG signals from patients.
5
Powerlab by ADInstruments
Sourced in Australia, United States, United Kingdom, New Zealand, Germany, Japan, Spain, Italy, China
PowerLab is a data acquisition system designed for recording and analyzing physiological signals. It provides a platform for connecting various sensors and transducers to a computer, allowing researchers and clinicians to capture and analyze biological data.
6
Trigno wireless emg system by Delsys
Sourced in United States
The Trigno Wireless EMG System is a compact and portable device designed for the recording and analysis of electromyographic (EMG) signals. It features a wireless design for ease of use and flexibility during data collection. The system captures and transmits EMG data from multiple sensor units, allowing for the simultaneous monitoring of muscle activity.
7
Labview by National Instruments
Sourced in United States, Germany, United Kingdom, Japan, Switzerland, Canada, Australia, Netherlands, Morocco
LabVIEW is a software development environment for creating and deploying measurement and control systems. It utilizes a graphical programming language to design, test, and deploy virtual instruments on a variety of hardware platforms.
8
Labchart 7 by ADInstruments
Sourced in Australia, United States, New Zealand, United Kingdom, Germany, Colombia, Japan
LabChart 7 is a data acquisition and analysis software designed for recording, visualizing, and analyzing physiological signals. It provides a user-friendly interface for capturing data from various types of laboratory equipment and sensors. LabChart 7 offers tools for real-time display, analysis, and offline processing of the acquired data.
9
Bagnoli 8 emg system by Delsys
Sourced in United States
The Bagnoli 8 EMG System is a high-quality, multi-channel electromyography (EMG) device designed for recording and analyzing muscle activity. It features 8 independent channels for simultaneous EMG data acquisition, providing a comprehensive solution for various clinical and research applications.
10
Mp150 by Biopac
Sourced in United States, Canada, United Kingdom, Germany
The MP150 is a data acquisition system designed for recording physiological signals. It offers high-resolution data capture and features multiple input channels to accommodate a variety of sensor types. The MP150 is capable of acquiring and analyzing data from various biological and physical measurements.

More about "Surface Electromyography"