EMG: Electromyography

Modular construction...extreme flexibility

MP systems offer features to support nearly every physiological recording scenario. The following advanced features apply to the application you selected.

If you don't see an Advanced Feature that interests you, please contact BIOPAC so we can identify the best solution for your particular need.

Active Electrodes and Fine Wire EMG

The TSD150 Series of active electrodes interface with the HLT100C High Level Transducer interface module. The TSD150 electrodes have built-in amplification, which allows the subject to be a greater distance from the recording equipment. The TSD150 will record both surface (sEMG) and fine wire EMG. The transducers are easily adapted to fine wire recording by […]

Automated EMG Analysis

AcqKnowledge includes a number of powerful automated EMG analysis features, including Derive Average Rectified EMG Derive Integrated EMG Root Means Square EMG EMG Frequency & Power Analysis   Locate Muscle Activation Derive Average Rectified EMG   Derive Average rectified EMG (ARV) is defined as a time-windowed mean of the absolute value of the signal. ARV […]

Automatic Spike

The Peak Detection features let users automatically analyze raw EMG spike data. Select the desired measurements and the software will calculate the values for each spike in the data file or within a selected area. This analysis can also be performed over pre-defined time intervalsenter a time interval and the software will run through the […]

EMG & Force

For in-depth studies of muscle work and fatigue, use the EMG100C amplifier with a hand dynamometer (TSD121C). The software will display the force measurements (calibrated in pounds or kilograms) as well as the raw and integrated EMG data. It is possible to simultaneously measure EMG with signals from force plates, load cells, and pressure transducers. Use […]

EMG Power Spectrum Analysis

A common tool for investigating electromyography (EMG) data is the Power Spectrum Density (PSD). Use AcqKnowledge for EMG Frequency & Power Analysis to compare responses from one part of the recording to the next and for data reduction of large EMG signals. This frequency domain technique splits the EMG signal into a fixed number of time […]

Facial EMG & Startle Response

Facial electromyography (fEMG) typically uses surface EMG electrodes to detect activity at the zygomaticus (cheek), orbicularis oculi (under eye), and/or corrugator supercilii (brow) muscle regions as a participant is exposed to a stimulus, such as sounds, pictures, or smells for psychophysiology or neuroscience studies. On-Demand Webinar | How to Record Great Facial EMG Data Multiple stimulus […]

H-Reflex Methodology

The Hoffmann reflex (H-reflex) is an electrically induced reflex that bypasses the muscle spindle. H-reflex is a useful measure to assess modulation of monosynaptic reflex activity in the spinal cord. H-reflex studies can be set up multiple ways and users should determine the best approach for their required protocol; BIOPAC cannot recommend a “standard” approach […]

Histogram Analysis

Use the Histogram display features to identify trends within the EMG data. Select an area of data, or the entire data file, and the Histogram feature will bin the values into their appropriate amplitude ranges. The software will automatically determine the display range and the number of bins, or you can set them manually. Histogramming […]

Integrated (RMS) EMG

Integrated EMG (iEMG) is defined as the area under the curve of the rectified EMG signal; that is, the mathematical integral of the absolute value of the raw EMG signal. When the absolute value of the signal is taken, noise will make the mathematical integral have a constant increase. Integrated EMG splits up the signal […]

Interface With Imaging Equipment

The MP System can be synchronized with imaging systems (MRI, video capture, etc.). An imaging system can be used to trigger the recording or, alternatively, the MP System can be used to trigger the imager. With CAM-HFR-A and AcqKnowledge media tools, it’s possible to obtain synchronization within 1 video frame (10 ms) between physiological data […]