This add-on is designed to extract useful statistical temporal and spectral information from electromyography data acquired with the Electromyography (EMG) sensor. Its own automatic onset detection algorithm is designed to detect muscle activations in the EMG signal, allowing the user to select and derive activation-specific parameters for further analysis of the EMG signal.
The onset detection algorithm can be fine-tuned for application-specific muscle activation detection by defining the frequency ranges of interest using the available low pass, high pass, and band pass filters. This add-on can also be used for muscle activation order analysis and to conduct a Maximum Voluntary Contraction-dependent statistical analysis.
- BITalino Electromyography (EMG)
- biosignalsplux Electromyography (EMG)
- biosignalsplux muscleBAN
Included in the following kits
The EMG Analysis add-on extracts the parameters and features listed below which can be exported as reports in .CSV and .PDF file formats.
- Automatic onset detection algorithm
- Temporal & spectral feature extraction
- Maximum Voluntary Contraction-dependent statistical analysis
- Multi-channel signal processing
- Direct parameter comparison of 2 selected muscle activations
- Aquisition parameters (start, end, duration)
- Activation specific parameters
- Start & end time
- Max. & min. amplitude
- Peak-to-Peak amplitude
- Integral over activation segments
You can use the following sample data to test the add-on yourself (a free version of the add-on is included in the free OpenSignals base version):
You can download sample reports of this add-on here (PDF and .ZIP file with CSV files below):