Keywords: surface high density electromyogram (HDEMG), motor unit, spike train, motor unit merging, simulated data, experimental data, biceps brachii, dataset

SHARING/ACCESS INFORMATION
This dataset is available under the Creative Commons Public Domain Dedication (CC0) license.

Publicly accessible location of the data: https://dk.um.si/IzpisGradiva.php?lang=eng&id=88844

PID: 20.500.12556/DKUM-88844

Recommended citation for this dataset:
Holobar, Aleš, Škarabot, Jakob, Farina, Dario. “Simulated and experimental HDEMG signals of biceps brachii muscle for analysis of motor unit merging”. System Software Laboratory, Faculty of Electrical Engineering and Computer Science, University of Maribor, Slovenia. Digital library of University of Maribor. https://dk.um.si/IzpisGradiva.php?lang=eng&id=88844

DATA & FILE OVERVIEW
This dataset contains a collection of simulated and experimental surface HDEMG recordings of the biceps brachii muscle during the isometric elbow flexion. Simulated data contains 50 recordings: 5 subjects and 5 excitation levels, each with and without added noise. Experimental data contains 16 recordings: 2 subjects with 4 excitation levels and 2 repetitions of each level. Synthetic data was simulated using the cylindrical volume conductor model [1] and the motor unit recruitment and firing modulation model proposed in [2]. Each recording is 20 seconds in length with 90 HDEMG channels sampled at 2048 Hz and is stored as a 2D matrix of raw EMG values in Matlab's MAT format. Experimental surface EMG data was recorded on two volunteers during isometric contractions at constant force level. Each recording is 25 seconds in length with 64 HDEMG channels sampled at 2048 Hz and is also stored as a 2D matrix of raw EMG values in Matlab's MAT format. The dataset is approximately 1.5 GB in size.

File list:

• README.txt: this text file containing description of the dataset
• metadata.xml: Dublin Core metadata in XML format
• folder "SyntheticHDEMG":
•      - folders "Lib1" to "Lib5" contain data for 5 different (simulated) subjects
•      - each folder contains 10 files with simulated HDEMG recordings of the biceps brachii muscle:
•          - for 5 different excitation levels (as percentage of maximum voluntary contraction - MVC): 10, 30, 50, 70, 90
•          - for 2 different levels of added noise (as signal-to-ratio - SNR in dB): Inf, 20
•      - filenames are in format: SyntheticHDEMG_BicepsBrachii_Lib>lib_no<_ConstantExcitation>mvc_level<MVC_SNR>snr_level<dB.mat, where LIB_NO is the simulated subject number, MVC_LEVEL is the excitation level as percentage of MVC and SNR_LEVEL is the signal-to-noise ratio in dB
•      - MAT_file_content_synth.png: screenshot of the Matlab workspace with all the variables loaded from the MAT file, for synthetic data
• folder "ExperimentalHDEMG":
•      - folders "Subject1" and "Subject2" contain data for 2 different subjects (volunteers)
•      - each folder contains 8 files with recorded HDEMG of the biceps brachii muscle:
•          - for 4 different excitation levels (as percentage of maximum voluntary contraction - MVC): 10, 30, 50, 70
•          - for 2 repetitions: trial1, trial2
•      - filenames are in format: ExperimentalHDEMG_BicepsBrachii_Subject>sub_no<_ConstantExcitation>mvc_level<MVC_trial>trial_no<.mat, where SUB_NO is the subject number, MVC_LEVEL is the excitation level as percentage of MVC and TRIAL_NO is the repetition number
•      - MAT_file_content_exp.png: screenshot of the Matlab workspace with all the variables loaded from the MAT file, for experimental data
• MAT_file_content.png: screenshot of the Matlab workspace with all the variables loaded from the MAT file

All files with extension .MAT are in Matlab format, which is a proprietary format but its specifications are open and there are open source routines available for reading and writing:

• The GNU Octave software, which is an open source alternative to Matlab, can read and write .MAT files.
• The Python library Scipy can load MAT files.
• The Matio project on SourceForge is a C library for reading and writing Matlab MAT files.

METHODOLOGICAL INFORMATION
Description of methods used for collection/generation of data:
The synthetic multichannel sEMG data were generated by a multilayer cylindrical volume conductor model [1] for the biceps brachii muscle.

Model parameters:

• Motor unit conduction velocity: 4 m/s
• Tissue conductivities (in S/m):
•      - Bone: 0.02
•      - Muscle (radial and transverse): 0.1
•      - Muscle (longitudinal): 0.5
•      - Subcutaneous tissue: 0.05
•      - Skin: 0.1
• Muscle properties:
•      - Number of motor units: 500
•      - Number of muscle fibers: 165656
•      - Number of fibers in a motor unit (range): 25 - 1500
•      - Muscle cross-sectional area: 1413 square mm
•      - Average fiber length: 130 mm
•      - Skin thickness: 1 mm
•      - Subcutaneous tissue thickness: 4 mm
•      - Bone (radius): 20 mm
•      - Tendon ending spread: 5 mm
• Electrodes:
•      - Grid: 10 rows x 9 columns
•      - Circular (diameter): 0.5 mm
•      - Interelectrode distance: 5 mm
• Excitation level (% maximum):
•      - Constant force: 10, 30, 50, 70, 90 % of maximum voluntary contraction (MVC)
• Innervation zone in the middle
• Sample rate: 4096 Hz
• Total length: 20 s
• SNR: infinite (no noise added), 20 dB
• Monopolar recording mode

Simulated sEMG motor unit (MU) firing pattern model: The MU firing pattern was computed by the model proposed in [2] with the parameters adapted to the biceps brachii muscle. MU recruitment thresholds followed an exponential distribution with many low-threshold MUs and progressively fewer high-threshold MUs [2]. The last MU was recruited at 80% of maximal excitation level. MUs linearly increased the firing rates from 8 pulses per second (pps) at recruitment to 35 pps at 100 % of maximal excitation. Interspike interval of each MU followed Gaussian distribution with coefficient of variation equal to 20 %.

Experiemental sEMG was recorded on two volunteers (age: 30 +- 1 years, weight: 87 +- 9 kg, height: 183 +- 4 cm) using a 13x5 electrode grid (GR08MM1305, OT Bioelettronica, Torino, Italy) positioned over the lateral and medial biceps brachii muscle heads. Signals were recorded during isometric contractions at constant force level of 10, 30, 50 or 70 % of the maximum voluntary contraction (MVC). Each recording was repeated twice (two trials). EMG signals were sampled at 2048 Hz with 16 bit resolution (Quattrocento, OT Bioelettronica, Torino, Italy). The exerted force level was measured with a dedicated sensor, time synchronized with the EMG acquisition. The experimental procedures were approved by Loughborough University Ethical Committee (G05-P3) and were conducted in accordance with the Declaration of Helsinki except for registration in database.

Methods for processing the data:
The simulated raw multichannel sEMG signals were downsampled from 4096 to 2048 Hz so they have the same sampling frequency as the experimental recordings. The experimental recordings were recorded using the OTBiolab software (OT Bioelettronica, Italy) and stored in the .OTB file format. Afterwards they were converted with OpenOTBFiles software (OT Bioelettronica, Italy) and stored as 2D matrix of raw EMG values in Matlab's MAT format.

For generation of synthetic sEMG signals we used the multilayer cylindrical volume conductor model by D. Farina et al. [1].

Experimental signals were recorded using the OTBiolab software by OT Bioelettronica, Italy (https://otbioelettronica.it/en/download/ ,free download).

Experimental signals were converted to Matlab MAT format using the OpenOTBFiles software by OT Bioelettronica, Italy (https://otbioelettronica.it/en/download/#55-133-wpfd-openotbfiles, free download).

For reading the .MAT files we recommend the following options:

• Matlab software (https://www.mathworks.com).
• The GNU Octave software, an open source alternative to Matlab (https://octave.org/).
• The Python library Scipy (https://docs.scipy.org/doc/scipy/reference/generated/scipy.io.loadmat.html).
• The Matio project on SourceForge (https://sourceforge.net/projects/matio/).

Quality-assurance procedures performed on the data:
All simulated data was plotted and visually inspected for any errors or anomalies, but none were rejected. Experimental data was not modified.

DATA-SPECIFIC INFORMATION FOR SYNTHETIC SIGNALS (FOLDER "SyntheticHDEMG"):
Number of variables: 9

Variable list:

• fsamp: integer number. Data sampling frequency in Hz.
• sigLength: double number. Total length of the signals in seconds.
• HDEMG: structure array. Dimensions are the same as the simulated EMG electrode grid: 10 rows x 9 columns. Each cell contains a 1 x N vector of samples (double values) representing EMG voltage. N = total number of samples = fsamp * sigLength.
• sFirings: structure array. Contains M cells corresponding to M simulated motor units, each cell contains a 1 x L vector of motor unit firing instants (integer values indicating sample indices). M = number of simulated motor units, L = number of motor unit firings.
• library: integer number. Numerical ID label of simulated subject.
• excitationLevel: double array, 1 x N in size. Contains excitation level for each data sample.
• SNR: double number. Signal-to-noise ratio in dB.
• recordingMode: string. Denotes the simulated voltage measurement technique, "Monopolar" for this dataset.
• InterElectrodeDistance: double number. Interelectrode distance in mm.

DATA-SPECIFIC INFORMATION FOR EXPERIMENTAL SIGNALS (FOLDER "ExperimentalHDEMG"):
Number of variables: 9

Variable list:

• fsamp: integer number. Data sampling frequency in Hz.
• sigLength: double number. Total length of the signals in seconds.
• HDEMG: structure array. Dimensions are the same as the EMG electrode grid: 13 rows x 5 columns. Each cell contains a 1 x N vector of samples (double values) representing EMG voltage. N = total number of samples = fsamp * sigLength.
• subject: integer number. Numerical ID label of the subject.
• trial: integer number. Numerical index of the measurement repetition (trial).
• contractionLevel: integer number. Value of the target constant force level, expressed as % of the maximum voluntary contraction (MVC).
• force: double array, 1 x N in size. Contains measured exerted force for each time instant, synchronized with the EMG data samples.
• recordingMode: string. Denotes the simulated voltage measurement technique, "Monopolar" for this dataset.
• InterElectrodeDistance: double number. Interelectrode distance in mm.

REFERENCES:
[1] Farina, Dario, Luca Mesin, Simone Martina, and Roberto Merletti. "A surface EMG generation model with multilayer cylindrical description of the volume conductor." IEEE Transactions on Biomedical Engineering 51, no. 3 (2004): 415-426. doi: 10.1109/TBME.2003.820998.

[2] Fuglevand, Andrew J., David A. Winter, and Aftab E. Patla. "Models of recruitment and rate coding organization in motor-unit pools." Journal of neurophysiology 70, no. 6 (1993): 2470-2488.