Keywords: Surface high density electromyogram (HDEMG), electroencephalogram (EEG), dataset, tibialis anterior, isometric ankle dorsiflexion, beta-band oscillations, motor control , HybridNeuro

SHARING/ACCESS INFORMATION
This dataset is available under the Creative Commons Attribution (CC BY) 4.0 license.

Publicly accessible location of the data: https://dk.um.si/IzpisGradiva.php?id=96397&lang=eng

PID: 20.500.12556/DKUM-96397

Recommended citation for this dataset:
Zicher Blanka, McGeady Ciaran, Farina Dario, Divjak Matjaž, Murks Nina. “EEG + High-density surface EMG recordings of right tibialis anterior muscle during isometric ankle dorsiflexion (HybridNeuro project)”. 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=96397

DATA & FILE OVERVIEW
This dataset was prepared in the context of the HybridNeuro project (https://www.hybridneuro.feri.um.si/). It contains a collection of simultaneous EMG and EEG recordings from 7 healthy volunteers. The main purpose of data collection was to investigate the role of beta-band oscillations in motor control by examining how cortical beta activity propagates to the motor unit pool and can be measured at the peripheral level using high-density EMG. Surface EMG was recorded using 64-channel electrode grids arranged in a 13 x 5 configuration with one missing corner electrode and an interelectrode distance of 4 mm (OT Bioelettronica, Torino, Italy). Signals were amplified (150 V/V), sampled at 2048 Hz using a Quattrocento system (OT Bioelettronica, Torino, Italy), and band-pass filtered between 20 and 500 Hz. Different grid placements were employed to maximize the number of motor units decomposed from the EMG signals. EEG signals were recorded with 31 active gel-based electrodes positioned according to the International 10-20 system, with FCz as the reference electrode (actiCAP, Brain Products GmbH, Gilching, Germany). Signals were amplified and sampled at 1 kHz using a BrainVision actiCHamp Plus system (Brain Products GmbH, Gilching, Germany). EEG, EMG, and the exerted force signals were temporally synchronized using a common digital trigger sent to both recording systems. Participants performed 2 repetitions of 4 sets of trapezoidal submaximal isometric contractions using the right tibialis anterior muscle, at 4 different contraction levels. Total task length was 640 s (not including rests). Each task's data is stored in a separate file in Matlab format (.MAT). Total dataset size is 8.5 GB.

File list:

• README.txt: this text file containing description of the dataset
• README.pdf: formatted PDF file containing description of the dataset
• metadata.xml: Dublin Core metadata in XML format
• compressed (ZIPed) files "S1.zip" to "S7.zip" containing data folders for 7 different participants, each folder contains the same set of 8 files:
• - 15_1.mat: data for dorsiflexion at 15 % MVC, repetition 1
  - 15_2.mat: data for dorsiflexion at 15 % MVC, repetition 2
  - 20_1.mat: data for dorsiflexion at 20 % MVC, repetition 1
  - 20_2.mat: data for dorsiflexion at 20 % MVC, repetition 2
  - 25_1.mat: data for dorsiflexion at 25 % MVC, repetition 1
  - 25_2.mat: data for dorsiflexion at 25 % MVC, repetition 2
  - 30_1.mat: data for dorsiflexion at 30 % MVC, repetition 1
  - 30_1.mat: data for dorsiflexion at 30 % MVC, repetition 2
  
• figure1_protocol_steps.png: figure depicting all the steps of the experimental protocol
• figure2_mat_file_content.png: screenshot of the Matlab workspace with all the variables loaded from one 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 purpose of this data collection was to support a study on the role of beta-band oscillations in motor control by examining how cortical beta activity propagates to the motor unit pool and can be measured at the peripheral level using high-density EMG. Specifically, the study aimed to characterize the presence and behaviour of beta bursts in muscles during isometric contractions and assess their similarity to cortical beta activity.

Muscles during isometric contractions and assess their similarity to cortical beta activity. Subject's information and ethical agreement: A total of 7 participants (all males, ages: 21-38 years) took part in this experiment and gave their written informed consent. The study was conducted in accordance with the Declaration of Helsinki and was approved by the Imperial College Ethics committee (18IC4685). Environment: During the experiment, participants sat in a comfortable chair with their knee flexed at 75◦, their right leg securely fixed to an ankle dynamometer with Velcro straps, and their foot positioned onto a pedal at 30◦ in the plantarflexion direction, 0◦ being the foot perpendicular to the shank. A force transducer (TF022, CCT Transducer s.a., Torino, Italy) fixed to the pedal recorded the force. During all tasks, participants received visual feedback with a target representing the level of force to reach and a trace representing the force they produced.

Preparation: All participants were instructed to abstain from alcohol and caffeine on the day preceding and the day of the experimental protocol. They were also asked to wash their hair without using any hair products one day before testing and to shave the right leg over the tibialis anterior muscle. The tibialis anterior muscle was first identified by asking participants to perform a brief ankle dorsiflexion. The skin over the muscle belly was then prepared using an abrasive paste (Meditec-Every, Parma, Italy). Surface electrodes were prepared by placing an adhesive foam and filling the foam cavities with Ten20 conductive paste. The electrode was positioned over the muscle belly and secured using elastic straps. Two reference straps - one serving as the patient reference and the other as the preamplifier reference - were placed around the ankle. EMG signals were visually inspected. First quality check was performed with the participant in a relaxed state, during which the signals were visible as flat lines on all channels. Participant then performed a slight dorsiflexion contraction, resulting in clearly visible motor unit action potentials across all channels, which allowed for the observation of signal propagation.

Prior to EEG cap placement, head dimensions were measured from ear to ear and from nasion to inion to ensure accurate positioning. The cap was positioned by aligning the Cz electrode at the midpoint of both measurements. All electrodes were then filled with conductive gel (Neurogel, Spec Medica). The impedance was monitored and reduced to below 5 kΩ. The reference electrode (CDES003545, Spes Medica) was placed on the collarbone. EEG signal quality was verified by visual inspection for artifacts, including eye blinks, vertical and horizontal eye movements, and teeth clenching. Signal quality was further confirmed during a resting state with eyes closed by identifying the presence of alpha activity. The experimental protocol comprised the following tasks (Figure 1):

• Two maximal voluntary contractions (MVCs) of isometric ankle dorsiflexion were performed, each followed by 120 s of rest. The larger MVC value was used during the rest of the protocol.
• Participants then performed two repetitions of four trapezoidal submaximal isometric contractions. Each trapezoidal contraction included a 10 s ramp-up phase, a 60 s steady hold, and a 10 s ramp-down phase, with target forces set at 15%, 20%, 25%, and 30% of MVC. A 60 s rest period was provided between each contraction.

Methods for processing the data: Signals were recorded using the OTBiolab+ software (OT Bioelettronica, Torino, Italy). After the recording we converted the signals from OTB file format into Matlab format using the reader function provided by OT Bioelettronica. No additional processing was performed.

Quality-assurance procedures performed on the data:
Signal quality was visually checked and adjusted for each participant at the start of the protocol. For EMG we visually checked for flat signal lines on all electrodes during relaxed state and for clearly visible motor unit action potentials across all channels during a slight dorsiflexion. For EEG we visually checked for presence of clearly visible artifacts (eye blinks, vertical and horizontal eye movements, teeth clenching) and for presence of alpha activity during resting state with eyes closed. No additional quality assurance steps were performed after the acquisition.

Variable list:
Variables describing EEG:

• fSampEEG: Sampling frequency of the EEG signals in Hz (recorded at 1000 Hz).
• eeg: Matrix containing the raw EEG data from 31 channels, arranged as channels x samples.
• eegChannelLabels: Cell array of channel labels corresponding to the EEG channels, ordered identically to the rows of eeg. Electrodes are positioned according to the International 10-20 system.
• eegNSamples: Total number of samples acquired per EEG channel.
• eegChanUnit: Physical unit of the EEG signal amplitudes (e.g., µV).
• eegImpedanceGround: Measured impedance of the ground electrode at the time of EEG acquisition.
• eegImpedanceChannels: Vector containing impedance values of all EEG electrodes, ordered consistently with eeg and eegChannelLabels.
• eegResolution: Voltage resolution of the EEG acquisition system, expressed as the smallest detectable voltage change per digital unit.
• eegCap: Model of the EEG cap used for acquisition (actiCAP, Brain Products GmbH).
• eegTriggerSignalValue: String array containing the digital trigger codes used for temporal synchronization of EEG, EMG, and force signals.
• eegTriggerSignalSample: Sample indices at which each trigger event (eegTriggerSignalValue) occurs in the EEG recording.
• eegTriggerSignalDuration: Duration (in samples) of each trigger event corresponding to eegTriggerSignalValue.
• eegDataFormat: Data storage format of the EEG recording. EEG signals are stored in binary format, as provided by the acquisition system.
• eegDataOrientation: Data organization scheme used in the EEG recording. EEG signals are stored in a multiplexed format, where samples from all channels are interleaved sequentially in time.
• eegBinaryFormat: Binary encoding format used to store the EEG data. EEG signals are saved using the IEEE 754 32-bit floating-point format (ieee_float32), providing single-precision representation of signal amplitudes.

Variables describing EMG:

• emg: Matrix containing the raw surface EMG signals recorded from multi-channel electrode grids.
• emgNSamples: Total number of samples acquired per EMG channel.
• fSampEMG: Sampling frequency of the EMG signals in Hz (recorded at 2048 Hz).
• emgIED: Inter-electrode distance of the EMG electrode grid, in millimeters (4 mm).
• emgElectrode: Model identifier of the EMG electrode grid used (GR04MM1305, OT Bioelettronica).
• emgMode: EMG acquisition mode (e.g., monopolar recording).
• emgMuscle: Muscle from which the EMG signals were recorded (Tibialis Anterior).
• emgSide: Body side on which the EMG electrodes were mounted (Right).
• emgHPF: High-pass filter cutoff frequency applied to the EMG signals during acquisition, in Hz.
• emgLPF: Low-pass filter cutoff frequency applied to the EMG signals during acquisition, in Hz.
• emgRefAux: Auxiliary reference signal acquired alongside EMG (e.g., force signal), sampled at the EMG sampling frequency and expressed in volts.
• emgRefTriggerSignal: Digital trigger signal recorded in the EMG system and used for synchronization with EEG and force recordings.