DOI: 10.6084/m9.figshare.29589566.v1
title: Physiotherapist-Assisted Wrist Movement Protocol for EEG-Based Corticokinematic Coherence Assessment

description: This dataset accompanies the manuscript titled 'Physiotherapist-Assisted Wrist Movement Protocol for EEG-Based Corticokinematic Coherence Assessment' and includes synchronized EEG and movement recordings collected during a physiotherapist-assisted wrist movement task for corticokinematic coherence (CKC) analysis. The data are organized per participant and trial.<b>Contents</b>Each participant's data are stored in files using the following naming convention:<pre><pre>SXXX_ckc_HH_SS_BB<br></pre></pre>Where:<b>SXXX</b>: anonymized subject ID (random 3-digit code, e.g., S113, S479),<b>HH</b>: movement hand (<code>bal</code> = left hand, <code>jobb</code> = right hand),<b>SS</b>: session number (t1),<b>BB</b>: trial block number (01, 02).<b>File Types</b>Each trial includes the following two files:<br><b>Movement file</b> (no extension, e.g., <code>S113_ckc_bal_t1_01</code>):<br>Custom binary format containing synchronized hand acceleration data collected via a 3-axis accelerometer placed on the wrist.<b>Movement File Structure</b>Each entry contains:<code><strong>time</strong></code>: a 32-bit unsigned integer indicating the timestamp in milliseconds,<code><strong>x</strong></code>, <code><strong>y</strong></code>, <code><strong>z</strong></code>: 16-bit signed integers representing acceleration along the respective axes,<code><strong>trigger</strong></code>: an 8-bit unsigned integer used to mark event-related triggers for synchronization with the EEG data (e.g., movement onset).<br><br><b>EEG files (</b><code><strong>.hed</strong></code><b>/</b><code><strong>.flo</strong></code><b> pair)</b><br>EEG was recorded with a 64-channel Synamp RT system (Compumedics Neuroscan, Victoria, Australia) at 2000 Hz.Converted from the original Neuroscan CNT format into an open binary format.<code><strong>.hed</strong></code>: plain-text header describing the dataset (channels, sampling rate, etc.). Each line starts with a keyword such as:<code>Datatype</code>: always <code>float</code> (4-byte floats),<code>Number of timepoints</code>: total samples,<code>Starting timepoint</code>: always 0,<code>Sampling rate</code>: 1000 Hz,<code>Ch</code>: channel labels in order of appearance in the <code>.flo</code> file.<br>Other fields (e.g. <i>Number of channels hint</i>) can be ignored.<br><code><strong>.flo</strong></code>: binary file with EEG samples stored as little-endian 4-byte floats in <b>channel-major order</b>:<br>[Channel 1: sample 1 ... last sample] [Channel 2: sample 1 ... last sample] ...<b>Example (Python, using numpy):</b><pre><pre>import numpy as np, os<br><br>filename = "S113_ckc_bal_t1_01"<br><br># Read channel labels from .hed<br>channels = []<br>with open(filename + ".hed", "r") as f:<br> for line in f:<br> if line.startswith("Ch:"):<br> channels.append(line.split(":")[1].strip())<br>n_channels = len(channels)<br><br># Determine number of samples<br>filesize = os.path.getsize(filename + ".flo")<br>n_samples = filesize // (4 * n_channels)<br><br># Load EEG data<br>raweeg = np.fromfile(filename + ".flo", dtype="f4")<br>raweeg = raweeg.reshape(n_channels, n_samples)<br></pre></pre><b>Notes</b>Data are organized by movement side (<code>bal</code> = left, <code>jobb</code> = right), trial (<code>t1</code>), and block repetition (01, 02).The EEG and movement files are time-locked to enable CKC computation.Stimuli were delivered manually by a trained physiotherapist with visual pacing using a screen-based metronome.<b>Usage</b>These data can be used to replicate the analyses reported in the manuscript, or for methodological and clinical studies of proprioception using EEG-based CKC.Please cite the associated paper when using this dataset.