<div class="sc-cmRAlD dkqmWS"><div class="sc-UEtKG dGqiYy sc-flttKd cguEtd"><div class="sc-fqwslf gsqkEc"><div class="sc-cBQMlg kAHhUk"><h2 class="sc-dcKlJK sc-cVttbi gqEuPW ksnHgj">About Dataset</h2></div></div></div><div class="sc-jgvlka jFuPjz"><div class="sc-gzqKSP ktvwwo"><div style="min-height: 80px;"><div class="sc-etVRix jqYJaa sc-bMmLMY ZURWJ"><p><strong>Description</strong>:<br>

This dataset consists of EEG recordings of five essential words commonly used in speech therapy for post-stroke patients. The data was collected from a single female participant using a NeuroSky Mindwave Mobile 2 headset in a controlled environment, ensuring minimal noise interference and high-quality signal acquisition.</p>

<p><strong>Purpose</strong>:<br>

The dataset aims to facilitate research in neuroscience and brain-computer interface (BCI) development, specifically for post-stroke rehabilitation. It provides a foundation for creating machine learning models that decode EEG signals into meaningful linguistic outputs, offering potential breakthroughs in assistive technologies for individuals with speech and motor impairments.</p>

<p><strong>Data Structure</strong>:<br>

<strong>EEG Signal Data</strong>: Captures brainwave patterns corresponding to five essential words.<br>

<strong>Participant</strong>: Post-stroke patients engaged in tasks designed to evoke EEG responses tied to the target words.<br>

<strong>Recording Settings</strong>: Standardized environment with participants focusing on auditory and visual stimuli associated with each word.</p>

<p><strong>Applications</strong>:<br>

Development of classification algorithms for EEG signals linked to word recognition.<br>

Training BCIs to assist in real-time communication for post-stroke patients.<br>

Studying neural activity associated with speech therapy exercises.</p>

<p><strong>Potential Use Cases</strong>:<br>

Creation of assistive communication devices for individuals with speech and motor challenges.<br>

Research into personalized EEG signal responses during language-based rehabilitation.<br>

Advancement of neurotechnology for targeted healthcare applications.</p>

<p><strong>Dataset Features</strong>:<br>

High-quality EEG recordings of five essential rehabilitation words.<br>

Precise, noise-minimized data collection.<br>

Open-access format to encourage reproducibility and collaboration in EEG and healthcare research.</p></div></div></div>