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Dhruva Shaw
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_layouts/distill.liquid

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{% endif %}
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{% include scripts/jquery.liquid %}
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{% include scripts/mathjax.liquid %}
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{% include scripts/mermaid.liquid %}
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{% include scripts/diff2html.liquid %}
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{% include scripts/leaflet.liquid %}
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{% include scripts/chartjs.liquid %}
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{% include scripts/echarts.liquid %}
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{% include scripts/vega.liquid %}
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{% include scripts/tikzjax.liquid %}
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{% include scripts/typograms.liquid %}
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{% include scripts/misc.liquid %}
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{% comment %}
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misc.liquid loads interactive features like the code copy button to prevent dynamic elements from displaying incorrectly at the end of the article.
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{% endcomment %}
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<!-- Distill js -->
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<script src="{{ '/assets/js/distillpub/template.v2.js' | relative_url }}"></script>
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<script src="{{ '/assets/js/distillpub/transforms.v2.js' | relative_url }}"></script>
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<d-citation-list></d-citation-list>
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</d-appendix>
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{% if page.citation %}
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{% include citation.liquid %}
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{% endif %}
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<d-bibliography src="{{ page.bibliography | prepend: '/assets/bibliography/' | relative_url }}"></d-bibliography>
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{% if site.disqus_shortname and page.disqus_comments %}{% include disqus.liquid %}{% endif %}
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{% include scripts/analytics.liquid %}
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{% include scripts/progressBar.liquid %}
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{% include scripts/back_to_top.liquid %}
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{% include scripts/search.liquid %}
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</body>
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</html>

_projects/mcba.md

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@@ -79,14 +79,14 @@ The dataset, originally provided in **CSV format**, underwent a comprehensive pr
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* Each individual channel's EEG data was converted into **audio signals** and saved in **.wav format**, allowing the brain signals to be audibly analyzed.
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* The entire preprocessing workflow was implemented in **Python** to ensure scalability and accuracy.
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The dataset captured brainwave signals corresponding to the following activities:
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1) **BEO** (Baseline with Eyes Open): One-time recording at the beginning of each run [3].
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2) **CLH** (Closing Left Hand): Five recordings per run [3].
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3) **CRH** (Closing Right Hand): Five recordings per run [3].
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4) **DLF** (Dorsal Flexion of Left Foot): Five recordings per run [3].
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5) **PLF** (Plantar Flexion of Left Foot): Five recordings per run [3].
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6) **DRF** (Dorsal Flexion of Right Foot): Five recordings per run [3].
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7) **PRF** (Plantar Flexion of Right Foot): Five recordings per run [3].
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8) **Rest**: Recorded between each task to capture the resting state [3] [4].
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1. **BEO** (Baseline with Eyes Open): One-time recording at the beginning of each run [3].
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2. **CLH** (Closing Left Hand): Five recordings per run [3].
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3. **CRH** (Closing Right Hand): Five recordings per run [3].
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4. **DLF** (Dorsal Flexion of Left Foot): Five recordings per run [3].
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5. **PLF** (Plantar Flexion of Left Foot): Five recordings per run [3].
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6. **DRF** (Dorsal Flexion of Right Foot): Five recordings per run [3].
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7. **PRF** (Plantar Flexion of Right Foot): Five recordings per run [3].
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8. **Rest**: Recorded between each task to capture the resting state [3] [4].
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### 3. Feature Extraction and Classification
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Feature extraction and activity classification were performed using **transfer learning** with **YamNet** [5], a deep neural network model.
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## Protocols
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Here is the protocol(steps) to reproduce our work with ease.
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<iframe src="https://www.protocols.io/widgets/doi?uri=dx.doi.org/10.17504/protocols.io.n92ldr869g5b/v1" style="width: 520px; height: 300px; border: 1px solid transparent;"></iframe>
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<object data="https://dhruvashaw.in/assets/pdf/resume.pdf" type='application/pdf'/>

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