{
  "abstract": "Real-time monitoring of student stress and focus requires low-cost EEG systems, but fixed spectral thresholds may not transfer reliably across users because EEG amplitude and band power vary between individuals and recording conditions. This study investigates a subject-specific thresholding approach using a two-channel Brain BioAmp acquisition setup (FP1 and FP2) and an ESP32-based FFT pipeline. Beta/Alpha and Theta/Alpha ratios are calculated from spectral band estimates and compared with thresholds derived from Baseline, Focused, and Stressed task-condition recordings. In the reported pilot results, the mean Beta/Alpha ratio increased from 2.76 during Baseline to 2.80 during Focused and 2.88 during Stressed conditions. The Theta/Alpha ratio was lowest during Focused (0.95) and highest during Stressed (1.04), compared with 0.99 during Baseline. These are descriptive observations; classification accuracy, statistical significance, and generalization across participants have not been established. The signal-processing calculations and plotted frequency ranges should be checked against the original implementation before these values are treated as final.",
  "abstract_shown": true,
  "affiliations": [
    "Vivekanand Education Society's Institute of Technology"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "A. K. Jha"
    },
    {
      "name": "A. Kalsekar"
    },
    {
      "name": "M. S. Chogle"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9ehf0qp8wchhz.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.20.759906",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.20.759906v1.full",
  "id": "9ehf0qp8wchhz",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.20.759906v1",
  "language": null,
  "licence": "CC-BY-NC",
  "licence_label": "CC BY-NC",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "bioengineering"
    ],
    [
      "openalex",
      "2805|EEG and Brain-Computer Interfaces"
    ]
  ],
  "openalex": "W7223566657",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.20.759906v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-20",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/9ehf0qp8wchhz.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:29:34Z",
      "native_id": "10.64898/2026.10.20.759906",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.20.759906v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioengineering",
      "subfield": "systems-synthetic"
    }
  ],
  "title": "A Personalized Approach to Student Mental Health: Real-Time EEG Biofeedback for Stress and Focus Management",
  "title_text": "A Personalized Approach to Student Mental Health: Real-Time EEG Biofeedback for Stress and Focus Management",
  "type": "preprint",
  "updated_at": "2026-10-30T12:29:34Z",
  "url": "https://research.draconitic.com/paper/9ehf0qp8wchhz",
  "venue": "bioRxiv",
  "versions": []
}