{
  "annotation_id": "65f3f812-2e78-44c1-a344-a4f9b11de415",
  "date_created": "2026-03-02T18:00:43.085000Z",
  "date_modified": "2026-03-02T18:00:43.085000Z",
  "file_hash": "dcbc29a2d75203b8498dd0775a481f54cb7839a060152e8b4004450b5aae2121",
  "private": false,
  "record": {
    "abstract": "Interictal spikes and sharp waves in human EEG are characteristic signatures\nof epilepsy. These potentials originate as a result of synchronous,\npathological discharge of many neurons. The reliable detection of such\npotentials has been the long standing problem in EEG analysis, especially after\nlong-term monitoring became common in investigation of epileptic patients. The\ntraditional definition of a spike is based on its amplitude, duration,\nsharpness, and emergence from its background. However, spike detection systems\nbuilt solely around this definition are not reliable due to the presence of\nnumerous transients and artifacts. We use wavelet transform to analyze the\nproperties of EEG manifestations of epilepsy. We demonstrate that the behavior\nof wavelet transform of epileptic spikes across scales can constitute the\nfoundation of a relatively simple yet effective detection algorithm.",
    "arxiv_id": "physics/0301065",
    "authors": [
      "Miroslaw Latka",
      "Ziemowit Was",
      "Andrzej Kozik",
      "Bruce J. West"
    ],
    "categories": [
      "physics.bio-ph",
      "physics.med-ph",
      "q-bio"
    ],
    "doi": "10.1103/PhysRevE.67.052902",
    "title": "Wavelet analysis of epileptic spikes",
    "url": "https://arxiv.org/abs/physics/0301065"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "79a451fa-31a3-4593-8c93-017c1c0e9450",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}