Circadian and Multi-day Rhythms in Generalized Tonic-Clonic Seizure: A Probabilistic Approach
Epilepsy is a chronic neurological disorder characterized by recurrent seizures that affect more than 50 million people worldwide, representing approximately 0.6\% of the global population. This condition poses significant public health challenges, with a heightened risk of premature mortality. Unde...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2023
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| Online Access: | https://hdl.handle.net/1721.1/152767 https://orcid.org/0000-0002-8446-7614 |
| _version_ | 1826206225856987136 |
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| author | Zhang, Boyu |
| author2 | Picard, Rosalind W. |
| author_facet | Picard, Rosalind W. Zhang, Boyu |
| author_sort | Zhang, Boyu |
| collection | MIT |
| description | Epilepsy is a chronic neurological disorder characterized by recurrent seizures that affect more than 50 million people worldwide, representing approximately 0.6\% of the global population. This condition poses significant public health challenges, with a heightened risk of premature mortality. Underdiagnosis and undertreatment remain pervasive, particularly in low- and middle-income countries.
Studies have discovered that seizure occurrences are phase-locking to subject-specific circadian and multi-day rhythms in human physiological signals. Also, various types of epilepsy have distinctive timing patterns with respect to sleep-wake cycles. However, it remains inconclusive how sleep parameters, non-invasive ambulatory physiological signals, and seizure occurrences are quantitatively related.
We first conduct an observational study on the association between sleep parameters, including duration, efficiency, fragmentation, and regularity, and generalized tonic-clonic seizure (GTCS) occurrences on the next day. We then conduct retrospective analyses of GTCS events phase-locking to rhythms in wrist electrodermal activity (EDA), validating previous claims. Ambulatory sleep-wake cycles and EDA recorded by smart wristbands from more than 1,000 patients diagnosed with GTCS are analyzed. GTCS events are detected by an FDA-cleared algorithm on the wristband. |
| first_indexed | 2024-09-23T13:26:05Z |
| format | Thesis |
| id | mit-1721.1/152767 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T13:26:05Z |
| publishDate | 2023 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1527672023-11-03T03:29:57Z Circadian and Multi-day Rhythms in Generalized Tonic-Clonic Seizure: A Probabilistic Approach Zhang, Boyu Picard, Rosalind W. Program in Media Arts and Sciences (Massachusetts Institute of Technology) Epilepsy is a chronic neurological disorder characterized by recurrent seizures that affect more than 50 million people worldwide, representing approximately 0.6\% of the global population. This condition poses significant public health challenges, with a heightened risk of premature mortality. Underdiagnosis and undertreatment remain pervasive, particularly in low- and middle-income countries. Studies have discovered that seizure occurrences are phase-locking to subject-specific circadian and multi-day rhythms in human physiological signals. Also, various types of epilepsy have distinctive timing patterns with respect to sleep-wake cycles. However, it remains inconclusive how sleep parameters, non-invasive ambulatory physiological signals, and seizure occurrences are quantitatively related. We first conduct an observational study on the association between sleep parameters, including duration, efficiency, fragmentation, and regularity, and generalized tonic-clonic seizure (GTCS) occurrences on the next day. We then conduct retrospective analyses of GTCS events phase-locking to rhythms in wrist electrodermal activity (EDA), validating previous claims. Ambulatory sleep-wake cycles and EDA recorded by smart wristbands from more than 1,000 patients diagnosed with GTCS are analyzed. GTCS events are detected by an FDA-cleared algorithm on the wristband. S.M. 2023-11-02T20:14:44Z 2023-11-02T20:14:44Z 2023-09 2023-09-14T18:08:51.696Z Thesis https://hdl.handle.net/1721.1/152767 https://orcid.org/0000-0002-8446-7614 In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
| spellingShingle | Zhang, Boyu Circadian and Multi-day Rhythms in Generalized Tonic-Clonic Seizure: A Probabilistic Approach |
| title | Circadian and Multi-day Rhythms in Generalized Tonic-Clonic Seizure: A Probabilistic Approach |
| title_full | Circadian and Multi-day Rhythms in Generalized Tonic-Clonic Seizure: A Probabilistic Approach |
| title_fullStr | Circadian and Multi-day Rhythms in Generalized Tonic-Clonic Seizure: A Probabilistic Approach |
| title_full_unstemmed | Circadian and Multi-day Rhythms in Generalized Tonic-Clonic Seizure: A Probabilistic Approach |
| title_short | Circadian and Multi-day Rhythms in Generalized Tonic-Clonic Seizure: A Probabilistic Approach |
| title_sort | circadian and multi day rhythms in generalized tonic clonic seizure a probabilistic approach |
| url | https://hdl.handle.net/1721.1/152767 https://orcid.org/0000-0002-8446-7614 |
| work_keys_str_mv | AT zhangboyu circadianandmultidayrhythmsingeneralizedtonicclonicseizureaprobabilisticapproach |