Circadian and Multi-day Rhythms in Generalized Tonic-Clonic Seizure: A Probabilistic Approach
Name
zhang-boyuz-SM-MAS-2023-thesis.pdf
Description
Thesis PDF
Size
17.76 MB
Format
Adobe PDF
Checksum (MD5)
e3fba8c4e3ea9d8ff3ad5bad75bc14da
Author(s)
Zhang, Boyu
Advisor(s)
Picard, Rosalind W.
Date Issued
September 2023
Publisher
Massachusetts Institute of Technology
Abstract
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.
MIT Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
In Copyright - Educational Use Permitted
Copyright retained by author(s)
Persistent DSpace Link
