Statistical characteristics of large‐scale objective tonic–clonic seizure records from medical smartwatches used in daily life

Key population-level patterns in seizure occurrence are recapitulated in wrist-worn device recordings, supporting their validity for tracking TCS burden. Compared to other approaches, wearables can provide noninvasive, objective, long-term data, revealing cycles in seizure risk. However, improved patient engagement with wristband alerts and further validation of detection accuracy in ambulatory settings are needed. Together, these findings suggest that data from smart wristbands may be used to derive features of TCS records and, ultimately, facilitate remote monitoring and the development of personalized forecasting tools for TCS management. Our findings may not generalize to other types of seizures.

Authors

Institutions

Publication Details

Journal
Epilepsia
Published
2024-09-17
DOI
https://doi.org/10.1111/epi.18109
Citations
5
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
1.71

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Statistical characteristics of large‐scale objective tonic–clonic seizure records from medical smartwatches used in daily life

Weixuan Chen, Giulia Regalia, Boyu Zhang, Daniel M. Goldenholz et al.
5 citations
Epilepsia
EEG and Brain-Computer Interfaces
1.71
article

Statistical characteristics of large‐scale objective tonic–clonic seizure records from medical smartwatches used in daily life

Weixuan Chen, Giulia Regalia, Boyu Zhang, Daniel M. Goldenholz, Rosalind W. Picard
article en
5 citations

Abstract

Key population-level patterns in seizure occurrence are recapitulated in wrist-worn device recordings, supporting their validity for tracking TCS burden. Compared to other approaches, wearables can provide noninvasive, objective, long-term data, revealing cycles in seizure risk. However, improved patient engagement with wristband alerts and further validation of detection accuracy in ambulatory settings are needed. Together, these findings suggest that data from smart wristbands may be used to derive features of TCS records and, ultimately, facilitate remote monitoring and the development of personalized forecasting tools for TCS management. Our findings may not generalize to other types of seizures.

EpilepsiaVol. 65(11)
Brigham and Women's Hospital (US), Beth Israel Deaconess Medical Center (US), Harvard University (US), Circadian (United States) (US), Massachusetts Institute of Technology (US)
National Institutes of Health, National Heart, Lung, and Blood Institute, National Institute of Neurological Disorders and Stroke
Openalex Percentile: Top 16%
EEG and Brain-Computer Interfaces
1.71
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Statistical characteristics of large‐scale objective tonic–clonic seizure records from medical smartwatches used in daily life — Weixuan Chen, Giulia Regalia, et al. · Epilepsia (2024) | TGRS Research Map | TGRS