Validation of a discrete electrographic seizure detection algorithm for extended-duration, reduced-channel wearable EEG

被引:0
作者
Newton, Tyler J. [1 ]
Frankel, Mitchell A. [1 ]
Tosi, Zoe [1 ]
Kazen, Avidor B. [1 ]
Muvvala, Vamshi K. [1 ]
Loddenkemper, Tobias [2 ,3 ]
Spitz, Mark C. [4 ]
Strom, Laura [4 ]
Friedman, Daniel [5 ]
Lehmkuhle, Mark J. [1 ]
机构
[1] Epitel, Salt Lake City, UT 84111 USA
[2] Boston Childrens Hosp, Dept Neurol, Div Epilepsy & Clin Neurophysiol, Boston, MA USA
[3] Harvard Med Sch, Boston, MA USA
[4] Univ Colorado, Dept Neurol, Epilepsy Sect, Aurora, CO USA
[5] NYU, Grossman Sch Med, NYU Langone Hlth, Dept Neurol, New York, NY USA
基金
美国国家卫生研究院;
关键词
EEG; electroencephalography; machine learning; seizure detection; wearables; EPILEPSY; LONG;
D O I
10.1111/epi.18365
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
ObjectiveReduced-channel wearable electroencephalography (EEG) may overcome the accessibility and patient comfort limitations of traditional ambulatory electrographic seizure monitoring during extended-duration use. Automated algorithms are necessary for review of extended-duration reduced-channel EEG, yet current clinical support software is designed only for full-montage recordings.MethodsThe performance of a novel automated seizure detection algorithm for reduced-channel EEG (Epitel) was evaluated in a clinical validation study involving 50 participants (31 with seizures) with diverse demographic and seizure representation.ResultsThe algorithm demonstrated an event-level sensitivity of 86.2% (95% confidence interval [CI] = 79.5%-93.2%) and a false detection rate of .162 per hour (95% CI = .116-.221), which is comparable to the performance of current clinical software for full-montage EEG. Performance varied by electrographic seizure type, with 91.4% sensitivity for focal evolving to generalized seizures, 86.7% for generalized seizures, and 77.3% for focal seizures. The algorithm maintained robust performance in both pediatric participants aged 6-21 years (83% sensitivity) and adults aged 22+ years (90% sensitivity), as well as in ambulatory (80%) and epilepsy monitoring unit (EMU) monitoring environments (87.5%). The false detection rate in ambulatory monitoring environments (.290 false positive [FP] detections/h), all of which involved pediatric participants, was notably higher than in the EMU (.136 FP/h), indicating an area with clear need for improvement for unrestricted at-home monitoring. The algorithm's supplemental Confidence metric, designed to engender trust in the algorithm, showed a strong correlation with detection precision.SignificanceThese results suggest that this algorithm can provide crucial support for review of extended-duration reduced-channel wearable EEG, enabling electrographic seizure monitoring with no restrictions on a person's daily life.
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页数:11
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共 31 条
  • [1] Interobserver Reproducibility of Electroencephalogram Interpretation in Critically Ill Children
    Abend, Nicholas S.
    Gutierrez-Colina, Ana
    Zhao, Huaqing
    Guo, Rong
    Marsh, Eric
    Clancy, Robert R.
    Dlugos, Dennis J.
    [J]. JOURNAL OF CLINICAL NEUROPHYSIOLOGY, 2011, 28 (01) : 15 - 19
  • [2] Austrian Institute of Technology, 2024, 510(k) summary: Encevis 2.0
  • [3] The role of EEG in patients with suspected epilepsy
    Benbadis, Selim R.
    Beniczky, Sandor
    Bertram, Edward
    Maclver, Stephanie
    Moshe, Solomon L.
    [J]. EPILEPTIC DISORDERS, 2020, 22 (02) : 143 - 155
  • [4] BESA Epilepsy, BESA Epilepsy 2.0
  • [5] Bourget D, 2015, I IEEE EMBS C NEUR E, P61, DOI 10.1109/NER.2015.7146560
  • [6] Visual EEG reviewing times with SCORE EEG
    Brogger, Jan
    Eichele, Tom
    Aanestad, Eivind
    Olberg, Henning
    Hjelland, Ina
    Aurlien, Harald
    [J]. CLINICAL NEUROPHYSIOLOGY PRACTICE, 2018, 3 : 59 - 64
  • [7] Epilepsy Foundation, About us
  • [8] Epitel Inc, 2024, 510(k) summary: REMIAI discrete detection module (REMIAI DDM)
  • [9] Epitel Inc, 2023, 510(k) summary: REMI remote EEG monitoring system
  • [10] Wearable Reduced-Channel EEG System for Remote Seizure Monitoring
    Frankel, Mitchell A.
    Lehmkuhle, Mark J.
    Spitz, Mark C.
    Newman, Blake J.
    Richards, Sindhu, V
    Arain, Amir M.
    [J]. FRONTIERS IN NEUROLOGY, 2021, 12