Multimodal wearable EEG, EMG and accelerometry measurements improve the accuracy of tonic-clonic seizure detection.
Physiol Meas
; 45(6)2024 Jun 07.
Article
in En
| MEDLINE
| ID: mdl-38772401
ABSTRACT
Objective. This paper aims to investigate the possibility of detecting tonic-clonic seizures (TCSs) with behind-the-ear, two-channel wearable electroencephalography (EEG), and to evaluate its added value to non-EEG modalities in TCS detection.Methods. We included 27 participants with a total of 44 TCSs from the European multicenter study SeizeIT2. The wearable Sensor Dot (Byteflies) was used to measure behind-the-ear EEG, electromyography (EMG), electrocardiography, accelerometry (ACC) and gyroscope. We evaluated automatic unimodal detection of TCSs, using sensitivity, precision, false positive rate (FPR) and F1-score. Subsequently, we fused the different modalities and again assessed performance. Algorithm-labeled segments were then provided to two experts, who annotated true positive TCSs, and discarded false positives.Results. Wearable EEG outperformed the other single modalities with a sensitivity of 100% and a FPR of 10.3/24 h. The combination of wearable EEG and EMG proved most clinically useful, delivering a sensitivity of 97.7%, an FPR of 0.4/24 h, a precision of 43%, and an F1-score of 59.7%. The highest overall performance was achieved through the fusion of wearable EEG, EMG, and ACC, yielding a sensitivity of 90.9%, an FPR of 0.1/24 h, a precision of 75.5%, and an F1-score of 82.5%.Conclusions. In TCS detection with a wearable device, combining EEG with EMG, ACC or both resulted in a remarkable reduction of FPR, while retaining a high sensitivity.Significance. Adding wearable EEG could further improve TCS detection, relative to extracerebral-based systems.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Seizures
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Signal Processing, Computer-Assisted
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Electroencephalography
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Electromyography
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Accelerometry
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Wearable Electronic Devices
Limits:
Adult
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Female
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Humans
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Male
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Middle aged
Language:
En
Journal:
Physiol Meas
/
Physiol. meas
/
Physiological measurement
Journal subject:
BIOFISICA
/
ENGENHARIA BIOMEDICA
/
FISIOLOGIA
Year:
2024
Document type:
Article
Affiliation country:
Bélgica
Country of publication:
Reino Unido