Patient-independent automated pediatric seizure monitoring based on expert-labeled electrographic ictal data as core reference knowledge

Figures

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  Fig. 1.. Overall study process. Two epileptologists annotated distinct electrographic focal-onset ictal EEG segments in ictal intervals for each channel, yielding an ictal EEG segment dataset comprising 1,604 singlechannel- level EEG time series. Seizure detection models were constructed by the ictal EEG dataset to evaluate patient-independent seizure detection performance using the following steps. In the internal validation, the assessment was conducted of 2 internal datasets (CHB-MIT and SNUBH) used for the ictal EEG segment annotation by the leave-one-patient-out scenario. In the external validation, the assessment was conducted for an external dataset (SNUCH) not used for the ictal EEG segment annotation by our final seizure detection model. CHB-MIT, Children’s Hospital Boston-Massachusetts Institute of Technology; EEG, encephalography; SNUBH, Seoul National University Bundang Hospital; SNUCH, Seoul National University Children’s Hospital.

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  Fig. 2.. A representative true-positive result in the event-level evaluation corresponding to the first seizure for SNUCH_E05. The blue- and red-colored vertical dashed lines represent epileptologist-annotated (58 seconds) and model-generated (47 seconds) ictal intervals, respectively. The upper panel represents the EEG time series with distinct seizure characteristics, particularly in the left hemisphere (red-colored channel names and signals). The lower panel represents post-processed outcomes: the blue- and red-colored solid lines represent epileptologist-annotated and channel-wise model-generated ictal intervals, respectively. The gray-colored solid lines represent ictal probabilities for individual channels. EEG, electroencephalography; SNUCH, Seoul National University Children’s Hospital.

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  Fig. 3.. Visualization of feature vectors from the last convolutional layer based on UMAP for the 4 channels (C3–P3, C4– P4, T3–T5, and, T4–T6) of the SNUCH_E05. The red-colored cross marks and blue-colored circles represent the ictal and interictal windows, respectively. The red- and blue-colored regions represent ictal and interictal distributions, respectively, based on Gaussian kernel density estimation. The darker the color, the higher the density. The numbers in parentheses represent Kullback-Leibler divergence values between the ictal and interictal distributions. SNUCH, Seoul National University Children’s Hospital; UMAP, uniform manifold approximation and projection.

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