Autonomic Signature-Driven Anesthesia Depth Monitoring with Biomimetic Wearable ECG and Knowledge Graph-Augmented Deep Networks

Considerable efforts have been devoted to accurately monitoring the depth of anesthesia to ensure patient safety during surgery. Traditional approaches typically rely on electroencephalogram (EEG)-based indices, such as the Bispectral Index (BIS), which require specialized equipment. In contrast, el...

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Bibliografische Detailangaben

Hauptverfasser:	Aoran Bao, Cheng Ding
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2026-06-01
Schriftenreihe:	Sensors
Schlagworte:	graph neural network (GNN) depth of anesthesia electrocardiogram (ECG) graph convolution layers
Online-Zugang:	https://www.mdpi.com/1424-8220/26/11/3498
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