ProjectsProject Details

Prediction of Anesthesia Depth based on EEG Signals

Project ID: 7170-2-23
Year: 2024
Student/s: Tamar Shapira and Adi Bruchian
Supervisor/s: Hadas Ofir

Spinal surgeries are complex surgeries with a high potential for future complications due to nerve injuries. These complications include paralysis, chronic pain and sensory loss. For that reason, during the operation EEG and EMG signals are used to monitor the effect of the anesthetic drugs on the depth of anesthesia. This monitoring helps to diagnose functional decline due to systemic or neurological changes, which can indicate damage to the nerve system. Monitoring the depth of anesthesia from these signals is not immediate and is currently performed in many surgeries by systems that calculates the Bispectral (BIS) index based on these signals and giving a score between 0 and 100 for the depth of the anesthesia.

In this project, we collaborated with Nervio Company to evaluate the BIS index. For this purpose, we examined two methods: the first, an analytical method based on the machine code of the BIS device, and the second is based on the implementation of a neural network.

Poster for Prediction of Anesthesia Depth based on EEG Signals
Collaborators:
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NERVIO