Diver’s disease is a complication that the human body suffers from after being in a high-pressure space and then quickly entering a low-pressure space. These pressures are very harmful for the tissues of the body, especially for the brain. Decompression sickness occurs when nitrogen bubbles up in the bloodstream, caused by staying underwater too long or surfacing too quickly. Decompression sickness symptoms usually appear with a delay after diving. By processing electroencephalography, information about neurophysiological disorders can be extracted precisely. Since the diagnosis of divers’ diseases has not been dealt with using a unique model, this paper deals with the diagnosis of brain abnormalities caused by diving. In this paper, an intelligent model using the electroencephalography of divers will be presented to diagnose the brain disorders. The proposed model based on the brain function can show the connections of the divers’ brain regions using cellular neural networks. First, the effective features are extracted from the signals, and then based on the proposed architecture based on the brain, the differences in the brain connections of divers compared to non-divers are expressed. The obtained results show that there are differences in intra-regional connections of some brain regions of divers including T7, T8, O1 and O2 ([Formula: see text] < 0.05) compared to nondivers.
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