[The data processing of neurophysiological examination and the diagnostic support system]

Area of Science:

• Neuroscience
• Medical Technology
• Signal Processing

Background:

• Neurophysiological examinations like EEG and EP are crucial for diagnosing neurological conditions.
• Effective data processing and diagnostic support systems are needed to interpret complex neurophysiological data.

Purpose of the Study:

• To discuss EEG and EP data processing techniques.
• To explore the application of these techniques in diagnostic support systems.
• To highlight advancements in neurophysiological data analysis for clinical use.

Main Methods:

• EEG data processing involved Fast Fourier Transform (FFT) and Autoregressive (AR) modeling for frequency analysis, and pattern recognition for spike/spindle detection.
• Second-order processing included amplitude/phase mapping for neurological disorder diagnosis and dipole source localization.
• Evoked Potentials (EP) like SEP and ABR were detected using averaging techniques.

Main Results:

• Amplitude/phase mapping aided in diagnosing neurological disorders and localizing electrical sources in the cerebral cortex.
• Topographic analysis of Somatosensory Evoked Potentials (SEP) assisted in identifying the central sulcus during neurosurgery.
• An EEG automatic reporting system with Japanese sentences and brain mapping was developed, alongside a digital EEG filing system.

Conclusions:

• Advanced EEG and EP data processing significantly improves diagnostic accuracy for neurological disorders.
• These techniques support neurosurgical procedures and enhance patient quality of life.
• The development of automated reporting and digital filing systems streamlines EEG data analysis and diagnostic support.