Alzheimer's disease detecting system and method based on electroencephalogram signals

Abstract

The invention provides an Alzheimer's disease detecting system based on electroencephalogram signals. An electrode cap comprises 16 conducting electrodes used for collecting 16 conducting signals of the human body scalp, the electrode cap and a UEA-FZ electroencephalogram amplifier are connected through a PCI parallel interface, and the collected signals are imported into the UEA-FZ electroencephalogram amplifier; the UEA-FZ electroencephalogram amplifier amplifies and records the 16 conducting electroencephalogram signals, and the recorded signals are imported into a data analysis system; the data analysis system comprises an EEGLab module, a signal processing module and a detecting module, the three modules are connected to detect abnormal electroencephalogram signals. The invention provides an Alzheimer's disease detecting method based on the electroencephalogram signals. The Alzheimer's disease detecting system has the advantages of effectively distinguishing the electroencephalogram difference between a control group and a patient group, and being capable of effectively differentiating the control group and the patient group by calculating worldlet degree and analyzing significance, and the Alzheimer's disease is effectively detected.

Description

technical field [0001] The invention relates to the field of biomedical engineering, in particular to a detection system and method for Alzheimer's disease based on electroencephalogram signals. Background technique [0002] Alzheimer's disease, commonly known as senile dementia, is a neurodegenerative disease and the most common dementia. It primarily affects people over the age of 65, and its prevalence is projected to double over the next 50 years. However, at this stage, there is no cure for Alzheimer's disease, and a large number of drugs can only delay the deterioration of the disease. Alzheimer's disease is divided into four distinct stages: the first stage is the mild cognitive impairment stage, which is usually manifested by memory loss but does not significantly affect daily life; followed by mild and moderate Alzheimer's disease The stage of Alzheimer's disease; the last is severe Alzheimer's disease, in which the memory, perception, thinking and even basic phys...

AI Technical Summary

Problems solved by technology

[0008] The first two methods are based on the linear synchronization between the leads to construct the brain function network, which cannot effectively reflect the nonlinear characteristics of the chaotic signal of EEG.

Although the third method uses a complex network method to extract EEG nonlinear features, it is only based on single-lead features and cannot reflect the abnormality of brain functional networks.

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