The Recognition and Screening for Alzheimer's Disease Based on Olfactory Neural Signal from Brain Computer Interface
A novel method for Alzheimer's disease(AD)recognition utilizing olfactory neural signals based on brain-computer interface in proposed.Flexible neural electrodes are developed and implanted into the olfactory system of mice to record in vivo neural activities.Time and frequency domain analysis of the spontaneous signals from the AD model mice and control group reveals that there are abnor-mal neural oscillations in the AD mice.Moreover,classification models are proposed to recognize AD.Several machine learning classifi-ers are constructed and trained using features extracted from the olfactory neural signals.The ANN model has the highest accuracy rate of 89.98%.The results provide a new technique method with great potential for AD screening and diagnosis.
biomedical engineeringDiagnosis of Alzheimer's diseaseolfactory neural signalmachine learning
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