System for diagnosing mental disorders using neurometrics
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Publication Number
US-10682096-B2
Publication Date
2020-06-16
Expiration Date
Abstract
Described are novel systems for the diagnosis of specific mental disorders using neurometrics. EEG parameters are compared to thresholds to determine if a person is suffering from autism spectrum disorder, Alzheimer's disease, anxiety, depression, or schizophrenia.
Core Innovation
A system for diagnosing Alzheimer's Disease is disclosed that includes an EEG recording device with a plurality of EEG channels and a processing device. The processing device generates an FFT graph for all EEG channels and calculates an average dominant frequency between 5 Hz and 15 Hz of EEG signals from all EEG channels.
The processing device also calculates an average coherence at the dominant frequency between EEG signals from at least one frontal EEG channel and at least one occipital-parietal EEG channel. The processing device generates a diagnosis indication of Alzheimer's Disease if the average dominant frequency is less than 8 Hz and the average coherence is less than 10%.
The disclosed approach emphasizes using frequency information obtained from FFT analysis together with coherence information between frontal and occipital-parietal EEG sites to drive the diagnostic indication. The background indicates that EEG-based neurometrics address multiple mental disorders, with illustrative separability shown between diagnostic versus normal subjects.
Claims Coverage
Independent claim clm-00001 provides an EEG-based diagnostic system for Alzheimer's Disease using two main computed inventive features: average dominant frequency from an FFT graph and average coherence at that dominant frequency between frontal and occipital-parietal EEG channels; both metrics are used with specific decision thresholds to generate a diagnosis indication. No other independent claims are provided in the supplied material.
Diagnosing Alzheimer's Disease using average dominant frequency and coherence thresholds
An EEG recording device records EEG of a person using a plurality of EEG channels, and a processing device generates an FFT graph for all EEG channels; calculates an average dominant frequency between 5 Hz and 15 Hz of EEG signals from all EEG channels; calculates an average coherence at the dominant frequency between EEG signals from at least one frontal EEG channel and at least one occipital-parietal EEG channel; and generates a diagnosis indication of Alzheimer's Disease if the average dominant frequency is less than 8 Hz and the average coherence is less than 10%.
The provided independent claim defines a diagnosis indication for Alzheimer's Disease based on computed FFT-derived average dominant frequency (5–15 Hz, compared to <8 Hz) combined with coherence at that dominant frequency between frontal and occipital-parietal channels (compared to <10%).
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