Early assistive diagnosis system of ADHD

An early assistive diagnosis system of attention deficit hyperactivity disorder (ADHD), comprising:

• an attention testing device providing a test to a subject;
• a brain-computer interface (BCI) including a plurality of electrodes and channels respectively corresponding to the electrodes, wherein the plurality of electrodes are configured to be arranged on a scalp of the subject to detect a plurality of electroencephalography (EEG) signals of the subject, wherein the plurality of EEG signals includes resting-state EEG signals detected during rest and task-state EEG signals during test;
• and
• a host connected to the attention testing device and the BCI to receive and analyze the plurality of EEG signals detected by the BCI, wherein the host includes:
• a controller connected to the attention testing device receives and generates a plurality of test scores of the test;
• a feature acquisition processor connected to the controller and the BCI acquires a plurality of ADHD-related features of the plurality of EEG signals of frequency band power of each of the channels on the plurality of electrodes and band ratio thereof, so as to obtain EEG feature data;
• a first filter, which connected with the BCI and the feature acquisition processor, wherein the first filter is configured to receive the plurality of EEG signals, removes artifacts in the plurality of EEG signals, and preserves primary frequency range of EEG;
• a second filter, which connected to the BCI and the first filter, wherein the second filter is configured to remove artifacts originating from eye or muscle movements within the plurality of EEG signals using an artificial-intelligence algorithm;
• a time-frequency converter, which connected to the BCI and the second filter, wherein the time-frequency converter is configured to transform time-domain signals of the resting-state EEG signals and the task-state EEG signals into frequency-domain signals, subsequently computing the frequency band power of each frequency band of each channel;
• and
• a feature analysis processor connected to the feature acquisition processor receives the EEG feature data, classifies the subject as typical development group or ADHD group according to the EEG feature data, and when the subject is classified as ADHD, the feature analysis processor combines the EEG feature data and the test scores corresponding to the subject to produce predicted index score ranges of a plurality of ADHD heterogeneity types.