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CN-122004786-A - Multi-modal data-based cognitive disorder typing diagnosis method based on brain electricity and heart rate

CN122004786ACN 122004786 ACN122004786 ACN 122004786ACN-122004786-A

Abstract

The invention discloses a cognitive disorder typing diagnosis method based on multimodal data of brain electricity and heart rate, and belongs to the technical field of cognitive disorder evaluation. The method comprises the steps of wearing an EEG cap to the brain of a patient, attaching ECG electrodes to the surface of the abdominal skin of the patient, enabling a stimulus presentation computer to synchronously trigger or release the on-off of the EEG cap and the ECG electrodes, enabling the EEG cap to collect EEG data of the patient and output the EEG data to an EEG collection computer, enabling the ECG electrodes to collect ECG data of the patient and output the ECG data to the EEG collection computer, synchronously superposing environmental stimulus data according to the obtained EEG data and the obtained ECG data, generating a multi-mode data set, processing the multi-mode data set, and outputting the ratio of the related potential data set exceeding a set threshold to the related potential data of the environmental stimulus. The invention can be used as auxiliary data support for diagnosing the cognitive impairment degree of a patient by a doctor, and further provides auxiliary data support for the doctor to specific typing in the cognitive impairment field.

Inventors

  • HU WEI
  • LI SHEN

Assignees

  • 江苏博而雅科技有限公司

Dates

Publication Date
20260512
Application Date
20260402

Claims (10)

  1. 1. The cognitive disorder typing diagnosis method based on the multimodal data of brain electricity and heart rate is characterized by comprising the following steps of: Step SS1, an EEG brain electrical cap is worn on the brain of a patient, an ECG electrode is attached to the surface of the abdominal skin of the patient, the EEG brain electrical cap and the output end of the ECG electrode are connected with an electroencephalogram acquisition computer through a signal adapter plate and a signal amplifier, and a stimulus presentation computer is connected with the signal amplifier through a synchronous box; Step SS2, the stimulation presentation computer synchronously triggers or releases the on-off of the EEG cap and the ECG electrode, the EEG cap acquires EEG data of a patient and outputs the EEG data to the EEG acquisition computer, and the ECG electrode acquires ECG data of the patient and outputs the ECG data to the EEG acquisition computer; And step SS3, synchronously superposing environmental stimulation data according to the acquired EEG brain electrical data and ECG electrocardio data, generating a multi-mode data set, processing the multi-mode data set, and outputting the percentage of the total number of the potential data sets exceeding a set threshold value to the total number of the environmental stimulation related potential data.
  2. 2. The method for diagnosing cognitive impairment of a multi-modal data based on brain waves and heart rates as defined in claim 1, wherein the environmental stimulus data comprises related event data, unrelated event data, and quasi-rope event data, and the brain wave acquisition computer outputs event related potentials ERP that are related to potential changes caused when a certain stimulus event is presented or withdrawn to the patient.
  3. 3. The method for diagnosing cognitive impairment of multi-modal data based on brain waves and heart rates as set forth in claim 1, wherein the EEG brain wave cap captures secondary currents induced by primary currents generated by neurons of the patient and outputs a waveform of the voltage generated on the scalp surface over time through the brain wave capture computer.
  4. 4. The method for diagnosing cognitive impairment of a multi-modal data based on electroencephalogram and heart rate as set forth in claim 1, wherein the ECG electrodes output a waveform of the time node and intensity of the sequence of heartbeat signals from an electroencephalogram acquisition computer by outputting a transmission of the electric potential of the heart of the patient.
  5. 5. The method for diagnosing cognitive impairment as set forth in claim 1, wherein the step SS3 comprises: Based on the related event data, irrelevant event data and quasi-rope event data in the environmental stimulus data, synchronously superposing the related event data to output EEG1 and ECG1 of a certain patient, synchronously superposing the irrelevant event data to output EEG2 and ECG2 of the patient, synchronously superposing the quasi-rope event data to output EEG3 and ECG3 of the patient, and then respectively comparing the EEG and ECG with the original EEG and ECG obtained at the same time without applying the environmental stimulus data to output the related event potential data with the change of the potential along with the time ERP1, unrelated event potential data ERP2, quasi-rope event potential data ERP3。
  6. 6. The method for diagnosing cognitive impairment as set forth in claim 5, wherein the step SS3 further comprises: electroencephalogram data EEG1 for related event data is noted as set VG1 (1,..once., x), where x is the number of related event questions, VG1 (x) is the electroencephalogram voltage signal of the xth related event question, and electrocardiograph data ECG1 for related event data is noted as set HG1 (1,..once., x), where x is the number of related event questions, HG1 (x) is the electrocardiograph voltage signal of the xth related event question; the EEG2 for the unrelated event data is denoted as set VG2 (1, y), where y is the number of unrelated event questions, VG2 (y) is the EEG signal of the y-th unrelated event question, the ECG2 for the unrelated event data is denoted as set HG2 (1, y), where y is the number of unrelated event questions, HG2 (y) is the ECG signal of the y-th unrelated event question, the EEG3 for the quasi-rope event data is denoted as set VG3 (1, z), where z is the number of quasi-rope event questions, VG3 (z) is the EEG signal of the z-th quasi-rope event question, the ECG3 for the quasi-rope event data is denoted as set HG3 (1, z), where z is the number of quasi-rope event questions, HG3 (z) is the ECG signal of the z-th quasi-rope event, the original EEG data of the same time when no environmental stimulus data is applied The electrocardio data ECG is marked as EEG0 and ECG0 respectively, and the related event potential data delta ERP1, the unrelated event potential data delta ERP2 and the quasi-rope event potential data delta ERP3 are respectively: ; ; ; Will correlate event potential data ERP1, unrelated event potential data ERP2, quasi-rope event potential data The parts exceeding the set thresholds PMax1, PMax2 and PMax3 in ERP3 form a new set ERP1X { 1..times., i }, ΔERP2Y { 1..times., j }, ΔERP3Z { 1..times., k }, where i≤x, j≤y, k≤z, PMax1 is the allowable potential change threshold for related event stimulus, PMax2 is the allowable potential change threshold for the extraneous event stimulus, and PMax3 is the allowable potential change threshold for the quasi-rope event stimulus.
  7. 7. The method for diagnosing cognitive impairment of multi-modal data based on an electroencephalogram and a heart rate as set forth in claim 6, wherein the step SS3 further comprises obtaining a percentage of the number of sets of associated potential data exceeding a set threshold value, respectively, to the total number of sets of environmental stimulus-related potential data, respectively, comprising: ; ; ; ; Wherein, C1 is the percentage of the number of the related event potential data sets exceeding the set threshold value to the related potential data sets of all the related event stimuli, C2 is the percentage of the number of the unrelated event potential data sets exceeding the set threshold value to the related potential data sets of all the unrelated event stimuli, C3 is the percentage of the number of the quasi-rope event potential data sets exceeding the set threshold value to the related potential data sets of all the quasi-rope event stimuli, C is the percentage of the number of the related potential data sets exceeding the set threshold value to the related potential data sets of all the environmental data stimuli, and the greater the percentage is, the more obvious the cognition of the patient to the environmental data stimuli is reflected, and the degree of cognitive impairment of the patient is relatively light.
  8. 8. The method for diagnosing cognitive impairment of a multi-modal data based on brain electricity and heart rate according to claim 1, wherein the number of channels of the signal adapter plate is 8-128.
  9. 9. The method for diagnosing cognitive impairment as recited in claim 1, wherein the signal amplifier is a 128-channel amplifier.
  10. 10. The method for diagnosing cognitive impairment of a multi-modal data-based brain and heart rate as set forth in claim 1, further comprising an eye tracker connected to the stimulus presentation computer via a synchronization box, wherein the eye tracker collects eye movement trace data of the patient and outputs the data to the brain electrical collection computer.

Description

Multi-modal data-based cognitive disorder typing diagnosis method based on brain electricity and heart rate Technical Field The invention relates to a cognitive disorder typing diagnosis method based on multimodal data of brain electricity and heart rate, and belongs to the technical field of cognitive disorder evaluation. Background As the global population ages, cognitive impairment has become a significant public health challenge affecting the health and quality of life of the elderly. Cognitive impairment not only brings heavy care burden and economic pressure to patients and families thereof, but also forms a serious test for social medical resources. Early recognition and effective intervention against cognitive disorders are key to slowing disease progression, improving patient prognosis. The incidence of cognitive disorders continues to rise as global aging increases. At present, no radical treatment means exists, and early intervention for delaying the progress of the disease process becomes a core clinical strategy. Non-pharmacological interventions (e.g. cognitive training, motor therapy, neuromodulation) and pharmacological intervention protocols are endless, but how to scientifically quantify the intervention effect is still an industry pain point. With the development of computer technology and neuroscience, brain-computer interface technology is being widely used in the assisted rehabilitation therapy for improving the attention of cognitive disorders such as autism spectrum disorder. The brain-computer interface is a technology for realizing man-machine interaction by converting a brain nerve signal into an operable command signal, and can realize objective monitoring and quantification of the attention of a patient in the aspects of monitoring and evaluating the attention of the patient, so that the change of the attention of the patient can be evaluated more accurately. For example, brain-computer interfaces may be used to record the brain-electrical signals of a patient and to determine the patient's state of attention by analyzing these signals. In the field of cognitive disorder typing, particularly in terms of specific typing of impaired cognitive function, the prior art cannot continuously and comprehensively collect multi-mode data of a user based on natural life scenes, lacks continuous perceptibility of real states from the angle of data analysis, does not realize patient and environment adaptation in evaluation and task selection, causes insufficient accuracy of cognitive disorder typing, lacks quantitative effect verification and closed loop optimization after general typing, and cannot assist doctors to realize synchronization and effectiveness real-time judgment of cognitive disorder typing diagnosis. Disclosure of Invention The invention aims to overcome the technical defects in the prior art, solve the technical problems, and provide a multi-modal data-based cognitive disorder typing diagnosis method based on brain electricity and heart rate, which realizes auxiliary typing diagnosis of cognitive disorder from the perspective of cognitive data analysis. The invention adopts the following technical scheme that the cognitive disorder typing diagnosis method based on the multimodal data of brain electricity and heart rate comprises the following steps: Step SS1, an EEG brain electrical cap is worn on the brain of a patient, an ECG electrode is attached to the surface of the abdominal skin of the patient, the EEG brain electrical cap and the output end of the ECG electrode are connected with an electroencephalogram acquisition computer through a signal adapter plate and a signal amplifier, and a stimulus presentation computer is connected with the signal amplifier through a synchronous box; Step SS2, the stimulation presentation computer synchronously triggers or releases the on-off of the EEG cap and the ECG electrode, the EEG cap acquires EEG data of a patient and outputs the EEG data to the EEG acquisition computer, and the ECG electrode acquires ECG data of the patient and outputs the ECG data to the EEG acquisition computer; And step SS3, synchronously superposing environmental stimulation data according to the acquired EEG brain electrical data and ECG electrocardio data, generating a multi-mode data set, processing the multi-mode data set, and outputting the percentage of the total number of the potential data sets exceeding a set threshold value to the total number of the environmental stimulation related potential data. As a preferred embodiment, the environmental stimulus data includes related event data, unrelated event data, quasi-rope event data, and the electroencephalogram acquisition computer outputs event related potential ERP of related potential change caused when presenting or withdrawing a certain stimulus event to the patient. As a preferred embodiment, the EEG brain electrical cap collects the secondary current induced by the primary current generated by th