US 2025/0082252 A1Published application

Inph prediction method and device based on the new/old stimulus bci paradigm

AssigneeTianjin University

InventorsXiuyun LIU, Dong MING, Congying HAO, Zihua ZHANG, Huijie YU, Yulin SUN, Xiaoyi WANG, Kai YU, Fang GUO, Kuo ZHANG, Meijun PANG

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Abstract

The current innovation pertains to the medical data processing domain and introduces a method for formulating an iNPH prediction model using a new/old stimulus BCI paradigm. The process involves conducting new/old stimulus BCI paradigm experiments on a target population both before and after the Lumbar Tap Test, obtaining electroencephalogram (EEG) signal data. After preprocessing the EEG signal data, the model extracts features related to new and old stimulus event-related potentials before and after the test, specifically focusing on P600 amplitude features. The iNPH prediction model is then trained based on these event-related potential features. This innovation facilitates quantifying cognitive function improvement, aiding physicians in prompt iNPH diagnosis and enabling timely and effective patient treatment.

Claims10

Dependent claims

A method for constructing an iNPH prediction model based on the new/old stimulus BCI paradigm, the method comprises:

performing new/old stimulus BCI paradigm experiments on the target population before Lumbar Tap Test to obtain pre-LTT new stimulus EEG signal data and pre-LTT old stimulus EEG signal data for the target population;
performing the same new/old stimulus BCI paradigm experiments on the target population after Lumbar Tap Test to obtain post-LTT new stimulus EEG signal data and post-LTT old stimulus EEG signal data for the target population;
performing pre-processing on the pre-LTT new stimulus EEG signal data, pre-LTT old stimulus EEG signal data, post-LTT new stimulus EEG signal data and post-LTT old stimulus EEG signal data to obtain the pre-LTT new stimulus event-related potential features, the pre-LTT old stimulus event-related potential features, the post-LTT new stimulus event-related potential features and the post-LTT old stimulus event-related potential features, wherein the event-related potential features are the P600 amplitude features;
training iNPH prediction model to obtain the iNPH prediction model based on the pre-LTT new stimulus event-related potential features, the pre-LTT old stimulus event-related potential features, the post-LTT new stimulus event-related potential features, and the post-LTT old stimulus event-related potential features;
and
one of the target populations is iNPH patients.

3 more elements

A device for constructing an iNPH prediction model based on a new/old stimulus BCI paradigm, wherein the device comprises:

a data receiving module, said data receiving module being configured to:
receive pre-LTT new stimulation EEG signal data, pre-LTT old stimulation EEG signal data, post-LTT new stimulation EEG signal data, and post-LTT old stimulation EEG signal data of the target population, wherein said pre-LTT new stimulation EEG signal data and pre-LTT old stimulation EEG signal data, and post-LTT new stimulation EEG signal data and post-LTT old stimulated EEG signal data, and post-LTT new stimulated EEG signal data and post-LTT old stimulated EEG signal data are obtained through the BCI paradigm experiments in which the target population received new/old stimulated BCI paradigm experiments before and after lumbar Tap Test, respectively;
a data processing module, said data processing module being configured to pre-process the pre-LTT new stimulus EEG signal data, the pre-LTT old stimulus EEG signal data, the post-LTT new stimulus EEG signal data and the post-LTT old stimulus EEG signal data received by said data receiving module, to obtain the pre-LTT new stimulus event-related potential feature, the pre-LTT old stimulus event-related potential feature, the post-LTT new stimulus event-related potential features, old stimulus event-related potential features, new stimulus event-related potential features, new stimulus event-related potential features and old stimulus event-related potential features after lumbar Tap Test, of which, the event-related potential features are P600 amplitude features;
a model training module, said model training module being configured to train to obtain an iNPH prediction model based on the pre-LTT new stimulus event related potential features, the pre-LTT old stimulus event related potential features, the post-LTT new stimulus event related potential features and the post-LTT old stimulus event related potential features obtained by said data processing module.

1 more element

Dependencies are inferred from the claim text.