Design And Implementation Of Navigation EEG Signal Analysis Algorithm Based On Deep Learning

Navigation is one of the most basic cognitive abilities of human beings,as location awareness and route planning are crucial skills in our daily life.The navigation process requires the brain to integrate information from different sensory inputs,and involves the interaction of perception,memory,decision-making and other activities.EEG signals can reflect the activity state of the brain.Hence,it helps further our understanding of this complex cognitive process to analyze the feature of EEG signals induced by different navigation states.This study used the EEG data from 20 subjects during the navigation tasks.According to the characteristics of EEG signal,the raw data was first preprocessed to improve the signal quality.Segmentation processing method was then used to generate more samples.And all of the EEG data was annotated according to the navigation cognitive load corresponding to the task to establish a navigation EEG dataset.In order to solve the problem of information loss in traditional feature extraction process,all navigation EEG signals are converted into two-dimensional power spectrum image.Such an EEG power spectrum image can retain the global information of the signal to the greatest extent.Furthermore,a navigation state recognition model based on deep learning is implemented.Firstly,the video of EEG power map is generated by several continuous window signals,and the change information of EEG signal with time is represented by picture frame sequence.Then,the parallel Convolutional Neural Network(CNN)combined with Long Short-Term Memory Network(LSTM)is applied to the recognition of navigation state.The experimental results show that the recognition accuracy of the model is significantly higher than that of the traditional classification algorithm.On this basis,we analyzes the classification effect of different brain regions,and determines the key brain regions in navigation cognitive state recognition.Finally,a navigation EEG analysis system is designed and implemented.The system consists of EEG data file processing,signal feature extraction and uploading,navigation cognitive state recognition,model publishing and training.In this paper,the requirements analysis,design and implementation of the system are described in detail,and the function and performance of the system are verified by testing.