Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Electroencephalogram (EEG) recordings of brain waves have been shown to have unique pattern for each individual and thus have potential for biometric applications. ,  propose an EEG feature extraction and hashing approach for person authentication. Multi-variate autoregressive (mAR) coefficients are extracted as features from multiple EEG channels and then hashed by using our recently proposed Fast Johnson-Lindenstrauss Transform (FJLT)-based hashing algorithm to obtain compact hash vectors. Based on the EEG hash vectors, a Naive Bayes probabilistic model is employed for person authentication. Our EEG hashing approach presents a fundamental departure from existing methods in EEG-biometry study. The promising results suggest that hashing may open new research directions and applications in the emerging EEG-based biometry area.
['Chen He', 'Xudong Lv', 'Z. Jane Wang']
I am writing a research paper on a idea Hashing the mAR coefficients from EEG data for person authentication
[{"from": "human", "value": "I am writing a research paper on a idea Hashing the mAR coefficients from EEG data for person authentication"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Electroencephalogram (EEG) recordings of brain waves have been shown to have unique pattern for each individual and thus have potential for biometric applications. ,  propose an EEG feature extraction and hashing approach for person authentication. Multi-variate autoregressive (mAR) coefficients are extracted as features from multiple EEG channels and then hashed by using our recently proposed Fast Johnson-Lindenstrauss Transform (FJLT)-based hashing algorithm to obtain compact hash vectors. Based on the EEG hash vectors, a Naive Bayes probabilistic model is employed for person authentication. Our EEG hashing approach presents a fundamental departure from existing methods in EEG-biometry study. The promising results suggest that hashing may open new research directions and applications in the emerging EEG-based biometry area."}]