Starfast is a wearable, wireless biometry system based on the new ENOBIO 4- channel electrophysiology recording device developed at Star lab. Features extracted from electroencephalogram (EEG) and electrocardiogram (ECG) recordings have proven to be unique enough between subjects for biometric applications. We show here that biometry based on these recordings offers a novel way to robustly authenticate or identify subjects. In this paper, we present a rapid and unobtrusive authentication method that only uses 2 frontal electrodes and a wrist worn electrode referenced to another one placed at the ear lobe. Moreover, the system makes use of a multistage fusion architecture, which demonstrates to improved system performance. The performance analysis of the system presented in this paper stems from an experiment with 416 test trials, where an Equal Error Rate (EER) of 0% is obtained after the EEG and ECG modalities fusion and using a complex boundary decision. If a lineal boundary decision is used we obtain a True Acceptance Rate (TAR) of 97.9% and a False Acceptance Rate (FAR) of 0.82%. The obtained performance measures improve the results of similar systems presented in earlier work.
Instrumentation
1 comments: on "STARFAST: a Wireless Wearable EEG Biometric System based on the ENOBIO Sensor"
I am ashok from maharashtra.thank you very much, for all this information.
Post a Comment