Abstract
This research proposes a subject identification method using PPG (Photoplethysmogram) signals towards continuous authentication. The proposed method uses feature values derived from heartbeat and respiration extracted from PPG signals by means of frequency filtering and MFCC (Mel-Frequency Cepstrum Coefficients) to identify subjects. An experiment was conducted using an open dataset containing PPG signals to investigate the identification performance of the method. The feature values were extracted from the PPG signals and classifiers were generated to evaluate the performance of the method. As a result, the proposed method was found to be capable of identifying 46 people with the accuracy of 92.9 % by using feature values derived from heartbeat and respiration.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
