This study proposed and validated using the Intra-body communications channel as a biometric identity.
Combining experimental measurements collected from five subjects and two multi-layer tissue mimicking materials’ phantoms, different machine learning algorithms were used and compared to test and validate using the channel characteristics and features as a biometric identity for subject identification. An accuracy of 98.5 percent was achieved, together with a precision and recall of 0.984 and 0.984, respectively, when testing the models against subject identification over results collected from the total samples. Using a simple and portable setup, this work shows the feasibility, reliability, and accuracy of the proposed biometric identity, which enables continuous identification and verification. (publisher abstract modified)
Downloads
Similar Publications
- Understanding the Potential for Multidisciplinary Threat Assessment and Management Teams to Prevent Terrorism: Conducting a Formative Evaluation of the MassBay Threat Assessment Team, Executive Summary
- The Impact of Mobile Technology Devices on Street Checks and Crime Incidents Reported: Results of a Randomised Controlled Trial
- Learning about ShotSpotter — and Gun Violence — from Chicago