Patel, VrajeshriBurns, MartinFlorescu, IonutChandramouli, RajarathnamVinjamuri, Ramana2021-05-192021-05-192017-11-29Patel, Vrajeshri; Burns, Martin; Florescu, Ionut; Chandramouli, Rajarathnam; Vinjamuri, Ramana; A Novel Biometric based on Neural Representations of Synergistic Hand Grasps; Future Technologies Conference (FTC) 2017. https://saiconference.com/Downloads/FTC2017/Proceedings/113_Paper_271-A_Novel_Biometric_based_on_Neural_Representations.pdfhttp://hdl.handle.net/11603/21570Future Technologies Conference (FTC) 2017 29-30 November 2017| Vancouver, Canada—To meet the growing need of robust and secure identity verification systems, a new biometric based on neural representations of synergistic hand grasps is proposed here. In this preliminary study five subjects were asked to perform six synergistic hand grasps that are shared most often in common activities of daily living. Their scalp electroencephalographic (EEG) signals were analyzed using 20 scalp electrodes. In our previous work, we found that hand kinematics of these synergistic grasps showed potential as a biometric. In the current work, we asked if the neural representations of these synergistic grasps can provide a unique signature to be a biometric. The results show that across 300 entries, the system, in its best configuration, achieved an accuracy of 92.2% and an EER of ~4.7% when tasked with identifying these five individuals. The implications of these preliminary results and applications in the near future are discussed. We believe that this study could lead to the development of a novel biometric as a potential future technology.6 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.biometricshand synergiesquadratic discriminant classifierelectroencephalography (EEG)feature extractionText