CaNViS: A cardiac and neurological-based verification system that uses wearable sensors

The prevalence of more portable physiological sensors in medical, lifestyle and security fields have ushered in more viable biometric attributes that can be used for the task of identification and authentication. The portability of these sensors also allows systems that require more than one signal source to be feasible and more practical. Once these biological signals are captured, they can then be combined for the purposes of authentication. The study proposes such a multi-factor biometric system, by fusing cardiac and neurological components captured with an electrocardiograph (ECG) and electroencephalograph (EEG) respectively and using them as a biometric attribute. Representing each of these components in a common format and fusing them at a feature level allows one to create a novel biometric system that is interoperable with different biological signal sources. The results indicate the system portrays a sufficient false rejection (FRR) and false acceptance rates (FAR). The results also show there is value in implementing multi-factor biological signal-based biometric systems using wearable sensors.