Beat-ID: Towards a computationally low-cost single heartbeat biometric identity check system based on electrocardiogram wave morphology

• Published in: PloS one Vol. 12; no. 7; p. e0180942
• Main Authors: Paiva, Joana S., Dias, Duarte, Cunha, João P. S.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 18.07.2017; Public Library of Science (PLoS)
• Subjects: Accuracy; Adult; Algorithms; Analysis; Biology and Life Sciences; Biomedical engineering; Biomedical research; Biometric Identification - methods; Biometric recognition systems; Biometrics; Biometry; Brain research; Classification; Complexity; Computation; Computer and Information Sciences; Computer applications; Computer architecture; Devices; Dynamical systems; EKG; Electrocardiography; Engineering and Technology; Entertainment; Feature extraction; Feature recognition; Female; Gene expression; Hardware; Heart; Heart rate; Humans; Identification; Identification methods; Innovations; Internet of Things; Iris recognition; Male; Marketing; Markets; Mathematical morphology; Medical research; Medicine and Health Sciences; Methods; Morphology; Pattern recognition; Physical characteristics; Physical Sciences; Product testing; Rejection; Rejection rate; Research and Analysis Methods; Researchers; Security; Signal Processing, Computer-Assisted; Social Sciences; State of the art; Studies; Time Factors; Wearable technology; Portugal
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0180942

In recent years, safer and more reliable biometric methods have been developed. Apart from the need for enhanced security, the media and entertainment sectors have also been applying biometrics in the emerging market of user-adaptable objects/systems to make these systems more user-friendly. However, the complexity of some state-of-the-art biometric systems (e.g., iris recognition) or their high false rejection rate (e.g., fingerprint recognition) is neither compatible with the simple hardware architecture required by reduced-size devices nor the new trend of implementing smart objects within the dynamic market of the Internet of Things (IoT). It was recently shown that an individual can be recognized by extracting features from their electrocardiogram (ECG). However, most current ECG-based biometric algorithms are computationally demanding and/or rely on relatively large (several seconds) ECG samples, which are incompatible with the aforementioned application fields. Here, we present a computationally low-cost method (patent pending), including simple mathematical operations, for identifying a person using only three ECG morphology-based characteristics from a single heartbeat. The algorithm was trained/tested using ECG signals of different duration from the Physionet database on more than 60 different training/test datasets. The proposed method achieved maximal averaged accuracy of 97.450% in distinguishing each subject from a ten-subject set and false acceptance and rejection rates (FAR and FRR) of 5.710±1.900% and 3.440±1.980%, respectively, placing Beat-ID in a very competitive position in terms of the FRR/FAR among state-of-the-art methods. Furthermore, the proposed method can identify a person using an average of 1.020 heartbeats. It therefore has FRR/FAR behavior similar to obtaining a fingerprint, yet it is simpler and requires less expensive hardware. This method targets low-computational/energy-cost scenarios, such as tiny wearable devices (e.g., a smart object that automatically adapts its configuration to the user). A hardware proof-of-concept implementation is presented as an annex to this paper.