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Activity‐based electrocardiogram biometric verification using wearable devices

Bıçakcı, Hazal Su, Santopietro, Marco, Guest, Richard (2022) Activity‐based electrocardiogram biometric verification using wearable devices. IET Biometrics, 12 (1). pp. 38-51. ISSN 2047-4946. (doi:10.1049/bme2.12105) (KAR id:99214)

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Activity classification and biometric authentication have become synonymous with wearable technologies such as smartwatches and trackers. Although great efforts have been made to develop electrocardiogram (ECG)‐based biometric verification and identification modalities using data from these devices, in this paper, we explore the use of adaptive techniques based on prior activity classification in an attempt to enhance biometric performance. In doing so, we also compare two waveform similarity distances to provide features for classification. Two public datasets which were collected from medical and wearable devices provide a cross‐device comparison. Our results show that our method is able to be used for both wearable and medical devices in activity classification and biometric verification cases. This study is the first study which uses only ECG signals for both activity classification and biometric verification purposes.

Item Type: Article
DOI/Identification number: 10.1049/bme2.12105
Uncontrolled keywords: ORIGINAL RESEARCH, activity classification, behavioural biometrics, biometrics (access control), ECG biometrics, emotion recognition, wearable devices
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TK Electrical engineering. Electronics. Nuclear engineering
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Funders: University of Kent (
SWORD Depositor: JISC Publications Router
Depositing User: JISC Publications Router
Date Deposited: 16 Dec 2022 14:39 UTC
Last Modified: 07 Feb 2023 16:49 UTC
Resource URI: (The current URI for this page, for reference purposes)
Bıçakcı, Hazal Su:
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