학술논문

Locality Sensitive Hashing for ECG-based Subject Identification
Document Type
Conference
Source
2019 International Conference on Electrical and Computing Technologies and Applications (ICECTA) Electrical and Computing Technologies and Applications (ICECTA), 2019 International Conference on. :1-4 Nov, 2019
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
ECG
subject identification
Locality Sensitive Hashing
LSH
Language
Abstract
There are more than 3.5 billion people around the world has utilized Internet-based services for various purposes such as news, businesses, communication and office applications; and accessing to the Internet by various modern devices for instance smartphone, tablet and laptop. Indeed, the way of doing businesses across the world also have been changed toward relying upon providing services through the internet network; at the same time the threats usually exist alongside within these technologies. Different technologies have been utilized to secure access to these services. Biometrics approaches, likewise, fingerprint has a popular use for user identification but they have some serious limitations such as cost, reliability, and etc. In this paper, we propose electrocardiogram (ECG)-based subject identification system using Locality Sensitive Hashing (LSH) with fiducial and non-fiducial feature extraction approaches. The proposed identification system was evaluated on 42 subjects of Capnobase dataset. The results show that the system scored 99.07% identification accuracy for LSH-fiducial based approach and 99.16% for the LSH-non-fiducial based approach.