CorNET: Deep Learning Framework for PPG-Based Heart Rate Estimation and Biometric Identification in Ambulant Environment

• Published in: IEEE transactions on biomedical circuits and systems Vol. 13; no. 2; pp. 282 - 291
• Main Authors: Biswas, Dwaipayan, Everson, Luke, Liu, Muqing, Panwar, Madhuri, Verhoef, Bram-Ernst, Patki, Shrishail, Kim, Chris H., Acharyya, Amit, Van Hoof, Chris, Konijnenburg, Mario, Van Helleputte, Nick
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.04.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Artificial neural networks; Average heart rate; biometric; Biometric Identification; Biometrics; Convolution; convolutional neural network; Data processing; Deep Learning; EKG; Electrocardiography; Estimation; Heart rate; Heart Rate - physiology; Humans; Long short-term memory; Monitoring; Neural networks; Neurons; Photoplethysmography; PPG; Remote monitoring; Remote sensors; Sensors; Signal monitoring; Signal Processing, Computer-Assisted; Walking - physiology; Wireless sensor networks; Wrist

Advancements in wireless sensor network technologies have enabled the proliferation of miniaturized body-worn sensors, capable of long-term pervasive biomedical signal monitoring. Remote cardiovascular monitoring has been one of the beneficiaries of this development, resulting in non-invasive, photo...