Jingting Yao

Jingting Yao (S’12) received the B.E. degree in electrical and computer engineering from the Nanjing University of Posts and Telecommunications, Nanjing, China, in 2014. She is currently pursuing the Ph.D. degree in electrical and computer engineering at Georgia Institute of Technology, GA, USA. Her current research is focused on digital signal processing of cardiac signals and development of novel gating strategies for optimizing computed tomography.

Associated articles

JTEHM, Articles, Published Articles
An Adaptive Seismocardiography (SCG)-ECG Multimodal Framework for Cardiac Gating Using Artificial Neural Networks
To more accurately trigger data acquisition and reduce radiation exposure of coronary computed tomography angiography (CCTA), a multimodal framework utilizing both electrocardiography (ECG) and seismocardiography (SCG) for CCTA prospective gating is presented. Relying upon a three-layer artificial neural network that... Read more
JTEHM, Articles, Published Articles
Near Real-Time Implementation of An Adaptive Seismocardiography — ECG Multimodal Framework for Cardiac Gating
   Early Access Note: Early Access articles are new content made available in advance of the final electronic or print versions and result from IEEE’s Preprint or Rapid Post processes. Preprint articles are peer-reviewed but not fully edited. Rapid Post articles are... Read more
JTEHM, Articles, Published Articles
Seismocardiography-Based Cardiac Computed Tomography Gating Using Patient-Specific Template Identification and Detection
    To more accurately trigger cardiac computed tomography angiography (CTA) than electrocardiography (ECG) alone, a sub-system is proposed as an intermediate step toward fusing ECG with seismocardiography (SCG). Accurate prediction of quiescent phases is crucial to prospectively gating CTA, which is... Read more