no code implementations • 12 Jan 2021 • Thijs E Nassi, Wolfgang Ganglberger, Haoqi Sun, Abigail A Bucklin, Siddharth Biswal, Michel J A M van Putten, Robert J Thomas, M Brandon Westover
Using 9, 656 polysomnography recordings from the Massachusetts General Hospital (MGH), we trained a neural network (WaveNet) based on a single respiratory effort belt to detect obstructive apnea, central apnea, hypopnea and respiratory-effort related arousals.
no code implementations • 24 Feb 2021 • Wolfgang Ganglberger, Abigail A. Bucklin, Ryan A. Tesh, Madalena Da Silva Cardoso, Haoqi Sun, Michael J. Leone, Luis Paixao, Ezhil Panneerselvam, Elissa M. Ye, B. Taylor Thompson, Oluwaseun Akeju, David Kuller, Robert J. Thomas, M. Brandon Westover
The objective is to automatically detect abnormal respiration and estimate the Apnea-Hypopnea-Index (AHI) with a wearable respiratory device, compared to an SpO2 signal or polysomnography using a large (n = 412) dataset serving as ground truth.