Contactless Polysomnography: What Radio Waves Tell Us about Sleep

no code implementations • 20 May 2024 • Hao He, Chao Li, Wolfgang Ganglberger, Kaileigh Gallagher, Rumen Hristov, Michail Ouroutzoglou, Haoqi Sun, Jimeng Sun, Brandon Westover, Dina Katabi

The ability to assess sleep at home, capture sleep stages, and detect the occurrence of apnea (without on-body sensors) simply by analyzing the radio waves bouncing off people's bodies while they sleep is quite powerful.

Sleep Apnea and Respiratory Anomaly Detection from a Wearable Band and Oxygen Saturation

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.

Anomaly Detection

Automated Respiratory Event Detection Using Deep Neural Networks

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.

Event Detection