System to measure sleep apnea using portable non-contact sensors and a machine learning algorithm

Case ID:
2595
Web Published:
8/31/2018
Description:

Summary

Method and system for automatic diagnosis of sleep apnea in the home environment. The system uses pressure sensitive sensors placed underneath a mattress and an algorithm to classify the severity of sleep apnea.

 

Technology Overview

This in home system to diagnose sleep apnea saves the patient from having to spend a night in a sleep clinic attached to numerous sensors and wires. In the comfort of their own home, patients will put a rectangular metal plate with attached load cell sensors under their mattress. During the course of the night, these sensors record respiration rate, breathing, and movement. Recordings of patient data are analyzed using signal processing and machine learning algorithms to identify sleep apnea severity.

 

Publications

•       Beattie Z, Jacobs PG, Riley TC, Hagen CC: A time-frequency respiration tracking system using non-contact bed sensors with harmonic artifact rejection. Conf Proc IEEE Eng Med Biol Soc. 2015 August;2015:8111-8114

 

Patent Information:
Category(s):
Device
Diagnostics
For Information, Contact:
Michele Gunness
Senior Technology Development Manager
Oregon Health & Science University
(503) 494-8200
gunnessm@ohsu.edu
Inventors:
Peter Jacobs
Clara Mosquera-Lopez
Joseph Leitschuh
John Condon
Keywords:
Device
Diagnostics
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