Estimation of Respiratory Information from the Built-In Pressure Sensors of a Dialysis Machine

Frida Sandberg, Mattias Holmer, Bo Olde, Kristian Solem

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingResearchpeer-review

2 Citations (SciVal)

Abstract

The purpose of the present study is to determine the feasibility of estimating respiratory information from the built-in pressure sensors of a dialysis machine. The study database consists of simultaneous recordings of pressure signals and capnographic signals from 6 patients during 7 hemodialysis treatment sessions. Respiration rates were estimated using respiratory induced variations in the beat- to-beat interval series of the cardiac component of the pressure signal and respiratory induced baseline varia- tions in the pressure signal, respectively. The estimated respiration rates were compared to a reference respira- tion rate determined from the capnograhpic signal. The root-mean-square error of the estimated respiration rate from the baseline variations of the pressure signal was 2.10 breaths/min; the corresponding error of the estimated res- piration rate from the beat-to-beat interval series of the cardiac component was 4.95 breaths/min. The results sug- gest that it is possible to estimate respiratory information from the pressure sensors.
Original languageEnglish
Title of host publication[Host publication title missing]
EditorsAlan Murray
PublisherComputing in Cardiology
Pages853-856
Number of pages4
Volume41
Publication statusPublished - 2014
EventComputing in Cardiology 2014 - Cambridge, Massachusetts, United States
Duration: 2014 Sep 72014 Sep 10

Publication series

Name
Volume41
ISSN (Print)0276-6574

Conference

ConferenceComputing in Cardiology 2014
Country/TerritoryUnited States
CityCambridge, Massachusetts
Period2014/09/072014/09/10

Subject classification (UKÄ)

  • Medical Engineering

Fingerprint

Dive into the research topics of 'Estimation of Respiratory Information from the Built-In Pressure Sensors of a Dialysis Machine'. Together they form a unique fingerprint.

Cite this