@inproceedings{dacbea4523e34603831a4840f6e5e2db,
title = "Estimation of Respiratory Information from the Built-In Pressure Sensors of a Dialysis Machine",
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.",
author = "Frida Sandberg and Mattias Holmer and Bo Olde and Kristian Solem",
year = "2014",
language = "English",
volume = "41",
publisher = "Computing in Cardiology",
pages = "853--856",
editor = "Alan Murray",
booktitle = "[Host publication title missing]",
note = "Computing in Cardiology 2014 ; Conference date: 07-09-2014 Through 10-09-2014",
}