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Prediction of intradialytic hypotension using PPG and ECG

Sandberg, Frida LU ; Bailon, Raquel ; Hernando, David ; Laguna, Pablo ; Martinez, Juan Pablo ; Solem, Kristian LU and Sornmo, Leif LU (2013) 2013 40th Computing in Cardiology Conference, CinC 2013 40. p.1227-1230
Abstract

Intradialytic hypotension (IDH) is the most common complication during hemodialysis; early prediction and prevention of IDH would dramatically improve the living conditions for patients with end stage renal disease. A recently published study suggests that a decrease in the envelope of the photoplethysmograpy (PPG) signal can be used for predicting acute symptomatic IDH. In the present study, the PPG based method is extended by introducing a patient dependent detection threshold, which involves information on heart rate variability (HRV) and heart rate turbulence (HRT) from the current dialysis session. This is motivated since several studies have found significant differences in HRV and HRT between hypotension-prone and... (More)

Intradialytic hypotension (IDH) is the most common complication during hemodialysis; early prediction and prevention of IDH would dramatically improve the living conditions for patients with end stage renal disease. A recently published study suggests that a decrease in the envelope of the photoplethysmograpy (PPG) signal can be used for predicting acute symptomatic IDH. In the present study, the PPG based method is extended by introducing a patient dependent detection threshold, which involves information on heart rate variability (HRV) and heart rate turbulence (HRT) from the current dialysis session. This is motivated since several studies have found significant differences in HRV and HRT between hypotension-prone and hypotension-resistant patients. Recordings from 15 patients during 38 hemodialysis sessions were used to evaluate the method. Symptomatic IDH was correctly predicted in 9 out of 14 cases, while 5 out of 24 cases were falsely predicted. The performance was better for acute symptomatic IDH, 5 out of 5 cases were correctly predicted. The present method represents a novel approach to combining information derived from ECG and PPG signals.

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author
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organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
2013 Computing in Cardiology
volume
40
article number
6713605
pages
4 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
2013 40th Computing in Cardiology Conference, CinC 2013
conference location
Zaragoza, Spain
conference dates
2013-09-22 - 2013-09-25
external identifiers
  • scopus:84894190867
ISBN
9781479908844
language
English
LU publication?
yes
id
331f6a3f-8b08-4c2a-aec0-0a23ebd05dbf
alternative location
https://ieeexplore.ieee.org/document/6713605
date added to LUP
2019-06-04 15:44:40
date last changed
2020-01-13 01:58:05
@inproceedings{331f6a3f-8b08-4c2a-aec0-0a23ebd05dbf,
  abstract     = {<p>Intradialytic hypotension (IDH) is the most common complication during hemodialysis; early prediction and prevention of IDH would dramatically improve the living conditions for patients with end stage renal disease. A recently published study suggests that a decrease in the envelope of the photoplethysmograpy (PPG) signal can be used for predicting acute symptomatic IDH. In the present study, the PPG based method is extended by introducing a patient dependent detection threshold, which involves information on heart rate variability (HRV) and heart rate turbulence (HRT) from the current dialysis session. This is motivated since several studies have found significant differences in HRV and HRT between hypotension-prone and hypotension-resistant patients. Recordings from 15 patients during 38 hemodialysis sessions were used to evaluate the method. Symptomatic IDH was correctly predicted in 9 out of 14 cases, while 5 out of 24 cases were falsely predicted. The performance was better for acute symptomatic IDH, 5 out of 5 cases were correctly predicted. The present method represents a novel approach to combining information derived from ECG and PPG signals.</p>},
  author       = {Sandberg, Frida and Bailon, Raquel and Hernando, David and Laguna, Pablo and Martinez, Juan Pablo and Solem, Kristian and Sornmo, Leif},
  booktitle    = {2013 Computing in Cardiology},
  isbn         = {9781479908844},
  language     = {eng},
  month        = {12},
  pages        = {1227--1230},
  publisher    = {IEEE - Institute of Electrical and Electronics Engineers Inc.},
  title        = {Prediction of intradialytic hypotension using PPG and ECG},
  url          = {https://ieeexplore.ieee.org/document/6713605},
  volume       = {40},
  year         = {2013},
}