Cardiac signal estimation based on the arterial and venous pressure signals of a hemodialysis machine

Research output: Contribution to journalArticle


Continuous cardiac monitoring is usually not performed during hemodialysis treatment, although a majority of patients with kidney failure suffer from cardiovascular disease. In the present paper, a method is proposed for estimating a cardiac pressure signal by combining the arterial and the venous pressure sensor signals of the hemodialysis machine. The estimation is complicated by the periodic pressure disturbance caused by the peristaltic blood pump, with an amplitude much larger than that of the cardiac pressure signal. Using different techniques for combining the arterial and venous pressure signals, the performance is evaluated and compared to that of an earlier method which made use of the venous pressure only. The heart rate and the heartbeat occurrence times, determined from the estimated cardiac pressure signal, are compared to the corresponding quantities determined from a photoplethysmographic reference signal. Signals from 9 complete hemodialysis treatments were analyzed. For a heartbeat amplitude of 0.5 mmHg, the median absolute deviation between estimated and reference heart rate was 1.3 bpm when using the venous pressure signal only, but dropped to 0.6 bpm when combining the pressure signals. The results show that the proposed method offers superior estimation at low heartbeat amplitudes. Consequently, more patients can be successfully monitored during treatment without the need of extra sensors. The results are preliminary, and need to be verified on a separate dataset.


External organisations
  • Baxter Medical AB
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Medical Laboratory and Measurements Technologies
Original languageEnglish
Pages (from-to)1499-1515
Number of pages17
JournalPhysiological Measurement
Issue number9
Publication statusPublished - 2016 Aug 11
Publication categoryResearch

Related research output

Holmer, M., 2017 May 19, 1 ed. Lund: Department of Biomedical Engineering, Lund university. 187 p.

Research output: ThesisDoctoral Thesis (compilation)

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