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

Holmer, M; Sandberg, F; Solem, K; Olde, B, et al. (2016-08-11). Cardiac signal estimation based on the arterial and venous pressure signals of a hemodialysis machine. Physiological Measurement, 37, (9), 1499 - 1515
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| Published | English
Authors:
Holmer, M ; Sandberg, F ; Solem, K ; Olde, B , et al.
Department:
Department of Biomedical Engineering
Electrical Engineering (M.Sc.Eng.)
Department of Electrical and Information Technology
Biomedical Engineering (M.Sc.Eng.)
Abstract:
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.
ISSN:
0967-3334
LUP-ID:
0c0866be-f811-42ab-a103-de64454934d3 | Link: https://lup.lub.lu.se/record/0c0866be-f811-42ab-a103-de64454934d3 | Statistics

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