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Real-time closed-loop control of human heart rate and blood pressure


Sarabadani Tafreshi, Amirehsan; Klamroth-Marganska, Verena; Nussbaumer, Silvio; Riener, Robert (2015). Real-time closed-loop control of human heart rate and blood pressure. IEEE Transactions on Bio-Medical Engineering, 62(5):1434-1442.

Abstract

Prolonged bed rest has significant negative impacts on the human body, particularly on the cardiovascular system. To overcome adverse effects and enhance functional recovery in bed-ridden patients, the goal is to mobilize patients as early as possible while controlling and stabilizing their cardiovascular system. In this paper we used a robotic tilt table that allows early mobilization by modulating body inclination and automated leg movement, to control the cardiovascular variables heart rate (HR) or systolic or diastolic blood pressures (sBP, dBP). The design and use of a control system is often done with a simulation model of a plant, but the time-variant and nonlinear nature of the cardiovascular system and subject-specific responses to external stimuli makes the modelling and identification challenging. Instead, we implemented an intelligent self-learning fuzzy controller that does not need any prior knowledge about the plant. The controller modulates the body inclination in order to adjust the cardiovascular parameters, with leg movement considered as a perturbing factor to the controller. The controller performance was evaluated in six healthy subjects. Measured mean values of HR, sBP and dBP differed from desired reference values by 1.11 beats per minute, 5.10 mmHg and 2.69 mmHg, respectively. With this new control strategy, HR and dBP could be successfully controlled within medically tolerable ranges (deviations < 2.5 bpm and < 5 mmHg from desired values, respectively). The control of sBP was less accurate; the results suggest that simultaneous control of multiple input stimuli rather than only adaptive automatic change of the tilt table angle might improve the controllability.

Abstract

Prolonged bed rest has significant negative impacts on the human body, particularly on the cardiovascular system. To overcome adverse effects and enhance functional recovery in bed-ridden patients, the goal is to mobilize patients as early as possible while controlling and stabilizing their cardiovascular system. In this paper we used a robotic tilt table that allows early mobilization by modulating body inclination and automated leg movement, to control the cardiovascular variables heart rate (HR) or systolic or diastolic blood pressures (sBP, dBP). The design and use of a control system is often done with a simulation model of a plant, but the time-variant and nonlinear nature of the cardiovascular system and subject-specific responses to external stimuli makes the modelling and identification challenging. Instead, we implemented an intelligent self-learning fuzzy controller that does not need any prior knowledge about the plant. The controller modulates the body inclination in order to adjust the cardiovascular parameters, with leg movement considered as a perturbing factor to the controller. The controller performance was evaluated in six healthy subjects. Measured mean values of HR, sBP and dBP differed from desired reference values by 1.11 beats per minute, 5.10 mmHg and 2.69 mmHg, respectively. With this new control strategy, HR and dBP could be successfully controlled within medically tolerable ranges (deviations < 2.5 bpm and < 5 mmHg from desired values, respectively). The control of sBP was less accurate; the results suggest that simultaneous control of multiple input stimuli rather than only adaptive automatic change of the tilt table angle might improve the controllability.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Balgrist University Hospital, Swiss Spinal Cord Injury Center
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:13 January 2015
Deposited On:12 Mar 2015 12:58
Last Modified:08 Dec 2017 12:26
Publisher:Institute of Electrical and Electronics Engineers
ISSN:0018-9294
Publisher DOI:https://doi.org/10.1109/TBME.2015.2391234
PubMed ID:25594957

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