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 bedridden 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 modeling 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/min, 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 beats/min 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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