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Central Hypovolemia Detection During Environmental Stress-A Role for Artificial Intelligence?
Björn J P van der Ster1,2,3, Yu-Sok Kim3,4, Berend E Westerhof3,5
1Department of Internal Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands.
Understanding central blood volume (CBV) changes during exercise and recovery is crucial for preventing orthostatic intolerance. New methods using AI and wearable sensors aim to improve hemodynamic monitoring and predict outcomes in various populations.
Area of Science:
- Physiology
- Cardiovascular Science
- Biomedical Engineering
Background:
- Assuming an upright posture causes blood to shift to the lower body, reducing central blood volume (CBV) and potentially leading to orthostatic intolerance.
- Post-exercise, the cessation of leg muscle pump function and maintained peripheral vascular conductance can cause a drop in cardiac output, leading to post-exercise hypotension (PEH).
- Quantifying CBV is challenging, with limited readily available instruments for healthy subjects.
Purpose of the Study:
- To explore methodologies for quantifying central blood volume (CBV) and its implications during and after exercise.
- To investigate the use of advanced technologies like AI and wearable sensors for improved hemodynamic monitoring.
- To understand the physiological responses to postural stress and hypovolemia in both healthy and clinical populations.
Main Methods:
- Utilizing postural stressors like lower body negative pressure (LBNP) and head-up tilt (HUT) in laboratory settings.
- Quantifying key biomedical parameters related to blood flow and oxygenation.
- Developing and applying artificial intelligence (AI) algorithms and wearable sensors for hemodynamic monitoring.
Main Results:
- Postural stress, exercise cessation, and blood loss can significantly reduce CBV and stroke volume, impacting cardiac output.
- Imbalances in vascular conductance and cardiac output contribute to post-exercise hypotension.
- Emerging technologies show promise in enhancing the prediction of outcomes and guiding treatment through improved CBV monitoring.
Conclusions:
- Accurate quantification and monitoring of central blood volume are vital for understanding cardiovascular regulation during stress.
- AI and wearable sensor technologies offer promising avenues for advancing hemodynamic monitoring and clinical applications.
- Research into CBV dynamics is relevant for diverse populations, from athletes to patients experiencing hypovolemia or undergoing anesthesia.
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