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Review
. 2023 Jun 20;23(12):5744.
doi: 10.3390/s23125744.

Estimation of Physiologic Pressures: Invasive and Non-Invasive Techniques, AI Models, and Future Perspectives

Sharanya Manga  1 , Neha Muthavarapu  1 , Renisha Redij  2 , Bhavana Baraskar  3 , Avneet Kaur  4 , Sunil Gaddam  4 , Keerthy Gopalakrishnan  2   4 , Rutuja Shinde  5 , Anjali Rajagopal  5 , Poulami Samaddar  4 , Devanshi N Damani  1   6 , Suganti Shivaram  7 , Shuvashis Dey  4   8 , Dipankar Mitra  4   9 , Sayan Roy  4   10 , Kanchan Kulkarni  11   12 , Shivaram P Arunachalam  2   3   4   5
Affiliations
Review

Estimation of Physiologic Pressures: Invasive and Non-Invasive Techniques, AI Models, and Future Perspectives

Sharanya Manga et al. Sensors (Basel). .

Abstract

The measurement of physiologic pressure helps diagnose and prevent associated health complications. From typical conventional methods to more complicated modalities, such as the estimation of intracranial pressures, numerous invasive and noninvasive tools that provide us with insight into daily physiology and aid in understanding pathology are within our grasp. Currently, our standards for estimating vital pressures, including continuous BP measurements, pulmonary capillary wedge pressures, and hepatic portal gradients, involve the use of invasive modalities. As an emerging field in medical technology, artificial intelligence (AI) has been incorporated into analyzing and predicting patterns of physiologic pressures. AI has been used to construct models that have clinical applicability both in hospital settings and at-home settings for ease of use for patients. Studies applying AI to each of these compartmental pressures were searched and shortlisted for thorough assessment and review. There are several AI-based innovations in noninvasive blood pressure estimation based on imaging, auscultation, oscillometry and wearable technology employing biosignals. The purpose of this review is to provide an in-depth assessment of the involved physiologies, prevailing methodologies and emerging technologies incorporating AI in clinical practice for each type of compartmental pressure measurement. We also bring to the forefront AI-based noninvasive estimation techniques for physiologic pressure based on microwave systems that have promising potential for clinical practice.

Keywords: blood pressure; capillary wedge pressure; conductivity; dielectric properties; hepatic portal gradients; intracranial pressures; microwave imaging; microwaves; noninvasive sensors; permittivity.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Pictorial representation of several invasive and noninvasive methods for pressure estimation.
Figure 2
Figure 2
Pictorial representation for noninvasive pressure estimation using AI-assisted microwave systems.
See this image and copyright information in PMC

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