Video-based estimation of blood pressure

Ananyananda Dasari1, Laszlo A Jeni2, Conrad S Tucker1,2

  • 1Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America.

Plos One
|January 30, 2025
PubMed

Insights

This study introduces a non-contact, video-based method for estimating blood pressure using pulse transit time. This approach offers a scalable and robust alternative to traditional cuff-based devices, improving accessibility for health monitoring.

Area of Science:

  • Biomedical Engineering
  • Medical Imaging
  • Cardiovascular Health

Background:

  • Traditional blood pressure monitoring relies on cuff-based devices, which are costly and limited in scalability.
  • Hypertension and cardiovascular diseases necessitate continuous and accessible blood pressure monitoring.
  • Existing methods require physical contact, posing limitations in certain clinical and remote settings.

Purpose of the Study:

  • To develop a non-contact, video-based blood pressure estimation method (V-BPE).
  • To overcome the limitations of traditional contact-based blood pressure devices.
  • To provide a scalable, robust, and infection-risk-reducing approach to blood pressure monitoring.

Main Methods:

  • Leveraging Pulse Transit Time (PTT) derived from video signals.
  • Utilizing computer vision techniques and subject-specific demographic data (height, weight) to estimate blood vessel parameters.
  • Analytically estimating blood pressure based on the inverse relationship between blood pressure and pulse wave velocity.

Main Results:

  • Demonstrated that PTT-based blood pressure estimation requires subject-specific vascular parameters.
  • Successfully incorporated subject-specific parameters using computer vision and demographic data.
  • Validated the robustness of V-BPE in diverse, real-world conditions with varied demographics.

Conclusions:

  • V-BPE offers a non-contact, scalable, and robust method for blood pressure estimation.
  • The incorporation of subject-specific information enhances the accuracy and applicability of video-based blood pressure monitoring.
  • This technology has the potential to significantly improve cardiovascular disease monitoring and management.

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