Application of Real-Time Image Processing Algorithms for Enhanced Respiratory Monitoring in Neonatal and Adult Ventilation Systems

Authors: Akshat Bhutiani

DOI: https://doi.org/10.5281/zenodo.14208735

Short DOI: https://doi.org/g8rrc4

Country: USA

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Abstract: This paper explores the application of real-time image processing algorithms to improve respiratory monitoring in neonatal and adult ventilation systems. Conventional respiratory monitoring techniques frequently use intrusive sensors or ones that react slowly to patient changes. This method provides a non-invasive, high-precision solution for ongoing monitoring by combining sophisticated image processing techniques such as motion detection and respiratory rate estimation through real-time video analysis. The system can detect irregularities like apnea or labored breathing by using deep learning to track subtle movements of the chest and provide real – time feedback on respiratory patterns. By minimizing physical contact, this innovative method not only improves patient comfort but also enables early identification of respiratory diseases, leading to a more responsive and flexible respiratory support in critical care environments.

Keywords: Real-time image processing, respiratory monitoring, neonatal ventilation, adult ventilation, deep learning, motion detection.

Paper Id: 231630

Published On: 2023-04-05

Published In: Volume 11, Issue 2, March-April 2023

Cite This: Application of Real-Time Image Processing Algorithms for Enhanced Respiratory Monitoring in Neonatal and Adult Ventilation Systems - Akshat Bhutiani - IJIRMPS Volume 11, Issue 2, March-April 2023. DOI 10.5281/zenodo.14208735

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