Depth-based Patient Monitoring in the NICU with Non-Ideal Camera Placement

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  • Depth cameras can improve the performance of patient monitoring systems without the introduction of multiple sensors in the NICU. A method was developed to correct non-ideal camera placement. The mean absolute percentage error of the method tested on 28 patients was 5.58 for camera angles up to 38.58° away from the optimal camera placement. An ROI selection method was developed and tested for the use of extracting a respiratory rate signal. The ROI selection method was found to have an average Sørensen-Dice coefficient of 0.62 and Jaccard index of 0.46. The signal was compared to a simpler method resulting in an improvement to the percentage of acceptable estimates. An intervention detection method was developed using a vision transformer model, and the performance was compared to the state-of-the-art in the field. The best model was found to achieve a sensitivity of 85.6%, precision of 89.8%, and F1-Score of 87.6%.

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  • Copyright © 2023 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.
Date Created
  • 2023


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