Liao W, Zhang C, Alić B, Wildenauer A, Dietz-Terjung S, Ortiz Sucre JG, Sutharsan S, Schöbel C, Seidl K, Notni G. Leveraging 3D convolutional neural network and 3D visible-near-infrared multimodal imaging for enhanced contactless oximetry.
JOURNAL OF BIOMEDICAL OPTICS 2024;
29:S33309. [PMID:
39170819 PMCID:
PMC11338290 DOI:
10.1117/1.jbo.29.s3.s33309]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 07/30/2024] [Accepted: 08/01/2024] [Indexed: 08/23/2024]
Abstract
Significance
Monitoring oxygen saturation (SpO 2 ) is important in healthcare, especially for diagnosing and managing pulmonary diseases. Non-contact approaches broaden the potential applications ofSpO 2 measurement by better hygiene, comfort, and capability for long-term monitoring. However, existing studies often encounter challenges such as lower signal-to-noise ratios and stringent environmental conditions.
Aim
We aim to develop and validate a contactlessSpO 2 measurement approach using 3D convolutional neural networks (3D CNN) and 3D visible-near-infrared (VIS-NIR) multimodal imaging, to offer a convenient, accurate, and robust alternative forSpO 2 monitoring.
Approach
We propose an approach that utilizes a 3D VIS-NIR multimodal camera system to capture facial videos, in whichSpO 2 is estimated through 3D CNN by simultaneously extracting spatial and temporal features. Our approach includes registration of multimodal images, tracking of the 3D region of interest, spatial and temporal preprocessing, and 3D CNN-based feature extraction andSpO 2 regression.
Results
In a breath-holding experiment involving 23 healthy participants, we obtained multimodal video data with referenceSpO 2 values ranging from 80% to 99% measured by pulse oximeter on the fingertip. The approach achieved a mean absolute error (MAE) of 2.31% and a Pearson correlation coefficient of 0.64 in the experiment, demonstrating good agreement with traditional pulse oximetry. The discrepancy of estimatedSpO 2 values was within 3% of the referenceSpO 2 for ∼ 80 % of all 1-s time points. Besides, in clinical trials involving patients with sleep apnea syndrome, our approach demonstrated robust performance, with an MAE of less than 2% inSpO 2 estimations compared to gold-standard polysomnography.
Conclusions
The proposed approach offers a promising alternative for non-contact oxygen saturation measurement with good sensitivity to desaturation, showing potential for applications in clinical settings.
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