Remote photonic sensing of blood oxygen saturation via tracking of anomalies in micro-saccades patterns
| Autor: | Yafim Beiderman, Zeev Zalevsky, Aviya Bennett, Zeev Kalyuzhner, Sergey Agdarov |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Adult
Computer science 02 engineering and technology Tracking (particle physics) 01 natural sciences Convolutional neural network 010309 optics Machine Learning Photometry Speckle pattern Young Adult Optics 0103 physical sciences medicine Saccades Humans Computer vision Oximetry Oxygen saturation Oxygen saturation (medicine) Aged Artificial neural network business.industry Eye movement Hypoxia (medical) Middle Aged 021001 nanoscience & nanotechnology Atomic and Molecular Physics and Optics Healthy Volunteers Oxygen medicine.anatomical_structure Remote Sensing Technology Human eye Artificial intelligence Photonics medicine.symptom 0210 nano-technology business Algorithms |
| Zdroj: | Optics express. 29(3) |
| ISSN: | 1094-4087 |
| Popis: | Speckle pattern analysis has been found by many researchers to be applicable to remote sensing of various biomedical parameters. This paper shows how analysis of dynamic differential speckle patterns scattered from subjects’ sclera illuminated by a laser beam allows extraction of micro-saccades movement in the human eye. Analysis of micro-saccades movement using advanced machine learning techniques based on convolutional neural networks offers a novel approach for non-contact assessment of human blood oxygen saturation level (SpO2). Early stages of hypoxia can rapidly progress into pneumonia and death, and lives can be saved by advance remote detection of reduced blood oxygen saturation. |
| Databáze: | OpenAIRE |
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