Contactless Oxygen Saturation Detection Based on Face Analysis: An Approach and Case Study

Hamoud, Batol; Othman, Walaa; Shilov, Nikolay; Kashevnik, Alexey

doi:10.23919/fruct58615.2023.10143059

Cited by 7 publications

(1 citation statement)

References 12 publications

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“…Our dataset contains a video of the operator's face and torso. Based on this video, using modern computer vision technologies, we determined the following operator characteristics: respiratory rate [42], heart rate [43], blood pressure [44], oxygen saturation [45] as well eyes/mouth openness and closeness [46] and head/body movements using our developed earlier human analyzing tool. The tool marks every second of the video by vital signs determined using the methods presented in our previous papers mentioned above.…”

Section: Videomentioning

confidence: 99%

OperatorEYEVP: Operator Dataset for Fatigue Detection Based on Eye Movements, Heart Rate Data, and Video Information

Kovalenko

Mamonov

Kuznetsov

et al. 2023

Sensors

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Detection of fatigue is extremely important in the development of different kinds of preventive systems (such as driver monitoring or operator monitoring for accident prevention). The presence of fatigue for this task should be determined with physiological and objective behavioral indicators. To develop an effective model of fatigue detection, it is important to record a dataset with people in a state of fatigue as well as in a normal state. We carried out data collection using an eye tracker, a video camera, a stage camera, and a heart rate monitor to record a different kind of signal to analyze them. In our proposed dataset, 10 participants took part in the experiment and recorded data 3 times a day for 8 days. They performed different types of activity (choice reaction time, reading, correction test Landolt rings, playing Tetris), imitating everyday tasks. Our dataset is useful for studying fatigue and finding indicators of its manifestation. We have analyzed datasets that have public access to find the best for this task. Each of them contains data of eye movements and other types of data. We evaluated each of them to determine their suitability for fatigue studies, but none of them fully fit the fatigue detection task. We evaluated the recorded dataset by calculating the correspondences between eye-tracking data and CRT (choice reaction time) that show the presence of fatigue.

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Section: Videomentioning

confidence: 99%

OperatorEYEVP: Operator Dataset for Fatigue Detection Based on Eye Movements, Heart Rate Data, and Video Information

Kovalenko

Mamonov

Kuznetsov

et al. 2023

Sensors

Self Cite

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Contactless Video-Based Vital-Sign Measurement Methods: A Data-Driven Review

Brieva,

Moya-Albor,

Ponce

et al. 2024

Studies in Big Data

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Innovative approaches in imaging photoplethysmography for remote blood oxygen monitoring

Zhu,

Liu,

Jing

et al. 2024

Sci Rep

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Peripheral Capillary Oxygen Saturation (SpO 2 ) has received increasing attention during the COVID-19 pandemic. Clinical investigations have demonstrated that individuals afflicted with COVID-19 exhibit notably reduced levels of SpO 2 before the deterioration of their health status. To cost-effectively enable individuals to monitor their SpO 2 , this paper proposes a novel neural network model named “ITSCAN” based on Temporal Shift Module. Benefiting from the widespread use of smartphones, this model can assess an individual’s SpO 2 in real time, utilizing standard facial video footage, with a temporal granularity of seconds. The model is interweaved by two distinct branches: the motion branch, responsible for extracting spatiotemporal data features and the appearance branch, focusing on the correlation between feature channels and the location information of feature map using coordinate attention mechanisms. Accordingly, the SpO 2 estimator generates the corresponding SpO 2 value. This paper summarizes for the first time 5 loss functions commonly used in the SpO 2 estimation model. Subsequently, a novel loss function has been contributed through the examination of various combinations and careful selection of hyperparameters. Comprehensive ablation experiments analyze the independent impact of each module on the overall model performance. Finally, the experimental results based on the public dataset (VIPL-HR) show that our model has obvious advantages in MAE (1.10%) and RMSE (1.19%) compared with related work, which implies more accuracy of the proposed method to contribute to public health.

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Contactless Oxygen Saturation Detection Based on Face Analysis: An Approach and Case Study

Cited by 7 publications

References 12 publications

OperatorEYEVP: Operator Dataset for Fatigue Detection Based on Eye Movements, Heart Rate Data, and Video Information

OperatorEYEVP: Operator Dataset for Fatigue Detection Based on Eye Movements, Heart Rate Data, and Video Information

Contactless Video-Based Vital-Sign Measurement Methods: A Data-Driven Review

Innovative approaches in imaging photoplethysmography for remote blood oxygen monitoring

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