SpO2 estimation
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Benchmarks
Most implemented
Efficient Deep Learning-based Estimation of the Vital Signs on Smartphones
Summit Vitals: Multi-Camera and Multi-Signal Biosensing at High Altitudes
Liquid Structural State-Space Models
Papers
VideoPulse: Neonatal heart rate and peripheral capillary oxygen saturation (SpO2) estimation from contact free video
Remote photoplethysmography (rPPG) enables contact free monitoring of vital signs and is especially valuable for neonates, since conventional methods often require sustained skin contact with adhesive probes that can irr…
SpO2 estimationFace AlignmentRapid Adaptation of SpO2 Estimation to Wearable Devices via Transfer Learning on Low-Sampling-Rate PPG
Blood oxygen saturation (SpO2) is a vital marker for healthcare monitoring. Traditional SpO2 estimation methods often rely on complex clinical calibration, making them unsuitable for low-power, wearable applications. In …
Transfer LearningSpO2 estimationSummit Vitals: Multi-Camera and Multi-Signal Biosensing at High Altitudes
Video photoplethysmography (vPPG) is an emerging method for non-invasive and convenient measurement of physiological signals, utilizing two primary approaches: remote video PPG (rPPG) and contact video PPG (cPPG). Monito…
SpO2 estimationContrasting Deep Learning Models for Direct Respiratory Insufficiency Detection Versus Blood Oxygen Saturation Estimation
We contrast high effectiveness of state of the art deep learning architectures designed for general audio classification tasks, refined for respiratory insufficiency (RI) detection and blood oxygen saturation (SpO2) esti…
Audio ClassificationBinary ClassificationregressionSpO2 estimationBlood Oxygen Saturation Estimation from Facial Video via DC and AC components of Spatio-temporal Map
Peripheral blood oxygen saturation (SpO2), an indicator of oxygen levels in the blood, is one of the most important physiological parameters. Although SpO2 is usually measured using a pulse oximeter, non-contact SpO2 est…
SpO2 estimationLiquid Structural State-Space Models
A proper parametrization of state transition matrices of linear state-space models (SSMs) followed by standard nonlinearities enables them to efficiently learn representations from sequential data, establishing the state…
Heart rate estimationLong-range modelingSpeech RecognitionSpO2 estimation+2