Abstract: Provided are systems and methods for determination of a concentration of one or more blood biomarkers of a human subject. The method including: determining, using a first machine learning model trained with a hemoglobin concentration (HC) changes training set, bit values from a set of bitplanes in a captured image sequence that represent the HC changes of the subject, the set of bitplanes being those that are determined to approximately maximize a signal-to-noise ratio (SNR), the HC changes training set including bit values from each bitplane of images captured from a set of subjects for which HC changes are known; determining, using a second machine learning model trained using a blood biomarkers training set, concentration of one or more blood biomarkers, the blood biomarkers training set including previously determined HC change signals from other subjects and one or more blood panels from those subjects as ground truth data.

Abstract: A system and method for detection of synthesized videos of humans. The method including: determining blood flow signals using a first machine learning model trained with a hemoglobin concentration (HC) changes training set, the first machine learning model taking as input bit values from a set of bitplanes in a captured image sequence, the HC changes training set including bit values from each bitplane of images captured from a set of subjects for which HC changes are known; determining whether blood flow patterns from the video are indicative of a synthesized video using a second machine learning model, the second machine learning model taking as input the blood flow signals, the second machine learning model trained using a blood flow training set including blood flow data signals from at least one of a plurality of videos of other human subjects for which it is known whether each video is synthesized.

Abstract: Provided are systems and methods for determination of a concentration of one or more blood biomarkers of a human subject. The method including: determining, using a first machine learning model trained with a hemoglobin concentration (HC) changes training set, bit values from a set of bitplanes in a captured image sequence that represent the HC changes of the subject, the set of bitplanes being those that are determined to approximately maximize a signal-to-noise ratio (SNR), the HC changes training set including bit values from each bitplane of images captured from a set of subjects for which HC changes are known; determining, using a second machine learning model trained using a blood biomarkers training set, concentration of one or more blood biomarkers, the blood biomarkers training set including previously determined HC change signals from other subjects and one or more blood panels from those subjects as ground truth data.

Abstract: A system and method for detection of synthesized videos of humans. The method including: determining blood flow signals using a first machine learning model trained with a hemoglobin concentration (HC) changes training set, the first machine learning model taking as input bit values from a set of bitplanes in a captured image sequence, the HC changes training set including bit values from each bitplane of images captured from a set of subjects for which HC changes are known; determining whether blood flow patterns from the video are indicative of a synthesized video using a second machine learning model, the second machine learning model taking as input the blood flow signals, the second machine learning model trained using a blood flow training set including blood flow data signals from at least one of a plurality of videos of other human subjects for which it is known whether each video is synthesized.

Abstract: Provided are systems and methods for determination of a concentration of one or more blood biomarkers of a human subject. The method including: determining, using a first machine learning model trained with a hemoglobin concentration (HC) changes training set, bit values from a set of bitplanes in a captured image sequence that represent the HC changes of the subject, the set of bitplanes being those that are determined to approximately maximize a signal-to-noise ratio (SNR), the HC changes training set including bit values from each bitplane of images captured from a set of subjects for which HC changes are known; determining, using a second machine learning model trained using a blood biomarkers training set, concentration of one or more blood biomarkers, the blood biomarkers training set including previously determined HC change signals from other subjects and one or more blood panels from those subjects as ground truth data.

Abstract: A system and method for detection of synthesized videos of humans. The method including: determining blood flow signals using a first machine learning model trained with a hemoglobin concentration (HC) changes training set, the first machine learning model taking as input bit values from a set of bitplanes in a captured image sequence, the HC changes training set including bit values from each bitplane of images captured from a set of subjects for which HC changes are known; determining whether blood flow patterns from the video are indicative of a synthesized video using a second machine learning model, the second machine learning model taking as input the blood flow signals, the second machine learning model trained using a blood flow training set including blood flow data signals from at least one of a plurality of videos of other human subjects for which it is known whether each video is synthesized.