Patents by Inventor Evgueni KABAKOV
Evgueni KABAKOV has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20230260611Abstract: 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.Type: ApplicationFiled: May 1, 2023Publication date: August 17, 2023Inventors: Kang LEE, Evgueni KABAKOV, Winston DE ARMAS, Alan DING, Darshan SINGH PANESAR
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Patent number: 11676690Abstract: 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.Type: GrantFiled: June 30, 2020Date of Patent: June 13, 2023Assignee: NURALOGIX CORPORATIONInventors: Kang Lee, Evgueni Kabakov, Winston De Armas, Alan Ding, Darshan Singh Panesar
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Publication number: 20220262148Abstract: 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.Type: ApplicationFiled: June 30, 2020Publication date: August 18, 2022Inventors: Kang LEE, Evgueni KABAKOV, Winston DE ARMAS, Alan DING, Darshan SINGH PANESAR
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Patent number: 11337626Abstract: A system and method for contactless blood pressure determination. The method includes: receiving a captured image sequence; determining, using a trained hemoglobin concentration (HC) changes machine learning model, bit values from a set of bitplanes in the captured image sequence that represent the HC changes of the subject; determining a blood flow data signal; extracting one or more domain knowledge signals associated with the determination of blood pressure; building a trained blood pressure machine learning model with a blood pressure training set, the blood pressure training set including the blood flow data signal of the one or more predetermined ROIs and the one or more domain knowledge signals; determining, using the blood pressure machine learning model trained with a blood pressure training set, an estimation of blood pressure; and outputting the determination of blood pressure.Type: GrantFiled: December 2, 2020Date of Patent: May 24, 2022Inventors: Kang Lee, Evgueni Kabakov, Phil Levy
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Publication number: 20210085227Abstract: A system and method for contactless blood pressure determination. The method includes: receiving a captured image sequence; determining, using a trained hemoglobin concentration (HC) changes machine learning model, bit values from a set of bitplanes in the captured image sequence that represent the HC changes of the subject; determining a blood flow data signal; extracting one or more domain knowledge signals associated with the determination of blood pressure; building a trained blood pressure machine learning model with a blood pressure training set, the blood pressure training set including the blood flow data signal of the one or more predetermined ROIs and the one or more domain knowledge signals; determining, using the blood pressure machine learning model trained with a blood pressure training set, an estimation of blood pressure; and outputting the determination of blood pressure.Type: ApplicationFiled: December 2, 2020Publication date: March 25, 2021Inventors: Kang LEE, Evgueni KABAKOV, Phil LEVY
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Patent number: 10888256Abstract: A system and method for contactless blood pressure determination. The method includes: receiving a captured image sequence; determining, using a trained hemoglobin concentration (HC) changes machine learning model, bit values from a set of bitplanes in the captured image sequence that represent the HC changes of the subject; determining a blood flow data signal; extracting one or more domain knowledge signals associated with the determination of blood pressure; building a trained blood pressure machine learning model with a blood pressure training set, the blood pressure training set including the blood flow data signal of the one or more predetermined ROIs and the one or more domain knowledge signals; determining, using the blood pressure machine learning model trained with a blood pressure training set, an estimation of blood pressure; and outputting the determination of blood pressure.Type: GrantFiled: May 8, 2019Date of Patent: January 12, 2021Assignee: NURALOGIX CORPORATIONInventors: Kang Lee, Evgueni Kabakov, Phil Levy
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Patent number: 10702173Abstract: A system and method for camera-based heart rate tracking. The method includes: determining bit values from a set of bitplanes in a captured image sequence that represent the HC changes; determining a facial blood flow data signal for each of a plurality of predetermined regions of interest (ROIs) of the subject captured by the images based on the HC changes; applying a band-pass filter of a passband approximating the heart rate to each of the blood flow data signals; applying a Hilbert transform to each of the blood flow data signals; adjusting the blood flow data signals from revolving phase-angles into linear phase segments; determining an instantaneous heart rate for each the blood flow data signals; applying a weighting to each of the instantaneous heart rates; and averaging the weighted instantaneous heart rates.Type: GrantFiled: July 9, 2019Date of Patent: July 7, 2020Assignee: NuraLogix CorporationInventors: Kang Lee, Evgueni Kabakov, Phil Levy
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Publication number: 20200129103Abstract: A system and method for contactless blood pressure determination. The method includes: receiving a captured image sequence; determining, using a trained hemoglobin concentration (HC) changes machine learning model, bit values from a set of bitplanes in the captured image sequence that represent the HC changes of the subject; determining a blood flow data signal; extracting one or more domain knowledge signals associated with the determination of blood pressure; building a trained blood pressure machine learning model with a blood pressure training set, the blood pressure training set including the blood flow data signal of the one or more predetermined ROIs and the one or more domain knowledge signals; determining, using the blood pressure machine learning model trained with a blood pressure training set, an estimation of blood pressure; and outputting the determination of blood pressure.Type: ApplicationFiled: May 8, 2019Publication date: April 30, 2020Inventors: Kang LEE, Evgueni KABAKOV, Phil LEVY
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Publication number: 20190328247Abstract: A system and method for camera-based heart rate tracking. The method includes: determining bit values from a set of bitplanes in a captured image sequence that represent the HC changes; determining a facial blood flow data signal for each of a plurality of predetermined regions of interest (ROIs) of the subject captured by the images based on the HC changes; applying a band-pass filter of a passband approximating the heart rate to each of the blood flow data signals; applying a Hilbert transform to each of the blood flow data signals; adjusting the blood flow data signals from revolving phase-angles into linear phase segments; determining an instantaneous heart rate for each the blood flow data signals; applying a weighting to each of the instantaneous heart rates; and averaging the weighted instantaneous heart rates.Type: ApplicationFiled: July 9, 2019Publication date: October 31, 2019Inventors: Kang LEE, Evgueni KABAKOV, Phil LEVY
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Patent number: 10448847Abstract: A system and method for camera-based heart rate tracking. The method includes: determining bit values from a set of bitplanes in a captured image sequence that represent the HC changes; determining a facial blood flow data signal for each of a plurality of predetermined regions of interest (ROIs) of the subject captured by the images based on the HC changes; applying a band-pass filter of a passband approximating the heart rate to each of the blood flow data signals; applying a Hilbert transform to each of the blood flow data signals; adjusting the blood flow data signals from revolving phase-angles into linear phase segments; determining an instantaneous heart rate for each the blood flow data signals; applying a weighting to each of the instantaneous heart rates; and averaging the weighted instantaneous heart rates.Type: GrantFiled: October 5, 2018Date of Patent: October 22, 2019Assignee: NURALOGIX CORPORATIONInventors: Kang Lee, Evgueni Kabakov, Phil Levy
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Patent number: 10376192Abstract: A system and method for contactless blood pressure determination. The method includes: receiving a captured image sequence; determining, using a trained hemoglobin concentration (HC) changes machine learning model, bit values from a set of bitplanes in the captured image sequence that represent the HC changes of the subject; determining a blood flow data signal; extracting one or more domain knowledge signals associated with the determination of blood pressure; building a trained blood pressure machine learning model with a blood pressure training set, the blood pressure training set including the blood flow data signal of the one or more predetermined ROIs and the one or more domain knowledge signals; determining, using the blood pressure machine learning model trained with a blood pressure training set, an estimation of blood pressure; and outputting the determination of blood pressure.Type: GrantFiled: March 16, 2018Date of Patent: August 13, 2019Assignee: NURALOGIX CORPORATIONInventors: Kang Lee, Evgueni Kabakov, Phil Levy
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Publication number: 20190038159Abstract: A system and method for camera-based heart rate tracking. The method includes: determining bit values from a set of bitplanes in a captured image sequence that represent the HC changes; determining a facial blood flow data signal for each of a plurality of predetermined regions of interest (ROIs) of the subject captured by the images based on the HC changes; applying a band-pass filter of a passband approximating the heart rate to each of the blood flow data signals; applying a Hilbert transform to each of the blood flow data signals; adjusting the blood flow data signals from revolving phase-angles into linear phase segments; determining an instantaneous heart rate for each the blood flow data signals; applying a weighting to each of the instantaneous heart rates; and averaging the weighted instantaneous heart rates.Type: ApplicationFiled: October 5, 2018Publication date: February 7, 2019Inventors: Kang LEE, Evgueni KABAKOV, Phil LEVY
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Patent number: 10117588Abstract: A system and method for camera-based heart rate tracking. The method includes: determining bit values from a set of bitplanes in a captured image sequence that represent the HC changes; determining a facial blood flow data signal for each of a plurality of predetermined regions of interest (ROIs) of the subject captured by the images based on the HC changes; applying a band-pass filter of a passband approximating the heart rate to each of the blood flow data signals; applying a Hilbert transform to each of the blood flow data signals; adjusting the blood flow data signals from revolving phase-angles into linear phase segments; determining an instantaneous heart rate for each the blood flow data signals; applying a weighting to each of the instantaneous heart rates; and averaging the weighted instantaneous heart rates.Type: GrantFiled: March 16, 2018Date of Patent: November 6, 2018Assignee: NURALOGIX CORPORATIONInventors: Kang Lee, Evgueni Kabakov, Phil Levy
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Publication number: 20180199838Abstract: A system and method for camera-based heart rate tracking. The method includes: determining bit values from a set of bitplanes in a captured image sequence that represent the HC changes; determining a facial blood flow data signal for each of a plurality of predetermined regions of interest (ROIs) of the subject captured by the images based on the HC changes; applying a band-pass filter of a passband approximating the heart rate to each of the blood flow data signals; applying a Hilbert transform to each of the blood flow data signals; adjusting the blood flow data signals from revolving phase-angles into linear phase segments; determining an instantaneous heart rate for each the blood flow data signals; applying a weighting to each of the instantaneous heart rates; and averaging the weighted instantaneous heart rates.Type: ApplicationFiled: March 16, 2018Publication date: July 19, 2018Inventors: Kang LEE, Evgueni KABAKOV, Phil LEVY
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Publication number: 20180199870Abstract: A system and method for contactless blood pressure determination. The method includes: receiving a captured image sequence; determining, using a trained hemoglobin concentration (HC) changes machine learning model, bit values from a set of bitplanes in the captured image sequence that represent the HC changes of the subject; determining a blood flow data signal; extracting one or more domain knowledge signals associated with the determination of blood pressure; building a trained blood pressure machine learning model with a blood pressure training set, the blood pressure training set including the blood flow data signal of the one or more predetermined ROIs and the one or more domain knowledge signals; determining, using the blood pressure machine learning model trained with a blood pressure training set, an estimation of blood pressure; and outputting the determination of blood pressure.Type: ApplicationFiled: March 16, 2018Publication date: July 19, 2018Inventors: Kang LEE, Evgueni KABAKOV, Phil LEVY