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    MULTIMODAL CONTACTLESS VITAL SIGN MONITORING
    3.
    发明申请
    MULTIMODAL CONTACTLESS VITAL SIGN MONITORING 有权

    公开(公告)号：US20230128766A1

    公开(公告)日：2023-04-27

    申请号：US17841063

    申请日：2022-06-15

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： Korosh Vatanparvar ,  Wenchuan Wei ,  Li Zhu ,  Migyeong Gwak ,  Jilong Kuang ,  Jun Gao

    IPC: A61B5/0205 ,  G06T7/215 ,  G06T7/246

    Abstract: A multimodal, contactless vital sign monitoring system is configured to perform the following operations. Images are received from a video capture device. An image of a subject is identified within the images. The image of the subject is segmented into a plurality of segments. A first analysis is performed on the plurality of segments to identify a color feature. A second analysis is performed of the plurality of segments to identify a motion feature. Using a combination of the color feature and the motion feature a plurality of vital signs for the subject are determined. The first analyzing and the second analyzing are performed in parallel. The plurality of vital signs include one or more of heart rate, respiration rate, oxygen saturation, heart rate variability, and atrial fibrillation.

    DEVICE-INVARIANT, FREQUENCY-DOMAIN SIGNAL PROCESSING WITH MACHINE LEARNING
    6.
    发明申请
    DEVICE-INVARIANT, FREQUENCY-DOMAIN SIGNAL PROCESSING WITH MACHINE LEARNING 有权

    公开(公告)号：US20220269958A1

    公开(公告)日：2022-08-25

    申请号：US17245951

    申请日：2021-04-30

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： Mohsin Yusuf Ahmed ,  Li Zhu ,  Korosh Vatanparvar ,  Md Mahbubur Rahman ,  Tousif Ahmed ,  Jilong Kuang ,  Jun Gao

    IPC: G06N5/04 ,  G06N20/00

    Abstract: Device-invariant, frequency-domain signal processing with machine learning includes retrieving with a host device a device-specific alien dataset corresponding to an alien device. The device-specific alien dataset is retrieved from a remote data storage device communicatively coupled with the host device. A plurality of frequency-domain features are extracted from the device-specific alien dataset and a machine learning model is trained using the plurality of frequency-domain features. The host device extracts frequency-domain features from signals generated by sensors operatively coupled with the host device. Real-time frequency bin adaptation of the frequency-domain features extracted by the host device is performed. Based on the frequency-domain features extracted by the host device, as adapted, an inference is performed using the machine learning model.

    NON-INVASIVE CONTINUOUS HEART RHYTHM MONITORING BASED ON WEARABLE SENSORS
    7.
    发明申请
    NON-INVASIVE CONTINUOUS HEART RHYTHM MONITORING BASED ON WEARABLE SENSORS 有权

    公开(公告)号：US20220183608A1

    公开(公告)日：2022-06-16

    申请号：US17124438

    申请日：2020-12-16

    Applicant: SAMSUNG ELECTRONICS CO., LTD. ,  The Regents of the University of California

    Inventor： Li Zhu ,  Viswam Nathan ,  Md Mahbubur Rahman ,  Jilong Kuang ,  Jeong Woo Kim ,  Jun Gao ,  David W. Mortara ,  Jeffrey E. Olgin

    IPC: A61B5/364 ,  A61B5/00

    Abstract: Continuously monitoring heart rhythm can include grouping, using computer hardware, a plurality of inter-beat intervals (IBI) data for a user into a plurality of epochs, wherein each epoch includes a subset of the IBI data corresponding to a predetermined time span. For each epoch, a selected feature set selected from a plurality of feature sets is extracted based on a determination of temporal consistency of the epoch. A plurality of epoch classifications may be generated for the epochs using a selected feature processor, wherein each epoch classification indicates whether arrhythmia is detected for the epoch from which the epoch classification is generated. The selected feature processor is selected from a plurality of different feature processors on a per-epoch basis based on the selected feature set extracted from the epoch. An indication of arrhythmia may be output, via an output device of the computer hardware, based on the epoch classifications.

    SYSTEMS AND METHODS TO DETECT AND CHARACTERIZE STRESS USING PHYSIOLOGICAL SENSORS
    10.
    发明公开
    SYSTEMS AND METHODS TO DETECT AND CHARACTERIZE STRESS USING PHYSIOLOGICAL SENSORS 审中-公开

    公开(公告)号：US20230233123A1

    公开(公告)日：2023-07-27

    申请号：US18156292

    申请日：2023-01-18

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Md Mahbubur Rahman ,  Viswam Nathan ,  Li Zhu ,  Tousif Ahmed ,  Jungmok Bae ,  Jilong Kuang ,  Jeong Woo Kim ,  Jun Gao

    IPC: A61B5/16 ,  A61B5/00

    CPC classification number: A61B5/165 ,  A61B5/486 ,  A61B5/7246 ,  A61B5/6802 ,  A61B5/7267

    Abstract: A method includes receiving multimodal data collected using at least one wearable device during an assessment window. The method also includes extracting biomarker features from the multimodal data, based on changes in the extracted biomarker features. The method also includes detecting that a stress event occurred during the assessment window. The method also includes accessing a plurality of templates of patterns in biomarker features, wherein a first subset of the templates is associated with unhealthy response to stress and a second subset of the templates is associated with healthy response to stress. The method also includes determining whether the stress event corresponds to a healthy response or an unhealthy response based on similarities between a pattern in the extracted biomarker features and the plurality of templates. The method also includes responsive to the stress event corresponding to an unhealthy response, providing a stress management recommendation.

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