System and method for determining psychological stress of a person

    公开(公告)号:US11311198B2

    公开(公告)日:2022-04-26

    申请号:US15069632

    申请日:2016-03-14

    Abstract: A system and method for determining stress level of a person in real-time have been disclosed. In one aspect, the system captures physiological data associated to the person. In one embodiment, the physiological data may be captured by using a plurality of sensors attached at wrist or ankle or neck or waist or hip of the person, for a predetermined time interval. The plurality of sensors may include a wrist watch or a wristband or a textile material. The system further pre-processes the physiological data in order to extract one or more physiological parameters. In one aspect, the pre-processing may include performing an analysis on the physiological data. The system further determines the stress level of the person upon performing the statistical analysis on the one or more physiological parameters. According to another embodiment, a method for real time determination of stress level of the person has also been provided.

    Systems and methods for atrial fibrillation (AF) and cardiac disorders detection from biological signals

    公开(公告)号:US12220262B2

    公开(公告)日:2025-02-11

    申请号:US17203578

    申请日:2021-03-16

    Abstract: Continuous monitoring of subject's cardiac system using biological signal(s) (BS) during day-to-day activities is essential for managing personal cardiac health/disorders, etc. Conventional systems/methods lack in improvising overall classification results and configured for specific device/signal say ECG or PPG and so on. Present disclosure provides systems and methods for classifying BS obtained from users, wherein BS are preprocessed to obtain filtered signals (FS). Corresponding feature extraction module is utilized for feature set extraction based on features in FS. The feature set is reduced and segmented into test and training data. Biological signal classification model(s) are generated using training data and a BCM is applied on test data to classify biological signals (BS) as one of Atrial Fibrillation (AF), a non-AF, a cardiac arrythmia disorder, or ischemia. Accelerometer features of connected device associated with the users can be obtained to detect activities which in conjunction with the BCM's output improvises above classification.

    Secure data communication
    4.
    发明授权
    Secure data communication 有权
    安全数据通信

    公开(公告)号:US09473493B2

    公开(公告)日:2016-10-18

    申请号:US14041301

    申请日:2013-09-30

    Abstract: A system and a method for secure data communication over a network are described. In one embodiment, a method comprises generating a visual flashing code containing encrypted data, wherein the visual flashing code is transmitted to a user on a user device. Further, the method comprises obtaining real time biometric data of the user from at least one biometric device connected to the user device. Furthermore, the method comprises authenticating the user based on the real time biometric data. Upon authentication, the encrypted data is decrypted at the user device based on electroencephalogram (EEG) data obtained from an EEG device, wherein the EEG data comprises brain signals indicative of brain activity of the user corresponding to the visual flashing code.

    Abstract translation: 描述了一种通过网络进行安全数据通信的系统和方法。 在一个实施例中,一种方法包括生成包含加密数据的视觉闪烁代码,其中将视觉闪烁代码发送到用户设备上的用户。 此外,该方法包括从连接到用户设备的至少一个生物测定设备获得用户的实时生物特征数据。 此外,该方法包括基于实时生物特征数据认证用户。 在认证时,基于从EEG设备获得的脑电图(EEG)数据,用户设备对加密的数据进行解密,其中EEG数据包括指示与视觉闪烁代码对应的用户的大脑活动的脑信号。

    System and method for shoulder proprioceptive analysis

    公开(公告)号:US11642046B2

    公开(公告)日:2023-05-09

    申请号:US17072304

    申请日:2020-10-16

    Abstract: This disclosure relates generally to a system and method for shoulder proprioceptive analysis of the person. The present disclosure monitors the shoulder joint motion by quantitative measure of range of motion (ROM) and kinesthesia of shoulder using a smart watch, thereby assessing the limit of active motion and the ability to passively reposition the arm in space. The present disclosure estimates the ROM, velocity, quality of joint movement, direction of hand movement using the sensor data captured by the smart watch. Further, the present disclosure provides a performance metrics of the shoulder function by comparing the shoulder motion before and after a prosthesis procedure. The present disclosure implements a rule engine-based approach classifying the shoulder/arm movement which includes flexion, extension, abduction, and adduction, internal and external rotation.

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