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    Upper limb multi-joint impedance measurement method and apparatus using the same
    1.
    发明授权
    Upper limb multi-joint impedance measurement method and apparatus using the same 有权

    公开(公告)号：US12127841B2

    公开(公告)日：2024-10-29

    申请号：US15716536

    申请日：2017-09-27

    Applicant: Ulsan National Institute of Science and Technology

    Inventor： Sang Hoon Kang ,  Sung Shin Kim ,  Hyunah Kang

    IPC: A61B5/24 ,  A61B5/00 ,  A61B5/01 ,  A61B5/053 ,  A61B5/11 ,  A61B5/389

    CPC classification number: A61B5/24 ,  A61B5/053 ,  A61B5/1107 ,  A61B5/6824 ,  A61B5/01 ,  A61B5/1124 ,  A61B5/389 ,  A61B5/7257

    Abstract: The present disclosure relates to an upper limb multi-joint impedance measurement method and an apparatus using the same. An upper limb multi-joint impedance measurement apparatus includes an upper limb end connector connected to an end of an upper limb of a subject, a driver configured to drive the upper limb end connector so that the upper limb end connector applies perturbations to the end of the upper limb of the subject, a measurement controller configured to provide the driver with a control signal for the perturbations, a force sensor configured to detect a magnitude of a perturbation force applied to the end of the upper limb of the subject by the upper limb end connector, a position sensor configured to detect a variation of a position of the upper limb end connector according to the applied perturbations, an impedance calculator configured to calculate a mechanical impedance of the upper limb of the subject by using force data and position data indicating the detected magnitude of the force and the detected variation of the position, and an impedance output unit configured to output an output signal indicating a value of the calculated mechanical impedance.

    METHOD AND SYSTEM FOR NEUROMODULATION
    4.
    发明公开
    METHOD AND SYSTEM FOR NEUROMODULATION 审中-公开

    公开(公告)号：US20240321430A1

    公开(公告)日：2024-09-26

    申请号：US18638043

    申请日：2024-04-17

    Applicant: xSensa Labs

    Inventor： Natasha Kovacevic

    IPC: G16H20/70 ,  A61B5/00 ,  A61B5/16 ,  A61B5/246 ,  A61B5/374

    CPC classification number: G16H20/70 ,  A61B5/0075 ,  A61B5/165 ,  A61B5/246 ,  A61B5/374 ,  A61B5/7257

    Abstract: A method and system for neuromodulation therapy is described. One or more psychophysiological parameters based on an electrical signal of a user's brain activity are determined and used to generate a neuromodulation marker using a neuromodulation recipe. The neuromodulation marker may be determined using statistical estimates of the psychophysiological parameters in relation to a reference distribution. Feedback is then provided to the user based on the neuromodulation marker. Weighting parameters may be used to vary the neuromodulation recipe and personalize the neuromodulation therapy in response to performance or user input.

    SBL-based SSR brain source localization method
    6.
    发明授权
    SBL-based SSR brain source localization method 有权

    公开(公告)号：US12089965B2

    公开(公告)日：2024-09-17

    申请号：US17285087

    申请日：2020-07-30

    Applicant: SOOCHOW UNIVERSITY

    Inventor： Nan Hu ,  Mingwen Qu

    IPC: A61B5/00 ,  A61B5/291 ,  A61B5/374 ,  A61B5/38 ,  G06N7/01 ,  G06N20/00 ,  G16H30/20

    CPC classification number: A61B5/7267 ,  A61B5/374 ,  A61B5/38 ,  A61B5/7203 ,  A61B5/7257 ,  G06N7/01 ,  G06N20/00 ,  G16H30/20 ,  A61B5/291

    Abstract: The invention discloses a sparse Bayesian learning (SBL)-based SSR brain source localization method. An SSR record is divided into multiple data segments, frequency-domain information of the data segments is extracted through FFT, and a data matrix is constructed. An automatic iteration stop condition and initial values of a sparse support vector and a spontaneous electroencephalography (EEG)-electrical noise joint power vector are set. The posteriori mean and covariance of SSR components are iteratively estimated and the sparse support vector and the spontaneous EEG-electrical noise joint power vector are updated accordingly. When the iteration ends, the ultimate sparse support vector is used to give a source localization result. An SSR source localization problem is modeled in the frequency domain, the joint sparsity of signals in multiple data segments is involved, and a brain source localization method applicable to various SSRs is given in an SBL framework.

    Monitoring bone characteristics
    7.
    发明授权
    Monitoring bone characteristics 有权

    公开(公告)号：US12082941B2

    公开(公告)日：2024-09-10

    申请号：US17589828

    申请日：2022-01-31

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Joep Van Berkel

    IPC: A61B5/00 ,  A61B8/08 ,  A61C17/22 ,  A61C19/04

    CPC classification number: A61B5/4547 ,  A61B5/0022 ,  A61B5/0075 ,  A61B5/0082 ,  A61B5/0095 ,  A61B5/4509 ,  A61B5/6898 ,  A61B5/7257 ,  A61B5/7264 ,  A61B5/7275 ,  A61B8/0875 ,  A61C17/225 ,  A61C19/04

    Abstract: The present disclosure is directed to methods and apparatus for monitoring bone characteristics for various conditions such as osteoporosis and/or periodontitis. In various embodiments, a dental hygiene appliance (100) may include: a handle (102) adapted to be held by a user; a tool (106) secured to the handle to perform a dental hygiene-related task; emitter(s) (114A, 116, 360A) mounted on the dental hygiene appliance to emit wave(s) (252, 362) towards a mandible (250, 350) of the user; sensor(s) (114B, 116, 360B) mounted on the dental hygiene appliance to detect wave(s) (254, 364) propagating away from the mandible, wherein the detected wave(s) originate from or are caused by the emitted wave(s); and a controller (108) communicatively coupled with the emitter(s) and the sensor(s). The controller may: receive, from the sensor(s), signal(s) indicative of the detected waves; and determine, based on the signal(s), bone characteristic(s) of the user.

    Neural oscillation monitoring system
    8.
    发明授权
    Neural oscillation monitoring system 有权

    公开(公告)号：US12076166B2

    公开(公告)日：2024-09-03

    申请号：US15257019

    申请日：2016-09-06

    Applicant: Newton Howard

    Inventor： Newton Howard

    IPC: A61B5/00 ,  A61B5/16 ,  A61B5/316 ,  A61B5/369

    CPC classification number: A61B5/7267 ,  A61B5/316 ,  A61B5/369 ,  A61B5/165 ,  A61B5/4824 ,  A61B5/7257 ,  A61B5/726

    Abstract: Embodiments of the present invention may provide automated techniques for signal analysis that may continuously provide up-to-date results that link EEG and behaviors that are important for daily activities. Such techniques may provide automation, objectivity, real-time monitoring and portability. In an embodiment of the present invention, a computer-implemented method for monitoring neural activity may comprise receiving data representing at least one signal representing neural activity of a test subject, pre-processing the received data by performing at least one of band-pass filtering, artifact removal, identifying common spatial patterns, and temporally segmentation, processing the pre-processed data by performing at least one of time domain processing, frequency domain processing, and time-frequency domain processing, generating a machine learning model using the processed data as a training dataset, and outputting a characterization of the neural activity based on the machine learning model.

    Method and system for brain attack triage (BAT)
    9.
    发明授权
    Method and system for brain attack triage (BAT) 有权

    公开(公告)号：US12076106B2

    公开(公告)日：2024-09-03

    申请号：US17202028

    申请日：2021-03-15

    Applicant: NaviSalute, LLC

    Inventor： Howard J Federoff ,  Ophir Frieder ,  Massimo S. Fiandaca ,  Ramesh Jain

    IPC: A61B5/00 ,  A61B5/374 ,  G16H40/67 ,  G16H50/20 ,  G16H50/30 ,  G16H50/70 ,  G16H80/00

    CPC classification number: A61B5/0022 ,  A61B5/7257 ,  A61B5/7275 ,  A61B5/7282 ,  A61B5/0024 ,  A61B5/374 ,  A61B5/7264 ,  G16H80/00

    Abstract: Embodiments herein relate to biosensors and other elements combined in real-time for health applications that acquire health data of an individual from one or more data streams by a first element and integrate these data through a second element that is configured to predict and/or recognize an interruptive health event and then via one or more successive elements alert one or more providers of a possible interruptive health event, enable the providers to propose one or more effective interventions, communicate directly with the individual and providers and/or caregivers, and/or provide confirmation in the event that effective interventions were made. Embodiments also relate to predicting and recognizing brain attack in real-time by acquiring and integrating health data from one or more data streams, interfacing with one or more providers so that they can propose and/or effect one or more effective interventions, and communicating with an affected individual, providers, and/or caregivers.

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