Computer Implemented Classification Tool And Method For Classification Of Microelectrode Recordings Taken During A Deep Brain Stimulation

    公开(公告)号:US20240289592A1

    公开(公告)日:2024-08-29

    申请号:US18412819

    申请日:2024-01-15

    CPC classification number: G06N3/0464 A61B5/383

    Abstract: A method of creating a computer implemented classification tool for classification of microelectrode recordings taken during a deep brain stimulation using deep residual neural network with attention comprising steps collecting a data set of recordings taken during a deep brain stimulation; splitting recordings into overlapping time chunks, and converting time chunks into spectrograms; dividing data set into a training set, a validation set, and a test set putting each spectrogram into a deep neural network of ResNet architecture augmented with a self-attention layer added after each of ResNet layers, with a head layer comprising a single 2D convolutional layer followed by batch normalization and ReLU activation function wherein the network is trained to return zero for time chunks taken from recordings made outside of the STN region of a brain and to return one for time chunks taken form recordings made within the STN region of a brain, fine tuning the network with the validation set, cross checking the network with the test set.

    Modular NeuroNet-VII Intraoperative Neurophysiological Monitoring System

    公开(公告)号:US20230329626A1

    公开(公告)日:2023-10-19

    申请号:US17901376

    申请日:2022-09-01

    CPC classification number: A61B5/383 A61B5/378 A61B5/38 A61B90/20 A61B50/13

    Abstract: The invention provides an advanced, modular, intraoperative neurophysiological monitoring (IONM) system, referred to as a “NeuroNet-VII” System, which is the first IONM system designed with a USB hub architecture comprising serially-connected functional “pods which provides multi-modality simultaneous data acquisition which supports all data types useful in operating rooms, diagnostic laboratories, intensive care units, and epilepsy monitoring units. The unique pod architecture makes the IONM system highly modular compared to current systems which typically place components in a limited number of centralized enclosures. The modular architecture of the invention also provides for real-time collection of data so that information may be communicated with a remotely-located physician; a user needs only to purchase pods that are needed; repair of a single pod may easily be replaced without disabling the entire system; and advances in hardware designs may be implemented for a specific pod without requiring replacement of the entire system.

    IMPROVING COGNITIVE FUNCTION
    5.
    发明公开

    公开(公告)号:US20240091531A1

    公开(公告)日:2024-03-21

    申请号:US18254153

    申请日:2021-11-23

    Abstract: A system for improving cognitive function is disclosed. The system comprises a non-invasive brain stimulation device (150); a human computer interface; and a computer (101) configured to control the non-invasive brain stimulation device (150) and the human computer interface. The computer (101) controls the brain stimulation device (150) and the human computer interface to assess a subject's baseline cognitive function by interaction with the subject using the human computer interface. If the subject's baseline cognitive function is impaired, the computer (101) uses the human computer interface to provide the subject with a strategy for improving performance in a cognitive function test and stimulates the subjects brain with the non-invasive brain stimulation device (150) while training the subjects cognitive function.

    SYSTEMS AND METHODS FOR GENERATING AND USING RESPONSE MAPS FOR ELECTRICAL STIMULATION

    公开(公告)号:US20230181090A1

    公开(公告)日:2023-06-15

    申请号:US18075835

    申请日:2022-12-06

    CPC classification number: A61B5/383 A61B5/384 G16H30/40

    Abstract: A method or system for generating a clinical effects map for electrical stimulation includes receiving stimulation parameters and at least one clinical response for each of a plurality of stimulation instances; for each of the stimulation instances, determining a radius of a stimulation field according to the stimulation parameters for the stimulation instance; generating the clinical effects map using the at least one clinical response and the stimulation parameters for each of the stimulation instances, wherein, for each of the stimulation instances, the at least one clinical response for the stimulation instance is assigned to the radius of the stimulation field determined for the stimulation instance; and displaying the clinical effects map.

    Modular NeuroNet-VII intraoperative neurophysiological monitoring system

    公开(公告)号:US12048551B2

    公开(公告)日:2024-07-30

    申请号:US17901376

    申请日:2022-09-01

    CPC classification number: A61B5/383 A61B5/378 A61B5/38 A61B50/13 A61B90/20

    Abstract: The invention provides an advanced, modular, intraoperative neurophysiological monitoring (IONM) system, referred to as a “NeuroNet-VII” System, which is the first IONM system designed with a USB hub architecture comprising serially-connected functional “pods which provides multi-modality simultaneous data acquisition which supports all data types useful in operating rooms, diagnostic laboratories, intensive care units, and epilepsy monitoring units. The unique pod architecture makes the IONM system highly modular compared to current systems which typically place components in a limited number of centralized enclosures. The modular architecture of the invention also provides for real-time collection of data so that information may be communicated with a remotely-located physician; a user needs only to purchase pods that are needed; repair of a single pod may easily be replaced without disabling the entire system; and advances in hardware designs may be implemented for a specific pod without requiring replacement of the entire system.

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