Yale University

University of North Carolina at Charlotte

Itn Energy Systems, Inc.

Alva Health Inc.

Other

International Business Machines Corporation

University of Connecticut

Hitten P Zaveri

Dennis D Spencer

Bruce Lanning

Bharat S Joshi

Gregory J Nuebel

James A Nolan

Ronald R Coifman

Kevin N Sheth

Denis Filatov

Hariklia Deligianni

Roy Rongqing Yu

Emily R Kinser

Mark T Reed

David A Putz

Mohan S Misra

David M Binkley

Themis Kyriakides

Ipsita Acharya

Mengdi Bao

Davina Jaiswal

Kazunori Hoshino

Ariane Garrett

Ryan Grant

Garrett Soler

Michael Diluna

Jason Gerrard

The present invention provides devices comprising multimodal depth electrodes for real-time quantification of chemistry and electrophysiology of the body. The devices are useful in several applications, including monitoring primary and secondary brain injury. The multimodal depth electrodes electrically transduce signals from biological parameters of interest, including EEG, temperature, pressure, oxygen level, blood flow, and chemistry.

Multiplexed implantable sensor probe

In an example system, multi-sensor motion data that reflects the motion of a user over a period of time is received as recorded by a plurality of motion sensors on wearable devices, specific changes are determined in the data by, firstly, quantifying it using a two-dimensional data transform; secondly, extracting an anomalous area; and thirdly, calculating a number of the anomaly's properties, and the results are input into a machine learning model to detect that the user fell. The machine learning model processes the anomaly's properties and evaluates the current state of the user's activity by classifying the properties against a state space previously calculated by analyzing historical activities of daily living. Depending on a two-dimensional transform implemented, the machine learning model detects when the user falls, as well as potentially allows predicting that the user will suffer a fall in advance of the actual event, aiming at solving the stroke prediction problem.

Detecting falls with multiple wearable motion sensors

A real-time automated method to diagnose and/or detect stroke and engage the patient, care-takers, emergency medical system and stroke neurologists in the management of this condition includes the steps of continuously measuring natural limb activity, conveying the measurements to a cloud based real-time data processing system, identifying patient specific alert conditions, and determining solutions for acting upon needs of the patient. The system by which the method is implemented includes at least one body worn sensor continuously measuring natural limb activity and a patient worn data transmission device conveying the measurements to a cloud based real-time data processing system that identities patient specific alert conditions and determines solutions for acting upon needs of the patient.

System and method for diagnosing and notification regarding the onset of a stroke

A structure for monitoring and stimulation includes an external power supply unit. The structure also includes an internal hub communicatively coupled to the external power supply unit. The structure further includes a plurality of sensor modules communicatively coupled to the internal hub by a plurality of flexible interconnects. The plurality of sensor modules include three-dimensional (3D) comb sensor devices.

Three-dimensional silicon-based comb probe with optimized biocompatible dimensions for neural sensing and stimulation

The present disclosure provides a fluidic device including (a) a first channel including a first inlet and a first outlet, (b) a second channel including a second inlet and a second outlet, wherein the second inlet of the second channel is in fluid communication with the first outlet of the first channel, and (c) a sensor positioned between the first outlet and the second inlet, wherein the sensor includes a sensor configured to deflect in response to a flow between the first channel and the second channel.

Flow sensor for cerebral fluidic device

A real-time automated method to diagnose and/or detect stroke and engage the patient, care-takers, emergency medical system and stroke neurologists in the management of this condition includes the steps of continuously measuring natural limb activity, conveying the measurements to a cloud based real-time data processing system, identifying patient specific alert conditions, and determining solutions for acting upon needs of the patient. The system by which the method is implemented includes at least one body worn sensor continuously measuring natural limb activity and a patient worn data transmission device conveying the measurements to a cloud based real-time data processing system that identifies patient specific alert conditions and determines solutions for acting upon needs of the patient.

A clinical grid electrode system for seizure control through local cooling, mapping brain function and me provision of reversible functional ablation. The system includes a modular, scalable, cooling and sensing array composed of a plurality of cooling sensing elements. The system also includes a control system to which die cooling and sensing array is coupled for providing for control and monitoring of die cooling sensing elements making up the cooling and sensing array.

Brain cooling system

A wireless system for brain monitoring/mapping of neurological-disorder patients includes a plurality of electrodes each configured for surface abutment of brain tissue and main circuitry for placement outside a body of a patient and configured to transmit power at radio frequencies and send and receive data using infrared energy. Remote circuitry is provided for subcutaneous implantation in a head of the patient. The remote circuitry is connected to the plurality of electrodes and includes a multiplexer sampling signals from the plurality of electrodes. The multiplexer outputs electrode signals to an amplifier and A/D converter for transmission to the main circuitry. The remote circuitry is configured to (a) receive transmitted power at radio frequencies from the main circuitry, (b) capture and digitize full-bandwidth EEG signals from each of the electrodes, and (c) send data to and receive data from the main circuitry using infrared energy.

Wireless system for epilepsy monitoring and measurement

A multielectrode array with fault-tolerance for use in conjunction with a brain implantable device includes a sensor grid composed of a plurality of sensors, the plurality of sensors including primary sensors and spare sensors. The multielectrode array also includes signal processing circuitry associated with the plurality of sensors and a control system associated with the sensor grid for replacing faulty primary sensors with spare sensors.

Fault-tolerant multielectrode array for brain implantable device

A wireless system for monitoring a patient's brain tissue including (1) a plurality of electrodes abutting brain tissue, (2) main circuitry outside the patient's body to transmit power at radio frequencies and send/receive data using infrared energy, and (3) subcutaneously-implanted remote circuitry connected to the electrodes and configured to (a) receive transmitted RF power, (b) capture and digitize EEG signals from the electrodes, and (c) send/receive data to/from the main circuitry using IR energy, including sending digitized EEG signals from each electrode to capture the full bandwidth of each EEG signal. The system preferably includes circuitry to measure the electrical impedance of each electrode for real-time monitoring of the condition of the electrode/tissue interfaces to enhance interpretation of captured EEG signals.

Growing community of inventors

New Haven, CT, United States of America

Hitten P Zaveri