Covidien LP

Nellcor Puritan Bennett Ireland

Nellcor Puritan Bennett Incorporated

Other

Cardiodigital Limited

Medtronic, Inc.

Nelleor Puritan Bennett Ireland

Neilcor Puritan Bennett Ireland

Nellcor Puritan Bennet Ireland

Addison, Paul

Montgomery, Dean

Watson, James

Paul Stanley Addison

James Nicholas Watson

Dean Montgomery

Dominique Jacquel

James Ochs

Scott McGonigle

Philip C Smit

Andre Antunes

Edward M McKenna

Rakesh Sethi

Bo Chen

Youzhi Li

David Ming Hui Foo

David Foo

Braddon M Van Slyke

Keith Manning

André Antunes

David Clifton

James Dripps

Paul A Edney

Clark Raymond Baker, Jr

Peter M Galen

Keith Batchelder

Robert Stoughton

Daniel Wayne Bartlett

Peter Doyle

Mark Su

Eric Morland

Michael Mestek

Rui Wang

Anthony P Addison

Peter Nicholas Braido

Shantanu Sarkar

Zhongping C Yang

Ron Kadlec

Randal C Schulhauser

Daniel M Lisogurski

Nicolas Coulombe

Niranjan Maharajh

Mark Kolnsberg

Corinne H Johnson

Ronald Kadlec

George Keith Manning

Binwel Weng

Jimmy Dripps

Andrew M Cassidy

Michael Addison

Graeme A Lyon

David J Giarracco

Clark R Baker

Joseph D Brannan

Max L Balter

Andrew Cassidy

Scott Mcgonigle

Edward Mckenna

James Wolstencroft

James Watson

An example autoregulation monitoring system includes processing circuitry configured to receive a blood pressure signal indicative of a blood pressure of a patient; determine a derivative of at least a portion of the blood pressure signal; determine, based on the derivative, a characteristic arterial pressure (CAP) value; determine, based on the CAP value, an autoregulation value of the patient; and output a signal indicative of the autoregulation value of the patient.

Determining arterial pressures

System and methods for non-contact video-based patient monitoring are described. The systems and methods may include locating one or more condensation removal elements on a transparent enclosure for removal of condensation that may be obstructing the view between a video camera used to monitor a patient and the patient. The systems and methods may further include steps for monitoring the quality of the video stream and automatically initiating the condensation removal elements when a deterioration in the quality of the video stream is detected.

Systems and methods for improved non-contact patient monitoring of incubated neonates

Novel tools and techniques are provided for implementing intelligent assistance ('IA') or extended intelligence (“EI”) ecosystem for pulmonary procedures. In various embodiments, a computing system might analyze received one or more first layer input data (i.e., room content-based data) and received one or more second layer input data (i.e., patient and/or tool-based data), and might generate one or more recommendations for guiding a medical professional in guiding a surgical device(s) toward and within a lung of the patient to perform a pulmonary procedure, based at least in part on the analysis, the generated one or more recommendations comprising 3D or 4D mapped guides toward, in, and around the lung of the patient. The computing system might then generate one or more XR images, based at least in part on the generated one or more recommendations, and might present the generated one or more XR images using a UX device.

Extended intelligence for pulmonary procedures

A monitor configured to monitor autoregulation includes a memory encoding one or more processor-executable routines and a processor configured to access and execute the one or more routines encoded by the memory. When executed, the routines cause the processor to receive one or more physiological signals from a patient, determine a measure indicative of an autoregulation status of the patient based on the one or more physiological signals, generate an autoregulation alarm indicative of an impaired autoregulation status when the measure exceeds a predetermined threshold for more than a predetermined period of time.

System and method for identifying blood pressure zones during autoregulation monitoring

Methods and systems for non-contact monitoring of a patient to determine respiratory parameters such as respiration rate, tidal volume, minute volume, oxygen saturation, and other parameters such as motion or activity. The systems and methods receive a first, video signal from the patient and from that extract a distance or depth signal from the relevant area to calculate the parameter(s) from the depth signal. The systems and methods also receive a second, light intensity signal from an IR feature projected onto the patient, and from that calculate the parameter(s) from the light intensity signal. The parameter(s) from the two signals can be combined or compared to provide a qualified output parameter.

Systems and methods for non-contact respiratory monitoring

System and methods for non-contact monitoring in vehicles are described. The systems and methods may use depth sensing cameras as part of the non-contact monitoring system. In some embodiments, depth data from at least one depth sensing device that has a field of view of at least part of the interior of the vehicle is received, wherein the depth data represents depth information as a function of position across the field of view. The depth data is then processed to obtain further information related to the occupant within the vehicle.

Non-contact depth sensing monitoring in vehicles

In some examples, a method includes receiving a signal indicative of a blood pressure of a patient and identifying at least one first portion of the signal comprising a first characteristic of the signal exceeding a first threshold. The method also includes identifying at least one first portion of the signal comprising a second characteristic of the signal exceeding a second threshold, the first characteristic being different than the second characteristic. The method further includes determining a filtered signal indicative of the blood pressure of the patient by excluding the at least one first portion and the at least one second portion from the signal. The method includes determining a set of mean arterial pressure values based on the filtered signal and determining an autoregulation status of the patient based on the set of mean arterial pressure values.

Blood pressure and autoregulation monitoring

Described herein are various embodiments of an informative display that may be used in conjunction with non-contact patient monitoring systems and methods. The informative display may include one or more patient data images providing historical and real time data relating the patient being monitored by the non-contact patient monitoring system. The patient data images may be configured to display visualizations of various patient events, such as low flow, apnea, and/or patient movement.

Informative display for non-contact patient monitoring

The present invention relates to the field of medical monitoring, and in particular non-contact video monitoring to measure tidal volume of a patient. Systems, methods, and computer readable media are described for determining a region of interest of a patient and monitoring that region of interest to determine tidal volume of the patient. This may be accomplished using a depth sensing camera to monitor a patient and determine how their chest and/or other body parts are moving as the patient breathes. This sensing of movement can be used to determine the tidal volume measurement.

Systems and methods for video-based non-contact tidal volume monitoring

The present invention relates to the field of medical monitoring, and in particular non-contact monitoring and communication with other medical monitoring devices. Systems and methods are described for receiving a video signal of a medical monitoring device that is outputting a light signal, identifying the light signal emitted by the medical monitoring device from the video signal, decoding information from the light signal, and determining a communication from the decoded information related to a patient being monitored or the medical monitoring device itself.

Systems and methods for video-based monitoring of a patient

Implementations described herein disclose a method of classifying oxygen level desaturation events. In one implementation, the method includes receiving input signal sequences, the input signals indicative of a physiological condition of a patient, generating an input sequence of oxygen saturation levels based on the input signal sequence, comparing the input sequence of oxygen saturation levels to a desaturation alarm threshold to determine a desaturation event, generating an input feature matrix based on at least one of the input signal sequences and the input sequence of oxygen saturation levels, and classifying based on the input feature matrix, using a neural network, the desaturation event being a severe desaturation event (SDE) or a non-severe desaturation event (non-SDE).

Desaturation severity prediction and alarm management

A system for monitoring autoregulation may include processing circuitry configured to receive a blood pressure signal indicative of an acquisition blood pressure of a patient at an acquisition site and an oxygen saturation signal indicative of an oxygen saturation of the patient. The processing circuitry may determine a cerebral autoregulation status value based on the blood pressure signal and the oxygen saturation signal. The processing circuitry may determine a non-cerebral autoregulation status value based on the cerebral autoregulation status value and an adjustment value. The processing circuitry provide to an output device a signal indicative of the non-cerebral autoregulation status value and a signal indicative of the cerebral autoregulation status value to enable a clinician to monitor the autoregulation status of the patient.

Non-cerebral organ autoregulation status determination

A method for monitoring autoregulation includes, using a processor, using a processor to execute one or more routines on a memory. The one or more routines include receiving one or more physiological signals from a patient, determining a correlation-based measure indicative of the patient's autoregulation based on the one or more physiological signals, and generating an autoregulation profile of the patient based on autoregulation index values of the correlation-based measure. The autoregulation profile includes the autoregulation index values sorted into bins corresponding to different blood pressure ranges. The one or more routines also include designating a blood pressure range encompassing one or more of the bins as a blood pressure safe zone indicative of intact regulation and providing a signal to a display to display the autoregulation profile and a first indicator of the blood pressure safe zone.

System and method for providing blood pressure safe zone indication during autoregulation monitoring

A combined physiological sensor and methods for detecting one or more physiological characteristics of a subject are provided. The combined sensor (e.g., a forehead sensor) may be used to detect and/or calculate at least one of a pulse blood oxygen saturation level, a regional blood oxygen saturation level, a respiration rate, blood pressure, an electrical physiological signal (EPS), a pulse transit time (PTT), body temperature associated with the subject, a depth of consciousness (DOC) measurement, any other suitable physiological parameter, and any suitable combination thereof. The combined sensor may include a variety of individual sensors, such as electrodes, optical detectors, optical emitters, temperature sensors, and/or other suitable sensors. The sensors may be advantageously positioned in accordance with a number of different geometries. The combined sensor may also be coupled to a monitoring device, which may receive and/or process one or more output signals from the individual sensors to display information about the medical condition of the subject. In addition, several techniques may be employed to prevent or limit interference between the individual sensors and their associated input and/or output signals.

Combined physiological sensor systems and methods

The present invention relates to the field of medical monitoring, and in particular non-contact, video-based monitoring of pulse rate, respiration rate, motion, and oxygen saturation. Systems and methods are described for capturing images of a patient, producing intensity signals from the images, filtering those signals to focus on a physiologic component, and measuring a vital sign from the filtered signals.

System and methods for video-based monitoring of vital signs

Growing community of inventors

Edinburgh, United Kingdom

Paul Stanley Addison