Icu Medical Inc.

Sensys Medical, Inc.

Zyomed Corp.

Instrumentation Metrics, Inc.

Hospira, Inc.

Other

Glt Acquisition Corp.

Nihon Kohden Digital Health Solutions, Inc.

Monarch Medical Technologies, LLC

Saensys Medical, Inc.

Timothy Lewis Ruchti

Thomas B Blank

Kevin H Hazen

Stephen L Monfre

Alexander D Lorenz

Anatoly S Belkin

Paul T Kotnik

Mohammad M Khair

Sandeep Gulati

John Hicks Dumas, Iii

George M Acosta

Steven R Wehba

John L Smith

Kunal Sur

Brian G Markey

Mutua Mattu

Marcy R Makarewicz

Suresh Thennadil

Jessica Rennert

William P Van Antwerp

William Kenneth Day

Tamas Ban

Stephen F Malin

James Ryan Henderson

Candida Arvelo

Devy Amy Lee

James A Hume

Robert Mayer

Alan Abul-Haj

Nancy G Hedlund

Harsh Dharwad

Gabriele Christensen

Meriyan Oruklu

Glenn Aaron Kees

Brian Jeffrey Wenzel

Linda J Hockersmith

Lynn D Neuhardt

Aaron P Perez

Carol Dian Martin

John Harrison Thornley

Joanne Marie Watt

Frank S Grochocki

Christopher Slawinski

Tamara L Troy

Abel Lin

Ronald Lisiecki

Ken Meissner

N Alan Abul Haj

William Patrick Burgess

Laura Santana

Suresh N Thennadil

James Matthew Welch

John Hicks Dumas

Roxanne E Abul-Haj

Paul G Hughes

Suzanne Willey

Thomas George

Timothy Stippick

N Alan Abul-Haj

William V Antwerp

Suresh N Thennadill

Joshua Andrew Ehrenberg

Gabriele Ott

Sedar R Brown

Donovan D Berry

Christopher C Briggs

Barry C Elliott

Jeffrey J Garside

Nancy H Hedlund

John H Dumas

Joanne M Watt

Carol Martin

John H Thornley

John Iii Dumas

John Hicks Dumas Iii

A method for time-synchronizing waveforms from different patient monitors that does not require devices to have high-precision synchronized clocks or to be coupled to a triggering synchronization signal generator. Comparable signals may be obtained from different devices either by placing selected sensors from the devices in the same locations, or by filtering signals from one device to obtain a signal comparable to signals from another device. Filtering may for example transform waveforms into independent components and identify a component that matches a signal from another device. The comparable signals may then be transformed into frequency variation curves, such as time intervals between peak values, to facilitate detection of the time shift between the signals. Cross correlation of the frequency variation curves may be used to locate the precise time shift between the signals. Use of frequency variation curves may be more robust than directly comparing and correlating the original signals.

Method for synchronizing biological signals from different monitoring devices

This disclosure describes systems and methods for a graphical interface including a graphical representation of medical data. The graphical interface platform may receive medical data and provide medical safety reporting capabilities including reporting of history data and real-time visual monitoring data. The graphical interface platform may be configured to identify potential problems and corrections to medical devices in operation while a reporting cycle is underway through visual representation of performance metrics.

Systems and methods for a graphical interface including a graphical representation of medical data

A system and method to configure a rule set used in connection with a medical monitoring system for monitoring patients and patient care equipment, especially medication delivery pumps, based on a variety of conditions and parameters associated with monitored biometric information and equipment information and for providing user-defined responses to those conditions and parameters.

System and method for configuring a rule set for medical event management and responses

A system that synchronizes waveforms received over a network from one or more devices, such as medical devices. Because of network delays or losses, waveforms can arrive at varying rates and times. Precise post-synchronization of the received data, to within a few milliseconds, is needed for accurate analysis. Applications include automatic classification of waveforms, such as detection of myocardial infraction from heart monitor waveforms. Synchronization uses sequence numbers assigned by each device, but must also account for sequence number wraparounds. Waveforms may also be synchronized across devices, by calculating the bias between within-device synchronized times and a common time source or common disturbance. Waveform data may also be stored data in a database or data warehouse; embodiments may index the data using a key with a date-time prefix and a hash code suffix, to support distributed indexing while reducing the chance of hash collisions to a very small probability.

Waveform synchronization system for data received from a network

To detect air in a fluid delivery line of an infusion system, infusion fluid is pumped through a fluid delivery line adjacent to at least one sensor. A signal is transmitted and received using the at least one sensor into and from the fluid delivery line. The at least one sensor is operated, using at least one processor, at a modified frequency which is different than a resonant frequency of the at least one sensor to reduce an amplitude of an output of the signal transmitted from the at least one sensor to a level which is lower than a saturation level of the analog-to-digital converter to avoid over-saturating the analog-to-digital converter. The signal received by the at least one sensor is converted from analog to digital using an analog-to-digital converter. The at least one processor determines whether air is in the fluid delivery line based on the converted digital signal.

Infusion system and method of use which prevents over-saturation of an analog-to-digital converter

An infusion system for being operatively connected to a fluid delivery line and to an infusion container includes a pump, a plurality of different types of sensors connected to the pump or the fluid delivery line, at least one processor, and a memory. The plurality of different types of sensors are configured to indicate whether air is in the fluid delivery line. The memory includes programming code for execution by the at least one processor. The programming code is configured to, based on measurements taken by the plurality of different types of sensors, determine: whether there is air in the fluid delivery line; whether there is a partial occlusion or a total occlusion in the fluid delivery line; or a percentage of the air present in the fluid delivery line or the probability of the air being in the fluid delivery line.

Multi-sensor infusion system for detecting air or an occlusion in the infusion system

A system and method for monitoring and delivering medication to a patient. The system includes a controller that has a control algorithm and a closed loop control that monitors the control algorithm. A sensor is in communication with the controller and monitors a medical condition. A rule based application in the controller receives data from the sensor and the closed loop control and compares the data to predetermined medical information to determine the risk of automation of therapy to the patient. A system monitor is also in communication with the controller to monitor system, remote system, and network activity and conditions. The controller then provides a predetermined risk threshold where below the predetermined risk threshold automated closed loop medication therapy is provided. If the predetermined risk threshold is met or exceeded, automated therapy adjustments may not occur and user/clinician intervention is requested.

System for monitoring and delivering medication to a patient and method of using the same to minimize the risks associated with automated therapy

Various systems and methods for detecting air in a chamber of an infusion system are disclosed. In one embodiment, a determination is made that air is contained in the chamber on the basis of a change in the average force exerted against the plunger utilizing a derivative spike for event detection and a systematic reduction in the average force to confirm the nature of the change. In another embodiment, a determination is made that the chamber contains air when a difference between the current force profile and a baseline force profile crosses a threshold. In an additional embodiment, a force profile is classified as being an air force profile or a liquid force profile based on extracted features of the force profile.

Air detection system and method for detecting air in a pump of an infusion system

An infusion pump automation system and method includes an infusion pump, an infusion pump and a remote processor. The remote processor is remote to the infusion pump and includes a controller interface and a controller, such that the controller bidirectionally communicates with the infusion pump, determines a current infusion state of the infusion pump and a current infusion pump user interface state and accepts a command to change the infusion state of the infusion pump from an external server. The controller determines if the command is consistent with the current infusion state of the infusion pump and the current infusion pump user interface state, executes the command if the command is able to be successfully executed, and confirms that the command is successfully executed.

Infusion pump automation system and method

Growing community of inventors

Gurnee, IL, United States of America

Timothy Lewis Ruchti