Aspect Medical Systems, Inc.

Covidien LP

Nellcor Puritan Bennett Incorporated

Jeffrey C Sigl

Scott D Greenwald

Nassib G Chamoun

Philip H Devlin

Charles P Smith

Systems and methods for assessing a patient's risk of poor outcome in real-time are provided. The real-time risk may be used by a physician to guide decision making during a procedure.

System and method for integrating clinical information to provide real-time alerts for improving patient outcomes

The present invention is a system and method of deriving and computing features and indices that predict the likelihood of psychological and neurological adverse events such as suicidal thoughts and/or actions. The method of the present invention further predicts the likelihood of suicidal thoughts and/or actions prior to and or during treatment for psychological disease. To obtain such features and indices, power spectrum and time domain values are derived from biopotential signals acquired from the subject being tested. The system and method identify people who are likely to experience changing, especially worsening, symptoms of psychological and neurological adverse events such as suicidal thoughts or actions and who therefore may be at risk (e.g. suicide).

System and method for prediction of adverse events during treatment of psychological and neurological disorders

The present invention is a system and method that produces features and indices that indicate the presence or absence of a disease or condition, or of the progression of a disease or condition. The system and method of the present invention also produce features and indices that predict responsiveness to medication from a premedication baseline. The system and method of the present invention further incorporates a testing methodology to improve the performance characteristics of the features or indices. To obtain such features and indices, time domain, power spectrum, bispectrum and higher order spectrum values are derived from biopotential signals taken from the subject being tested.

System and method of assessment of neurological conditions using EEG

Disclosed is a system and method to derive a diagnostic index indicative of a selected cerebral phenomena which obtains 19 unipolar EEG signals from regions of interest on both the left and right hemispheres of a subject's brain. The system uses high-gain, low-noise amplifiers to maximize the dynamic range for low energy wave components of the signals. Band-pass filtering is used to reduce noise and to avoid aliasing. The system applies commonly used digital signal processing (DSP) techniques to digitize, to low-pass filter (100 Hz), and to decimate the signals. Power spectral, bispectral, and higher-order spectral processing is then performed. In a preferred embodiment, the system divides the most recent 63 seconds of digitized EEG data from each lead into 60 4-second intervals, each with 3 seconds of overlap with the previous interval. For a selected set of derived leads, the system produces auto power spectrum, autobispectrum, and auto higher-order spectrum variables, by using either a Fast Fourier Transform (FFT) based approach or a parametric approach. Any pair of leads can be combined to compute cross power spectrum, cross bispectrum, and cross higher-order spectrum variables. The spectral values are separated into bins and a value representative of the bin is selected or computed and then each value is multiplied by a predetermined coefficient. The resulting products are summed to arrive at the diagnostic index.

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Medway, MA, United States of America

Jeffrey C Sigl