Abstract:
This document discusses, among other things, systems and methods to determine an indication of discharge readiness for a patient using received physiologic information of the patient corresponding to hospitalization of the patient and received physiologic information of the patient corresponding to a time after hospitalization.
Abstract:
The exemplary systems and methods may be configured for use in the determination of ectopic beat-compensated electrical heterogeneity information. Electrical activity can be monitored by a plurality of external electrodes. Ectopic beat information can be detected. Ectopic beat-compensated electrical heterogeneity information can be generated based on the monitored electrical activity and the detected ectopic beat information.
Abstract:
A system, a computer readable storage medium (120), and a method (10 or 20) for analyzing electroencephalogram signals can include a plurality of sensors (145) configured to contact a skull and capture the electroencephalogram signals, one or more computer memory units for storing computer instructions and data, and one or more processors (102) configured to perform the operations of clustering (12, 25A or 25C) the electroencephalogram signals using at least stored objective data and added subjective data including patient profile data (24 and/ or 23) to provide clustered data results and predicting (14 or 26) one or more among a medical diagnosis, assessment, plan, necessary forms, or recommendations for follow up based on the clustered data results.
Abstract:
A medical device is utilized to monitor physiological parameters of a patient and capture segments of the monitored physiological parameters. The medical device includes circuitry configured to monitor one or more physiological parameters associated with the patient and an analysis module that includes a buffer and a processor. The buffer stores monitored physiological parameters and the processor analyzes the monitored physiological parameters and triggers capture of segments from the buffer in response to a triggering criteria being satisfied. The analysis module selects a pre-trigger duration based at least in part on the triggering criteria.
Abstract:
Systems and methods for tracking EEG data and providing enhanced seizure detection and prediction are disclosed. The systems and methods use input sensors for receiving and collecting data from a plurality of EEG channels in association with a subject and processing said data to calculate and average Lyapunov exponents for a composite EEG data set. The systems and methods convert the average Lyapunov exponents into graphical representations that are displayed against a time axis. The graphical output adjusts in real-time according to the input data obtained from EEG channels. The systems and methods utilize pattern recognition to output alarms based upon input data and recommend diagnoses related to seizures.
Abstract:
Provided are methods of assessing and/or training cognitive fitness. Aspects of the instant methods generally relate to identifying and observing neural activity that underlies an event occurring in response to the stimulus or sequence of stimuli of a cognitive task performed by a subject. As such, the instant methods generally include presenting a cognitive task to a subject that includes a stimulus or sequence of stimuli, and monitoring the neural activity of the subject during performance of the cognitive task. Monitoring of such neural activity may be used, at least in part, to determine a neural performance level of a subject which may, in turn, be used in various ways including e.g., as an assessment of cognitive fitness, to tailor a subsequently presented cognitive task to train the cognitive fitness of the subject, etc. Systems and computer readable media for practicing the methods of the present disclosure are also provided.
Abstract:
In one embodiment, an ECG monitoring system includes two or more electrodes configured to record cardiac potentials from a patient, at least one processor, and a rapid acquisition module executable on the at least one processor to: determine that an impedance of each electrode is less than an impedance threshold; record initial ECG lead data based on the cardiac potentials; determine that a noise level in each ECG lead of the initial ECG data is less than a noise threshold; start a recording timer once the noise level is below the noise threshold; record an ECG dataset while the noise level is maintained below the noise threshold until the recording timer reaches a predetermined test duration; store the ECG dataset and provide a completion alert.