A system (100) for assessing fluid responsiveness includes an infusion pump (24) in communication with at least one processor (32), and a plurality of physiological monitors (40,42,44,46) operable to receive physiological signals from an associated patient. Physiological signals (48,50) acquired from the associated patient (10) during a fluid challenge are synchronized with a timing signal (54) of the infusion pump (24) administering the fluid challenge. One or more dynamic indices and/or features (58) is calculated from the synchronized physiological signals (50), and one or more dynamic indices and/or features (50) is calculated from baseline physiological signals (48) acquired from the associated patient (10) prior to the fluid challenge. A fluid responsiveness probability value (64) of the patient (10) is determined based on dynamic indices and/or features (58) from the synchronized physiological signals (50) and dynamic indices and/or features (50) from the baseline physiological signals (48).

A transmitting element for generating a magnetic field for tracking of an object includes a first spiral trace that extends from a first outer origin inward to a central origin in a first direction. A second spiral trace can extend from the central origin outward to a second outer origin in the first direction. The second spiral trace can extend from the central origin to the second outer origin in the first direction. The first spiral trace and the second spiral trace can be physically connected at the central origin to form the fluorolucent magnetic transmitting element and at least a portion of the first spiral trace overlaps at least a portion of the second spiral trace.

A voxel tagging system (100) includes a sensing enabled device (104) having an optical fiber (126) configured to sense induced strain within the device (Bragg grating sensor). An interpretation module (112) is configured to receive signals from the optical fiber interacting with an internal organ, e.g. heart, and to interpret the signals to determine positions visited by the at least one optical fiber within the internal organ. A data source (152, 154) is configured to generate data associated with an event or status, e.g. respiration, ECG phase, time stamp, etc. A storage device (116) is configured to store a history (136) of the positions visited in the internal organ and associate the positions with the data generated by the data source (152, 154).

A mobile electronic device 1 includes a plurality of sensors, a detector that detects a biological reaction by one of the sensors, and at least one controller 10 that performs control to change a detection cycle of other sensors according to whether the biological reaction is detected.

The present specification describes a system and method of detecting sleep disordered breathing, that includes acquiring a set of unconditioned sleep test data that includes oximetry data and at least one other physiological sensor data; sampling the set of unconditioned sleep test data; storing the sampled set of unconditioned sleep test data; receiving, through a display, an input indicative of a degree of analyzing to be applied to the sampled set of unconditioned sleep test data; based on said input, applying a corresponding degree of analyzing to the unprocessed sleep test data to generate processed sleep test data; and visually displaying the processed sleep test data.

A method includes receiving acoustic inputs; generating signal channels from the acoustic inputs; pre-processing data in the signal channels; extracting S1-S2 peaks from the pre-processed data; removing artifacts and outliers from the S1-S2 peaks; generating S1-S2 signal channels based on the S1-S2 peaks in the pre-processed signal channels; selecting two or more of the S1-S2 signal channels; and combining the selected two or more S1-S2 signal channels to produce an acoustic uterine monitoring signal.

An apparatus for analyzing coronary vessels and a corresponding method are provided in which simulated pullback data obtained from (non-invasively) acquired diagnostic images is co-registered with invasively acquired intravascular pullback data and the co-registration is used to identify disparities in the pullback data obtained using the two modalities. These disparities allow for deriving further information about the vessel geometry and/or the blood flow through the vessel. They may therefore be used to improve the physiological model.

Systems and methods for generating an electromechanical map are disclosed herein. The methods includes obtaining ultrasound data comprising a series of consecutive image frames and radio frequency (RF) signals corresponding to the location in the heart; measuring displacements and strains based on the ultrasound data to determine an electromechanical activation in the location; converting the ultrasound data into a series of isochrone maps; and combining the series of isochrone maps to generate the electromechanical map. The electromechanical map illustrates the electromechanical activation and internal wall structures of the heart.

A method of imaging a tissue region may comprise visualizing one or more lesions in vivo over a tissue region within a body through an imaging catheter. The method may further comprise measuring a temperature or an electrical potential of the one or more lesions. The method may further comprise overlaying a gradient indicative of the temperature or the electrical potential upon a visual image of the one or more lesions captured in vivo. The method may further comprise registering ablation parameters to the visual image of the one or more lesions and displaying the visual image with the overlaid gradient and the registered ablation parameters.

Provided herein are systems and methods for generating fetal cardiac magnetic resonance (MR) images of a living fetus, within a uterus of a parent of the fetus, by imaging the fetus within the uterus using a magnetic resonance imaging (MRI) system. Also provided herein are methods for deriving information indicative of fetal cardiac cycles from MR data obtained by an MRI system while imaging the fetus, the MR data including MR data for the center of k-space. The derived information may be used to differentiate the fetal cardiac cycles from other sources of noise in the MR data such as the parental cardiac cycles.