An exemplary method is disclosed that can be used in the diagnosis of hypertrophic cardiomyopathy (HCM) using a biophysical-sensor system configured to non-invasively and concurrently acquire electrocardiographic signals, seismographic signals, photoplethysmographic, and/or phonocardiographic signals, collectively referred to herein as biophysical signals, from at least the thoracic region of a subject. The acquired biophysical signals may be assessed for one or more conditions or indicators of hypertrophic cardiomyopathy and concurrently with other cardiac diseases, conditions, or indicators of either.

The present disclosure relates to a device, method and system for calculating, estimating, or monitoring the blood pressure of a subject based on physiological features and personalized models. At least one processor, when executing instructions, may perform one or more of the following operations. A first signal representing a pulse wave relating to heart activity of a subject may be received. A plurality of second signals representing time-varying information on a pulse wave of the subject may be received. A personalized model for the subject may be designated. Effective physiological features of the subject based on the plurality of second signals may be determined. A blood pressure of the subject based on the effective physiological features and the designated model for the subject may be calculated.

A method for synchronizing operation of a heart assist pump device to a patient's cardiac cycle includes obtaining a signal from a motor of a heart assist pump device and filtering the signal to remove noise. The method also includes determining a speed synchronization start point at which time the motor of the heart assist pump device will begin a change in speed of operation based on the filtered signal. The method further includes modulating a speed of the motor of the heart assist pump device to a target speed at the speed synchronization start point, thereby synchronizing the change in speed of operation with a patient's cardiac cycle.

An apparatus for estimating bio-information, includes a sensor including a cover having a transmitting area provided at a center of the cover, and non-transmitting areas provided at both edges of the cover, a light source configured to emit light onto an object that is in contact with the cover, and a detector configured to detect a first optical signal of the emitted light that is scattered or reflected from the object after passing through the transmitting area, and a second optical signal of the emitted light that is reflected from the non-transmitting areas. The apparatus further includes a processor configured to estimate bio-information, based on the detected first optical signal and the detected second optical signal.

A method measures a perfusion wave upstroke associated with leg perfusion dynamics, the perfusion wave upstroke including two phases, an initial slow phase and a fast-rising phase, and using prolongation of the slow phase to detect a presence of arterial stenosis and to assess stenosis severity.

Methods and systems implement a pain assessment regularizing system to autonomously observe pained expressions and physiological measurements of a patient, in order to systematically collect data inputs which may be converted to pain assessment factors. The pain assessment regularizing system, by collecting this data, may combine it with clinical appraisals of pain intensity and patient self-reporting of pain intensity, weighing each factor appropriately in a manner sensitive to the progression of a patient care program, so as to lessen confounding effects of subjective pain assessment. The pain assessment regularizing system may generate a time series of regularized pain assessment factors, and further forecast a regularized pain assessment trend. A clinician may further operate the pain assessment regularizing system to review a visualization of both the time series and the forecast, providing the clinician with rigorously sampled and analytically predicted data which cannot be derived through manual and mental efforts.

Systems and methods are provided for enhanced heart medical imaging operations, particularly as by incorporating use of artificial intelligence (AI) based fetal heart functional analysis and/or real-time and automatic ejection fraction (EF) measurement and analysis.

A system for visualizing a tissue region of interest comprises a deployment catheter defining a lumen and a hood coupled to and extending distally from the deployment catheter. The hood has a low-profile configuration within a delivery sheath and a deployed configuration when extended distally of the delivery sheath. The hood in the deployed configuration defines an open area in fluid communication with the lumen. A distal portion of the deployment catheter extends into the open area. An imaging element is coupled to an imager support member. When in the deployed configuration, the imaging element is configured to extend distally of the distal portion while the imager support member extends within the deployment catheter. The imaging element comprises a tapered surface and the deployment catheter comprises a complementary tapered surface. Retraction of the imaging element causes the imaging element to shift radially outward from a longitudinal axis.

The present specification discloses systems and methods of patient monitoring in which multiple sensors are used to detect physiological parameters and the data from those sensors are correlated to determine if an alarm should, or should not, be issued, thereby resulting in more precise alarms and fewer false alarms. Electrocardiogram readings can be combined with invasive blood pressure, non-invasive blood pressure, and/or pulse oximetry measurements to provide a more accurate picture of pulse activity and patient respiration. In addition, the monitoring system can also use an accelerometer or heart valve auscultation to further improve accuracy.

The present specification discloses systems and methods of patient monitoring in which multiple sensors are used to detect physiological parameters and the data from those sensors are correlated to determine if an alarm should, or should not, be issued, thereby resulting in more precise alarms and fewer false alarms. Electrocardiogram readings can be combined with invasive blood pressure, non-invasive blood pressure, and/or pulse oximetry measurements to provide a more accurate picture of pulse activity and patient respiration. In addition, the monitoring system can also use an accelerometer or heart valve auscultation to further improve accuracy.