The present disclosure relates to a device, method and system for estimating or monitoring the health condition of a subject. At least one processor, when executing instructions, may perform one or more of the following operations. At least one physiological signal or information including a physiological signal of a subject may be received. At least one physiological parameter of interest may be generated based on the physiological signal. The physiological parameter of interest may be analyzed according to an analysis model. A physiological result may be generated. A recommendation may be provided based on the physiological analysis result.

The present invention describes a system and method for continuous monitoring of central (aortic) and peripheral Blood Pressure. The system includes a fully mobile, non-invasive, continuous blood pressure monitoring system that includes one or more Biostrip devices affixed on a user, coupled with an application running on a computing device, which is further connected to a web server in the cloud. The system performs various computations on the Biostrip device, or on the gateway device (Smartphone or Smartwatch), or on the Cloud, and provides the user and authorized third parties with various insights about the blood pressure levels of the user. Further, the system enables the user to receive biofeedback training for controlling hypertension, and schedule online appointments, pay online for such appointments, share data the data securely to obtain insights.

In accordance with embodiments of the present disclosure, a user-platform apparatus, such as a bodyweight sensing scale, includes a heart/cardiogram sensor which is used to detect heart and vascular characteristics of a user, and provide a cardiogram output indicative of the detected cardiovascular characteristics. The cardiogram output can be used for various purposes, such as detecting arterial stiffness and/or aging.

A system and method for tracking catheter electrode locations with the body of a patient during an MRI scan sequence includes mitigation logic configured to identify one or more impedance measurements that were taken during potentially noise-inducing conditions (i.e., magnet gradients, RF pulses), and were thus subject to corruption by noise. The mitigation logic is configured to replace the potentially corrupt impedance measurements with previously-obtained impedance measurements taken from an immediately preceding acquisition cycle (e.g., from a previous time-slice).

A method for characterizing an electrocardiogram, including receiving a first unipolar signal from a first location of a heart and a second unipolar signal from a second location of the heart. The method further includes generating a bipolar signal from the first and second unipolar signals, and analyzing the bipolar signal to delineate a time period during which the first and second locations generate a bipolar complex. The method also includes analyzing the first unipolar signal within the time period to determine an activation time of the first location.

Described herein are methods, apparatuses, and systems for heart monitoring of a patient. The heart monitoring system can be used to take an electrocardiogram (ECG) using only two electrodes. A handheld device can be used to sequentially measure the electrical signal between different positions on a patient's body. The electrical signals can be processed and analyzed to prepare an ECG for the patient, including a 12-lead ECG.

A vehicle seat in accordance with the present disclosure includes a seat bottom and a seat back. The seat back is coupled to the seat bottom and arranged to extend in an upward direction away from the seat bottom. The vehicle seat further includes an electronics system.

Method for quantifying the elasticity of a material by ultrasounds, comprising the generation of one acoustic disturbance ultrasound beam (10) for the first excitation point (1), for generating a shear wave (11), a measurement of the shear wave (11) at a plurality of lines of sight placed in a region of interest (2) at different predetermined distances from the first excitation point (1), the calculation of the speed of the measured shear wave (11) and the assessment, by calculation, of a mean stiffness value of the material in the region of interest (2) on the basis of the measured speed of the shear wave (11). In the acquired image (3) a second excitation point (4) is defined, in such a position that the region of interest (2) is interposed between the first excitation point (1) and the second excitation point (4). The method for the second excitation point (4) is carried out, for calculating the speed of the shear wave (11) for the second excitation point (4), and the assessment by calculation of the mean stiffness value is carried out on the basis of the average between the speed of the shear wave measured for the first excitation point (1) and the speed of the shear wave measured for the second excitation point (4).

A heartrate monitor detects heartbeats in a test signal. A local heartrate and an energy of acceleration are associated with the detected heartbeats. Detected heartbeats are included or excluded from a test set of heartbeats based on the local heartrate and energy of acceleration associated with the respective heartbeats. Anomalous heartbeats in the test set of heartbeats are detected using a sparse approximation model. The heartrate monitor may detect heartbeats in a training heartbeat signal. A reference heart rate and an energy of acceleration are associated with detected beats of the training heartbeat signal and selectively included in a set of training data based on the heart rate and energy of acceleration associated with the detected beat in the training heartbeat signal. A dictionary of the sparse representation model may be generated using the set of training data.

This disclosure relates generally to biomedical signal processing, and more particularly to method and system for physiological parameter derivation from pulsating signals with reduced error. In this method, pulsating signals are extracted, spurious perturbations in the extracted pulsating signals are removed for smoothening, local minima points in the smoothened pulsating signal are derived, systolic maxima point between two derived local minima are derived, most probable pulse duration and most probable peak-to-peak distance are derived, dicrotic minima is removed while ensuring that every dicrotic minima is preceded by a systolic maxima point and followed by a beat start point of said systolic maxima, diastolic peak is derived while ensuring that every dicrotic maxima is preceded by a diastolic notch followed by next beat start point of that maxima, and physiological parameters are derived from the derived local minima points, systolic maxima points, dicrotic notch and diastolic peak.