The present invention belongs to the field of medicine and discloses a method for assessing volume responsiveness and a processing device for assessing volume responsiveness. The method comprises: acquiring, by using one or more vibration sensitive sensors, a first parameter associated with a change in preload in a first time interval before a subject performs a passive straight-leg lift in a passive leg raising (PLR) test; acquiring, by using the one or more vibration sensitive sensors, a second parameter associated with a change in preload in a second time interval after the subject performs a passive straight-leg lift in the PLR test; and determining the volume responsiveness of the subject according to the first parameter associated with a change in preload and the second parameter associated with a change in preload. The method provides a convenient and easy determination of volume responsiveness.

The invention relates to a determination system (1) for determining a heart failure risk for a subject (4). The determination system is adapted to provide a cardiogram selected from a group consisting of a ballistocardiogram, a seismocardiogram and an impedance cardiogram of the subject, to detect at least one of a presence of a postextrasystolic potentiation (PESP) and a disturbed force-frequency relation (FFR) based on the provided cardiogram and to determine the heart failure risk based on this detection. By using the detection of the presence of the PESP and/or of a disturbed FFR, the heart failure risk can be reliably determined. In particular, it can be determined that the heart failure risk is relatively large, if a PESP is not present and/or if the FFR is disturbed.

An apparatus for detecting object features can include: a probe signal transmitter configured to load a digital intermediate frequency signal onto a carrier signal, and to transmit a loaded signal outwards; an echo signal receiver configured to receive an echo signal, and to extract an object feature signal by performing respective down conversions on a quadrature signal of the carrier signal and a quadrature signal of the digital intermediate frequency signal; and a signal processor configured to identify object features according to the object feature signal.

A wearable monitoring device can include an electronics module containing a printed circuit board (PCB) to which one or more sensors are coupled. The one or more sensors can include one or more contacting sensors and/or one or more non-contacting sensors. In some cases, the wearable monitoring device can include an onboard power supply (e.g., a battery) and a wireless communication antenna. The PCB can be constructed to specifically include the one or more sensors on a first side facing the skin of the user when the wearable monitoring device is being worn, allowing one or more processors, memory, and other components to be included on the opposite side facing away from the user. Certain components, such as the power supply and wireless communication antenna, can be spaced apart from the PCB and located opposite the PCB from the one or more sensors.

In at least one embodiment, a system for assessing biometric information for an occupant in a vehicle is provided. The system includes a plurality of sensors and a controller. The plurality of sensors is positioned about a main cabin of the vehicle and being configured to provide the biometric information for the occupant in response to a stimulus and to transmit a first signal indicative of the biometric information. The controller is positioned in the vehicle and is configured to activate the stimulus in the vehicle and to receive the biometric information after the stimulus has been activated. The controller is further configured to transmit the biometric information to at least one of another controller in the vehicle or to a server that is remote from the vehicle to assess the biometric information to determine the effect of the stimulus on the occupant.

The present disclosure is related to systems and methods for motion detection. The method includes obtaining, via at least one detection device, detection data of a subject located in a field of view (FOV) of a medical device. The method also includes determining motion data of the subject based on the detection data.

An apparatus for generating a blood pressure estimation model includes: a signal acquirer configured to receive input a first signal and a second signal from a user; and a processor configured to obtain a pulse transit time (PTT) as a first predictor variable value based on the first signal and the second signal, to extract at least one feature from the second signal, to obtain a second predictor variable value based on the extracted at least one feature, and to generate a blood pressure estimation model based on the first predictor variable value and the second predictor variable value.

A system and method of automatically assessing pediatric and neonatal pain using facial expressions along with crying sounds, body movement, and vital signs change to improve the diagnosis and treatment of pain in the pediatric patient population.

A biological data obtaining device includes a storage unit, a first generation unit, and a second generation unit. The storage unit is configured to store time-series data in which first to N.sup.th distance-based fluctuation data are arranged. The first to N.sup.th distance-based fluctuation data are obtained based on reflected waves which are reflected from a living body at different times, wherein n.sup.th distance-based fluctuation data indicates changes in signal strength with respect to distance. The first generation unit is configured to generate time-based fluctuation data by performing strength obtaining process. The strength obtaining process includes obtaining one corresponding strength information, wherein the one corresponding strength information is a signal strength based on reflected waves from a predetermined detection part of the living body. The second generation unit is configured to generate biological data of the detection part of the living body based on the time-based fluctuation data.

A system includes a controller coupled to one or more sensors. The controller receives sensor data indicative of biometric data an occupant of a vehicle seat from the sensors. The controller receives the sensor data and analyzes the data to provide biometric data associated with the occupant of the vehicle seat.