The present disclosure relates to cardiac health assessment system for use with a handheld electronic device for assessing cardiac health of a user and a method for assessing cardiac health of a user. The disclosure further relates to systems and methods for training a machine learning model to estimate intracardiac pressure data.

Aspects of the technology described herein relate to techniques for guiding an operator to use an ultrasound device. Thereby, operators with little or no experience operating ultrasound devices may capture medically relevant ultrasound images and/or interpret the contents of the obtained ultrasound images. For example, some of the techniques disclosed herein may be used to identify a particular anatomical view of a subject to image with an ultrasound device, guide an operator of the ultrasound device to capture an ultrasound image of the subject that contains the particular anatomical view, and/or analyze the captured ultrasound image to identify medical information about the subject.

The ultrasonic diagnostic apparatus according to a present embodiment includes processing circuitry. The processing circuitry is configured to: detect, based on an electrocardiogram signal, a specific heart phase in a former heartbeat and a specific heart phase in a latter heartbeat thereafter; sequentially calculate a delay time from the specific heart phase in the latter heartbeat based on a time interval between the specific heart phase in the former heartbeat and the specific heart phase in the latter heartbeat, and control an ultrasonic probe to initiate an ultrasonic scan at a timing when the sequentially calculated delay time is elapsed from the specific heart phase in the latter heartbeat.

Aspects of the technology described herein relate to techniques for guiding an operator to use an ultrasound device. Thereby, operators with little or no experience operating ultrasound devices may capture medically relevant ultrasound images and/or interpret the contents of the obtained ultrasound images. For example, some of the techniques disclosed herein may be used to identify a particular anatomical view of a subject to image with an ultrasound device, guide an operator of the ultrasound device to capture an ultrasound image of the subject that contains the particular anatomical view, and/or analyze the captured ultrasound image to identify medical information about the subject.

An ultrasound scanning apparatus comprises an ultrasound scanning unit, an ultrasound controller for controlling the operation of the ultrasound scanning unit, detecting the operation state of the ultrasound scanning unit, generating a first enable signal when detecting that the operation state of the ultrasound scanning unit is transferred from an operating state to a non-operating state and generating a second enable signal when detecting that the operation state of the ultrasound scanning unit is transferred from the non-operating state to the operating state, and an enable output end for transmitting the first enable signal or the second enable signal to the breathing machine to control the running of the breathing machine.

Disclosed are ultrasound medical detection devices and an imaging method, an imaging system and a display terminal. This method comprises: displaying an ultrasonic image on a first display screen, obtaining a mark point within the active area of a bicuspid valve on the ultrasonic image, automatically searching for a ventricular internal diameter reference point according to the mark point, calculating a hemodynamic parameter according to the internal diameter reference point and outputting the calculation result of the hemodynamic parameter.

Implementations described and claimed herein provide systems and methods for managing one or more patients. In one implementation, an imaging window is determined based on a location of a probe. A primary image cross-section for the imaging window is identified for the imaging window. At least one image is generated along the primary image cross-section using patient data captured using the probe. The at least one image is compared to an expected image contour scaffold of the primary image cross-section. The probe is commanded to fine-tune an imaging plane based on the comparison until the at least one image matches the expected image contour scaffold of the primary image cross-section.

A device is provided for automatically assessing functional hemodynamic properties of a patient is provided, the device comprising: a housing; an ultrasound unit coupled to the housing and adapted for adducing ultrasonic waves into the patient at a vessel; a detector adapted to sense signals obtained as a result of adducing ultrasonic waves into the patient at the vessel and to record the ; and a processor adapted for receiving the recorded signals as data and transforming the data for output at an interface. Other devices, systems, methods, and/or computer-readable media may be provided in relation to assessing functional hemodynamics of a patient.

A method and system for determining hemodynamic indices, such as fractional flow reserve (FFR), for a location of interest in a coronary artery of a patient is disclosed. Medical image data of a patient is received. Patient-specific coronary arterial tree geometry of the patient is extracted from the medical image data. Geometric features are extracted from the patient-specific coronary arterial tree geometry of the patient. A hemodynamic index, such as FFR, is computed for a location of interest in the patient-specific coronary arterial tree based on the extracted geometric features using a trained machine-learning based surrogate model. The machine-learning based surrogate model is trained based on geometric features extracted from synthetically generated coronary arterial tree geometries.

An event-driven medical treatment data notification system is disclosed. Embodiments are directed to a treatment protocol for detecting Return of Spontaneous Circulation by employing a Doppler effect analysis on a signal transmitted at a patient's heart. A reflected signal is evaluated to determine if the patient's heart is moving, thereby indicating that the patient's heart is beating and, therefore, that blood is flowing.