Abstract: Systems, methods and devices for providing combined ultrasound, electrocardiography, and auscultation data are provided. One such system includes an ultrasound sensor, an electrocardiogram (EKG) sensor, an auscultation sensor, and a computing device. The computing device includes memory and a processor, and the processor receives signals from the ultrasound sensor, the EKG sensor, and the auscultation sensor. Artificial intelligence techniques may be employed for automatically analyzing the data obtained from the ultrasound sensor, the EKG sensor, and the auscultation sensor and producing a clinically-relevant determination based on a combined analysis of the data.

Abstract: Devices, systems, and methods are provided in which noise or artifacts generated by motion of a probe are attenuated in acquired physiological data, such as auscultation or ultrasound data. One such method includes acquiring physiological data of a patient by a handheld device. Motion of the handheld device is sensed, and a determination is made as to whether the sensed motion of the handheld device exceeds a motion threshold. The method further includes generating conditioned physiological data of the patient by attenuating a portion of the acquired physiological data in response to determining that the sensed motion of the handheld device exceeds the motion threshold.

Abstract: Ultrasound image recognition systems and methods, and artificial intelligence training networks for such systems and methods, are provided. An ultrasound data information system includes an ultrasound image recognition training network that is configured to receive ultrasound training images and to develop ultrasound image knowledge based on the received ultrasound training images. An ultrasound imaging device acquires ultrasound images of a patient, and the device includes an ultrasound image recognition module. The ultrasound image recognition module is configured to receive the ultrasound image knowledge, receive the acquired ultrasound images from the ultrasound imaging device, and determine, based on the ultrasound image knowledge, whether the received ultrasound images represent a clinically desirable view of an organ or whether the clinically desirable views indicate normal function or a particular pathology.

Abstract: Systems, methods and devices for providing combined ultrasound, electrocardiography, and auscultation data are provided. One such system includes an ultrasound sensor, an electrocardiogram (EKG) sensor, an auscultation sensor, and a computing device. The computing device includes memory and a processor, and the processor receives signals from the ultrasound sensor, the EKG sensor, and the auscultation sensor. Artificial intelligence techniques may be employed for automatically analyzing the data obtained from the ultrasound sensor, the EKG sensor, and the auscultation sensor and producing a clinically-relevant determination based on a combined analysis of the data.

Abstract: Ultrasound image recognition systems and methods, and artificial intelligence training networks for such systems and methods, are provided. An ultrasound data information system includes an ultrasound image recognition training network that is configured to receive ultrasound training images and to develop ultrasound image knowledge based on the received ultrasound training images. An ultrasound imaging device acquires ultrasound images of a patient, and the device includes an ultrasound image recognition module. The ultrasound image recognition module is configured to receive the ultrasound image knowledge, receive the acquired ultrasound images from the ultrasound imaging device, and determine, based on the ultrasound image knowledge, whether the received ultrasound images represent a clinically desirable view of an organ or whether the clinically desirable views indicate normal function or a particular pathology.

Abstract: Automated ultrasound image labeling and quality grading systems and methods are provided. An ultrasound system includes an ultrasound imaging device configured to acquire ultrasound images of a patient. An anatomical structure recognition and labeling module receives the acquired ultrasound images from the ultrasound imaging device, and automatically recognizes anatomical structures in the received ultrasound images. The anatomical structure recognition and labeling module automatically labels the anatomical structures in the images with information that identifies the anatomical structures. The acquired ultrasound images and the labeled anatomical structures are displayed on a display of the ultrasound imaging device.

Abstract: Systems, methods and devices for providing combined ultrasound, electrocardiography, and auscultation data are provided. One such system includes an ultrasound sensor, an electrocardiogram (EKG) sensor, an auscultation sensor, and a computing device. The computing device includes memory and a processor, and the processor receives signals from the ultrasound sensor, the EKG sensor, and the auscultation sensor. Artificial intelligence techniques may be employed for automatically analyzing the data obtained from the ultrasound sensor, the EKG sensor, and the auscultation sensor and producing a clinically-relevant determination based on a combined analysis of the data.

Abstract: Devices and systems are provided that include an auxiliary electrocardiogram (ECG) assembly that can be utilized to acquire ECG data of a patient and transmit the ECG data to a handheld probe, such as an ultrasound probe. The handheld probe may include a housing and an ultrasound sensor that is at least partially surrounded by the housing. The ultrasound sensor may be located at or near a sensor face of the handheld probe. An auxiliary ECG connector is included that is at least partially exposed by the housing of the handheld probe. The auxiliary ECG connector may be utilized to electrically couple one or more auxiliary ECG leads to the handheld probe.

Abstract: A clinical data acquisition system includes a probe and a mobile clinical viewing device communicatively coupleable to the probe. The probe includes at least one sensor that acquires physiological data of a patient. The mobile clinical viewing device includes a frame, a display, and a handle. The display is secured to a first side of the frame. The handle is secured to a second side of the frame. The handle includes a plurality of user input elements, and a user may control one or more operations of the mobile clinical viewing device by providing input via the user input elements on the handle. This allows a user to comfortably hold the mobile clinical viewing device and to control operations of the device in one hand, while the other hand is free to perform other operations such as holding the probe during examination of the patient.

Abstract: Enhanced ultrasound imaging apparatus and associated methods of work flow are disclosed herein. In one embodiment, a method of ultrasound scanning includes receiving a first dataset representing ultrasonic scanning of a target anatomy of a patient in a two-dimensional mode and generating a two-dimensional ultrasound image of the scanned target anatomy based on the received first dataset. The method also includes accepting a definition of at least one of a sagittal plane, a transverse plane, and a coronal plane on the displayed two-dimensional ultrasound image. Thereafter, a second dataset representing ultrasonic scanning of the target anatomy in a three-dimensional mode is received and an ultrasound image at the coronal plane of the target anatomy is generated based on (1) the three-dimensional scanning and (2) the accepted definition of at least one of the sagittal plane, the transverse plane, and the coronal plane.

Abstract: Enhanced ultrasound imaging apparatus and associated methods of work flow are disclosed herein. In one embodiment, a method of ultrasound scanning includes receiving a first dataset representing ultrasonic scanning of a target anatomy of a patient in a two-dimensional mode and generating a two-dimensional ultrasound image of the scanned target anatomy based on the received first dataset. The method also includes accepting a definition of at least one of a sagittal plane, a transverse plane, and a coronal plane on the displayed two-dimensional ultrasound image. Thereafter, a second dataset representing ultrasonic scanning of the target anatomy in a three-dimensional mode is received and an ultrasound image at the coronal plane of the target anatomy is generated based on (1) the three-dimensional scanning and (2) the accepted definition of at least one of the sagittal plane, the transverse plane, and the coronal plane.

Abstract: A device obtains ultrasound signals with ultrasound sensors without using ultrasound coupling gels on the face of the device. One such device includes an acoustic coupling pad that is placed on the ultrasound sensors. The acoustic coupling pad replaces conventional water-based ultrasound sensing gels to obviate the need for using such gels that may cause an electrical short circuit between electrode leads of electrocardiogram sensors positioned adjacent to the ultrasound sensors in the face of the device.

Abstract: Systems, methods and devices for providing combined ultrasound, electrocardiography, and auscultation data are provided. One such system includes an ultrasound sensor, an electrocardiogram (EKG) sensor, an auscultation sensor, and a computing device. The computing device includes memory and a processor, and the processor receives signals from the ultrasound sensor, the EKG sensor, and the auscultation sensor. Artificial intelligence techniques may be employed for automatically analyzing the data obtained from the ultrasound sensor, the EKG sensor, and the auscultation sensor and producing a clinically-relevant determination based on a combined analysis of the data.

Abstract: Systems, methods and devices for providing combined ultrasound, electrocardiography, and auscultation data are provided. One such system includes an ultrasound sensor, an electrocardiogram (EKG) sensor, an auscultation sensor, and a computing device. The computing device includes memory and a processor, and the processor receives signals from the ultrasound sensor, the EKG sensor, and the auscultation sensor. Artificial intelligence techniques may be employed for automatically analyzing the data obtained from the ultrasound sensor, the EKG sensor, and the auscultation sensor and producing a clinically-relevant determination based on a combined analysis of the data.

Abstract: Systems, methods and devices for providing combined ultrasound, electrocardiography, and auscultation data are provided. One such system includes an ultrasound sensor, an electrocardiogram (EKG) sensor, an auscultation sensor, and a computing device. The computing device includes memory and a processor, and the processor receives signals from the ultrasound sensor, the EKG sensor, and the auscultation sensor. Artificial intelligence techniques may be employed for automatically analyzing the data obtained from the ultrasound sensor, the EKG sensor, and the auscultation sensor and producing a clinically-relevant determination based on a combined analysis of the data.

Abstract: Systems and methods which implement a plurality of different imaging signatures in generating an image frame are shown. A first imaging signature may be configured for providing relatively high quality images with respect to subsurface regions of living tissue, for example, whereas a second imaging signature may be configured for providing relatively high quality images with respect to interventional instruments inserted into living tissue at a steep angle. Image sub-frames generated using each such different imaging signature are blended to form a frame of the final image providing a relatively high quality image of various objects within the volume being imaged.