WO2024149612A1

WO2024149612A1 - Distributed ultrasound including a wearable ultrasound device

Info

Publication number: WO2024149612A1
Application number: PCT/EP2023/087787
Authority: WO
Inventors: Hoa T. M. PHAM
Original assignee: Koninklijke Philips NV
Current assignee: Koninklijke Philips NV
Priority date: 2023-01-10
Filing date: 2023-12-26
Publication date: 2024-07-18
Anticipated expiration: 2025-07-10

Abstract

An ultrasound system includes a wearable ultrasound device. The wearable ultrasound device includes a memory that stores instructions; and a processor that executes the instructions. The first instructions cause the ultrasound system to: transmit ultrasound waves and receive ultrasound echoes while automatically switching between modes including an imaging mode and a Doppler mode; and generate ultrasound data for ultrasound images during the imaging mode for localization of fetal anatomy of a fetus in the ultrasound images in the imaging mode to produce biomarkers including fetal heart, fetal movements, amniotic fluid quantity and fetal heart rate measurement in the Doppler mode.

Description

DISTRIBUTED UETRASOUND INCLUDING A WEARABEE ULTRASOUND DEVICE

BACKGROUND

[0001] A biophysical profile is the result of a prenatal ultrasound combining diagnostic and monitoring modalities during the third trimester of pregnancy to evaluate a baby’s health. The biophysical profile may be obtained due to certain pregnancy symptoms and/or due to a known relative high risk for the pregnancy.

[0002] Currently, the biophysical profile combines two devices/sy stems to evaluate five areas including fetal body movements, muscle tone, breathing movements, amniotic fluid, and heartbeat. The two devices/sy stems are a fetal monitor and an ultrasound system. Each of these five areas is given a score of either 0 (abnormal) or 2 (normal). These scores are then added up for a total score ranging from 0 to 10. In general, a score of 8 or 10 is normal, while 6 is borderline. Below 6 is a sign of possible problems. The test results can also help your healthcare provider decide if your baby might need to be born early.

[0003] The requirements of a caregiver and the use of two separate devices/systems to obtain the biophysical profile is not particularly efficient or cost effective. Generation of an optimal biophysical profile to score fetal health requires a collaborative evaluation that performs the monitoring correctly, interprets the biophysical profile appropriately, and communicates the findings effectively and in a timely fashion to all members of the care team when a high-risk pattern is detected.

SUMMARY

[0004] According to an aspect of the present disclosure, an ultrasound system includes a first wearable ultrasound device. The first wearable ultrasound device includes a first memory that stores first instructions and a first processor that executes the instructions. When executed by the first processor, the first instructions cause the ultrasound system to: transmit ultrasound waves and receive ultrasound echoes while automatically switching between modes including an imaging mode and a Doppler mode; and generate ultrasound data for ultrasound images during the imaging mode for localization of fetal anatomy of a fetus in the ultrasound images in the imaging mode to produce biomarkers including fetal heart, fetal movements, amniotic fluid quantity and fetal heart rate measurement in the Doppler mode.

[0005] According to another aspect of the present disclosure, a system for scoring fetal health includes a memory that stores instructions; and a processor that executes the instructions. When executed by the processor, the instructions cause the system to: identify, by analyzing ultrasound images of a fetus, five biomarkers including fetal heart, respiratory movement, limb movement, gross movement, and amniotic fluid quantity; assign an individual score to each of the five biomarkers including fetal heart, respiratory movement, limb movement, gross movement, and amniotic fluid quantity; sum the individual score for each of the five biomarkers to obtain a sum; compare the sum to a predetermined threshold to score fetal health for the fetus; and provide feedback including at least one of the sum or the score for the fetal health.

[0006] According to another aspect of the present disclosure, an ultrasound method includes transmitting, from a wearable ultrasound device, ultrasound waves and receiving, by the wearable ultrasound device, echoes of the ultrasound waves, while automatically switching between modes including an imaging mode and a Doppler mode; and generating, by the wearable ultrasound device, ultrasound data for ultrasound images during the imaging mode and the Doppler mode for localization of fetal anatomy of a fetus in the ultrasound images in the imaging mode to produce biomarkers including fetal heart, fetal movements, and amniotic fluid quantity in the Doppler mode.

BRIEF DESCRIPTION OF THE DRAWINGS

[0007] The example embodiments are best understood from the following detailed description when read with the accompanying drawing figures. It is emphasized that the various features are not necessarily drawn to scale. In fact, the dimensions may be arbitrarily increased or decreased for clarity of discussion. Wherever applicable and practical, like reference numerals refer to like elements.

[0008] FIG. 1 illustrates a system for distributed ultrasound including a wearable ultrasound device, in accordance with a representative embodiment.

[0009] FIG. 2 illustrates a method for distributed ultrasound including a wearable ultrasound device, in accordance with a representative embodiment. [0010] FIG. 3 illustrates a table of definitions for biomarkers for a fetal biophysical profile used in distributed ultrasound including a wearable ultrasound device, in accordance with a representative embodiment.

[0011] FIG. 4 illustrates an output of a trained artificial intelligence model for distributed ultrasound including a wearable ultrasound device, in accordance with a representative embodiment.

[0012] FIG. 5 illustrates an output from a single wearable ultrasound device in distributed ultrasound including a wearable ultrasound device, in accordance with a representative embodiment.

[0013] FIG. 6 illustrates FHR monitoring in distributed ultrasound including a wearable ultrasound device, in accordance with a representative embodiment.

[0014] FIG. 7 illustrates a computer system, on which a method for distributed ultrasound including a wearable ultrasound device is implemented, in accordance with another representative embodiment.

DETAILED DESCRIPTION

[0015] In the following detailed description, for the purposes of explanation and not limitation, representative embodiments disclosing specific details are set forth in order to provide a thorough understanding of embodiments according to the present teachings. However, other embodiments consistent with the present disclosure that depart from specific details disclosed herein remain within the scope of the appended claims. Descriptions of known systems, devices, materials, methods of operation and methods of manufacture may be omitted so as to avoid obscuring the description of the representative embodiments. Nonetheless, systems, devices, materials and methods that are within the purview of one of ordinary skill in the art are within the scope of the present teachings and may be used in accordance with the representative embodiments. It is to be understood that the terminology used herein is for purposes of describing particular embodiments only and is not intended to be limiting. Definitions and explanations for terms herein are in addition to the technical and scientific meanings of the terms as commonly understood and accepted in the technical field of the present teachings.

[0016] It will be understood that, although the terms first, second, third etc. may be used herein to describe various elements or components, these elements or components should not be limited by these terms. These terms are only used to distinguish one element or component from another element or component. Thus, a first element or component discussed below could be termed a second element or component without departing from the teachings of the inventive concept. [0017] As used in the specification and appended claims, the singular forms of terms ‘a’, ‘an’ and ‘the’ are intended to include both singular and plural forms, unless the context clearly dictates otherwise. Additionally, the terms "comprises", and/or "comprising," and/or similar terms when used in this specification, specify the presence of stated features, elements, and/or components, but do not preclude the presence or addition of one or more other features, elements, components, and/or groups thereof. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.

[0018] Unless otherwise noted, when an element or component is said to be “connected to”, “coupled to”, or “adjacent to” another element or component, it will be understood that the element or component can be directly connected or coupled to the other element or component, or intervening elements or components may be present. That is, these and similar terms encompass cases where one or more intermediate elements or components may be employed to connect two elements or components. However, when an element or component is said to be “directly connected” to another element or component, this encompasses only cases where the two elements or components are connected to each other without any intermediate or intervening elements or components.

[0019] The present disclosure, through one or more of its various aspects, embodiments and/or specific features or sub-components, is thus intended to bring out one or more of the advantages as specifically noted below.

[0020] As described herein, a fetal biophysical profile may be scored using distributed ultrasound including a wearable ultrasound device. The distributed ultrasound may identify five main biomarkers including fetal heart, respiratory movements, limb movements, gross movements, and amniotic fluid quantity. An ultrasound device with a flexible form factor may be assisted with artificial intelligence to perform multiple modalities to identify all five biomarkers, including fetal movements, fetal respiratory movements, amniotic fluid volume, fetal tone and fetal heart. Each biomarker is localized and measured by switching different ultrasound modes, including imaging and Doppler, and the switching may be performed automatically insofar as the wearable ultrasound device is used as the ultrasound device.

[0021] FIG. 1 illustrates a system 100 for distributed ultrasound including a wearable ultrasound device, in accordance with a representative embodiment.

[0022] The system 100 in FIG. 1 is an ultrasound system. The system 100 is a system for distributed ultrasound including a wearable ultrasound device and includes components that may be provided together or that may be distributed. The system 100 includes a wearable ultrasound probe 110, a wearable ultrasound probe 111, an ultrasound base 120, an analysis system 190 and a medical office 199. The ultrasound base 120 includes a controller 150, and the controller 150 includes a memory 151 that stores instructions and a processor 152 that executes the instructions. The wearable ultrasound probe 110 and the wearable ultrasound probe 111 may comprise remote ultrasound systems used, for example, at home, such that ultrasound data is sent directly to the ultrasound base 120 and indirectly to the analysis system 190.

[0023] The wearable ultrasound probe 110 may comprise a first wearable ultrasound probe, and the wearable ultrasound probe 111 may comprise a second wearable ultrasound probe. For example, the wearable ultrasound probe 110 and the wearable ultrasound probe 111 may be patches configured as ultrasound probes with wireless hardware to send ultrasound images back to the ultrasound base 120. The wearable ultrasound probe 110 and the wearable ultrasound probe 111 may be worn simultaneously by the same pregnant mother, such as when the same pregnant mother is pregnant with twins and each of the wearable ultrasound probe 110 and the wearable ultrasound probe 111 is to be temporarily dedicated to different ones of the twins. The system 100 may include only one of the wearable ultrasound probe 110 or the wearable ultrasound probe 111, such as when the pregnant mother is pregnant with only a single child. Of course, the system 100 may include more than the two wearable ultrasound probes shown in FIG. 1, such as when the pregnant mother is pregnant with triplets or even more than three children.

[0024] As an example, the wearable ultrasound probe 110 and/or the wearable ultrasound probe 111 may comprise an ultrasound patch with an ultrasound transducer module that includes a printed circuit board (PCB). An ultrasound patch may comprise an array of capacitive micromachined ultrasonic transducers (CMUTs) implemented on an application-specific integrated circuit (ASIC) on the PCB as part of the ultrasound transducer module. The PCB may also include capacitors as passive components, and a wire adapter or wireless module to communicate with the ultrasound base 120. The ultrasound patch may also comprise a microcontroller with a memory that stores one or more algorithms and a processor such as a microprocessor that executes the one or more algorithms. The algorithms may provide anatomy recognition and data analysis. The ultrasound patch may further comprise a small power source to provide power to the ASIC and the microcontroller. The ultrasound patch may be temporarily attached to the pregnant mother using an acoustic interface material such as a wet gel or a dry gel, and may comprise a small belt with more than one attachment point to be attached to the pregnant mother using the acoustic interface material.

[0025] In order from the portion that will attach to the skin to the portion farthest from the skin, an ultrasound patch may include a tear off sheet under which the acoustic interface material is provided, the acoustic interface material to adhere to the skin, a cover for the CMUT to shield the CMUT from the acoustic interface material, and the CMUT implemented on the PCB. A lid may be provided to cover the PCB and shield the PCB. The CMUT and PCB may also be shielded on sides by another cover.

[0026] The wearable ultrasound probe 110 may include a first memory that stores first instructions; and a first processor that executes the first instructions. The wearable ultrasound probe 111 may include a second memory that stores second instructions, and a second processor that executes the second instructions. When executed by the first processor, the first instructions cause the wearable ultrasound probe 110 to: transmit ultrasound waves and receive ultrasound echoes while automatically switching between modes including an imaging mode and a Doppler mode; and generate ultrasound data for ultrasound images during the imaging mode for localization of fetal anatomy of a fetus in the ultrasound images in the imaging mode to produce biomarkers including fetal heart, fetal movements, amniotic fluid quantity and fetal heart rate measurement in the Doppler mode. When executed by the second processor, the second instructions cause the wearable ultrasound probe 111 : transmit ultrasound waves and receive ultrasound echoes while automatically switching between modes including an imaging mode and a Doppler mode; generate ultrasound data for ultrasound images during the imaging mode for localization of fetal anatomy of a fetus in the ultrasound images in the imaging mode to produce biomarkers including fetal heart, fetal movements, and amniotic fluid quantity and the fetal heart rate measurement in the Doppler mode. The ultrasound base 120, the analysis system 190 and/or the medical office 199 are configured to distinguish location of a first heart measured by the first wearable ultrasound device from location of a second heart measured by the second wearable ultrasound device. Each of the wearable ultrasound probe 110 and the wearable ultrasound probe 111 may include a transmitter that transmits the ultrasound data directly to the ultrasound base 120 and/or indirectly the analysis system 190 through the ultrasound base 120. For example, the transmitter may comprise an interface by which the ultrasound data is transmitted to a cloud service which localizes the fetal anatomy of the fetus in the ultrasound images to produce the biomarkers including fetal heart, fetal movements, and amniotic fluid quantity. A method performed by either or both of the wearable ultrasound probes may include transmitting the ultrasound data to a cloud service which localizes the fetal anatomy of the fetus in the ultrasound images to produce the biomarkers including fetal heart, fetal movements, and amniotic fluid quantity.

[0027] The ultrasound base 120 may be an electronic device or system installed in a home, such as in a home of a pregnant mother. The ultrasound base 120 may comprise, for example, an ultrasound beamformer that generates the data for the ultrasound beams to be emitted by the wearable ultrasound probe 110 and the wearable ultrasound probe 111. The wearable ultrasound probe 110 and the wearable ultrasound probe 111 communicate with the ultrasound base 120 via communication network #1. Communication network #1 may be a local area network (LAN) such as a WiFi network. In other embodiments, the ultrasound base 120 may comprise adapters to connect to wires that lead to the wearable ultrasound probe 110 and the wearable ultrasound probe 111. The adapters may be provided in a connector module that also includes adapters for a universal serial bus (USB) data connection and a power connection. The ultrasound base 120 may also comprise interfaces such as user interfaces with screens and buttons, along with a battery for power for the other elements of the ultrasound base 120. The controller 150 of the ultrasound base 120 executes instructions stored in the memory 151 to implement processes described herein. The ultrasound base 120 may provide real-time execution of artificial intelligence models, such as an artificial intelligence model that locates biomarkers or generates alarms or warnings. Other instances of artificial intelligence models used for trends, predictions and other types of monitoring may be implemented at the analysis system 190, such as for functionality that does not require real-time implementation.

[0028] The controller 150 includes at least the memory 151 that stores instructions and the processor 152 that executes the instructions. A computer that can be used to implement the ultrasound base 120 is depicted in FIG. 7, though an ultrasound base 120 may include more or fewer elements than depicted in FIG. 1 or FIG. 7. In some embodiments, multiple different elements of the system 100 in FIG. 1 may include a controller such as the controller 150.

[0029] The system 100 may score fetal health using the ultrasound base 120, the analysis system 190 and/or the medical office 199. When executed by the processor 152, the instructions from the memory 151 cause the system (the ultrasound base 120) to: identify, by analyzing ultrasound images of a fetus, five biomarkers including fetal heart, respiratory movement, limb movement, gross movement, and amniotic fluid quantity; assign an individual score to each of the five biomarkers including fetal heart, respiratory movement, limb movement, gross movement, and amniotic fluid quantity; sum the individual score for each of the five biomarkers to obtain a sum; compare the sum to a predetermined threshold to score fetal health for the fetus; and provide feedback including at least one of the sum or the score for the fetal health. This method performed by the controller 150 may be for images and data from the wearable ultrasound probe 110 or the wearable ultrasound probe 111. However, this method may be performed simultaneously or sequentially for images and data from both the wearable ultrasound probe 110 and the wearable ultrasound probe 111, as well as any other wearable ultrasound systems worn by the same mother.

[0030] In some embodiments, the ultrasound base 120 interacts with the wearable ultrasound probe 110 and the wearable ultrasound probe 111 while ultrasound imaging is performed. For example, the ultrasound base 120 may implement a trained artificial intelligence model that is applied to ultrasound images from the wearable ultrasound probe 110 and the wearable ultrasound probe 111 in real-time, and that instructs the wearable ultrasound probe 110 and the wearable ultrasound probe 111 to switch between an imaging mode and a Doppler mode.

[0031] In other embodiments, the timing for switching between the imaging mode and the Doppler mode may be predetermined. In some embodiments, predetermined timing stored at the wearable ultrasound probe 110 and the wearable ultrasound probe 111 may be updated based on analysis performed at the ultrasound base 120, such as after one or more ultrasound imaging sessions. In this way, the timing for imaging switching may be customized for the mother based on artificial intelligence applied by the ultrasound probe.

[0032] The analysis system 190 may comprise a centralized system which receives, over a communications network, the ultrasound images from the wearable ultrasound probe 110 and/or the wearable ultrasound probe when the ultrasound images are generated. The analysis system may report the score for the fetal health over the communications network in response to receiving the ultrasound images. For example, the analysis system 190 may comprise a server in a hospital facility which includes the medical office 199 or in the cloud such as at a data center. The ultrasound base 120 may send data to the analysis system 190 via the communication network #1. The communication network #2 may be a wide area network (WAN) such as the Internet. The data sent to the analysis system 190 may include data generated by or derived from the wearable ultrasound probe 110 and the wearable ultrasound probe 111. Results of analysis by the analysis system 190 may be sent to the medical office 199 for review by a medical professional such as a physician. The analysis system 190 may comprise a centralized system that receives the ultrasound images from one or more remote ultrasound system such as the wearable ultrasound probe 110 and the wearable ultrasound probe 111, over a communications network such as the communications network #2. The analysis system 190 may generate and report the score for the fetal health over the communications network to the medical office 199 in response to receiving the ultrasound images and generating the score for the fetal health. [0033] In some embodiments, the artificial intelligence model is implemented by the analysis system 190, and the analysis system 190 interacts with the wearable ultrasound probe 110 and the wearable ultrasound probe 111 via the ultrasound base 120 in real-time.

[0034] The wearable ultrasound probe 110 and the wearable ultrasound probe 111 are assistant with artificial intelligence implemented by the ultrasound base 120 and/or the analysis system 190. The wearable ultrasound probe 110 and the wearable ultrasound probe 111 can switch between both ultrasound imaging and ultrasound monitoring modalities to measure all biomarkers to score biophysical profile in the antenatal care. Each of the wearable ultrasound probe 110 and the wearable ultrasound probe 111 includes one or more ultrasound transducers with multiple planes that support continuous monitoring. Each of the wearable ultrasound probe 110 and the wearable ultrasound probe 111 may contain an IMU sensor to remove maternal movement artifacts during measurement. A deep learning based algorithm implemented by the ultrasound base 120 and/or the analysis system 190 runs on the images to localize where the fetal anatomy is with respect to the wearable ultrasound probe 110 and/or the wearable ultrasound probe 111. One or more fetal anatomies may be localized. After the position of the fetal anatomy is defined using imaging mode ultrasound data, five biomarkers may be quantified automatically. Each measurement may be scored and summarized to evaluate the fetal well-being.

[0035] The medical office 199 may include a display that displays results from the analysis system 190. The display may be a monitor such as a computer monitor, a display on a mobile device, an augmented reality display, a television, an electronic whiteboard, or another screen configured to display electronic imagery. The display may also include one or more input interface(s) such as those noted above that may connect to other elements or components, as well as an interactive touch screen configured to display prompts to users and collect touch input from users.

[0036] The controller 150 may perform some of the operations described herein directly and may implement other operations described herein indirectly. For example, the controller 150 may indirectly control operations such as by generating and transmitting content such as the ultrasound images and/or other ultrasound data to the analysis system 190. The controller 150 may directly control other operations such as logical operations performed by the processor 152 executing instructions from the memory 151 based on input received from electronic elements and/or users via the interfaces. Accordingly, the processes implemented by the controller 150 when the processor 152 executes instructions from the memory 151 may include steps not directly performed by the controller 150.

[0037] In some embodiments, the wearable ultrasound probe 110 and the wearable ultrasound probe 111 may interactively operate with the ultrasound base 120. For example, an artificial intelligence model implemented by the ultrasound base 120 may receive and analyze ultrasound data in real-time to instruct the wearable ultrasound probe 110 and the wearable ultrasound probe

111 to switch between an ultrasound imaging mode and an ultrasound Doppler mode. In other embodiments, the switching may be automatically, such as based on preset timing.

[0038] FIG. 2 illustrates a method for distributed ultrasound including a wearable ultrasound device, in accordance with a representative embodiment.

[0039] The method of FIG. 2 starts at S210 by transmitting ultrasound waves and receiving ultrasound echoes while automatically switching between modes. S210 may be performed by the wearable ultrasound probe 110 or the wearable ultrasound probe 111 in FIG 1. For example, a mother at home or in a medical office may place one or more wearable patch comprising the wearable ultrasound probe 110 and/or the wearable ultrasound probe 111 on the belly. S210 may be repeatedly performed while one or more of the following steps in FIG. 2 are performed, such as for up to 15 minutes.

[0040] At S220, the method of FIG. 2 includes generating ultrasound data. S220 may be performed by the wearable ultrasound probe 110 or the wearable ultrasound probe 111 in FIG 1. The wearable ultrasound probe 110 and/or the wearable ultrasound probe 111 may switch between an ultrasound imaging mode and a Doppler mode intermittently. The ultrasound imaging mode is used to localize the fetal anatomy at S240, and once the localization is stable the Doppler mode is used for continuous color/pulse wave Doppler tracing.

[0041] At S230, the method of FIG. 2 includes transmitting ultrasound data. S230 may be performed by the wearable ultrasound probe 110 or the wearable ultrasound probe 111 in FIG 1. The ultrasound data transmitted at S230 is transmitted to the ultrasound base 120 via the communication network #1 in FIG. 1. In some embodiments, the ultrasound data is passed from the ultrasound base 120 to the analysis system 190 via the communication network #2 in FIG. 1. For example, each of the wearable ultrasound probe 110 and the wearable ultrasound probe 111 may include a transmitter that transmits the ultrasound data directly to the ultrasound base 120 and/or indirectly to the analysis system 190 through the ultrasound base 120. For example, the transmitter may comprise an interface by which the ultrasound data is transmitted to the analysis system 190 in a cloud service which localizes the fetal anatomy of the fetus in the ultrasound images to produce the biomarkers including fetal heart, fetal movements, and amniotic fluid quantity. A method performed by either or both of the wearable ultrasound probes may include transmitting the ultrasound data to a cloud service which localizes the fetal anatomy of the fetus in the ultrasound images to produce the biomarkers including fetal heart, fetal movements, and amniotic fluid quantity. The cloud service may operate to provide ultrasound analysis services for dozens, hundreds, thousands or more mothers simultaneously, on-demand, and at any time of the day or night.

[0042] At S240, the method of FIG. 2 includes receiving the ultrasound data and applying an artificial intelligence model to the ultrasound data to localize fetal anatomy based on image mode ultrasound images. Individual fetal anatomy which is localized may include heart, lungs and limbs. S240 may be performed by the ultrasound base 120 or by the analysis system 190 in FIG.

1. The artificial intelligence model may be trained to recognize fetal anatomy in individual ultrasound images and over time in sequences of individual ultrasound images.

[0043] In instances where the mother is pregnant with multiple babies, a set of landmarks for the fetal heart may serve as the basis for distinguishing a first fetal heart from a second fetal heart in a twin pregnancy using key salient points so that the fetuses are always tagged even after repositioning. A first fetal heart and a second fetal heart may be distinguished from a third fetal heart in instances where the mother is pregnant with more than two babies. The fetal anatomies may be localized using deep learning based techniques in the imaging ultrasound mode. The imaging ultrasound mode is used to provide the depth and the position for Doppler gating before the wearable ultrasound probe 110 and the wearable ultrasound probe 111 switch to the Doppler mode for continuous color/pulse wave Doppler tracing when the localization of the fetal anatomies is stable.

[0044] The ultrasound data may be labelled so that the ultrasound base 120 or the analysis system 190 recognizes ultrasound data captured in the ultrasound imaging mode and ultrasound data captured in the Doppler mode. A visual indicator may be provided to show the mode in which the wearable ultrasound probe 110 or the wearable ultrasound probe 111 is operating when the ultrasound data is generated at S220. At S240, the deep learning algorithm may relocalize the fetal anatomies or reconfirm the position and the depth of the fetal heart and switch to the Doppler mode accordingly.

[0045] At S250, an artificial intelligence model is applied to the ultrasound data to provide biomarkers based on Doppler mode ultrasound images. The artificial intelligence model applied at S250 may be the same as the artificial intelligence model applied at S240, or may be different. S250 may be performed by the ultrasound base 120 or by the analysis system 190 in FIG. 1. [0046] The artificial intelligence model applied at S240 and S250 is used to recognize fetal anatomy. For each measurement, the artificial intelligence model may either recognize the fetal heart in the ultrasound images. The artificial intelligence model also classifies movement across ultrasound images, to classify respiratory movement and fetal heart rate. The artificial intelligence model may measure anatomical features including changes in measurements between individual ultrasound images, and then classify the fetal features.

[0047] At S250, the presentation of the fetal orientation and fetal heart location is provided as an easily understandable graphic representation superimposed with the ultrasound image. In some embodiments, an avatar may be displayed.

[0048] At S260, individual scores are assigned to each identified biomarker. That is, the biophysical profile is scored based on the measured parameters. The individual scores are then summed for the identified biomarkers to obtain a cumulative score. S260 may be performed by the ultrasound base 120 or by the analysis system 190.

[0049] The assignment of individual scores based on evaluation of measurements is used to support a clinical decision. Each parameter scores 0 or 2 based on the measured data. The sum of all scores may be displayed in the medical office 199 either with color code or numbers.

[0050] At S270, the cumulative score is compared to a predetermined threshold to obtain a final score. S270 may involve more than one predetermined threshold. For example, a threshold of 6 may be considered a borderline threshold, so cumulative scores below 6 may indicate a possible problem. A threshold of 8 may be considered another borderline threshold, so cumulative scores at or higher than 8 may be indicative of a healthy fetus. Scores of 6 or 7 may warrant closer reading of the ultrasound images, such as by a medical professional. S270 may be performed by the ultrasound base 120 or by the analysis system 190.

[0051] At S280, the final score is output based on the cumulative score. The final score may be output by the analysis system 190. In most embodiments based on the method of FIG. 2, the intent will be to display the final score to a medical professional rather than the mother, in the event of low or intermediate scores. Accordingly, the final score may be output from the analysis system 190 to the medical office 199.

[0052] FIG. 3 illustrates a table of definitions for biomarkers for a fetal biophysical profile used in distributed ultrasound including a wearable ultrasound device, in accordance with a representative embodiment.

[0053] As shown in FIG. 3, five biomarkers sought by the artificial intelligence model at S250 include fetal movements, fetal tone, fetal breathing movement, amniotic fluid volume, and nonstress test. Fetal movements may be defined as three body or limb movements by the baby. Fetal tone may be defined as one episode of active extension and flexion of the limbs, including opening and closing of a hand of the baby. Fetal breathing movement may be defined as an episode at or greater than thirty seconds in thirty minutes, including hiccups. Amniotic fluid volume may be based on a single measurement of a pocket with dimensions of two centimeter by two centimeter, or more. The non-stress test may be defined as at least two accelerations higher than fifteen beats per minute of at least a fifteen second duration.

[0054] FIG. 4 illustrates an output of a trained artificial intelligence model for distributed ultrasound including a wearable ultrasound device, in accordance with a representative embodiment.

[0055] A you only look once (YOLO) algorithm is used to localize fetal anatomies as in FIG. 4. The confidence level of the YOLO output is a regression, which is trained to output the intersection of union (I OU) between output bounding box and ground truth bounding box. FIG. 4 shows the bounding box over the heart. The image in FIG. 4 is derived from a single CMUT sensor.

[0056] FIG. 5 illustrates an output from a single wearable ultrasound device in distributed ultrasound including a wearable ultrasound device, in accordance with a representative embodiment.

[0057] FIG. 5 shows imaging from the imaging mode. The imaging mode generates images from individual ultrasound transducers from an ultrasound array. The imaging mode is important in detecting the tissues and measuring the amniotic fluid volume.

[0058] FIG. 6 illustrates FHR monitoring in distributed ultrasound including a wearable ultrasound device, in accordance with a representative embodiment.

[0059] Doppler mode is used to quantify fetal movement and/or measure fetal heart rate. The artificial intelligence model detects the tissue, the depth, and the angle at which the m-mode has to be enabled, the data is passed for subsequent analysis at the ultrasound base 120 or the analysis system 190. The YOLO model output is used to enter the Doppler mode. Center of the bounding box in FIG. 4 is used to obtain the point from which the scanline passes. The angle of scanline is also obtained to get into Doppler mode. [0060] Sensor information is fused along with image information. Each IMU sensor provides the position and orientation of the fan beam geometry on which key points of the heart have been identified. This provides orientation and position of each heart with respect to the global coordinate system. At this point, the position and orientation of each heart may be tracked based on a nearest neighbor linear approximation from the previous position and orientation. Subsequent acquisition is performed in a limited field of view knowing that the lie of the baby is a gradual movement, as compared to limb movement. If at any point, the heart is not detected in the search window, the field of view may be broadened in line with the ALARA principle.

[0061] FIG. 7 illustrates a computer system, on which a method for distributed ultrasound including a wearable ultrasound device is implemented, in accordance with another representative embodiment.

[0062] Referring to FIG.7, the computer system 700 includes a set of software instructions that can be executed to cause the computer system 700 to perform any of the methods or computer- based functions disclosed herein. The computer system 700 may operate as a standalone device or may be connected, for example, using a network 701, to other computer systems or peripheral devices. In embodiments, a computer system 700 performs logical processing based on digital signals received via an analog-to-digital converter.

[0063] In a networked deployment, the computer system 700 operates in the capacity of a server or as a client user computer in a server-client user network environment, or as a peer computer system in a peer-to-peer (or distributed) network environment. The computer system 700 can also be implemented as or incorporated into various devices, such as a workstation that includes a controller, a stationary computer, a mobile computer, a personal computer (PC), a laptop computer, a tablet computer, or any other machine capable of executing a set of software instructions (sequential or otherwise) that specify actions to be taken by that machine. The computer system 700 can be incorporated as or in a device that in turn is in an integrated system that includes additional devices. In an embodiment, the computer system 700 can be implemented using electronic devices that provide voice, video or data communication. Further, while the computer system 700 is illustrated in the singular, the term “system” shall also be taken to include any collection of systems or sub-systems that individually or jointly execute a set, or multiple sets, of software instructions to perform one or more computer functions. [0064] As illustrated in FIG. 7, the computer system 700 includes a processor 710. The processor 710 may be considered a representative example of a processor of a controller and executes instructions to implement some or all aspects of methods and processes described herein. The processor 710 is tangible and non-transitory. As used herein, the term “non- transitory” is to be interpreted not as an eternal characteristic of a state, but as a characteristic of a state that will last for a period. The term “non-transitory” specifically disavows fleeting characteristics such as characteristics of a carrier wave or signal or other forms that exist only transitorily in any place at any time. The processor 710 is an article of manufacture and/or a machine component. The processor 710 is configured to execute software instructions to perform functions as described in the various embodiments herein. The processor 710 may be a general- purpose processor or may be part of an application specific integrated circuit (ASIC). The processor 710 may also be a microprocessor, a microcomputer, a processor chip, a controller, a microcontroller, a digital signal processor (DSP), a state machine, or a programmable logic device. The processor 710 may also be a logical circuit, including a programmable gate array (PGA), such as a field programmable gate array (FPGA), or another type of circuit that includes discrete gate and/or transistor logic. The processor 710 may be a central processing unit (CPU), a graphics processing unit (GPU), or both. Additionally, any processor described herein may include multiple processors, parallel processors, or both. Multiple processors may be included in, or coupled to, a single device or multiple devices.

[0065] The term “processor” as used herein encompasses an electronic component able to execute a program or machine executable instruction. References to a computing device comprising “a processor” should be interpreted to include more than one processor or processing core, as in a multi-core processor. A processor may also refer to a collection of processors within a single computer system or distributed among multiple computer systems. The term computing device should also be interpreted to include a collection or network of computing devices each including a processor or processors. Programs have software instructions performed by one or multiple processors that may be within the same computing device or which may be distributed across multiple computing devices.

[0066] The computer system 700 further includes a main memory 720 and a static memory 730, where memories in the computer system 700 communicate with each other and the processor 710 via a bus 708. Either or both of the main memory 720 and the static memory 730 may be considered representative examples of a memory of a controller, and store instructions used to implement some or all aspects of methods and processes described herein. Memories described herein are tangible storage mediums for storing data and executable software instructions and are non-transitory during the time software instructions are stored therein. As used herein, the term “non-transitory” is to be interpreted not as an eternal characteristic of a state, but as a characteristic of a state that will last for a period. The term “non-transitory” specifically disavows fleeting characteristics such as characteristics of a carrier wave or signal or other forms that exist only transitorily in any place at any time. The main memory 720 and the static memory 730 are articles of manufacture and/or machine components. The main memory 720 and the static memory 730 are computer-readable mediums from which data and executable software instructions can be read by a computer (e.g., the processor 710). Each of the main memory 720 and the static memory 730 may be implemented as one or more of random access memory (RAM), read only memory (ROM), flash memory, electrically programmable read only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, a hard disk, a removable disk, tape, compact disk read only memory (CD-ROM), digital versatile disk (DVD), floppy disk, blu-ray disk, or any other form of storage medium known in the art. The memories may be volatile or non-volatile, secure and/or encrypted, unsecure and/or unencrypted. [0067] “Memory” is an example of a computer-readable storage medium. Computer memory is any memory which is directly accessible to a processor. Examples of computer memory include, but are not limited to RAM memory, registers, and register files. References to “computer memory” or “memory” should be interpreted as possibly being multiple memories. The memory may for instance be multiple memories within the same computer system. The memory may also be multiple memories distributed amongst multiple computer systems or computing devices. [0068] As shown, the computer system 700 further includes a video display unit 750, such as a liquid crystal display (LCD), an organic light emitting diode (OLED), a flat panel display, a solid-state display, or a cathode ray tube (CRT), for example. Additionally, the computer system 700 includes an input device 760, such as a keyboard/virtual keyboard or touch-sensitive input screen or speech input with speech recognition, and a cursor control device 770, such as a mouse or touch-sensitive input screen or pad. The computer system 700 also optionally includes a disk drive unit 780, a signal generation device 790, such as a speaker or remote control, and/or a network interface device 740.

[0069] In an embodiment, as depicted in FIG. 7, the disk drive unit 780 includes a computer- readable medium 782 in which one or more sets of software instructions 784 (software) are embedded. The sets of software instructions 784 are read from the computer-readable medium 782 to be executed by the processor 710. Further, the software instructions 784, when executed by the processor 710, perform one or more steps of the methods and processes as described herein. In an embodiment, the software instructions 784 reside all or in part within the main memory 720, the static memory 730 and/or the processor 710 during execution by the computer system 700. Further, the computer-readable medium 782 may include software instructions 784 or receive and execute software instructions 784 responsive to a propagated signal, so that a device connected to a network 701 communicates voice, video or data over the network 701. The software instructions 784 may be transmitted or received over the network 701 via the network interface device 740.

[0070] In an embodiment, dedicated hardware implementations, such as application-specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), programmable logic arrays and other hardware components, are constructed to implement one or more of the methods described herein. One or more embodiments described herein may implement functions using two or more specific interconnected hardware modules or devices with related control and data signals that can be communicated between and through the modules. Accordingly, the present disclosure encompasses software, firmware, and hardware implementations. Nothing in the present application should be interpreted as being implemented or implementable solely with software and not hardware such as a tangible non-transitory processor and/or memory.

[0071] In accordance with various embodiments of the present disclosure, the methods described herein may be implemented using a hardware computer system that executes software programs. Further, in an exemplary, non-limited embodiment, implementations can include distributed processing, component/object distributed processing, and parallel processing. Virtual computer system processing may implement one or more of the methods or functionalities as described herein, and a processor described herein may be used to support a virtual processing environment. [0072] Accordingly, distributed ultrasound including a wearable ultrasound device enhances pregnancy care, notably for high risk pregnancies.

[0073] Although distributed ultrasound including a wearable ultrasound device has been described with reference to several exemplary embodiments, it is understood that the words that have been used are words of description and illustration, rather than words of limitation. Changes may be made within the purview of the appended claims, as presently stated and as amended, without departing from the scope and spirit of distributed ultrasound including a wearable ultrasound device in its aspects. Although distributed ultrasound including a wearable ultrasound device has been described with reference to particular means, materials and embodiments, distributed ultrasound including a wearable ultrasound device is not intended to be limited to the particulars disclosed; rather distributed ultrasound including a wearable ultrasound device extends to all functionally equivalent structures, methods, and uses such as are within the scope of the appended claims.

[0074] The illustrations of the embodiments described herein are intended to provide a general understanding of the structure of the various embodiments. The illustrations are not intended to serve as a complete description of all of the elements and features of the disclosure described herein. Many other embodiments may be apparent to those of skill in the art upon reviewing the disclosure. Other embodiments may be utilized and derived from the disclosure, such that structural and logical substitutions and changes may be made without departing from the scope of the disclosure. Additionally, the illustrations are merely representational and may not be drawn to scale. Certain proportions within the illustrations may be exaggerated, while other proportions may be minimized. Accordingly, the disclosure and the figures are to be regarded as illustrative rather than restrictive.

[0075] One or more embodiments of the disclosure may be referred to herein, individually and/or collectively, by the term “invention” merely for convenience and without intending to voluntarily limit the scope of this application to any particular invention or inventive concept. Moreover, although specific embodiments have been illustrated and described herein, it should be appreciated that any subsequent arrangement designed to achieve the same or similar purpose may be substituted for the specific embodiments shown. This disclosure is intended to cover any and all subsequent adaptations or variations of various embodiments. Combinations of the above embodiments, and other embodiments not specifically described herein, will be apparent to those of skill in the art upon reviewing the description.

[0076] The Abstract of the Disclosure is provided to comply with 37 C.F.R. §1.72(b) and is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, various features may be grouped together or described in a single embodiment for the purpose of streamlining the disclosure. This disclosure is not to be interpreted as reflecting an intention that the claimed embodiments require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter may be directed to less than all of the features of any of the disclosed embodiments. Thus, the following claims are incorporated into the Detailed Description, with each claim standing on its own as defining separately claimed subject matter.

[0077] The preceding description of the disclosed embodiments is provided to enable any person skilled in the art to practice the concepts described in the present disclosure. As such, the above disclosed subject matter is to be considered illustrative, and not restrictive, and the appended claims are intended to cover all such modifications, enhancements, and other embodiments which fall within the true spirit and scope of the present disclosure. Thus, to the maximum extent allowed by law, the scope of the present disclosure is to be determined by the broadest permissible interpretation of the following claims and their equivalents and shall not be restricted or limited by the foregoing detailed description.

Claims

CLAIMS:

1. An ultrasound system, comprising: a first wearable ultrasound device comprising: a first memory that stores first instructions; and a first processor that executes the first instructions, wherein, when executed by the first processor, the first instructions cause the ultrasound system to: transmit ultrasound waves and receive ultrasound echoes while automatically switching between modes including an imaging mode and a Doppler mode; and generate ultrasound data for ultrasound images during the imaging mode for localization of fetal anatomy of a fetus in the ultrasound images in the imaging mode to produce biomarkers including fetal heart, fetal movements, amniotic fluid quantity and fetal heart rate measurement in the Doppler mode.

2. The ultrasound system of claim 1, further comprising: a second wearable ultrasound device comprising: a second memory that stores second instructions; and a second processor that executes the second instructions, wherein, when executed by the second processor, the second instructions cause the ultrasound system to: transmit ultrasound waves and receive ultrasound echoes while automatically switching between modes including an imaging mode and a Doppler mode; generate ultrasound data for ultrasound images during the imaging mode for localization of fetal anatomy of a fetus in the ultrasound images in the imaging mode to produce biomarkers including fetal heart, fetal movements, and amniotic fluid quantity and the fetal heart rate measurement in the Doppler mode, wherein the ultrasound system is configured to distinguish location of a first heart measured by the first wearable ultrasound device from location of a second heart measured by the second wearable ultrasound device.

3. The ultrasound system of either of claims 1 or 2, wherein the fetal movements include respiratory movement, limb movement and gross movement.

4. The ultrasound system of any one of claims 1, 2 or 3, further comprising: a computer that analyses the ultrasound data to localize the fetal anatomy of the fetus in the ultrasound images to produce the biomarkers including fetal heart, fetal movements, and amniotic fluid quantity, wherein the first wearable ultrasound device further comprises a transmitter that transmits the ultrasound data to the computer.

5. The ultrasound system of claim 4, wherein the computer is configured to apply an artificial intelligence model to the ultrasound data to localize the fetal anatomy in the ultrasound images in the imaging mode, and after localizing the fetal anatomy in the ultrasound images in the imaging mode, continuously tracing the fetus in the ultrasound images.

6. The ultrasound system of any one of claims 1, 2, 3 or 4, further comprising: an interface by which the ultrasound data is transmitted to a cloud service which localizes the fetal anatomy of the fetus in the ultrasound images to produce the biomarkers including fetal heart, fetal movements, and amniotic fluid quantity.

7. A system for scoring fetal health, comprising: a memory that stores instructions; and a processor that executes the instructions, wherein, when executed by the processor, the instructions cause the system to: identify, by analyzing ultrasound images of a fetus, five biomarkers including fetal heart, respiratory movement, limb movement, gross movement, and amniotic fluid quantity; assign an individual score to each of the five biomarkers including fetal heart, respiratory movement, limb movement, gross movement, and amniotic fluid quantity; sum the individual score for each of the five biomarkers to obtain a sum; compare the sum to a predetermined threshold to score fetal health for the fetus; and provide feedback including at least one of the sum or a score for the fetal health.

8. The system of claim 7, further comprising: classifying the respiratory movement, limb movement and gross movement.

9. The system of either of claims 7 or 8, further comprising: receiving, over a communications network at a centralized system, the ultrasound images from a remote ultrasound system that generates the ultrasound images; and reporting the score for the fetal health over the communications network in response to receiving the ultrasound images.

10. The system of any one of claims 7, 8 or 9, wherein, when executed by the processor, the instructions further cause the system to: apply trained artificial intelligence to the ultrasound images to localize anatomy of the fetus and identify the five biomarkers.

11. The system of any one of claims 7, 8, 9 or 10, wherein, when executed by the processor, the instructions further cause the system to: distinguish between modes in which the ultrasound images are captured.

12. An ultrasound method, comprising transmitting, from a wearable ultrasound device, ultrasound waves and receiving, by the wearable ultrasound device, echoes of the ultrasound waves, while automatically switching between modes including an imaging mode and a Doppler mode; and generating, by the wearable ultrasound device, ultrasound data for ultrasound images during the imaging mode and the Doppler mode for localization of fetal anatomy of a fetus in the ultrasound images in the imaging mode to produce biomarkers including fetal heart, fetal movements, and amniotic fluid quantity in the Doppler mode.

13. The ultrasound method of claim 12, wherein the fetal movements include respiratory movement, limb movement and gross movement.

14. The ultrasound method of either of claims 12 or 13, further comprising: transmitting, by the wearable ultrasound device, the ultrasound data to a computer; analyzing, by the computer, the ultrasound data to localize the fetal anatomy of the fetus in the ultrasound images to produce the biomarkers including fetal heart, fetal movements, and amniotic fluid quantity.

15. The ultrasound method of claim 14, further comprising: applying, by the computer, an artificial intelligence model to the ultrasound data to localize the fetal anatomy in the ultrasound images in the imaging mode, and after localizing the fetal anatomy in the ultrasound images in the imaging mode, continuously tracing the fetus in the ultrasound images.

16. The ultrasound method of any one of claims 12, 13 or 14, further comprising: transmitting the ultrasound data to a cloud service which localizes the fetal anatomy of the fetus in the ultrasound images to produce the biomarkers including fetal heart, fetal movements, and amniotic fluid quantity.