Systems, Devices, Apps, and Methods for Capsule Endoscopy Procedures

Abstract

Disclosed are systems, devices, and methods for a capsule endoscopy procedure. The system for a capsule endoscopy procedure includes a capsule device configured to capture in-vivo images of at least a portion of a person's gastrointestinal tract (GIT) over time, a wearable device configured to be secured to the person, the wearable device configured to receive at least some of the in-vivo images from the capsule device and to communicate at least some of the received images to a communication device co-located with the wearable device, and a storage medium storing machine-executable instructions configured to be executed on a computing system remote from the location of the wearable device.

Description

Technical Field

[0001] (Cross - Reference to Related Applications) This application claims the benefit and priority of U.S. Provisional Application No. 62 / 849,508, filed on May 17, 2019, and U.S. Provisional Application No. 62 / 867,050, filed on Jun. 26, 2019. The entire contents of all priority applications are incorporated herein by reference.

[0002] (Field of the Invention) The present disclosure generally relates to capsule endoscopy procedures, and more specifically, to flexible systems, devices, apps, and methods for performing capsule endoscopy procedures in various ways and configurations.

Background Art

[0003] Capsule endoscopy (CE) enables endoscopic examination of the entire gastrointestinal tract (GIT). There are capsule endoscopy systems and methods aimed at examining specific parts of the GIT, such as the small intestine or colon. CE is a non - invasive procedure that does not require the patient to be hospitalized, and the patient can generally continue most daily activities while the capsule is inside the body. The patient can also continue to take regular medications.

[0004] In a typical CE procedure, the patient is referred for the procedure by a physician. The patient then arrives at a healthcare facility (such as a clinic or hospital) to have the procedure performed. The patient is admitted by a healthcare provider (HCP) such as a nurse and / or physician, who sets up, manages, and oversees the specific procedure. In some cases, the HCP may be the referring physician. A capsule, approximately the size of a multivitamin, is swallowed by the patient under the supervision of the HCP at the healthcare facility, and the patient is provided with a wearable device, such as a sensor belt, and a recorder placed within a pouch and strap that is placed around the patient's shoulder. The wearable device typically includes a memory device. After being given instructions and / or guidance, the patient may be released to go about their daily activities. The capsule captures images as it naturally moves through the GIT. The images and additional data (such as metadata) are then transmitted to the recorder worn by the patient. The capsule is disposable and progresses naturally with intestinal movement. The procedure data (such as the captured images or portions thereof and additional metadata) is stored on the memory device of the wearable device.

[0005] The wearable device is typically returned to the healthcare facility by the patient, along with the procedure data stored thereon. The procedure data is then downloaded to a computing device, typically located at the healthcare facility, where the engine software is stored. The received procedure data is then processed by the engine into a compiled investigation. Typically, the number of images processed is on the order of tens of thousands, averaging approximately 90,000 to 100,000. Typically, the compiled investigation includes thousands of images (about 6,000 to 9,000). Since the patient is required to return the wearable device to the HCP or healthcare facility and only then will the procedure data be processed, the compiled investigation and report will usually not be generated on the same day of the procedure or shortly thereafter.

[0006] The leader (who may be the treating supervising physician, the dedicated physician, or the referring physician) can access the compiled investigation via the leader application. The leader then reviews the compiled investigation, evaluates the treatment, and provides his input via the leader application. Since the leader needs to review thousands of images, the reading time of the compiled investigation usually may on average take half an hour to 1 hour, and the reading work can be cumbersome. Then, based on the compiled investigation and the leader's input, a report is generated by the leader application. On average, it takes 1 hour to generate the report. The report may include, for example, images of interest, such as treatment data, and / or images identified as including the pathology, evaluation, or diagnosis of the patient's medical condition, based on recommendations for follow-up and / or treatment. The report may then be transferred to the referring physician. The referring physician can determine the necessary follow-up or treatment based on the report.

[0007] Some capsule procedures, specifically those directed to the colon, may require patient preparation. For example, it may be necessary to empty the colon and / or small intestine. To wash the intestine, the physician may prescribe a diet and / or medications, such as a prep solution and / or a relaxant that the patient takes before the procedure. It is important that the patient follow all instructions and take all preparatory medications to ensure that the patient's GIT can be properly viewed. In addition, the patient may also be required to follow a diet and / or take medications (such as a relaxant) after the capsule is swallowed and during the procedure (referred to herein as "boost"). The recorder can warn the patient if this step needs to be repeated to ensure a complete procedure. Typically, the physician (e.g., the referring physician or the physician supervising the procedure) determines the preparation suitable for the patient and the desired type of capsule procedure. SUMMARY OF THE INVENTION PROBLEMS TO BE SOLVED BY THE INVENTION

[0008] The present disclosure relates to systems, devices, apps, and methods for capsule endoscopy procedures. More specifically, the present disclosure relates to systems, devices, apps, and methods for coordinating, performing, evaluating, and monitoring multiple capsule endoscopy procedures simultaneously. The networked systems and devices provide the ability for a patient to perform a capsule endoscopy procedure, in whole or in part, outside of a healthcare facility, if desired, and for healthcare professionals to remotely access and evaluate data from the capsule endoscopy procedure during and / or after the procedure. The disclosed systems, devices, apps, and methods are flexible and enable capsule endoscopy procedures to be performed in a variety of ways and configurations.

Means for Solving the Problems

[0009] According to an aspect of the present disclosure, a system for a capsule endoscopy procedure includes a capsule device configured to capture in vivo images of at least a portion of a human gastrointestinal tract (GIT) over time, a wearable device configured to be secured to a person, the wearable device being configured to receive at least some of the in vivo images from the capsule device and to communicate at least some of the received images to a communication device at the same location as the wearable device, and a storage medium storing machine-executable instructions configured to be executed on a remote computing system from the location of the wearable device. The instructions, when executed, cause the computing system to receive communication images from the communication device, execute processing of the communication images received from the communication device, and communicate with at least one healthcare provider device.

[0010] In various embodiments of the present system, the computing system is a cloud system, and the cloud system includes the storage medium.

[0011] In various embodiments of the system, the communication device is a mobile device carried by a person, and the system further comprises a patient app configured to be installed on the mobile device and to interoperate with wearable devices and computing systems.

[0012] In various embodiments of the system, the patient app is configured to set up the communication of data from a wearable device to a computing system via the mobile device.

[0013] In various embodiments of the system, when executed, the instructions further cause the computing system to coordinate the communication between the patient app and at least one of at least one healthcare provider device.

[0014] In various embodiments of the system, prior to a capsule endoscopy procedure, the patient app is configured to receive patient confirmation that the patient preparation regimen has been completed and to communicate the patient confirmation to the computing system, and when executed, the instructions cause the computing system to communicate the patient confirmation to at least one of at least one healthcare provider device.

[0015] In various embodiments of the system, during a capsule endoscopy procedure, the wearable device is configured to communicate to the patient app instructions for a person to ingest a boosting agent.

[0016] In various embodiments of the system, the patient app is configured to receive instructions, to display on the mobile device instructions for a person to ingest a boosting agent, and to receive patient confirmation that the instructions have been completed.

[0017] According to an aspect of the present disclosure, a method for a capsule endoscopy procedure includes capturing in vivo images of at least a portion of a human gastrointestinal tract (GIT) over time by a capsule device, receiving at least some of the in vivo images from the capsule device by a wearable device configured to be fixed to a person, communicating at least some of the received images by the wearable device to a communication device at the same position as the wearable device, receiving a communicated image from the communication device by a remote computing system from the position of the wearable device, executing processing of the communicated image received from the communication device by the computing system, and communicating by the computing system with at least one healthcare provider device.

[0018] In various embodiments of the method, the computing system is a cloud system.

[0019] In various embodiments of the method, the communication device is a mobile device carried by a person, and the mobile device comprises a patient app configured to interoperate with the wearable device and the computing system.

[0020] In various embodiments of the method, the method further comprises setting up communication of data from the wearable device to the computing system via the mobile device by the patient app.

[0021] In various embodiments of the method, the method further comprises coordinating communication between the patient app and at least one of the at least one healthcare provider device by the computing system.

[0022] In various embodiments of the method, the method further includes receiving, by a patient app, patient confirmation that a patient preparation regimen has been completed prior to a capsule endoscopy procedure; communicating, by the patient app, the patient confirmation to a computing system; and communicating, by the computing system, the patient confirmation to at least one of at least one healthcare provider device.

[0023] In various embodiments of the method, the method further includes communicating, by a wearable device, to a patient app, instructions for a person to ingest a boosting agent during a capsule endoscopy procedure.

[0024] In various embodiments of the method, the method further includes receiving, by the patient app, the instructions; displaying, on a mobile device, the instructions for ingesting the boosting agent; and receiving, by the patient app, patient confirmation that the instructions have been completed.

[0025] In various embodiments of the method, the method includes displaying, on a display device, for user review, a subset of images from an in-vivo image over time, wherein the subset of images represents at least a portion of the captured in-vivo image, and the subset of images is automatically selected from the in-vivo image by one or more hardware processors according to a first selection method; receiving a user selection of one of the displayed images from the subset of displayed images; displaying, on the display device, one or more additional images corresponding to the one displayed image based on the user selection, wherein the one or more additional images are automatically selected from the in-vivo image by one or more hardware processors according to a second selection method, and the second selection method is based on a relationship between an image of the in-vivo image and the one displayed image; and generating a report, wherein the report includes an image from the displayed image selected by the user.

[0026] In various embodiments of the method, the method further includes selecting a subset of images according to a first selection method and, for each image of at least a portion of the subset of images, selecting one or more corresponding additional images from the in vivo images according to a second selection method.

[0027] According to an aspect of the present disclosure, a system for a capsule endoscopy procedure includes a capsule device configured to capture in vivo images of at least a portion of a human gastrointestinal tract (GIT) over time, and a wearable device configured to be fixed to a person and receive at least some of the in vivo images from the capsule device, the wearable device storing the received images, and a storage medium storing machine-executable instructions configured to be executed on a computer system. The instructions, when executed, cause the computing system to receive at least some of the stored images from the wearable device during a capsule endoscopy procedure, perform online processing of the images received from the wearable device during the capsule endoscopy procedure, and provide the results of the online processing during the capsule endoscopy procedure.

[0028] In various embodiments of the system, executing online processing of the images includes applying machine learning to the images received from the wearable device to estimate whether the images received from the wearable device include a transition from an image of a segment of the GIT to an image beyond the segment of the GIT, the system of claim 19.

[0029] In various embodiments of the system, if the image includes a transition, the computing system is configured to communicate a message indicating that the capsule endoscopy procedure is complete and the wearable device can be removed, the message being communicated to at least one of a device carried by a person or the wearable device.

[0030] In various embodiments of the system, the segment of the GIT is the small intestine, and the images include the transition from images of the small intestine to images of the colon.

[0031] In various embodiments of the system, performing online processing of the images includes applying machine learning to estimate the location of the GIT where the image was captured for each image received from the wearable device.

[0032] In various embodiments of the system, performing online processing of the images includes estimating the presence of at least one event indicator.

[0033] In various embodiments of the system, at least one event indicator is within a predetermined category of urgent medical risk, and when the presence of at least one event indicator is estimated, the computing system is configured to communicate a warning message indicating the estimated presence of the urgent medical risk to the device of the healthcare provider.

[0034] In various embodiments of the system, the warning message includes at least one image indicating at least one event indicator, and the warning message optionally includes the location of the GIT where at least one event indicator is estimated to be present.

[0035] In various embodiments of the system, at least one event indicator requires a colonoscopy.

[0036] In various embodiments of the system, the computing system is configured to communicate a message regarding an order for a same-day colonoscopy to the device of the person, and the same-day colonoscopy is scheduled on the same day as the capsule endoscopy procedure.

[0037] In various embodiments of the system, at least one event indicator is a polyp.

[0038] In various embodiments of the present system, at least one event indicator that requires a colonoscopy is reported to the healthcare provider's device as a provisional finding during a capsule endoscopy procedure, and the provisional finding is generated based on at least some of the in-vivo images captured up to that point by the capsule device at the time during the capsule endoscopy procedure.

[0039] In various embodiments of the present system, performing online processing of the images includes generating provisional findings based on at least some of the in-vivo images captured up to that point by the capsule device at the time during the capsule endoscopy procedure.

[0040] In various embodiments of the present system, the provisional findings include at least one of the in-vivo images indicating the presence of at least one event indicator.

[0041] In various embodiments of the present system, the provisional findings further include the location of the GIT where at least one event indicator is present.

[0042] In various embodiments of the present system, the time point is one of a preset time interval for generating provisional findings, a time corresponding to a request to generate provisional findings, or a time corresponding to the online detection of at least one event indicator.

[0043] In various embodiments of the present system, the online detection includes at least one of online detection of anatomical landmarks, online detection of anatomical segments, or online detection of the presence of a medical condition.

[0044] According to an aspect of the present disclosure, a method for a capsule endoscopy procedure includes capturing in vivo images of at least a portion of a human gastrointestinal tract (GIT) over time by a capsule device; receiving at least some of the in vivo images from the capsule device by a wearable device configured to be fixed to a person; storing the received images by the wearable device; receiving at least some of the stored images from the wearable device by a computing system during the capsule endoscopy procedure; performing online processing of the images received from the wearable device by the computing system during the capsule endoscopy procedure; and providing the results of the online processing by the computing system during the capsule endoscopy procedure.

[0045] In various embodiments of the method, performing online processing of the images includes applying machine learning to the images received from the wearable device to estimate whether the images received from the wearable device include a transition from an image of a segment of the GIT to an image beyond the segment of the GIT.

[0046] In various embodiments of the method, the method further includes communicating, by the computing system, a message indicating that the capsule endoscopy procedure is complete and the wearable device can be removed when the images include a transition, the message being communicated to at least one of a device carried by a person or the wearable device.

[0047] In various embodiments of the method, the segment of the GIT is the small intestine, and the images include a transition from an image of the small intestine to an image of the colon.

[0048] In various embodiments of the method, performing online processing of the images includes applying machine learning to estimate the location of the GIT where each image was captured for each image received from the wearable device.

[0049] In various embodiments of the method, performing online processing of an image includes inferring the presence of at least one event indicator.

[0050] In various embodiments of the method, at least one event indicator is within a predetermined category of urgent medical risk, and the method further includes, when it is inferred that at least one event indicator is present, communicating, by a computing system, a warning message indicating the inferred presence of urgent medical risk to a healthcare provider's device.

[0051] In various embodiments of the method, the warning message includes at least one image indicating at least one event indicator, and the warning message optionally includes the location of the GIT where at least one event indicator is inferred to be present.

[0052] In various embodiments of the method, at least one event indicator requires a colonoscopy.

[0053] In various embodiments of the method, the method further includes communicating, by a computing system, a message regarding an order for a same-day colonoscopy to a person's device, where the same-day colonoscopy is scheduled on the same day as a capsule endoscopy procedure.

[0054] In various embodiments of the method, at least one event indicator requires a colonoscopy.

[0055] In various embodiments of the method, at least one event indicator that requires a colonoscopy is reported to a healthcare provider's device as a provisional finding of a capsule endoscopy procedure during the capsule endoscopy procedure, and the provisional finding is generated based on at least some of the in-vivo images captured up to that point by the capsule device at a point in time during the capsule endoscopy procedure.

[0056] In various embodiments of the method, performing online processing of an image includes generating provisional findings based on at least some of the in-vivo images captured by the capsule device up to a point in time during a capsule endoscopy procedure.

[0057] In various embodiments of the method, the provisional findings include at least one of the in-vivo images indicating the presence of at least one event indicator.

[0058] In various embodiments of the method, the provisional findings further include the location of the GIT where at least one event indicator is present.

[0059] In various embodiments of the method, the point in time is one of a pre-set time interval for generating provisional findings, a time corresponding to a request to generate provisional findings, or a time corresponding to the online detection of at least one event indicator.

[0060] In various embodiments of the method, the online detection includes at least one of online detection of anatomical landmarks, online detection of anatomical segments, or online detection of the presence of a medical condition.

[0061] According to an aspect of the present disclosure, a system for a capsule endoscopy procedure includes a capsule device configured to capture in-vivo images of at least a portion of a human gastrointestinal tract (GIT) over time, and a wearable device configured to be fixed to a person, the wearable device being configured to wirelessly receive at least some of the in-vivo images captured by the capsule device, the wearable device and the capsule device being uniquely coupled such that the capsule device cannot communicate with another wearable device and the wearable device cannot communicate with another capsule device.

[0062] In various embodiments of the present system, the wearable device includes a transceiver configured to connect to a communication device, and the wearable device is configured to communicate at least some of the received images to a remote computing system via the communication device.

[0063] In various embodiments of the present system, the remote computing system is a cloud system.

[0064] In various embodiments of the present system, the transceiver is a cellular transceiver and the communication device is a device of a cellular network.

[0065] In various embodiments of the present system, the communication device is a router.

[0066] In various embodiments of the present system, the communication device is an Internet-enabled mobile device.

[0067] In various embodiments of the present system, the transceiver is configured to communicate data, and the wearable device further includes a second transceiver configured to communicate control information with an Internet-enabled mobile device.

[0068] In various embodiments of the present system, the wearable device is a patch configured to removably adhere to a person's skin.

[0069] In various embodiments of the present system, the patch is configured to be a single-use disposable device.

[0070] In various embodiments of the present system, the present system further includes a mailable kit including a uniquely coupled capsule device and a wearable device.

[0071] In various embodiments of the present system, the wearable device can be configured to operate in access point (AP) mode as a wireless access point and in client mode as a wireless client.

[0072] In various embodiments of the present system, in client mode, the wearable device is configured as a wireless client of a communication device and is configured to communicate at least some of the received images to a computing system via the communication device. In AP mode, the wearable device is configured as a wireless access point to another wireless device and is configured to communicate at least some of the received images to another wireless device.

[0073] In various embodiments of the present system, when the wearable device operates in AP mode, the wearable device is configured to activate client mode after a predetermined time to ping the communication device.

[0074] In various embodiments of the present system, the wearable device includes an internal storage device configured to store at least some of the images received from the capsule device. When the wearable device operates in AP mode, the wearable device is configured to communicate a copy of the images stored in the internal storage device to another wireless device and to maintain the stored images within the internal storage device.

[0075] In various embodiments of the present system, when AP mode ends, the wearable device is configured to activate client mode to communicate the stored images to a computing system via a mobile device.

[0076] In various embodiments of the present system, the wearable device includes an internal storage device, and the internal storage device stores machine-executable instructions that implement at least some online processing of the received images using machine learning.

[0077] In various embodiments of the present system, the capsule device is configured to perform at least some online processing of the in-vivo images to determine similarity, and based on the similarity determination, not to communicate at least one of the in-vivo images to the wearable device.

[0078] In various embodiments of the present system, the wearable device is configured to perform at least some online processing of the received images using machine learning.

[0079] According to an aspect of the present disclosure, a method for providing a capsule endoscopy procedure at home includes receiving an online registration for a capsule endoscopy procedure prescribed to a person by a healthcare provider (HCP), receiving an online indicator that the capsule endoscopy procedure has been started, receiving, in a cloud system, images of the person's gastrointestinal tract, the images being captured while the capsule device traverses the person's gastrointestinal tract and communicated to the cloud system via the wearable device during the capsule endoscopy procedure, generating a capsule endoscopy investigation based on at least some of the received images by the cloud system, providing access to the capsule endoscopy investigation to a reader, generating a capsule endoscopy report based on the capsule endoscopy investigation and the input provided by the reader, and providing the capsule endoscopy report to the HCP, wherein the capsule device and the wearable device are disposable and uniquely coupled, and the capsule device and the wearable device are ordered online based on a prescription provided by the HCP and mailed to the delivery address provided in the order.

[0080] In various embodiments of the method, the capsule endoscopy kit is a home screening capsule endoscopy kit, and the capsule endoscopy procedure is an endoscopy screening procedure.

[0081] In various embodiments of the method, the method comprises receiving an online order for a capsule endoscopy kit based on a prescription provided by a healthcare provider (HCP) for a person's capsule endoscopy procedure, wherein the capsule endoscopy kit includes a disposable capsule device and a disposable wearable device, the disposable capsule device and the disposable wearable device being uniquely coupled, and further comprising mailing the capsule endoscopy kit to a delivery address provided in the order.

[0082] According to an aspect of the present disclosure, a method for a colon capsule endoscopy procedure comprises receiving images of a person's gastrointestinal tract (GIT) captured during the colon capsule endoscopy procedure, wherein the GIT includes the colon, identifying, among the received images during the colon capsule endoscopy procedure and up to a predefined procedure event, one or more suspicious colon images, wherein the one or more suspicious colon images are identified as images of the colon and include candidates for a predefined event indicator that requires a colonoscopy, the predefined procedure event occurring while the colon capsule endoscopy device traverses the colon, providing the one or more suspicious colon images to a healthcare provider during the colon capsule endoscopy procedure, and storing an indicator that a colonoscopy required for the person is scheduled on the same day as the colon capsule endoscopy procedure.

[0083] In various embodiments of the method, the method further comprises instructing the person to take a preparation regimen prior to the colon capsule endoscopy procedure.

[0084] In various embodiments of the method, the pre - defined event indicator is a polyp growth that requires a colonoscopy.

[0085] In various embodiments of the method, the method further includes providing to a healthcare provider additional information including at least one of position information indicating which segment of the colon is shown in one or more suspect colon images, information regarding candidates in one or more suspect colon images, or an estimate of the type of event indicator, during a colon capsule endoscopy procedure.

[0086] In various embodiments of the method, the colonoscopy required for a person is based on a review of one or more suspect colon images by a healthcare provider and a determination by the healthcare provider that a colonoscopy is required. The method further includes communicating to the person a message that a colonoscopy is required and receiving an indication that the person has consented to a same - day colonoscopy.

[0087] In various embodiments of the method, identifying one or more suspect colon images is performed by a cloud system using machine learning. The present invention provides, for example, the following. (Item 1) A system for a capsule endoscopy procedure, a capsule device configured to capture in-vivo images of at least a portion of a human gastrointestinal tract (GIT) over time, a wearable device configured to be fixed to the human, the wearable device being configured to receive at least some of the in-vivo images from the capsule device, store the received images, and communicate at least some of the received images to a communication device at the same location as the wearable device, a wearable device, a storage medium storing machine-executable instructions configured to be executed on a remote computing system from the location of the wearable device, the instructions, when executed, causing the computing system to, receive a communication image from the communication device during the capsule endoscopy procedure, perform online processing of the communication image received from the communication device during the capsule endoscopy procedure, communicate the result of the online processing to at least one healthcare provider device during the capsule endoscopy procedure, a storage medium, a system comprising. (Item 2) The computing system is a cloud system, and the cloud system comprises the storage medium, the system according to item 1 or the method according to item 9. (Item 3) The communication device is a mobile device carried by the human, and the system further comprises a patient application configured to be installed on the mobile device and interoperate with the wearable device and the computing system, the patient application being configured to set up communication of data from the wearable device to the computing system via the mobile device, the system according to item 1. (Item 5) The instructions, when executed, further cause the computing system to adjust communication between the patient application and at least one of the at least one healthcare provider device, the system according to item 1. (Item 6) Before the capsule endoscopy procedure, The patient app is configured to receive patient confirmation that the patient preparation regimen has been completed and communicate the patient confirmation to the computing system. The system of item 5, wherein the instructions, when executed, cause the computing system to communicate the patient confirmation to at least one of the at least one healthcare provider device. (Item 7) During the capsule endoscopy procedure, the wearable device is configured to communicate to the patient app an instruction for the person to ingest a boost agent. The system of item 3, wherein the patient app is configured to receive the instruction on the mobile device, display the instruction for the person to ingest the boost agent, and receive patient confirmation that the instruction has been completed. (Item 9) A method for a capsule endoscopy procedure, comprising: capturing, by a capsule device, in-vivo images of at least a portion of a person's gastrointestinal tract (GIT) over time; receiving and storing, by a wearable device configured to be fixed to the person, at least some of the in-vivo images from the capsule device; communicating, by the wearable device, at least some of the received images to a communication device at the same location as the wearable device; receiving, during the capsule endoscopy procedure, by a remote computing system from the communication device, communication images from the location of the wearable device; performing, during the capsule endoscopy procedure, online processing of the communication images received from the communication device by the computing system; communicating, during the capsule endoscopy procedure, the results of the online processing to at least one healthcare provider device. (Item 20) Performing the online processing of the images includes applying machine learning to the images received from the wearable device to estimate whether the images received from the wearable device include a transition from an image of a segment of the GIT to an image beyond the segment of the GIT. (Item 21) When the image includes the transition, the computing system is configured to communicate a message indicating that the capsule endoscopy procedure is complete and that the wearable device can be removed, the message being communicated to at least one of the device carried by the person or the wearable device, the system of item 20. (Item 23) Executing the online processing of the image is applying machine learning to estimate the location of the GIT where the image was captured for each image received from the wearable device, or estimating the existence of at least one event indicator, the system of item 1 including at least one of these. (Item 25) The at least one event indicator is within a predetermined category of urgent medical risk, when the existence of the at least one event indicator is estimated, the computing system is configured to communicate a warning message indicating the estimated existence of the urgent medical risk to a device of a healthcare provider, the system of item 23. (Item 26) The warning message includes at least one image indicating the at least one event indicator, and the warning message optionally includes the location of the GIT where the at least one event indicator is estimated to exist, the system of item 25. (Item 27) The at least one event indicator requires a colonoscopy, the system of item 23. (Item 28) The computing system is configured to communicate a message regarding an order for a same-day colonoscopy to the person's device, the same-day colonoscopy being scheduled on the same day as the capsule endoscopy procedure, the system of item 27. (Item 31) Executing the online processing of the image includes generating provisional findings based on at least some of the in-vivo images captured by the capsule device up to that point in time during the capsule endoscopy procedure, the system of item 1. (Item 32) The provisional findings include at least one of the in-vivo images indicating the existence of at least one event indicator, The system according to item 31, wherein the tentative finding further includes the position of the GIT where the at least one event indicator is present. (Item 34) The system according to item 31, wherein the time point is one of a preset time interval for generating the tentative finding, a time corresponding to a request for generating the tentative finding, or a time corresponding to an online detection of at least one event indicator. (Item 35) The system according to item 34, wherein the online detection includes at least one of online detection of anatomical landmarks, online detection of anatomical segments, or online detection of the presence of a medical condition. (Item 53) The system according to item 1, wherein the wearable device and the capsule device are uniquely coupled such that the capsule device cannot communicate with another wearable device and the wearable device cannot communicate with another capsule device. (Item 54) The system according to item 1 or 53, wherein the wearable device includes a transceiver configured to connect to the communication device, and the wearable device is configured to communicate at least some of the received images to the remote computing system via the communication device. (Item 57) The system according to item 54, wherein the communication device is one of a router or an internet-enabled mobile device. (Item 60) The system according to item 1 or 53, wherein the wearable device is a patch configured to removably adhere to the person's skin. (Item 61) The system according to item 60, wherein the patch is configured to be a single-use disposable device. (Item 62) The system according to item 53, further comprising a mailable kit including the uniquely coupled capsule device and the wearable device. (Item 63) The system according to item 1 or 53, wherein the wearable device is configurable to operate in access point (AP) mode as a wireless access point and in client mode as a wireless client. (Item 68) The system according to item 1 or 53, wherein the wearable device includes an internal memory device, and the internal memory device stores machine-executable instructions that implement at least some online processing of the received images using machine learning. (Item 69) The system according to item 1 or 53, wherein the capsule device is configured to perform at least some online processing of the in-vivo images to determine similarity and, based on the similarity determination, not communicate at least one of the in-vivo images to the wearable device. (Item 71) A method for processing capsule endoscopy images, the method comprising receiving an online registration for a capsule endoscopy procedure prescribed to a person by a healthcare provider (HCP), receiving an online indicator that the capsule endoscopy procedure has been started, receiving, in a cloud system, images of the person's gastrointestinal tract, the images being captured by a capsule device while traversing the person's gastrointestinal tract and communicated to the cloud system via a wearable device during the capsule endoscopy procedure, generating, by the cloud system, a capsule endoscopy investigation based on at least some of the received images, providing access to the capsule endoscopy investigation to a reader, generating a capsule endoscopy report based on the capsule endoscopy investigation and input provided by the reader, providing the capsule endoscopy report to the HCP, wherein the capsule device and the wearable device are disposable and uniquely coupled, and the capsule device and the wearable device are ordered online based on a prescription provided by the HCP and mailed to a delivery address provided in the order. (Item 72) The method according to item 71, wherein the capsule endoscopy kit is a home screening capsule endoscopy kit and the capsule endoscopy procedure is an endoscopy screening procedure. (Item 74) A method for processing capsule endoscopy images, the method comprising Receiving an image of a person's gastrointestinal tract (GIT) captured during a colon capsule endoscopy procedure, wherein the GIT includes the colon, and identifying, during the colon capsule endoscopy procedure and up to a predefined procedure event, one or more suspicious colon images among the received images, wherein the one or more suspicious colon images are identified as images of the colon and including candidates for a predefined event indicator that requires a colonoscopy, and wherein the predefined procedure event occurs while the colon capsule endoscopy device is traversing the colon, and providing the one or more suspicious colon images to a healthcare provider during the colon capsule endoscopy procedure, and storing an indicator that a colonoscopy required for the person is scheduled on the same day as the colon capsule endoscopy procedure, a method comprising. (Item 77) The method according to item 74, further comprising providing to the healthcare provider additional information including at least one of position information indicating which segment of the colon is shown in the one or more suspicious colon images, information regarding the candidates in the one or more suspicious colon images, or an estimate of the type of the event indicator, during the colon capsule endoscopy procedure. (Item 78) Based on a review by the healthcare provider of the one or more suspicious colon images and a determination by the healthcare provider that a colonoscopy is required, the colonoscopy required for the person The method is The method according to item 74, further comprising communicating to the person a message that a colonoscopy is required and receiving an indicator that the person has consented to a same-day colonoscopy. (Item 79) The method according to item 74, wherein the identifying of the one or more suspicious colon images is performed by a cloud system using machine learning.

Brief Description of the Drawings

[0088] The above and other aspects and features of the present disclosure will become more apparent by considering the following detailed description together with the accompanying drawings. In the accompanying drawings, like reference numerals identify similar or identical elements.

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DETAILED DESCRIPTION OF THE INVENTION

[0119] For purposes of illustration and clarity, it will be understood that the elements shown in the figures are not necessarily drawn to scale. For example, the dimensions and / or aspect ratios of some of the elements may be exaggerated relative to other elements for clarity. Further, reference numbers may be repeated within the figures to indicate corresponding or similar elements throughout the series of figures where appropriate.

[0120] The present disclosure relates to systems, devices, apps, and methods for capsule endoscopy procedures. More specifically, the present disclosure relates to systems, devices, apps, and methods for coordinating, performing, evaluating, and monitoring multiple simultaneously-executed capsule endoscopy procedures. The networked systems and devices provide the ability for a patient to perform a capsule endoscopy procedure partially or fully outside of a healthcare facility, if desired, and for a healthcare professional to remotely monitor, access, and evaluate data from the capsule endoscopy procedure during and / or after the procedure. The disclosed systems and methods are flexible and enable capsule endoscopy procedures to be performed in a variety of ways and configurations. The disclosed systems, methods, devices, and apps are patient-friendly and can improve ease of use for both the patient and the healthcare provider, thereby enabling better performance and patient compliance. Further, by reducing the reading time of compiled investigations for capsule endoscopy, the disclosed systems, methods, devices, and apps enable better diagnosis and treatment.

[0121] In the following detailed description, specific details are set forth in order to provide a thorough understanding of the present disclosure. However, one skilled in the art would understand that the present disclosure may be practiced without these specific details. In other instances, well-known methods, procedures, and components have not been described in detail so as not to obscure the present disclosure. Some features or elements described with respect to one system may be combined with features or elements described with respect to other systems. For clarity, descriptions of the same or similar features or elements may not be repeated.

[0122] Although the present disclosure is not limited in this regard, for example, descriptions using terms such as "process," "calculate," "compute," "determine," "establish," "analyze," "check," etc. may refer to the operation(s) and / or process(es) of a computer, computing platform, computing system, or other electronic computing device, which device manipulates and / or transforms data represented as a physical (e.g., electronic) quantity within a computer register and / or memory into other data similarly represented as a physical quantity within a computer register and / or memory, or into other information in a non-transitory storage medium that may store instructions for performing the operations and / or processes.

[0123] Although the present disclosure is not limited in this regard, as used herein, "plurality" and "a plurality" may include, for example, "multiple" or "two or more." The terms "plurality" or "a plurality" may be used throughout this specification to describe two or more components, devices, elements, units, parameters, etc. As used herein, a set may include one or more items. Unless otherwise specified, the methods described herein are not limited to a particular order or sequence. Additionally, some of the described methods or elements thereof may be performed simultaneously, at the same point in time, or together.

[0124] The term "classify" may be used throughout this specification to indicate a determination to assign one of a set of categories to an image / frame.

[0125] The terms "image" or "frame" may be used interchangeably herein.

[0126] As used herein, the term "gastrointestinal tract" ("GIT") relates to, and may include, the entire digestive system extending from the mouth to the anus, including the pharynx, esophagus, stomach and intestines, and any other parts. The term "GIT portion" or "a portion of the GIT" may refer to any portion of the GIT (whether anatomically distinct or not). Depending on the context, the term GIT may refer not to the entire digestive system but to a portion of the entire digestive system.

[0127] The term "position" and its derivatives, when referred to in this specification with respect to an image, may refer to the estimated position of the capsule along the GIT during image capture, or the estimated position of a portion of the GIT shown within the image along the GIT.

[0128] The type of CE procedure may be determined, inter alia, based on the part of the GIT that is of interest and imaged (e.g., the colon or small bowel ("SB")), or based on a particular use (e.g., for checking the status of a GI disease such as Crohn's disease or for screening for colon cancer).

[0129] The terms "surrounding" or "adjacent", when referred to in this specification with respect to an image (e.g., an image surrounding another image / images, or an image adjacent to another image / images), may relate to spatial and / or temporal characteristics unless otherwise indicated. For example, an image surrounding or adjacent to an image of another image(s) may be an image presumed to be located in the vicinity of the image of another image(s) along the GIT, and / or an image captured near the capture time of another image within a specific threshold, e.g., within 1 cm, or 2 cm, or within 1 second, 5 seconds, or 10 seconds.

[0130] The term "treatment data" may refer to images and metadata stored on a wearable device and uploaded to a cloud or local computer for processing by engine software.

[0131] The term "compiled survey" or "survey" refers to and may include at least a set of images selected from the images captured by a capsule endoscopy device during a single capsule endoscopy procedure performed on a specific patient and at a specific time, and optionally may also include information other than images.

[0132] The term "capsule endoscopy report" or "report" refers to and may include a report generated based on a compiled survey for a single capsule endoscopy procedure performed on a specific patient at a specific time and based on reader input, and may include images, text summarizing findings, and / or recommendations for follow-up based on the compiled survey.

[0133] The terms "app" or "application" are used interchangeably and may refer to and include software or a program having machine-executable instructions that can be executed by one or more processors to perform various operations.

[0134] The term "online processing" can refer to operations performed during a CE procedure or before all of the treatment data has been uploaded. In contrast, the term "offline" can refer to operations performed after the CE procedure has been completed or after all of the treatment data has been uploaded.

[0135] Referring to FIG. 1, a diagram of an exemplary remote / cloud computing configuration for a CE procedure is shown. The illustrated configuration includes a capsule device 110, a wearable device 120 (such as the illustrated patch), a mobile device (such as the illustrated mobile phone), 130, a remote computing system (such as the illustrated cloud system), 140, and a medical facility 150.

[0136] The different capsule devices 110 can be used for different types of CE procedures. For example, the different capsule devices 110 may be designed to image a particular situation, such as imaging the small intestine, imaging the colon, imaging the entire GIT, or imaging the GIT with Crohn's disease. The terms "capsule" and "capsule device" may be used interchangeably herein. The capsule 110 may include processing capabilities that enable the capsule to prune or discard images, for example, to prune or discard very similar images. For example, if the capsule 110 captures images that are essentially identical, the processing within the capsule 110 can detect such similarity and determine to communicate only one of the essentially identical images to the wearable device 120. Thus, the capsule 110 does not have to communicate all of its images to the wearable device. In some embodiments, such filtering of similar images may alternatively or additionally be performed within the wearable device or the mobile device.

[0137] In some embodiments, the capsule can communicate images in a sparse manner, for example, only communicate images captured every x images (e.g., images captured every two images, every five or ten images). A device that receives the communicated images can process the images to determine a measure of similarity or differentiation between the communicated images. According to some aspects, if two consecutively communicated images are determined to be different based on such a measure, instructions for communicating the images captured between those two images may be communicated to the capsule. A receiving device on which such processing can be performed may be, for example, a wearable device, a mobile device, or a remote computing device (e.g., a cloud system). Such a similar image filtering configuration can lead to a reduction in communication and processing volume, thus enabling resource savings and potentially higher cost efficiency. Resource savings are particularly important in devices where resources are typically limited, such as the capsule and the wearable device 120.

[0138] The wearable device 120 can be a device designed to communicate with the capsule device 110 and receive GIT images from the capsule device 110. In aspects of the present disclosure, the wearable device 120 is referred to as a "patch" based on a form factor and light weight similar to a medical patch that can adhere to a patient's skin. The patch is, for example, smaller than a wearable device that must be fixed to a patient using a belt. The patch can be a single integrated device (as opposed to a device having separate components) that includes an adhesive configured to adhere to a patient's skin, such as the abdomen. The patch / wearable device 120 may be a single-use disposable device. For example, the patch / wearable device 120 may be non-rechargeable and can have sufficient power for only a single capsule endoscopy procedure. Then, the / wearable device 120 may be removed and discarded at the end of the procedure, for example, by the patient. Although the wearable device 120 is illustrated as a patch in FIG. 1, the wearable device 120 may be another type of wearable device, such as a belt that includes a data recorder device and a plurality of antennas distributed thereon, and can have other shapes and functions. For convenience, the wearable device 120 may be referred to as a "patch" herein, but it will be understood that the description of the patch herein is also applicable to other types of wearable devices.

[0139] Continuing to refer to FIG. 1, the wearable device 120 is fixed to the patient, and the patient ingests the capsule 110. In the illustrated configuration, the patient carries an Internet-enabled mobile device 130 such as a mobile smartphone device. The mobile device 130 may be a device owned by the patient or a device provided to the patient for the CE procedure. In the illustrated embodiment, the wearable device 120 is communicatively coupled to the Internet-enabled mobile device 130. The wearable device 120 receives data including an image of the patient's GIT captured by the capsule 110 from the capsule 110 and uploads the treatment data 122 to a computing system 140 (e.g., a cloud system) via the Internet-enabled mobile device 130 (e.g., via a cellular network). As described above, the term "treatment data" may refer to the images and metadata stored on the wearable device 120, and these images and metadata are uploaded to a remote computing system 140 or a local computing system for processing. The wireless connectivity between the wearable device 120 and the mobile device 130 will be described in connection with FIGS. 6-11.

[0140] The remote computing system 140 may be any system that performs computing, and in particular, may be configured in various ways including, but not limited to, cloud systems / platforms, shared computing systems, server farms, proprietary systems, networked intranet systems, centralized systems, distributed systems, or combinations of such systems. For convenience, the remote computing system 140 is illustrated as a cloud system in FIG. 1. However, all variations of the computing system 140 are intended to be within the scope of the present disclosure. In the following description, the remote computing system 140 is referred to as a cloud system, but it will be understood that the description of the cloud system is applicable to other variations of the remote computing system.

[0141] The cloud system 140 receives and stores the treatment data 122. The cloud system 140 can process and analyze the treatment data 122, for example, using cloud computing resources, to generate a compiled investigation 142. As described above, the term "compiled investigation" refers to and can include at least a set of images selected from the images captured by the capsule endoscopy device during a single capsule endoscopy procedure performed on a specific patient and at a specific time, and optionally can also include information other than images. The term "capsule endoscopy report" or "report" refers to and can include a report generated based on a compiled investigation for a single capsule endoscopy procedure performed on a specific patient at a specific time and based on reader input, and can include images, image metrics, images, text summarizing findings, and / or recommendations for follow-up based on the compiled investigation. In the cloud system 140, the software that processes the treatment data and generates the investigation may be referred to as an "AI engine". The AI engine includes a bundle of algorithms and may include machine learning algorithms such as deep learning algorithms and other types of algorithms. If the remote computing system 140 is not a cloud system, the remote computing system 140 can process and analyze the treatment data using centralized or distributed computing resources, which will be understood by those skilled in the art.

[0142] Typically, the reader 160, who is a healthcare professional, can remotely access the compiled survey 142 within the cloud system 140 using a client software application and / or a browser. The reader 160 can review and evaluate the compiled survey 142 and create a treatment report via a dedicated reading or viewing application, for example, while selecting, adding, or revising information. The capsule endoscopy (CE) report 144 is generated based on the compiled survey 142 and the reader's input via the reading application. The CE report 144 may then be transmitted to the healthcare facility 150 associated with the CE procedure and may be stored in the data system of the healthcare facility. In some embodiments, the CE report may be made available to healthcare providers within the healthcare facility or to healthcare providers who refer the procedure via a dedicated application. According to some aspects, the reading time of the compiled survey 142 can be reduced by generating a compiled survey that includes only a relatively small number of images (e.g., up to 100 images per procedure, up to several hundred images per procedure, or only up to about 1,000 images). This can be made possible, inter alia, by utilizing a selection method or decision-making method that provides high sensitivity (e.g., by providing a high probability of identifying images of interest) and high specificity (e.g., by providing a high probability of identifying images that are not of interest) for each procedure. According to some aspects, the generation of the compiled survey can be performed by adopting machine learning or specifically deep learning.

[0143] FIG. 2 shows a flow diagram of an exemplary CE procedure that uses a remote computing configuration such as the cloud configuration of FIG. 1. The illustrated procedure includes three stages, a pre-procedure stage, a capsule endoscopy procedure stage, and a post-procedure stage. In the pre-procedure stage, the patient checks in (205) for the capsule endoscopy procedure. In various embodiments, the patient can check in at a medical facility, and in various embodiments, the patient can check in remotely using a patient app described in more detail later herein. Devices for the procedure, such as a capsule device and a wearable device, are paired to be communicable with each other, and the wearable device is set on the patient (210). In various embodiments, the capsule and the wearable device can be uniquely coupled to each other during assembly at a factory or warehouse. As used herein, "unique coupling" indicates that the coupled capsule device and the coupled wearable device can communicate with each other, but the coupled capsule device cannot communicate with another wearable device and the coupled wearable device cannot communicate with another capsule device. In step 210, the wearable device is also paired with a mobile device (FIG. 1). The wireless connectivity of the devices is addressed in connection with FIGS. 6-11. Here, it is sufficient to note that the mobile device can provide a mobile hotspot that provides the wearable device with Internet connectivity, thereby enabling the wearable device to communicate with the remote computing system. In various configurations, the wearable device can include cellular connectivity that can enable the wearable device to communicate with the remote computing system without using a mobile device.

[0144] During the capsule endoscopy procedure, the patient ingests the capsule (215). If the patient is in a healthcare facility, the patient can either stay there or be discharged to go home or to another location (220). During the procedure, the capsule device captures images of the patient's GIT. The wearable device receives data from the capsule device. Using the Internet connectivity provided by the mobile device or its own cellular connectivity, the wearable device uploads the treatment data to the remote computing system when Internet connectivity is available (225). If there is no available connection, the treatment data can be stored in the internal storage device of the wearable device.

[0145] In various embodiments, the wearable device can determine that the capsule endoscopy procedure is complete, for example, by not receiving further data from the capsule, processing the treatment data to detect completion, and / or by other means (230). In various embodiments, the remote computing system can determine that the capsule endoscopy procedure is complete (230), which will be described in more detail later in this specification. In various embodiments, the procedure can be "completed" when the capsule has left the portion of the GIT that is of interest for the CE procedure, even if the capsule is still traversing the patient's GIT. In various embodiments, the procedure can be completed when the capsule exits the patient's body. When the completion of the CE procedure is detected, the patient is warned to remove the wearable device (235). In various embodiments, the warning can be provided by the wearable device, or by the mobile device, or by both. If the treatment data on the wearable device was not fully uploaded to the remote computing system because Internet connectivity was not available or for any other reason, the patient may be notified to provide the wearable device to the healthcare facility, where the treatment data can be uploaded from the wearable device to the remote computing system (240).

[0146] In the post-treatment phase, the remote computing system processes the treatment data, analyzes it, and generates a compiled investigation (245). The cloud system alerts one or more healthcare professionals that a compiled investigation is ready and available (250). The healthcare professional(s) may include specialists, referring physicians, and / or other medical professionals. The leader can review the compiled investigation and select, add, or revise specific information (255). When the review is complete, the computing system generates a report based on the compiled investigation and the healthcare professional's input. This report is then communicated to and stored in the data system of a healthcare facility, such as an electronic hospital record (EHR) (255).

[0147] The embodiments of FIGS. 1 and 2 are illustrative, and variations are intended to be within the scope of the present disclosure. For example, in various configurations, the wearable device 120 may include cellular connectivity that enables the wearable device 120 to communicate with the remote computing system 140 without using the intermediate mobile device 130. The wearable device 120 may include, for example, a cellular modem and a prepaid SIM card that are recognized and accepted by a cellular network for cellular communication. As another example, the wearable device 120 can connect to a wireless router (not shown) instead of the patient mobile device 130. In various embodiments, when the patient does not desire to connect the wearable device to an Internet connection, the treatment data is not uploaded to the remote computing system during the CE treatment, and the upload of the treatment data can be handled as described below in connection with FIGS. 3 and 4. Such variations are intended to be within the scope of the present disclosure.

[0148] Referring to FIG. 3, a diagram of an exemplary on-premises configuration for CE processing is shown. The on-premises configuration may be deployed, for example, when a healthcare facility 350 does not wish to communicate patient information off-site to a remote computing system. Thus, in an on-premises configuration, among other things, the computing resources for generating compiled investigations and CE reports are located at the healthcare facility 350. In FIG. 3, the illustrated configuration includes a capsule device 310, a wearable device 320 (such as the illustrated patch), and a healthcare facility computer, terminal, or workstation 330, and a computing system 340. The capsule endoscopy procedure may be performed entirely at the healthcare facility 350, or may be performed partially at the healthcare facility and partially away from the healthcare facility. In contrast to the remote / cloud configuration of FIG. 1, the wearable device 320 of the on-premises configuration is not connected to the Internet infrastructure. Thus, the wearable device 320 stores all treatment data 322 in an internal storage device over the entire duration of the CE procedure. When the capsule endoscopy procedure is completed, the patient provides the wearable device 320, or a removable storage device of the wearable device 320, to the healthcare facility 350, and the treatment data 322 is downloaded (e.g., via a USB cable connection) from the internal storage device of the wearable device 320 to a healthcare facility computer, terminal, or workstation 330 connected to a local computing system (e.g., one or more servers) of the healthcare facility 350. The treatment data is then stored in the local computing system 340 of the healthcare facility 350.

[0149] Next, computing system 340 processes and analyzes the treatment data 322 to generate a compiled investigation 342. In the computing system 340, the software that processes the treatment data and generates the investigation may sometimes be referred to as an "AI engine" as described above. The AI engine may include a bundle of algorithms, including machine learning algorithms such as deep learning algorithms, and additional algorithms. The AI engine can be installed in the computing system 340 in various ways. In various embodiments, the AI engine can be present within a stand-alone computer or a computing box and can be executed by the computing resources of the stand-alone computer. A leader 360, such as a healthcare professional, can access the compiled investigation 342 within the computing system 350 using a client software application and / or a browser. The leader 360 may review and evaluate the compiled investigation 342 and, for example, select, add, or revise specific information. Based on the compiled investigation 342 and the leader's input, the computing system 340 generates a capsule endoscopy (CE) report 344. The CE report 344 is then stored in the data system 346 of the medical facility. Thus, the treatment data 322 is stored in the medical facility's system after the CE procedure is completed, processed by the medical facility's system, and the compiled investigation 342 and the CE report 344 are also stored in and processed by the medical facility's system without such information being transferred to a remote computing system.

[0150] Figure 4 shows a flow diagram of an exemplary CE procedure using an on-premises configuration, such as the on-premises configuration of Figure 3. The illustrated procedure includes three stages: a pre-procedure stage, a capsule endoscopy procedure stage, and a post-procedure stage. In the pre-procedure stage, the patient checks in to a medical facility for the capsule endoscopy procedure (405). Devices for the procedure, such as a capsule device and a wearable device, are paired to be communicable with each other, and the wearable device is set on the patient (410). In various embodiments, the capsule and the wearable device can be uniquely coupled to each other during assembly in a factory or warehouse. In the capsule endoscopy procedure stage, the patient ingests the capsule (415). The patient can stay at the medical facility or be released to go home or to another location (420). During the procedure, the wearable device receives data from the capsule device and stores the procedure data in the internal storage device of the wearable device. The wearable device can determine that the capsule endoscopy procedure is complete, for example, by not receiving further data from the capsule, by processing the procedure data to detect completion, and / or by other means. As described above, the procedure can be "completed" when the capsule has left the portion of the GIT that is of interest for the CE procedure, even if the capsule is still traversing the patient's GIT. And in various embodiments, the procedure can be completed when the capsule exits the patient's body. When the completion of the procedure is detected, the wearable device warns the patient to remove the wearable device (430). In the post-procedure stage, the patient provides the wearable device, or a removable storage device of the wearable device, to the medical facility (435), where the wearable device is connected to a workstation / computer at the medical facility (440). The workstation / computer downloads the procedure data from the wearable device and uploads the procedure data to a local computing system / server at the medical facility (445). The computing system at the medical facility processes and analyzes the procedure data to generate a compiled investigation. (450).The computing system warns one or more healthcare providers that compiled surveys are available (455). The healthcare expert(s) may include specialists, referring physicians, and / or other medical professionals. A leader can review the compiled survey and add or revise specific information (460). When the review is complete, the computing system of the healthcare facility generates a treatment report based on the compiled survey and the input of the healthcare expert. This report is then stored in a data system of the healthcare facility, such as an electronic hospital record (EHR) (465). The embodiments of FIGS. 3 and 4 are illustrative and do not limit the scope of the present disclosure. Variations are intended to be within the scope of the present disclosure.

[0151] FIG. 5 shows a block diagram of exemplary components of a system or device 500. The block diagram is provided to illustrate possible implementations of the various parts of the disclosed systems and devices. For example, the components of FIG. 5 may implement a patient mobile device (130, FIG. 1), or a portion of a remote computing system (140, FIG. 1), or a healthcare provider device (FIG. 1). The components may also implement a healthcare facility computer (330, FIG. 3), or a portion of an on-premises computing system (340, FIG. 3). The components may also implement a stand-alone computer or computing box including the AI engine described above.

[0152] Computing system 500 includes a processor or controller 505 that can be or include, for example, one or more central processing unit processors (CPUs), one or more graphics processing units (GPUs or GPGPUs), and / or other types of processors such as microprocessors, digital signal processors, microcontrollers, programmable logic devices (PLDs), field programmable gate arrays (FPGAs), or any suitable computing or computational device. Computing system 500 also includes an operating system 515, a memory 520, a storage device 530, an input device 535, an output device 540, and a communication device 522. Communication device 522 may include one or more transceivers that enable communication with remote or external devices, and in particular may implement communication standards and protocols such as cellular communication (e.g., 3G, 4G, 5G, CDMA, GSM®), Ethernet®, Wi-Fi, Bluetooth®, Low Energy Bluetooth®, Zigbee®, Internet of Things protocol (mosquitto MQTT), and / or USB.

[0153] The operating system 515 is any code designed and / or configured to perform tasks involving adjusting, scheduling, arbitrating, supervising, controlling, or otherwise managing the operation of the computing system 500, such as scheduling the execution of programs, or may include such code. The memory 520 may be, for example, one or more random access memories (RAM), read-only memories (ROM), flash memories, volatile memories, non-volatile memories, cache memories, and / or other memory devices, or may include them. The memory 520 may store, for example, operations (such as executable code 525) and / or executable instructions for executing data. The executable code 525 may be any executable code, such as an app / application, program, process, task, or script. The executable code 525 may be executed by the controller 505.

[0154] The storage device 530 may be, for example, a hard disk drive, solid state drive, optical disk drive (such as a DVD or Blu-Ray (Registered Trademark) etc.), USB drive or other removable storage device, and / or one or more of other types of storage devices, or may include them. In particular, data such as instructions, code, treatment data, and medical images may be stored in the storage device 530, loaded from the storage device 530 into the memory 520, where it may be processed by the controller 505. The input device 535 may include, for example, a mouse, keyboard, touch screen or pad, or another type of input device. The output device 540 may include one or more monitors, screens, displays, speakers, and / or other types of output devices.

[0155] The illustrated components in FIG. 5 are examples, and variations are intended to be within the scope of the present disclosure. For example, the number of components may be more or less than those described, and the types of components may be different from those described. When the system 500 implements a machine learning system, for example, a large number of graphics processing units can be utilized. When the computing system 500 implements a data storage system, a large number of storage devices can be utilized. As another example, when the computing system 500 implements a server system, a large number of central processing units or cores can be utilized. Other variations and applications are intended to be within the scope of the present disclosure.

[0156] The above description has described various systems and methods for capsule endoscopy procedures. The communication capabilities between the various components of the described systems will be described below in connection with FIGS. 6-11. Software apps that utilize and / or rely on such communication capabilities will be described in connection with FIGS. 12-25.

[0157] Referring to FIG. 6, there are diagrams of various devices and systems for remote computing configurations and communications between devices and systems. This system includes a capsule endoscopy kit 610 including a capsule device 612 and a wearable device 614, a patient system 620 including an Internet-enabled mobile device 622 and / or a wireless router 624, a healthcare provider system 630 including a computer / workstation 632, a tablet device 634, and / or a wireless router 636, and a remote computing system 640. For convenience, the remote computing system 640 is illustrated as a cloud system and may be referred to as a cloud system. However, the following description regarding cloud systems will be understood to apply to other variations of remote computing systems.

[0158] In the capsule endoscopy kit 610, the capsule device 612 and the wearable device 614 can communicate with each other using a radio frequency (RF) transceiver. Those skilled in the art will understand how to implement the RF transceiver and the related electronic devices for interfacing with the RF transceiver. In various embodiments, the RF transceiver can be designed to use a frequency that is not overly interfered with by common communication devices such as cordless phones, or a frequency that is not interfered with at all. The wearable device 614 can include various communication capabilities, including Wi-Fi, low energy Bluetooth® (BLE), and / or USB connections. The term Wi-Fi includes wireless local area networks (WLANs) specified by the IEEE 802.11 family of standards. The Wi-Fi connection enables the wearable device 614 to upload treatment data to the cloud system 640. The wearable device 614 can connect to a Wi-Fi network in either the patient's network system 620 or the healthcare provider's network system 630, and then the treatment data is transferred to the cloud system 640 via the Internet infrastructure. The wearable device 614 also has a wired USB channel for transferring treatment data when a Wi-Fi connection is not available or when not all treatment data can be communicated using Wi-Fi. The Bluetooth® low energy (BLE) connection is used for control and messaging. Since the BLE connection uses relatively low power, BLE can be continuously on during the entire treatment and is suitable for control messaging. Depending on the device and its BLE implementation, the BLE connection can support communication speeds from approximately 250 Kbps to 270 Kbps to approximately 1 Mbps. Some BLE implementations can support somewhat higher communication speeds, but Wi-Fi connections can generally provide much higher communication speeds.Thus, to transfer the treatment data to the cloud system 640, generally a Wi-Fi connection is used, and the treatment data can be transferred at a transfer speed of 10 Mbps or more, depending on the connection quality and the amount of treatment data. In various embodiments, when the amount of treatment data to be transferred is suitable for the BLE connection transfer speed, the treatment data can be transferred using the BLE connection.

[0159] As shown in FIG. 6, there are many possible communication paths between the wearable device 614 and the cloud system 640 or various devices. FIGS. 7-11 address the connectivity between specific portions of FIG. 6 and are described below. The illustrated and described embodiments are merely exemplary, and in particular, other types of connections not shown or described, such as Zigbee® or Internet Protocol for Things, can be used.

[0160] Referring to FIG. 7, a diagram of an exemplary communication path between a wearable device 614 and a cloud system 640 via tethering or a mobile hotspot provided by a patient internet-connected mobile device 622 is shown. The patient internet-connected mobile device 622, which may be referred to herein as the mobile device 622, can include, but is not limited to, a smartphone, laptop, or tablet. The mobile device 622 can be any mobile device used by a patient, including a mobile device owned by the patient or a mobile device loaned to the patient for CE treatment. For convenience, a smartphone is illustrated in FIG. 7, but the present disclosure is intended to apply to other types of internet-connected mobile devices. By providing tethering or a mobile hotspot, the mobile device 622 can share its cellular internet connection 710 with the wearable device 614 via a Wi-Fi connection 720. When providing a mobile hotspot, the mobile device 622 acts as a router and provides a gateway to the cloud system 620. Since the mobile hotspot Wi-Fi connection 720 can be disconnected due to inactivity (e.g., no activity for 90 seconds), the wearable device 614 can be configured to periodically ping the mobile device 622 to keep the mobile hotspot Wi-Fi connection 720 active. Otherwise, if the mobile hotspot Wi-Fi connection 720 is permitted to become inactive, the patient would need to go through a reconfirmation process to re-establish the hotspot connection for security reasons, which can be inconvenient for the patient and can make the upload untrustworthy. Also, as described above, the mobile device 622 and the wearable device 614 can have a Bluetooth® Low Energy (BLE) connection 730 for communicating control messages. In various embodiments, the BLE connection 730 may be used to communicate treatment data when appropriate.

[0161] A patient software app can be used to set up a Wi-Fi connection 720 between the wearable device 614 and the mobile hotspot of the patient mobile device 622. The patient app is described later in this specification. Using the mobile hotspot, the wearable device 614 can communicate directly to a given Internet address or can connect to a subnet client (e.g., a default gateway address). The advantage of a direct connection is that the mobile device 622 transparently transfers treatment data to the cloud system 640 and no internal buffer is required, but a potential disadvantage is that the data transfer rate between the wearable device 614 and the mobile device 622 can vary depending on the upstream Internet connection quality such as the cellular signal strength 710. When the wearable device 614 connects to a mobile local subnet (default gateway), the wearable device 614 transfers treatment data to the local buffer of the mobile device 622, and the upload of treatment data from this buffer to the cloud system 640 is handled in parallel by a separate thread. In this case, the data transfer rate between the wearable device 614 and the mobile device 622 can advantageously utilize the full bandwidth of the Wi-Fi connection 720 regardless of the Internet connection quality 710, but a potential disadvantage is that the internal buffer of the mobile device 622 may expose treatment data to security threats. FIG. 7 is illustrative, and variations are intended to be within the scope of the present disclosure. For example, instead of using the cellular Internet connection 710, the mobile device 622 can alternatively share broadband Internet connectivity with the wearable device (not shown). Such and other variations are intended to be within the scope of the present disclosure.

[0162] FIG. 8 shows an exemplary communication path between wearable device 614 and cloud system 640 via a communication device such as router 624. When it is suitable for wearable device 614 to directly use Wi-Fi network 840 (e.g., a home network), the patient can manually specify Wi-Fi access credentials for wearable device 614 using a patient software app within patient mobile device 622. The Wi-Fi access credentials can be communicated by mobile device 622 to wearable device 614 using BLE connection 830. Whenever Wi-Fi network 840 is within the range of wearable device 614, wearable device 614 can connect to Wi-Fi network 840 and upload treatment data via communication device / router 624. In various embodiments, wearable device 614 can be selected to simultaneously maintain mobile hotspot Wi-Fi connection 820 and router Wi-Fi connection 840 by periodically pinging the mobile device, such as once every 60 seconds, via mobile hotspot Wi-Fi connection 820. If wearable device 614 does not periodically ping mobile device 622, mobile hotspot Wi-Fi connection 820 can become inactive to conserve power.

[0163] FIG. 9 shows a diagram of an exemplary communication path between the wearable device 614 and the cloud system 640 via the healthcare provider workstation 632. The illustrated communication path can be used whenever the treatment data in the internal storage device of the wearable device 614 has not been uploaded to or has not been fully uploaded to the cloud system 640. A patient can provide the wearable device 614, or a removable storage device of the wearable device 614, to a medical facility, and the personnel at the facility can connect the wearable device 614 or the removable storage device to the workstation 632 via the USB connection 910. The treatment data is transferred from the wearable device 614 to the workstation 632, and then the workstation 632 uses the facility's network infrastructure such as the router 636 and the local area network 920 to transfer the treatment data to the cloud system 640. The software application on the workstation 632 can coordinate the upload of the treatment data to the cloud system 640. Such a software application can use secure authentication and AES data encryption for data transfer via the USB connection 910. In addition, the treatment data can be transferred from the wearable device 614 to the workstation 632 using data integrity control such as the TCP / IP protocol via, for example, a USB. FIG. 9 is an illustration and is not intended to limit the scope of the present disclosure. For example, in various embodiments, the healthcare provider workstation 632 can be a laptop computer or another device. Such variations are intended to be within the scope of the present disclosure.

[0164] FIG. 10 shows an exemplary direct connection between a wearable device 614 and a healthcare provider device 634. According to aspects of the present disclosure, the wearable device 614 can function as an access point (AP) that can connect to a tablet or smartphone via Wi-Fi. By default, the wearable device 614 is set as a station (client) and periodically connects to a mobile hotspot 1020 or other Wi-Fi connection for data upload. Whenever the wearable device 614 receives a predetermined request, such as a “real-time view” request described later herein, the wearable device 614 changes its Wi-Fi settings from a station to an AP, enabling the healthcare provider device 634 to establish a Wi-Fi connection 1040 to the wearable device 614 functioning as an access point. In this way, the wearable device 614 advertises as a client and scans as a master to establish a WiFi connection. In summary, the “real-time view” enables the healthcare provider device 634 to receive an immediate snapshot of recent procedure data by connecting locally / directly to the wearable device 614. This feature may be available during a capsule endoscopy procedure when the patient is within a medical facility.

[0165] In the illustrated configuration, the connection between the wearable device 614 and the patient mobile device 622 includes a BLE connection (CHI) 1030 for control and messaging and a Wi-Fi connection 1020 for data upload (client / hotspot). The connection between the wearable device 614 and the healthcare provider device 634 includes a BLE connection (CH2) 1050 for the healthcare provider device 634 to control the "real-time view" functionality and a Wi-Fi connection 1040 for "real-time view" data transfer from the AP to the client. The wearable device 614 can ping the mobile device BLE connection (CH1) 1030 every 60 seconds (or another time interval) to confirm that the mobile device 622 is active and within range. If the mobile device 622 is detected to be in a position that is too far away based on the ping of the BLE connection 1030, the wearable device 614 can provide a warning (e.g., a beep warning) to the patient before the connection 1030 is lost.

[0166] Generally, the wearable device 614 operates as a Wi-Fi client to upload treatment data to the cloud system 640. The wearable device 614 can expose the BLE channel (CH2) 1050 always or periodically to check for "real-time view" requests. When such a request is received, the wearable device 614 can establish a TLS 1.2 (or higher) secure TCP / IP connection before data transmission. In various embodiments, the wearable device 614 can keep the Wi-Fi connection 1040 active for a period such as 60 seconds and then terminate the Wi-Fi connection 1040. The "real-time view" request may be re-established. However, the wearable device 614 also operates to ping the mobile hot-spot Wi-Fi connection 1020 of the mobile device every 60 seconds (or another time interval) to keep the mobile hot-spot Wi-Fi connection 1020 active so that it is not interrupted due to inactivity. The wearable device 614 may not upload treatment data to the cloud system 640 while the "real-time view" request is in progress. As a result, the upload of treatment data from the wearable device 614 to the cloud system 640 is delayed until the "real-time view" request ends.

[0167] FIG. 10 and the described embodiments are illustrative, and variations are intended to be within the scope of the present disclosure. In various embodiments, requests other than the "real-time view" can switch the wearable device 614 from station / client mode to AP mode. In various embodiments, the healthcare provider device 634 may not be a tablet and may be another type of device, such as a smartphone, laptop, or desktop computer. Such variations are intended to be within the scope of the present disclosure.

[0168] FIG. 11 shows a diagram of an exemplary communication path between a wearable device 614 and healthcare provider devices 632, 634. The communication path between the wearable device 614 and the cloud system 640 may be the same as that described above in connection with FIG. 7 or the same as that shown in FIG. 8. The communication path between the healthcare provider devices 632, 634 and the cloud system 640 is a normal connection via a network infrastructure such as a router 636. According to aspects of the present disclosure, the healthcare provider (HCP) devices 632, 634 can include a software application, herein referred to as the HCP app, which can initiate a command for the wearable device 614, referred to as the “near real-time view” command. The HCP app will be described in more detail later herein, including a “remote view” feature that is separate from the “near real-time view” feature. For now, it suffices to note that the near real-time view command can be transmitted to the cloud system 640 via the healthcare provider network infrastructure, and the cloud system 640 can transmit the corresponding command to the wearable device 614 via the Wi-Fi connection 1120 or the BLE connection 1130 of the patient mobile device 622. In various embodiments, the command from the cloud system 640 can be an instruction for the wearable device 614 to immediately upload the most recent treatment data that has not yet been uploaded to the cloud system 640. In various embodiments, in response to a command from the healthcare provider devices 632, 634, the cloud system 640 can check the timestamp of the most recent treatment data upload. Since the duration from the last upload exceeds a predetermined threshold, the cloud system 640 can communicate an upload command to the patient mobile device 622 to trigger the treatment data upload. The patient mobile device 622 can then send a signal to the wearable device 614 via the Wi-Fi connection 1120 or via the BLE connection (CH1) 1130 to provide the treatment data upload.In response, the wearable device 614 uses the Wi-Fi connection 1120 to initiate the transfer of the treatment data. The cloud system 640 receives the treatment data upload, communicates the treatment data to the healthcare provider devices 632, 634, whereby healthcare professionals can review the most recent treatment data in near real-time. Accordingly, this functionality, and its corresponding commands, are referred to herein as "near real-time view" and will be described in more detail later in this document.

[0169] Accordingly, in the above description, various devices, as well as the connections and communications between the devices, have been described with reference to FIGS. 6-11. Those skilled in the art will understand how to implement various communication connections, including, among other things, Wi-Fi, Bluetooth®, and USB connections.

[0170] As described above, various software apps / applications can be run on the device. FIG. 12 shows an illustration of exemplary software apps including a patient app 1210 on a patient mobile device, a healthcare provider "real-time view" app 1220, a healthcare provider app 1230 including "near real-time" functionality and "remote view" functionality, and a reader app 1240 that enables a reader to view a compiled survey, provide input, and generate a report. In various embodiments, apps 1210-1240 can be downloaded from an app store or from another source, such as from the website of the capsule endoscopy kit provider. Apps 1210-1240 can be configured to operate, among other things, in various operating systems such as iOS, Android (Registered Trademark) , Chrome OS, and / or Windows®, etc. Although the various apps are illustrated as separate apps in FIG. 12, the various apps can be combined into a single app having various features, or combined into different numbers of apps. Such variations are intended to be within the scope of the present disclosure.

[0171] The patient app 1210, the reader app 1240, and the healthcare provider app 1230 can communicate with the cloud system 640. In the illustrated configuration, such apps, 1210, 1230, and 1240 communicate with a portion of the cloud system 640 configured to receive and present data designated as the HCP cloud 642. Another portion of the cloud system 640 designated as the AI cloud 644 is a data processing and machine learning subsystem that executes processing of treatment data and generates data presented by the HCP cloud 642. Thus, the AI cloud can execute machine learning but can also execute non-AI processing and tasks. The AI cloud 644 can execute an operation to generate a compiled survey. In the AI cloud 644, software that processes treatment data and generates a survey may be referred to as an "AI engine". The AI engine includes a bundle of algorithms and may include machine learning algorithms such as deep learning algorithms and other types of algorithms. The AI cloud 644 can apply various algorithms and automated decision-making systems, including deep learning or other machine learning operations and techniques. The separation of the cloud system 640 into two subsystems provides isolation of the AI cloud 644, whereby the AI cloud 644 can only be accessed by the HCP cloud 642 and there is no direct connection between either the end user and the applications used by the AI cloud 644. Such a configuration can better protect the AI cloud from malicious behavior or unauthorized access. However, the use of the two subsystems is exemplary and is not intended to limit the scope of the present disclosure. Other types and / or numbers of subsystems within the cloud system 640 are within the scope of the present disclosure. Those skilled in the art will recognize how to implement the cloud system 640, including via a cloud service platform.

[0172] As described above, the term "online processing" can refer to processing that is performed on a remote computing system (e.g., AI cloud 644) during a procedure or before all of the procedure data has been uploaded (i.e., a complete upload of the procedure data), and only on a portion of the procedure data. Based on such online processing, for example, online detection of a pathology or anatomical structure of interest may be provided. According to some aspects, the online detection may be performed on a batch of images uploaded to the cloud system 640. For example, new bleeding, stenosis, capsule retention, or passage to another anatomical part of the GIT may be detected online. An introducing physician or healthcare provider who supervises the procedure may be notified in real time of suspicious findings such as new bleeding or stenosis that may require immediate treatment. Identification of anatomical structures, parts, or landmarks (e.g., the cecum or pyloric valve) may be used, for example, for capsule localization. According to some aspects, the uploaded images may be processed online to determine predictions regarding, for example, capsule transit time, speed, or motility. Such predictions may be used, for example, to change the capsule capture frame rate.

[0173] Next, each app / application will be described below.

[0174] The patient app is configured to provide a display screen for guiding the patient through the preparation for and during a capsule endoscopy procedure. In addition, the patient application provides patient information to the cloud system and enables the patient to set up the upload of procedure data from the wearable device to the cloud system. The patient app can be installed on a mobile device carried by the patient before the CE procedure begins. In various embodiments, the mobile device may be a dedicated device provided to the patient by a medical facility for the CE procedure, or a mobile device owned by the patient, such as the patient's personal mobile phone.

[0175] Referring to FIG. 13, an exemplary sign-in screen of the patient app is shown. Before a patient signs in using the patient app for a capsule endoscopy procedure, the patient generally consults with a healthcare provider and a medical facility and is provided with patient instructions, such as a patient instruction sheet. The patient instructions may include instructions on how to download the patient app and sign in to the capsule endoscopy procedure using the patient app. As used herein, signing in to a procedure does not mean starting the procedure. Instead, the term "sign in" refers to logging in to an account. In various embodiments, a patient can sign in for a next procedure to obtain more detailed information regarding preparation for the next procedure. In various embodiments, a patient can sign in for a procedure at a medical facility or at another location, such as at home. The illustrated sign-in screen of the patient app operates to scan a QR code (registered trademark) provided within the patient instructions of the healthcare provider (e.g., printed on the patient instruction sheet), although other methods of signing in for a procedure are contemplated to be within the scope of the present disclosure. For example, in various embodiments, a patient can sign in for a procedure by manually entering an alphanumeric code or by selecting a link within an email or text message. Other methods of signing in are within the scope of the present disclosure. FIG. 14 shows an example of a QR code (registered trademark) scanned by a patient mobile device to sign in for a capsule endoscopy procedure. As described above, the QR code (registered trademark) can be provided within the patient instructions by a healthcare provider, such as a QR code (registered trademark) printed on the patient instruction sheet.

[0176] According to aspects of the present disclosure, regimens can be identified in a QR code (registered trademark). A healthcare professional can select a regimen for a patient's CE treatment, and the regimen can be identified in a QR code (registered trademark) provided / printed within the patient instructions provided to the patient as described above. The QR code (registered trademark) can be generated based on the regimen selected by the physician and based on other information, and the QR code (registered trademark) can be printed within the patient instructions. An example of a regimen is shown within the patient app screen of FIG. 15, which is the screen displayed after the patient signs in. The scanned QR code (registered trademark) causes the patient app to retrieve the regimen selected by the healthcare professional, which includes obtaining medication by a certain date 1510, starting a clear liquid diet by another date 1520, and starting a treatment by a scheduled date 1530. The patient app displays the regimen and the date on the display screen.

[0177] The aspects and embodiments described in connection with FIGS. 13 - 15 are exemplary, and variations are intended to be within the scope of the present disclosure. For example, the patient app can access and display other regimens not illustrated or described herein. Further, other display screens may be displayed before, during, and / or after the display screens of FIGS. 13 - 15. For example, the display screen can request patient confirmation (not shown) that the regimen has been completed. The patient confirmation is communicated to the cloud system and then transmitted to the healthcare provider so that the healthcare provider can be kept informed regarding the patient's progress and compliance. As another example, various screens and operations of the patient app can be presented and executed offline, without an Internet connection and / or without a connection to the cloud system, so that the patient can follow the instructions in offline mode. Such variations are intended to be within the scope of the present disclosure.

[0178] FIG. 16 shows an exemplary display screen for initiating CE treatment. The display screen includes three initial tasks, including pairing the patient mobile device with the wearable device 1610, applying the patch / wearable device and ingesting the capsule 1620, and setting up a hot spot for the capsule 1630. In the first task 1610, as described above in connection with FIG. 7, the patient mobile device can be paired with the patch / wearable device using Bluetooth® low energy. Those skilled in the art will understand how to implement Bluetooth® discovery, pairing, and communication. In the second task 1620, if the patient is at a healthcare facility, the healthcare professional can attach the patch / wearable device to the patient. Otherwise, the patient can attach the patch / wearable device to their body. In the second task 1620, the wearable device need not be a patch and can be another type of wearable device. In the third task 1630, the patient application can set up the connection of the wearable device to the mobile hot spot provided by the patient mobile device, as described above in connection with FIG. 7. The illustrated start tasks 1610-1630 are exemplary, and the start procedure may include other tasks not described herein.

[0179] Figure 17 shows an example of a display screen when the task is completed and the CE treatment is property - configured. As shown in Figure 17, the display screen reminds the patient to maintain the internet connectivity of the mobile device and keep the mobile device close to the patient 1710. The display screen provides an option to connect the wearable device to a Wi - Fi network provided by a communication device (e.g., a router) 1720, which is the configuration illustrated and described above in Figure 8. Specifically, the patient can input Wi - Fi access credentials into the patient app as described above, and the patient app can communicate the credentials to the wearable device using BLE connection. When the wearable device is directly connected to a communication device such as a router, the wearable device can communicate treatment data using its Wi - Fi connection, but the patient mobile device can be periodically pinged to keep the mobile hotspot connection active.

[0180] Figure 18 shows an example of a display screen during a CE treatment where a regimen can be communicated to the patient. In various embodiments, the regimen may be pre - determined, and in various embodiments, the regimen may be prescribed during the CE treatment by a healthcare professional monitoring the treatment. The regimen may be communicated to and displayed on the patient mobile device. In the illustrated embodiment, the regimen 1810 is an instruction for the patient to take a boost (i.e., a drug) that may help or facilitate the capsule device's advancement through the gastrointestinal tract. Other types of boosts or drug administrations during the CE treatment are contemplated to be within the scope of the present disclosure. Further, various regimens and boosts may be presented offline, without an internet connection and / or without a connection to a cloud system, so that the patient can follow the instructions in offline mode. Information can be collected to determine the level of patient compliance throughout the treatment. Such information may be provided to the healthcare provider, reader, and / or referring physician monitoring the treatment.

[0181] FIG. 19 shows a display screen that notifies the patient that the procedure is complete and that the wearable device can be removed. In various embodiments, the wearable device can detect that the procedure is complete, for example, when it no longer receives any communication from the capsule. No longer receiving any communication can indicate that the capsule device has exited the body. In various embodiments, a computing system, such as the remote computing system of FIG. 1 or the AI cloud of FIG. 12, can process the images received from the wearable device during the CE procedure to determine whether the CE procedure has ended. In various embodiments, the wearable device can process the images within the treatment data to determine whether the CE procedure has ended. For example, if the CE procedure is intended to capture images of the small intestine and the capsule is passed into the colon, the remote computing system can process the images received from the wearable device and determine that the images are colon images and that the CE procedure has ended. In various embodiments, the remote computing system can apply machine learning in an online manner to classify the images during the CE procedure. One skilled in the art will understand how to train a machine learning system to classify tissue images, for example, to determine whether an image is a colon image or an image of another anatomical structure. By processing the images in an online manner, the remote processing system may determine that the CE procedure ended much earlier than when the capsule stopped transmitting to the wearable device. Thus, the patient may be able to resume activities more quickly and fully. In various embodiments, the capsule, the wearable device, and / or the patient mobile device may have the processing ability to process the images individually or collaboratively to determine whether the CE procedure has ended, and it may be possible to process them in such a way. Such embodiments are contemplated to be within the scope of the present disclosure.

[0182] If the treatment data within the wearable device is not fully uploaded to the cloud system, the patient may be instructed to provide the wearable device to a healthcare facility for manual transfer of the treatment data from the wearable device. According to some aspects, the healthcare provider may be notified when the treatment is completed, for example, via the healthcare provider application described below in connection with FIGS. 20-22.

[0183] FIG. 20 shows a display screen of a healthcare provider (HCP) application disposed on an HCP device, such as the HCP device shown in FIG. 10 or FIG. 11. In various embodiments, the HCP device can be, among other things, a tablet, laptop, netbook, workstation, or desktop computer. Healthcare professionals who handle and / or supervise CE procedures, such as nurses or physicians, may be provided with dedicated HCP software or applications. The HCP application may be installed on a mobile device (e.g., a tablet computer, iPad®, or another handheld device) used by the healthcare professional, and / or on a fixed device within a healthcare facility (e.g., a clinic or hospital where the patient is checked in by the HCP and swallows a capsule) where the healthcare professional accepts the patient and / or performs the procedure. The HCP device may be a dedicated device.

[0184] The HCP application can facilitate the handling and / or management of CE procedures, including the check-in process and the pairing process between various devices or components of the disclosed system. Advantageously, the HCP application can enable the HCP to review online the progress and status of CE procedures (e.g., by displaying a dashboard of ongoing procedures), access treatment data, and connect to the healthcare facility's data system. In the illustrated embodiment, the HCP application 2010 enables healthcare facilities and healthcare providers to obtain information regarding 2022 CE procedures 2020 that are ready to start, CE procedures 2024 that are in progress, 2026 CE procedures that are ready for review of compiled surveys, and CE surveys with completed reports 2028. Healthcare professionals can interact with the HCP application 2010 to obtain a list of such procedures 2030 and select a specific procedure 2040 to access. When a healthcare provider selects a specific procedure 2040, information related to the procedure, such as the type 2042 of the CE procedure, the status 2044 of the procedure, the duration 2046 of the procedure, and the latest images 2048 received from a wearable device or a cloud system, can be displayed on the display screen. The information displayed may also include a history 2050 of provisional findings, as described in connection with FIG. 21. As described in connection with FIG. 12, the information presented within the HCP application may be provided to the HCP application by the HCP cloud subsystem of the cloud system. However, the information generated from image and treatment data analysis may be generated within the cloud system by the AI cloud subsystem (FIG. 12).

[0185] The display screen of FIG. 20 is exemplary and is not intended to limit the scope of the present disclosure. Variations are contemplated as being within the scope of the present disclosure. According to some aspects, the HCP app may provide notification of malfunctions or problems in the device or ongoing CE procedures, including hardware problems, connection problems, or interference during an active CE procedure (e.g., a procedure being performed on a patient in a medical facility). For example, in various embodiments, the HCP app can provide online information indicating the stage of the procedure. In various embodiments, the HCP app can provide a warning when starting the check-in or setup stage of the procedure, where the reader (e.g., a GI physician) is not assigned to the procedure in the system. In various embodiments, the HCP app can provide a way to verify that the patient has appropriately completed and confirmed pre-procedure preparation.

[0186] Figure 21 shows a display screen of an HCP app that includes detailed information about a CE procedure, including patient-related information 2110, physician-related information 2120 related to the associated physician, and procedure-related information 2130. The illustrated display screen indicates that a particular procedure has been in progress for 3 hours and 30 minutes and that three provisional findings 2140 are available. One provisional finding was provided at approximately 1 hour and 47 minutes into the procedure, a second provisional finding was provided at approximately 2 hours and 15 minutes into the procedure, and a third provisional finding was provided at approximately 3 hours and 29 minutes into the procedure. A "provisional finding" may include, for example, an image of an identified object of interest and optionally an indicator of an identified event indicator (e.g., pathology) within the image. As used herein, the term "event indicator" refers to an indicator that an event has occurred. The event may be the presence of a pathology such as polyp growth or GIT bleeding, or a transition event such as a transition from one GIT portion to another GIT portion, or the appearance of an anatomical landmark such as the duodenal bulb in a transition from the small intestine to the colon, or other events not specifically mentioned herein. Thus, a "provisional finding" may include one or more images and, in some embodiments, may be a report provided during a CE procedure based on the procedure data obtained so far in this procedure. A fully compiled investigation or CE report is generated after the procedure is completed and is based on all the procedure data of the CE procedure, whereas a provisional finding is compiled during the CE procedure and provides a preview of partial findings to healthcare professionals as the procedure progresses. In various embodiments, a provisional finding can be initiated at a predetermined time during a CE procedure. In various embodiments, a provisional finding can be generated whenever a particular amount of procedure data has been received. A provisional finding may also be generated on demand at the request of a healthcare professional. Provisional finding 1240 may enable a healthcare professional to identify an immediate or urgent need for treatment.

[0187] According to some embodiments, online processing of images by a cloud system (e.g., an AI cloud subsystem) can provide online identification of polyps (e.g., via preliminary findings), enabling same-day colonoscopies. If the identified polyp needs to be removed, the physician who provided the preliminary findings can suggest to the patient that they have a colonoscopy on the same day to remove the polyp. Same-day colonoscopies can be more convenient and less difficult for the patient since they have already completed the pre-procedure preparation.

[0188] FIG. 22 shows an example of a display screen of an HCP app that provides an online warning 2210 regarding detected high / urgent medical risks. As described above, online processing by a cloud system (e.g., FIG. 12, AI cloud) can be applied to process images received from a wearable device during a CE procedure. The AI cloud can be operative to identify potential event indicators such as, among other things, cancer events, significant bleeding, or various pathologies. Those skilled in the art will understand how to train a machine learning system to identify various event indicators in images, including ways to train the machine learning system using training data. When online processing by the cloud system detects an event indicator classified as a high medical risk such as significant bleeding, the cloud system can provide an online warning 2210 to the HCP app that includes a detection 2212 and one or more images 2214 showing the detected pathology or event. In the example of FIG. 22, the cloud system has detected significant bleeding 2212 in the small intestine, and the HCP app provides an online warning 2210 showing the detected bleeding finding 2212 and the image 2214. In various embodiments, the HCP app can be pre-configured to detect specific event indicators or pathologies and can be pre-configured to identify specific events or pathologies as high / urgent medical risks. In various embodiments, a healthcare provider can select events or pathologies to classify as high / urgent medical risks and trigger an online warning.

[0189] In the above description, the aspects of the patient app and the HCP app were described. Below, the options for remote view, real-time view, and near real-time view will be described. A real-time view requires a separate app, while the near real-time view and the remote view may be provided as features of the HCP application.

[0190] FIG. 23 shows a display of a remote view that can be part (e.g., a feature) of the HCP app (1230, FIG. 12). The remote view operates to access images of a procedure uploaded to a cloud system. The illustrated image 2310 is the latest image uploaded to the cloud system. A healthcare professional can, for example, swipe left or right to access a previous or subsequent image, or use a keyboard or mouse or other interface device to navigate the image. When the cloud system receives additional images from the wearable device, they may become available in the remote view. In some aspects, the remote view may be available via a dedicated app. To enable the remote view, no special instructions other than those for accessing the available images for the procedure are communicated. Thus, even if the wearable device contains images that have not yet been uploaded to the cloud system, the wearable device is left to upload such images on its own schedule and by its own process. Since the remote view requires interaction only with the cloud system, it may be accessible via an Internet connection.

[0191] In contrast to the remote view feature or app, the real-time viewer app (1220, FIG. 12) operates to obtain an image from the wearable device as soon as possible using the connectivity shown in FIG. 10. As described above, with the connectivity of FIG. 10, the HCP device 634 is directly connected to the wearable device 614. The wearable device 614 operates as a Wi-Fi access point, the HCP device 634 operates as a Wi-Fi client, and these devices also have a BLE connection 1050. Since the HCP device 634 directly obtains an image from the wearable device 614, access to such an image is essentially in real time, and the wearable device 614 can communicate them to the HCP device 634 as soon as the wearable device receives the images. In various embodiments, the display screen of FIG. 23 can be applied to the real-time viewer app for viewing the images. Although not illustrated, a display screen for requesting a real-time view on the wearable device will be understood by those skilled in Wi-Fi and Bluetooth® communications. Since the real-time view relies on the connectivity shown in FIG. 10, the real-time viewer app is operable only for a healthcare professional who is in the same location as the wearable device and the patient. The real-time view may be used by an HCP, for example, to review an image received from the wearable device and in this way verify the proper operation of the procedure by confirming that the image was captured by the capsule device and received by the wearable device. Further, the real-time view may be used, for example, to verify that the capsule has reached a particular portion of the GIT, including, for example, the portion of the GIT of interest or the portion of the GIT being imaged. For example, the HCP can verify that the capsule is in the SB and, for example, not stuck in the stomach. If the HCP reviews the image received from the wearable device and realizes that the capsule is still in the stomach, he can administer a boost to advance the capsule.

[0192] The near real-time view provides the timing of image access between the timing provided by the remote view and the real-time view, and utilizes the connectivity shown in FIG. 11. According to FIG. 11, the near real-time view can exist on the wearable device 614 and the HCP devices 632, 634 remote from the patient. However, rather than waiting for the wearable device 614 to upload treatment data to the cloud system 640 on its own schedule, the near real-time view communicates special instructions to the cloud system 640 to check the age of the treatment data received from the wearable device 614. If the age of the treatment data is older than a threshold, the cloud system 640 sends an instruction to the wearable device 614 to immediately upload the treatment data stored thereon. In various embodiments, the age threshold can be set to minutes or seconds, whereby the wearable device 614 can immediately upload its image to the cloud system at any time when the treatment data is a few seconds or minutes old. In this way, the cloud system 640 receives treatment data from the wearable device in near real-time, and the near real-time view displays such images in near real-time. In various embodiments, the display of FIG. 23 can also be applied to the near real-time view for displaying images. Although not illustrated, a display screen for requesting a near real-time view to the cloud system will be understood by those skilled in the art.

[0193] FIG. 23 and the above embodiments are illustrative and do not limit the scope of the present disclosure. Variations of the display of FIG. 23 can be used for remote views, real-time views, and near real-time view applications.

[0194] The reader application 1240 of FIG. 12, sometimes referred to as a viewer app, will now be described. According to some aspects, a reading or viewer application or software may be provided that enables a reader, e.g., a GI physician, to access a compiled study of procedure data and provide input for generating a CE report for the procedure. In some aspects, such an application may be installed and used from a fixed or mobile computing device (e.g., a handheld device such as an iPad®) or accessed (e.g., via the web). In some aspects, the reading app may be incorporated into the HCP app. In some aspects, the reading application may enable a reader to access a compiled study and provide input for remotely generating a CE procedure report.

[0195] A treatment investigation may include images selected from treatment data (i.e., treatment data received by a computing system according to the disclosed systems and methods). The investigation images may be, for example, images selected to represent treatment data or GIT portions of interest, depending on the purpose of the CE treatment, images selected to include or represent one or more event indicators of interest, or images selected for such a combination. According to some aspects, the investigation may include additional data such as the estimated position of the image along the GIT, an indicator for an event indicator identified (with some level of certainty) within the image, and the size of such an event indicator. To select the images included in the investigation and receive additional data, the images may be processed and analyzed by a computing system (e.g., an AI cloud of a cloud system according to the disclosed systems and methods). In some embodiments, the investigation images may include two levels of images selected in two stages. In the first stage, the images of the first level may be selected as disclosed above. In the second stage, images of the second level may be selected to provide additional information regarding the images of the first level. According to some aspects, the images of the first level are displayed in the viewer by default, while the images of the second level are displayed only in accordance with a user action or request. The images of the first and second levels may be displayed as illustrated and described with respect to FIGS. 24 and 25 below of this specification.

[0196] According to some embodiments, a subset of the images of the captured stream of in-vivo images (i.e., the images of the treatment data) can be automatically selected from the stream of in-vivo images according to a first selection method. For each image of at least a portion of the subset of images, one or more corresponding additional images can be selected from the stream of in-vivo images according to a second selection method. For each image of the subset of images, one or more images can be selected according to the second selection method. The selected subset of images (i.e., the images of the first level) may be displayed for user review. Upon receiving user input (e.g., mouse click, activation of a GUI control, etc.), one or more additional images (i.e., the images of the second level) corresponding to the currently displayed image of the subset of images (i.e., the images of the first level) can be displayed. The second selection method may be based on the relationship between the images of the in-vivo image stream and the currently displayed image. Such a relationship between the images of the first level and the images of the second level can be identified such that the images include at least a portion of the same feature or the same event or event indicator, the images include at least a portion of the same type of feature or event or event indicator, the images are captured in temporal proximity, the images are located adjacent along at least a portion of the GIT of the subject, and combinations thereof. The subset of images and the one or more images corresponding to the subset of images may be automatically selected by a computing device (e.g., an AI cloud). According to some embodiments, the selection may involve the application of machine learning, particularly deep learning.

[0197] FIG. 24 shows an exemplary display screen of a compiled survey generated based on the systems and methods of the present disclosure. A GUI (or survey viewing application) can be used to display a survey regarding a user's review and generate a survey report (or CE procedure report). The survey may be generated based on or represent one or more pre-defined event indicators. The screen displays a set of still images included in the survey. A user can review the images of the survey and select one or more images of interest, for example, to display one or more pre-defined event indicators. For example, the small intestine may include multiple pathologies of interest such as ulcers, polyps, strictures, etc. These pathologies may be pre-defined as event indicators for generating a survey based on the present systems and methods. As another example, in a colon procedure for cancer screening, a polyp may be of interest. FIG. 24 shows a display of a survey of such a colon procedure. The illustrated screen shows a portion of the survey images. A user can review additional images, for example, by sliding between image pages or by switching tabs. According to some aspects, the survey images can be displayed according to their positions within the colon. This position can be any one of the following five anatomical colon segments: the cecum, ascending, transverse, descending sigmoid colon, and rectum (as shown in FIG. 25). The image in focus may be presented with additional information such as image 2410. The illustrated display screen may be used by a user, such as a clinician, to select images included in a procedure report. The illustrated display screen is exemplary, and variant forms are intended to be within the scope of the present disclosure.

[0198] Referring to FIG. 25, the screen shows the survey images according to their positions within the colon segments. The user can switch the display of images located in different segments by switching between the segment tabs. In some embodiments, the survey may also include additional images associated with the first-level images, i.e., second-level images, which are displayed by default 2510. In such cases, the user can request (via user input) to display the second-level images associated with the displayed images, e.g., the image in focus. By reviewing the associated images, the reader can receive additional information regarding the first-level images that can assist him in determining whether the first-level images (or optionally any other second-level images) are of interest.

[0199] FIG. 26 is a block diagram of an exemplary device and system for implementing a capsule endoscopy procedure and exemplary components. Various aspects of FIG. 26 have been addressed above. For example, the facility data center was addressed in relation to FIGS. 1 and 3, the patient's home system and the GI / PCP clinic system were addressed in relation to FIGS. 6 - 11, and aspects of the cloud system were addressed in relation to FIG. 12. Below, a more detailed description of the cloud system is provided, including the HCP cloud subsystem 2610 and the AI cloud subsystem 2620.

[0200] The illustrated cloud system is a multi-user system that can support a vast number of procedures executed in parallel, even when the resource load can vary dramatically at different times (e.g., peak time vs. "low activity" time or no activity time). Regarding system uptime, the cloud system is dynamically scalable, which allows for stable updates and changes to the cloud platform without affecting system uptime.

[0201] The AI cloud subsystem 2620 is responsible for processing data and can perform resource-intensive calculations such as machine learning and specifically deep learning. The AI cloud can also execute non-AI processing and tasks. Some machine learning algorithms are complex and require heavy computational resources. These resources need to scale out when the usage load increases in order to support multiple accounts / users simultaneously during peak levels and to maintain the expected service levels. To meet the ever-increasing need for high performance with powerful computing capabilities in a scalable platform, the software infrastructure must also effectively utilize cloud resources to provide both performance and efficiency.

[0202] As will be recognized by those skilled in the art, the difference between different software architectures is at the level of granularity. Generally, a more fine-grained architecture provides more flexibility. A software system is "monolithic" when the functionally distinguishable aspects (e.g., data input and output, data processing, error handling, and user interface) are woven together rather than being contained in architecturally distinct components. In the illustrated cloud system, the software architecture of the cloud system decomposes a large monolithic flow into small pieces of a structured pipeline that can be more easily managed and scaled by using microservice technology. Microservices, or microservice architecture, is an approach to application development where a large application is built as a suite of modular components or services. When the operations are split into microservices, each microservice can generally function independently without depending on most of the other microservices.

[0203] Such a software architecture enables the scalability of the system so that services can be added or removed on demand. Each microservice is packaged within a container, and optionally, it may be a package within the container docker. A container is a standard unit of software that packages code and all its dependencies, so that an application can be run quickly and reliably from one computing environment to another. A docker container is a lightweight, stand-alone executable package of software that includes everything needed to run an application, such as code, runtime, system tools, system libraries, and settings. A docker container is a type of virtual environment that holds, for example, an operating system and all the elements required to run microservices (such as applications). The cloud system of FIG. 26 can use microservices and can use docker containers to hold all the elements required to run the microservices.

[0204] Orchestrator applications such as Kubernetes can be used for container management. Container management applications can add or remove containers. With respect to groups of machines and containerized applications (such as Dockerized applications), the orchestrator can manage those applications across those machines. The use of an orchestrator can improve the performance of the system.

[0205] In the cloud system of FIG. 26, each machine (i.e., server) can execute one or more microservices. Communication between services can be implemented in various ways. One approach is a service bus or message bus, which enables services to communicate via the bus using a "send and forget" approach. Each service forwards requests to the bus and consumes requests from the bus when available, enabling responses to each request. Using a service bus can make communication more efficient because one message can be delivered to multiple services.

[0206] The above-described cloud system architecture provides a flexible and efficient cloud platform, simplifies upgrades within the cloud system, and enables scalability and compatibility for the specific needs of system clients. It supports and facilitates a multi-user system that serves a large number of end-users simultaneously. Also, since the services are mostly independent, it can handle malfunctions better. At each point in time, the health level of the system, such as the load level and exceptions in a particular microservice, can be monitored and addressed immediately. Such an architecture of the cloud system may be sufficient to meet the requirements of the disclosed systems and methods, including heavy computing tasks involving complex algorithms such as deep learning algorithms and processing of large amounts of data.

[0207] The above aspects are illustrative, and variations are intended to be within the scope of the present disclosure. For example, the above architecture may be applicable to on-premises computing systems such as the system of FIG. 3. Such variations are intended to be within the scope of the present disclosure.

[0208] Here, various operations related to FIGS. 27 to 30 will be described. These operations are examples of the use of the systems, devices, and methods of the present disclosure. In various embodiments, the operations of FIGS. 27 to 30 use various systems and devices such as those shown in FIG. 6. The above-described figures and embodiments are illustrative and do not limit the scope of the present disclosure.

[0209] FIG. 27 shows a flowchart of an exemplary operation for processing an image captured during a capsule endoscopy procedure. At block 2710, the operation involves the capsule device capturing in vivo images of at least a portion of a person's gastrointestinal tract (GIT) over time. At block 2720, the operation involves a wearable device configured to be fixed to a person receiving at least some of the in vivo images from the capsule device. At block 2730, the operation involves the wearable device communicating at least some of the received images to a communication device located at the same location as the wearable device. The communication device and the wearable device can be located at the same location when both are, for example, at the patient's home or at a healthcare provider's facility. At block 2740, the operation involves a remote computing system receiving the communicated images from the communication device from the location of the wearable device. At block 2750, the operation involves the computing system performing processing of the communicated images received from the communication device. At block 2760, the operation may optionally involve the computing system communicating with at least one healthcare provider device. In various embodiments, the computing system may communicate with at least one healthcare provider device regarding the progress and status of the patient before, during, and / or after the capsule endoscopy procedure, or regarding the result or a portion of the procedure. The operations of FIG. 27 are illustrative, and variations are contemplated to be within the scope of the present disclosure.

[0210] FIG. 28 shows a flowchart of exemplary operations for online processing of images captured during a capsule endoscopy procedure. At block 2810, the operation involves capturing in vivo images of at least a portion of a person's gastrointestinal tract (GIT) over time by a capsule device. At block 2820, the operation involves wirelessly transmitting by the capsule device at least some of the captured images to a wearable device configured to be fixed to a person during the capsule endoscopy procedure. At block 2830, the operation involves receiving by the wearable device the images transmitted by the capsule device. At block 2840, the operation involves wirelessly transmitting by the wearable device at least some of the images received from the capsule device to a computing system during the capsule endoscopy procedure. At block 2850, the operation involves performing by the computing system online processing of the images received from the wearable device during the capsule endoscopy procedure. The online processing may include utilizing machine learning and deep learning. And at block 2860, the operation involves providing by the computing system the results of the online processing during the capsule endoscopy procedure. In various embodiments, the online processing provides an array of multi-purpose and comprehensive tools that can be used during a capsule endoscopy procedure to better understand the patient's gastrointestinal health and to better understand treatment and care. The operations of FIG. 28 are exemplary, and variations are contemplated to be within the scope of the present disclosure.

[0211] Figure 29 shows a flowchart of exemplary operations for a capsule endoscopy procedure that can be performed entirely at home or in another non-medical environment. At block 2910, the operation involves receiving an online registration for a capsule endoscopy procedure prescribed to a person by a healthcare provider (HCP). At block 2920, the operation involves receiving an online indicator that the capsule endoscopy procedure has arrived. According to some aspects, such an indicator may not precede the upload of an image or may simply be the upload of an image. At block 2930, the operation is to receive, in a cloud system, images of a person's gastrointestinal tract, where the images are captured by a capsule device while traversing the person's gastrointestinal tract and communicated to the cloud system via a wearable device during the capsule endoscopy procedure. The images are captured by the capsule device while traversing the person's gastrointestinal tract and communicated to the cloud system via a wearable device during the capsule endoscopy procedure. At block 2940, the operation involves generating a capsule endoscopy investigation by the cloud system based on at least some of the received images. At block 2950, the operation involves providing access to the investigation to a reader. At block 2960, the operation involves generating a capsule endoscopy report based on the capsule endoscopy investigation and based on input provided by the reader. And at block 2970, the operation involves providing the capsule endoscopy report to the HCP. According to some aspects, the capsule device and the wearable device are disposable and uniquely coupled, and the capsule device and the wearable device are ordered online based on a prescription provided by the HCP and mailed to a delivery address provided in the order. According to some aspects, the kit is not ordered or purchased online but is ordered or purchased, for example, by ordering or purchasing at a vendor store. According to some aspects, the kit is not mailed to the delivery address provided in the order but is purchased, for example, at a vendor store (e.g., a pharmacy).

[0212] As an example of the operation of FIG. 29, the illustrated operation may be used for widespread population screening, such as colon cancer screening. Screening medical procedures are typically carried out on a wide scale and should therefore be user-friendly to achieve a high level of compliance. Thus, in some aspects, a kit including disposable capsules, such as patches as described above, and disposable wearable devices may be provided directly to customers (i.e., patients) along with a prescription. The patch may be a single integrated device (as opposed to a device having separate parts) that includes an adhesive configured to adhere to the patient's skin, such as the abdomen, and can be easily removed. The capsule and the disposable device may be pre-connected or coupled in the factory, and thus the customer can omit performing such pairing procedures. The kit may also include instructions written regarding how the medical procedure should be set up (e.g., setting up and wearing the wearable device, whether to swallow the capsule). The patient application may provide instructions for setting up the procedure. The patient may then self-administer the capsule swallowing. During the procedure, the procedure data may be uploaded from the wearable device to the cloud infrastructure via the patient mobile device, or directly to the cloud infrastructure (e.g., by incorporating a cellular modem and SIM device within the wearable device). An online warning can indicate to the patient that the procedure has ended, and he can remove the wearable device and fully resume his daily activities. The warning can be generated on the cloud by using online processing to identify that the capsule device has traversed the entire GIT part of interest. Alternatively, such detection may be performed on the wearable device. The procedure data can then be processed on the cloud system to generate a compiled investigation. The reader can access the compiled investigation via the reader application. The reader can review and evaluate the investigation via the reading application and generate a report.Notifications or copies of the report may be forwarded to the patient and / or the referring physician (e.g., via a patient application). According to some aspects, an HCP application similar to the HCP application described above may be provided to the referring physician. The referring physician may use this application to communicate, for example, with the patient and / or the leader, track or receive the status of a medical treatment, and receive or view the report. The embodiments described above with respect to FIG. 29 are illustrative, and variations are intended to be within the scope of the present disclosure.

[0213] Figure 30 shows a flowchart of an exemplary operation for scheduling a same-day colonoscopy based on findings during a colon capsule endoscopy procedure. At block 3010, the operation involves receiving an image of a person's gastrointestinal tract (GIT) captured during a colon capsule endoscopy procedure. At block 3020, the operation is to identify one or more suspicious colon images among the received images during the colon capsule endoscopy procedure and up to a predefined procedure event, where the one or more suspicious colon images are identified as images of the colon and including candidates for a predefined event indicator that requires a colonoscopy, and the predefined procedure event occurs while the colon capsule endoscopy device is traversing the colon, involving identifying. By using a cloud infrastructure as a platform for online processing, it may be possible to receive relatively fast results. By utilizing state-of-the-art algorithms such as machine learning and deep learning, it may be possible to improve performance in identifying suspicious images. At block 3030, the operation involves providing one or more suspicious colon images to a healthcare provider during the colon capsule endoscopy procedure. And at block 3040, an optional operation involves storing an indicator that a colonoscopy required for the person is scheduled on the same day as the colon capsule endoscopy procedure. Since the preparation for the colon capsule endoscopy procedure may be the same as or sufficient as the preparation for the colonoscopy, scheduling a colonoscopy on the same day as the colon capsule endoscopy procedure is more convenient for the patient and avoids another preparation round for the patient. The embodiments described with respect to Figure 30 are illustrative, and variations are intended to be within the scope of the present disclosure.

[0214] Accordingly, a system, device, method, and application example for a capsule endoscopy procedure are described herein. For the purpose of explanation, specific configurations and details are described to provide a complete understanding of the disclosed technical aspects. However, it will be apparent to those skilled in the art that the disclosed technology can be implemented without using any of the aspects presented herein.

[0215] Unless otherwise specified, as is apparent from the foregoing description, throughout the description of this specification, the use of terms such as "processing", "computing", "memory", "judgment", etc. refers to the action and / or process of a computer or computing system, or a similar electronic computing device that manipulates and / or transforms data represented as a physical quantity such as an electronic quantity in a register and / or memory of a computing system into other data similarly represented as a physical quantity in a memory, register, or other such information storage, transmission, or display device of the computing system.

[0216] Various aspects are disclosed herein. The features of a particular aspect can be combined with the features of other aspects, and thus a particular aspect can be a combination of the features of multiple aspects.

[0217] Although some embodiments of the present disclosure are described herein and / or illustrated in the drawings, the present disclosure is not intended to be limited thereto, and it is intended that the present disclosure cover the broadest possible scope in the relevant art and that this specification be interpreted similarly. Therefore, the above description should be construed merely as an exemplification of a particular embodiment and not as a limiting one. Other modifications that do not depart from the scope and spirit of the claims appended hereto will be apparent to those skilled in the art. (Item 1) A system for a capsule endoscopy procedure, A capsule device configured to capture in vivo images of at least a portion of a human gastrointestinal tract (GIT) over time, A wearable device configured to be fixed to the person, the wearable device being configured to receive at least some of the in-vivo images from the capsule device and to communicate at least some of the received images to a communication device at the same position as the wearable device, the wearable device, A storage medium storing machine-executable instructions configured to be executed on a remote computing system from the position of the wearable device, the instructions, when executed, causing the computing system to, Receive a communication image from the communication device and execute processing of the communication image received from the communication device, Communicate with at least one healthcare provider device, a storage medium, a system. (Item 2) The computing system is a cloud system, and the cloud system includes the storage medium, the system according to item 1. (Item 3) The communication device is a mobile device carried by the person, and the system further includes a patient application configured to be installed on the mobile device and to interoperate with the wearable device and the computing system, the system according to item 1. (Item 4) The patient application is configured to set communication of data from the wearable device to the computing system via the mobile device, the system according to item 3. (Item 5) The instructions, when executed, further cause the computing system to adjust communication between the patient application and at least one of the at least one healthcare provider device, the system according to item 1. (Item 6) Before the capsule endoscopy procedure, The patient app is configured to receive patient confirmation that the patient preparation regimen has been completed and to communicate the patient confirmation to the computing system. The system of item 5, wherein when the instruction is executed, the computing system is caused to communicate the patient confirmation to at least one of the at least one healthcare provider device. (Item 7) During the capsule endoscopy procedure The system of item 3, wherein the wearable device is configured to communicate to the patient app an instruction for the person to ingest a boost agent. (Item 8) The system of item 7, wherein the patient app is configured to receive the instruction on the mobile device, to display the instruction for the person to ingest the boost agent, and to receive patient confirmation that the instruction has been completed. (Item 9) A method for a capsule endoscopy procedure, comprising: capturing, by a capsule device, in-vivo images of at least a portion of a person's gastrointestinal tract (GIT) over time; receiving, by a wearable device configured to be fixed to the person, at least some of the in-vivo images from the capsule device; communicating, by the wearable device, at least some of the received images to a communication device at the same location as the wearable device; receiving, by a remote computing system from the location of the wearable device, communication images from the communication device; executing, by the computing system, processing of the communication images received from the communication device; communicating, by the computing system, with at least one healthcare provider device. (Item 10) The method according to item 9, wherein the computing system is a cloud system. (Item 11) The method according to item 9, wherein the communication device is a mobile device carried by the person, and the mobile device is provided with a patient app configured to interoperate with the wearable device and the computing system. (Item 12) The method according to item 11, further comprising setting, by the patient app, communication of data from the wearable device to the computing system via the mobile device. (Item 13) The method according to item 9, further comprising adjusting, by the computing system, communication between the patient app and at least one of the at least one healthcare provider device. (Item 14) Before the capsule endoscopy procedure, receiving, by the patient app, patient confirmation that a patient preparation regimen has been completed; communicating, by the patient app, the patient confirmation to the computing system; The method according to item 13, further comprising communicating, by the computing system, the patient confirmation to at least one of the at least one healthcare provider device. (Item 15) The method according to item 11, further comprising communicating, by the wearable device, to the patient app, an instruction for the person to ingest a boosting agent during the capsule endoscopy procedure. (Item 16) By the patient app, receiving the instruction; displaying, on the mobile device, the instruction for ingesting the boosting agent; and receiving patient confirmation that the instruction has been completed. The method according to item 15. (Item 17) displaying, on a display device, a subset of images from the in-vivo images over time for user review, wherein the subset of images represents at least a portion of the captured in-vivo images and the subset of images is automatically selected from the in-vivo images by one or more hardware processors according to a first selection method; receiving a user selection of one of the displayed images from the subset of the displayed images; displaying, on the display device, one or more additional images corresponding to the one displayed image based on the user selection, wherein the one or more additional images are automatically selected from the in-vivo images by one or more hardware processors according to a second selection method, and the second selection method is based on a relationship between an image of the in-vivo images and the one displayed image; generating a report, wherein the report includes an image from the displayed images selected by the user; and the method according to item 9 further includes the above steps. (Item 18) selecting the subset of images according to the first selection method; for each image of at least a portion of the subset of images, selecting the one or more corresponding additional images from the in-vivo images according to the second selection method; and the method according to item 17 further includes the above steps. (Item 19) A system for a capsule endoscopy procedure, a capsule device configured to capture in-vivo images of at least a portion of a human gastrointestinal tract (GIT) over time; a wearable device configured to be fixed to the human and receive at least some of the in-vivo images from the capsule device, wherein the wearable device stores the received images; A storage medium storing machine-executable instructions configured to be executed on a computing system, wherein the instructions, when executed, cause the computing system to receive, during the capsule endoscopy procedure, at least some of the stored images from the wearable device; perform online processing of the images received from the wearable device during the capsule endoscopy procedure; provide, during the capsule endoscopy procedure, the result of the online processing, a storage medium and a system comprising the storage medium. (Item 20) Performing the online processing of the images includes applying machine learning to the images received from the wearable device to estimate whether the images received from the wearable device include a transition from an image of the segment of the GIT to an image beyond the segment of the GIT, the system according to item 19. (Item 21) If the image includes the transition, the computing system is configured to communicate a message indicating that the capsule endoscopy procedure is complete and that the wearable device can be removed. The system according to item 20, wherein the message is communicated to at least one of the device carried by the person or the wearable device. (Item 22) The system according to item 21, wherein the segment of the GIT is the small intestine and the image includes a transition from an image of the small intestine to an image of the colon. (Item 23) Performing the online processing of the images includes applying machine learning to estimate the position of the GIT where the image was captured for each image received from the wearable device, the system according to item 19. (Item 24) The system according to item 19, wherein performing the online processing of the image includes estimating the existence of at least one event indicator. (Item 25) The at least one event indicator is within a predetermined category of urgent medical risk, The system according to item 24, wherein when it is estimated that the at least one event indicator exists, the computing system is configured to communicate a warning message indicating the estimated existence of the urgent medical risk to a device of a healthcare provider. (Item 26) The system according to item 25, wherein the warning message includes at least one image indicating the at least one event indicator, and the warning message optionally includes the location of the GIT where the at least one event indicator is estimated to exist. (Item 27) The system according to item 24, wherein the at least one event indicator requires a colonoscopy. (Item 28) The system according to item 27, wherein the computing system is configured to communicate a message regarding an order for a same-day colonoscopy to the device of the person, and the same-day colonoscopy is scheduled on the same day as the capsule endoscopy procedure. (Item 29) The system according to item 28, wherein the at least one event indicator is a polyp. (Item 30) The system according to item 27, wherein the at least one event indicator requiring a colonoscopy is reported as a provisional finding of the capsule endoscopy procedure to a device of a healthcare provider during the capsule endoscopy procedure, and the provisional finding is generated based on at least some of the in-vivo images captured by the capsule device up to that point in time during the capsule endoscopy procedure. (Item 31) Performing the online processing of the image includes generating preliminary findings based on at least some of the in-vivo images captured by the capsule device up to that point in time during the capsule endoscopy procedure, for the system according to item 19. (Item 32) The system according to item 31, wherein the preliminary findings include at least one of the in-vivo images indicating the presence of at least one event indicator. (Item 33) The system according to item 32, wherein the preliminary findings further include the location of the GIT where the at least one event indicator is present. (Item 34) For the system according to item 31, the point in time is one of a preset time interval for generating the preliminary findings, a time corresponding to a request to generate the preliminary findings, or a time corresponding to the online detection of at least one event indicator. (Item 35) For the system according to item 34, the online detection includes at least one of online detection of anatomical landmarks, online detection of anatomical segments, or online detection of the presence of a medical condition. (Item 36) A method for a capsule endoscopy procedure, Capturing in-vivo images of at least a portion of a human gastrointestinal tract (GIT) over time by a capsule device, Receiving at least some of the in-vivo images from the capsule device by a wearable device configured to be fixed to the human, Storing the received images by the wearable device, Receiving at least some of the stored images from the wearable device by a computing system during the capsule endoscopy procedure, During the capsule endoscopy examination procedure, the computing system performs online processing of the image received from the wearable device, During the capsule endoscopy examination procedure, the computing system provides the result of the online processing, the method comprising: (Item 37) Executing the online processing of the image includes applying machine learning to the image received from the wearable device to estimate whether the image received from the wearable device includes a transition from an image of a segment of the GIT to an image beyond the segment of the GIT, the method according to item 36. (Item 38) If the image includes the transition, the computing system further communicates a message indicating that the capsule endoscopy examination procedure is complete and that the wearable device can be removed, the method according to item 37, wherein the message is communicated to at least one of the device carried by the person or the wearable device. (Item 39) The method according to item 38, wherein the segment of the GIT is the small intestine and the image includes a transition from an image of the small intestine to an image of the colon. (Item 40) Executing the online processing of the image includes applying machine learning to estimate the position of the GIT at which the image was captured for each image received from the wearable device, the method according to item 36. (Item 41) Executing the online processing of the image includes estimating the presence of at least one event indicator, the method according to item 36. (Item 42) The at least one event indicator is within a predetermined category of urgent medical risk, The method according to item 41, further comprising, when it is estimated that the at least one event indicator exists, communicating, by the computing system, a warning message indicating the estimated existence of the acute medical risk to a device of a healthcare provider. (Item 43) The method according to item 42, wherein the warning message includes at least one image indicating the at least one event indicator, and the warning message optionally includes the location of the GIT where the at least one event indicator is estimated to exist. (Item 44) The method according to item 41, wherein the at least one event indicator requires a colonoscopy. (Item 45) by the computing system, on the same day The method according to item 44, further comprising communicating, to the device of the person, a message regarding an order for a colonoscopy, wherein the same-day colonoscopy is scheduled on the same day as the capsule endoscopy procedure. (Item 46) The method according to item 45, wherein the at least one event indicator is a polyp. (Item 47) The method according to item 44, wherein the at least one event indicator requiring a colonoscopy is reported, during the capsule endoscopy procedure, as a provisional finding of the capsule endoscopy procedure to a device of a healthcare provider, and the provisional finding is generated based on at least some of the in-vivo images captured by the capsule device up to that point in time during the capsule endoscopy procedure. (Item 48) The method according to item 36, wherein performing the online processing of the images includes generating a provisional finding based on at least some of the in-vivo images captured by the capsule device up to that point in time during the capsule endoscopy procedure. (Item 49) The method according to item 48, wherein the tentative finding includes at least one of the in-vivo images indicating the existence of at least one event indicator. (Item 50) The method according to item 49, wherein the tentative finding further includes the location of the GIT where the at least one event indicator exists. (Item 51) The method according to item 48, wherein the time point is one of a preset time interval for generating the tentative finding, a time corresponding to a request for generating the tentative finding, or a time corresponding to an online detection of at least one event indicator. (Item 52) The method according to item 51, wherein the online detection includes at least one of online detection of anatomical landmarks, online detection of anatomical segments, or online detection of the presence of a medical condition. (Item 53) A system for a capsule endoscopy procedure, comprising: A capsule device configured to capture in-vivo images of at least a portion of a human gastrointestinal tract (GIT) over time; and A wearable device configured to be fixed to the human, the wearable device being configured to wirelessly receive at least some of the in-vivo images captured by the capsule device. The system, wherein the wearable device and the capsule device are uniquely coupled such that the capsule device cannot communicate with another wearable device and the wearable device cannot communicate with another capsule device. (Item 54) The system according to item 53, wherein the wearable device includes a transceiver configured to connect to a communication device, and the wearable device is configured to communicate at least some of the received images to a remote computing system via the communication device. (Item 55) The system according to item 54, wherein the remote computing system is a cloud system. (Item 56) The system according to item 54, wherein the transceiver is a cellular transceiver and the communication device is a device of a cellular network. (Item 57) The system according to item 54, wherein the communication device is a router. (Item 58) The system according to item 54, wherein the communication device is an Internet-enabled mobile device. (Item 59) The system according to item 58, wherein the transceiver is configured to communicate data, and the wearable device further includes a second transceiver configured to communicate control information with the Internet-enabled mobile device. (Item 60) The system according to item 53, wherein the wearable device is a patch configured to be removably adhered to the person's skin. (Item 61) The system according to item 60, wherein the patch is configured to be a single-use disposable device. (Item 62) The system according to item 53, further comprising a mailable kit including the uniquely coupled capsule device and the wearable device. (Item 63) The system according to item 53, wherein the wearable device is configurable to operate in access point (AP) mode as a wireless access point and in client mode as a wireless client. (Item 64) In the client mode, the wearable device is configured as a wireless client of the communication device and to communicate at least some of the received images to a computing system via the communication device. In the AP mode, the wearable device is configured as a wireless access point to another wireless device and is configured to communicate at least some of the received images to the other wireless device, the system according to item 63. (Item 65) When the wearable device operates in the AP mode, the wearable device After a predetermined time, the client mode is activated to pin the communication device, the system according to item 64. (Item 66) The wearable device includes an internal storage device configured to store at least some of the images received from the capsule device. When the wearable device operates in the AP mode, the wearable device is configured to communicate a copy of the image stored in the internal storage device to the other wireless device and to maintain the stored image in the internal storage device, the system according to item 64. (Item 67) When the AP mode ends, the wearable device is configured to activate the client mode and communicate the stored image to the computing system via the mobile device, the system according to item 66. (Item 68) The wearable device includes an internal storage device, and the internal storage device stores machine-executable instructions that implement online processing of at least some of the received images using machine learning, the system according to item 53. (Item 69) The capsule device is configured to perform online processing of at least some of the in-vivo images to determine similarity and, based on the similarity determination, not to communicate at least one of the in-vivo images to the wearable device, the system according to item 53. (Item 70) The system according to item 53, wherein the wearable device is configured to perform online processing of at least some of the received images using machine learning. (Item 71) A method for providing a capsule endoscopy procedure at home, the method comprising receiving an online registration for a capsule endoscopy procedure prescribed for a person by a healthcare provider (HCP), receiving an online indicator that the capsule endoscopy procedure has been initiated, and receiving, in a cloud system, images of the person's gastrointestinal tract, the images being captured by a capsule device while traversing the person's gastrointestinal tract and communicated to the cloud system via a wearable device during the capsule endoscopy procedure, generating a capsule endoscopy investigation by the cloud system based on at least some of the received images, providing access to the capsule endoscopy investigation to a reader, generating a capsule endoscopy report based on the capsule endoscopy investigation and input provided by the reader, providing the capsule endoscopy report to the HCP, and wherein the capsule device and the wearable device are disposable and uniquely coupled, and the capsule device and the wearable device are ordered online based on a prescription provided by the HCP and mailed to a delivery address provided in the order. (Item 72) The method according to item 71, wherein the capsule endoscopy kit is a home screening capsule endoscopy kit and the capsule endoscopy procedure is an endoscopy screening procedure. (Item 73) Receiving an online order for a capsule endoscopy kit based on a prescription provided by a healthcare provider (HCP) for a person's capsule endoscopy procedure, wherein the capsule endoscopy kit comprises a disposable capsule device and a disposable wearable device, and the disposable capsule device and the disposable wearable device are uniquely coupled, Further comprising mailing the capsule endoscopy kit to a delivery address provided in the order, the method of item 71. (Item 74) A method for a colon capsule endoscopy procedure, the method comprising receiving images of a person's gastrointestinal tract (GIT) captured during the colon capsule endoscopy procedure, wherein the GIT includes the colon, During the colon capsule endoscopy procedure and up to a predefined procedure event, identifying one or more suspicious colon images among the received images, wherein the one or more suspicious colon images are identified as images of the colon and include candidates for a predefined event indicator that requires a colonoscopy, and the predefined procedure event occurs while the colon capsule endoscopy device traverses the colon, identifying; and during the colon capsule endoscopy procedure, providing the one or more suspicious colon images to a healthcare provider. Remembering an indicator that a colonoscopy required for the person is scheduled on the same day as the colon capsule endoscopy procedure, the method. (Item 75) The method of item 74, further comprising instructing the person to take a preparation regimen prior to the colon capsule endoscopy procedure. (Item 76) The method of item 74, wherein the predefined event indicator is polyp growth that requires a colonoscopy. (Item 77) The method according to item 74, further comprising providing to the healthcare provider at least one of location information indicating which segment of the colon is shown in the one or more suspicious colon images, information regarding the candidates in the one or more suspicious colon images, or an estimate of the type of the event indicator, during the colon capsule endoscopy procedure. (Item 78) The required colonoscopy for the person is based on a review by the healthcare provider of the one or more suspicious colon images and a determination by the healthcare provider that a colonoscopy is required. The method The method according to item 74, further comprising communicating to the person a message that a colonoscopy is required and receiving an indication that the person has consented to a same-day colonoscopy. (Item 79) The method according to item 74, wherein the identifying of the one or more suspicious colon images is performed by a cloud system using machine learning.

Claims

1. A system for a capsule endoscopy examination procedure, the system comprising: a capsule device configured to capture over time a plurality of in-vivo images of at least a portion of a human gastrointestinal tract (GIT); a wearable device configured to be fixed to the human, the wearable device being configured to receive at least some of the plurality of in-vivo images from the capsule device, store the received plurality of images, and communicate at least some of the received plurality of images to a communication device at the same location as the wearable device; a storage medium storing machine-executable instructions configured to be executed on a remote computing system from the location of the wearable device; comprising; the machine-executable instructions, when executed, cause the computing system to:[[]] receive, during the capsule endoscopy examination procedure, a plurality of communicated images from the communication device; perform online processing of the plurality of communicated images received from the communication device during the capsule endoscopy examination procedure; communicate the result of the online processing to at least one healthcare provider device during the capsule endoscopy examination procedure; A system that causes the computing system to perform.

2. The computing system is a cloud system, and the cloud system comprises the storage medium. The system according to claim 1.

3. The communication device is a mobile device carried by the human, and the system further comprises a patient app configured to be installed on the mobile device and interoperate with the wearable device and the computing system, The patient app is configured to set up communication of data from the wearable device to the computing system via the mobile device. The system according to claim 1.

4. The machine-executable instructions, when executed, further cause the computing system to adjust communication between at least one of the patient app and at least one of the at least one healthcare provider device. The system according to claim 3.

5. Before the capsule endoscopy procedure, the patient app is configured to receive a patient confirmation that the patient preparation regimen has been completed and communicate the patient confirmation to the computing system, The system of claim 4, wherein the machine-executable instructions, when executed, cause the computing system to communicate the patient confirmation to at least one of the at least one healthcare provider device.

6. During the capsule endoscopy procedure, the wearable device is configured to communicate instructions for the person to the patient app to ingest a boost agent, The system of claim 3, wherein the patient app is configured to receive the instructions for the person, display the instructions for the person on the mobile device to ingest the boost agent, and receive a patient confirmation that the instructions for the person have been completed.

7. A method for a capsule endoscopy procedure, comprising: a capsule device capturing a plurality of in-vivo images of at least a portion of a person's gastrointestinal tract (GIT) over time; a wearable device configured to be fixed to the person receiving and storing at least some of the plurality of in-vivo images from the capsule device; the wearable device communicating at least some of the received plurality of images to a communication device at the same location as the wearable device; during the capsule endoscopy procedure, a remote computing system receiving the plurality of communicated images from the communication device from the location of the wearable device; during the capsule endoscopy procedure, the computing system performing an online process of the plurality of communicated images received from the communication device; and during the capsule endoscopy procedure, communicating the result of the online process to at least one healthcare provider device. A method comprising.

8. The method of claim 7, wherein the computing system is a cloud system, and the cloud system comprises a storage medium.

9. Performing the online processing of the plurality of images includes estimating whether the plurality of images received from the wearable device include a transition from an image of a segment of the GIT to an image beyond the segment of the GIT by applying machine learning to the plurality of images received from the wearable device. The system according to claim 1.

10. When the plurality of images include the transition, the computing system is configured to communicate a message indicating that the capsule endoscopy procedure is complete and that the wearable device can be removed. The message is communicated to at least one of the device carried by the person or the wearable device. The system according to claim 9.

11. Performing the online processing of the plurality of images includes estimating, by applying machine learning, the position of the GIT where the plurality of images were captured for each image received from the wearable device, or estimating the presence of at least one event indicator. The system according to claim 1 includes at least one of these.

12. The at least one event indicator is within a predetermined category of urgent medical risk. When it is estimated that the at least one event indicator is present, the computing system is configured to communicate a warning message indicating the estimated presence of the urgent medical risk to a device of a healthcare provider. The system according to claim 11.

13. The warning message includes at least one image indicating the at least one event indicator. The warning message optionally includes the position of the GIT where the at least one event indicator is estimated to be present. The system according to claim 12.

14. The at least one event indicator requires a colonoscopy. The system according to claim 11.

15. The computing system is configured to communicate a message regarding an order for a same-day colonoscopy to the device of the person. The same-day colonoscopy is scheduled on the same day as the capsule endoscopy procedure. The system according to claim 14.

16. ​ Performing the online processing of the plurality of images includes generating provisional findings based on at least some of the plurality of in-vivo images captured by the capsule device up to that point in time during the capsule endoscopy procedure, for the system according to claim 1.

17. The provisional findings include at least one of the plurality of in-vivo images indicating the presence of at least one event indicator, The provisional findings further include the location of the GIT where the at least one event indicator is present, for the system according to claim 16.

18. The point in time is one of a preset time interval for generating the provisional findings, a time corresponding to a request to generate the provisional findings, or a time corresponding to an online detection of at least one event indicator, for the system according to claim 16.

19. The online detection includes at least one of online detection of anatomical landmarks, online detection of anatomical segments, or online detection of the presence of a medical condition, for the system according to claim 18.

20. The wearable device and the capsule device are uniquely coupled such that the capsule device cannot communicate with another wearable device and the wearable device cannot communicate with another capsule device, for the system according to claim 1.

21. The wearable device includes a transceiver configured to connect to the communication device, and the wearable device is configured to communicate at least some of the received plurality of images from the location of the wearable device to the remote computing system via the communication device, for the system according to claim 1 or claim 20.

22. The communication device is one of a router or an internet-enabled mobile device, for the system according to claim 21.

23. The wearable device is a patch configured to removably adhere to the person's skin, for the system according to claim 1 or claim 20.

24. The patch is configured to be a single-use disposable device, for the system according to claim 23.

25. The system further comprises a mail - able kit, wherein the mail - able kit includes the uniquely - coupled capsule device and the wearable device, and the system according to claim 20.

26. The wearable device is configured to operate in access point (AP) mode as a wireless access point and to operate in client mode as a wireless client, according to claim 1 or claim 20 of the system.

27. The wearable device comprises an internal storage device, and the internal storage device stores machine - executable instructions for implementing online processing of at least some of the received plurality of images using machine learning, according to claim 1 or claim 20 of the system.

28. The capsule device is configured to determine similarity by performing online processing of at least some of the plurality of in - vivo images, and not to communicate at least one of the plurality of in - vivo images to the wearable device based on the determined similarity from the online processing of the at least some of the plurality of in - vivo images, according to claim 1 or claim 20 of the system.

29. A method for processing capsule endoscopy images, the method comprising: receiving an online registration for a capsule endoscopy procedure prescribed for a person by a healthcare provider (HCP); receiving an online indicator that the capsule endoscopy procedure has started; receiving, in a cloud system, a plurality of images of the gastrointestinal tract of the person, the plurality of images being captured by a capsule device while traversing the gastrointestinal tract of the person and communicated to the cloud system via a wearable device during the capsule endoscopy procedure; the cloud system generating a capsule endoscopy investigation based on at least some of the received plurality of images; providing access to the capsule endoscopy investigation to a reader; generating a capsule endoscopy report based on the capsule endoscopy investigation and input provided by the reader; and providing the capsule endoscopy report to the HCP. Including The method is such that the capsule device and the wearable device are disposable and uniquely coupled, and the capsule device and the wearable device are ordered online based on a prescription provided by the HCP and mailed to a delivery address provided in the order.

30. A capsule endoscopy kit comprises the capsule device and the wearable device. The method according to claim 29, wherein the capsule endoscopy kit is a home screening capsule endoscopy kit, and the capsule endoscopy procedure is an endoscopy screening procedure.

31. A method for processing capsule endoscopy images, the method comprising: receiving a plurality of images of a person's gastrointestinal tract (GIT) captured during a colon capsule endoscopy procedure, wherein the GIT includes the colon; identifying, during the colon capsule endoscopy procedure and up to a predefined procedure event, one or more suspicious colon images from among the plurality of received images, wherein the one or more suspicious colon images are identified as images of the colon and include candidates for a predefined event indicator that requires colonoscopy, and the predefined procedure event occurs while the colon capsule endoscopy device traverses the colon; providing the one or more suspicious colon images to a healthcare provider during the colon capsule endoscopy procedure; and storing an indicator that a colonoscopy required for the person is scheduled on the same day as the colon capsule endoscopy procedure. The method includes.

32. The method according to claim 31, further comprising providing to the healthcare provider, during the colon capsule endoscopy procedure, at least one of position information indicating which segment of the colon is shown in the one or more suspicious colon images, information regarding the candidates in the one or more suspicious colon images, or an estimate of the type of the event indicator.

33. The required colonoscopy for the person is based on the review of the one or more suspicious colon images by the healthcare provider and the determination by the healthcare provider that a colonoscopy is required. The method communicates to the person a message that a colonoscopy is required, and receives an indication that the person has consented to a same-day colonoscopy. The method according to claim 31, further comprising. **Claim 34** The method according to claim 31, wherein identifying the one or more suspicious colon images is performed by a cloud system using machine learning.

Images