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EP-4734828-A1 - LUNG MONITORING SYSTEM

EP4734828A1EP 4734828 A1EP4734828 A1EP 4734828A1EP-4734828-A1

Abstract

Broadly speaking, embodiments of the present techniques relate to a lung monitoring system. In particular, the present techniques relate to a method and device for monitoring a patient's lung, particularly using a portable device. The lung monitoring techniques may then be used to infer information a patient's lung health. In particular, the techniques comprise a computer-implemented method for tracking a user's chest movement, the method comprising: receiving video data of the user's chest showing the user breathing, the video data comprising a plurality of images showing the user's chest; defining a plurality of template tracking areas in a first image of the plurality of images, each template tracking area comprising a plurality of pixels; for each other image in the plurality of images, locating a plurality of corresponding tracking areas in the image, wherein each corresponding tracking area corresponds to one of the plurality of template tracking areas; and for each of the plurality of corresponding tracking areas, determining a difference in location between the corresponding tracking area in the image and a previous image from the plurality of images; determining, using the determined location differences, movement of the user's chest; and outputting information on the determined movement of the user's chest.

Inventors

  • PATEL, Bipin Chandra
  • KARLAFTIS, Vasileios Misak
  • STEVENS, Joseph John
  • NEEDHAM, George Richard
  • WASHINGTON, Jazzmin Shuntel

Assignees

  • Electronrx Limited

Dates

Publication Date
20260506
Application Date
20240626

Claims (15)

  1. 1. A computer-implemented method for tracking a user’s chest movement, the method comprising: receiving video data of the user’s chest showing the user breathing, the video data comprising a plurality of images showing the user’s chest; defining a plurality of template tracking areas in a first image of the plurality of images, each template tracking area comprising a plurality of pixels by: defining a target area in the first image; and defining a grid of tracking areas across the target area, wherein the grid specifies a minimum number of pixels between adjacent tracking areas in the grid; for each other image in the plurality of images, locating a plurality of corresponding tracking areas in the image, wherein each corresponding tracking area corresponds to one of the plurality of template tracking areas; and for each of the plurality of corresponding tracking areas, determining a difference in location between the corresponding tracking area in the image and a previous image from the plurality of images ; determining, using the determined location differences, movement of the user’s chest; and outputting information on the determined movement of the user’s chest.
  2. 2. The method as claimed in claim 1 , wherein the template tracking areas have a uniform size and are uniformly arranged in the grid.
  3. 3. The method as claimed in any one of the preceding claims, wherein locating a plurality of corresponding tracking areas in each of the other images comprises, for each other image in the plurality of images, placing a search area at each location in the other image corresponding to a location of one of the plurality of template tracking areas and for each search area: defining multiple subareas within the search area, wherein each subarea has the same size and shape as the corresponding template tracking area; calculating, for each of the defined subareas, a difference score between pixel values of the template tracking area and pixel values of each defined subarea; and selecting, as the corresponding tracking area, the subarea which most closely matches the template tracking area using the calculated difference score.
  4. 4. The method as claimed in claim 3, wherein the search area comprises a peripheral area around an indicative tracking area having the same size and shape as the corresponding template tracking area, wherein the peripheral area comprises a fixed number of pixels in each direction around the indicative tracking area.
  5. 5. The method as claimed in claim 3 or claim 4, wherein the difference score is calculated using: where Rs, Gi and Bi correspond to the red, blue and green colour channels of i-th pixel within the template tracking area, Rs’, Gi’ and Bi’ to the red, blue and green colour channels of i-th pixel within each subarea, and N is the total number of pixels within the template tracking area or subarea.
  6. 6. The method of any one of the preceding claims, comprising before determining a difference in location between the corresponding tracking area in the image and a previous image, determining a confidence level in the located plurality of corresponding tracking areas; and only when the confidence level is above a confidence threshold, continuing with the determining a difference step.
  7. 7. The method as claimed in any of the preceding claims, further comprising determining that corresponding tracking areas have been located in a threshold number of other images; calculating a set of pixel values for pixels within each corresponding tracking area and updating the plurality of template tracking areas based on the calculated set of pixel values for the corresponding tracking areas.
  8. 8. The method as claimed in claim 7, wherein updating the plurality of template tracking areas comprises taking a weighted average of pixel values for each template tracking area and the calculated sets of pixel values.
  9. 9. The method as claimed in any preceding claim, wherein determining a difference in location between the corresponding tracking area in the image and a previous image comprises calculating a difference in position between at least one pixel in each tracking area.
  10. 10. The method as claimed in any preceding claim, wherein receiving video data of a user breathing comprises receiving pre-processed video data of a user breathing.
  11. 11. The method as claimed in any preceding claim, wherein outputting information on the determined movement of the user’s chest comprises outputting a loop diagram of the user’s breathing, wherein the loop diagram representing a user’s lung function.
  12. 12. The method as claimed in claim 11 , wherein outputting a loop diagram further comprises: obtaining a breathing signal based on the determined information on the movement of the user’s chest; determining stationary and zero crossing points of the breathing signal; computing a gradient signal from the breathing signal; determining stationary and zero crossing points of the gradient signal; analysing the stationary and zero crossing points of the breathing signal and the gradient signal to identify each individual breath cycle; and plotting each complete breath cycle as a loop diagram.
  13. 13. An apparatus for tracking a user’s chest movement, the apparatus comprising: an image capture device for capturing video data of the user’s chest that shows the user breathing; and at least one processor which is configured to track a user’s chest movement using the captured video data as set out in any one of the preceding claims.
  14. 14. The apparatus of claim 13, further comprising a user interface for directing the user to position the image capture device to capture a video of the user’s chest;
  15. 15. A non-transitory carrier carrying a computer program which when implemented on a computer, causes the computer to implement the method of any one of claims 1 to 12.

Description

Lung Monitoring System TECHNICAL FIELD [001] The invention relates to a method and device for monitoring a patient’s lung, particularly using a portable device. BACKGROUND [002] Respiratory patterns are a tool in primary and secondary care for patients. Respiration patterns can be used to determine whether a patient is sick. For example, Figure 1a compares the breathing patterns of a normal person with those of a sick patient and a severely sick patient. As a patient’s condition deteriorates, the rate of breathes per minute increases (e.g. from 12 breaths to 30 breaths per minute) and the volume of air inspired also increases from (e.g. 6 litres to over 25 litres per minute). Spirometry is a known technique which analyses respiration lung flow and volume to determine whether patients have specific lung conditions. Examples of the patterns associated with some major illnesses are shown in Figure 1 b. However, analysing these sounds often requires one- to-one and/or face-to-face presence to listen to sounds from the lungs. [003] US2017055878A1 discloses a method and corresponding apparatus for monitoring breathing by computing a calibration signal from a first sequence of images of a user's chest to produce a calibration model. The calibration signal is representative of movement of the user's chest during a first time period during which the user is using an incentive spirometer (IS). The first sequence of images corresponds to the first time period. A method and corresponding apparatus employ the calibration model to produce a breathing information estimate about the user's breathing from a second sequence of images of the user's chest corresponding to a second time period during which the user is not using the commercially-available IS. [004] US20140163405A1 discloses a physiological information measurement system including at least one video capture unit which captures at least one video. A calculating unit measures physiological information according to the video. The display unit shows the physiological information. [005] US11363990B2 discloses a system and method for monitoring one or more physiological parameters of a subject. The system includes a camera configured to capture and record a video sequence including at least one image frame of at least one region of interest (ROI) of the subject's body. A computer in signal communication with the camera to receive signals transmitted by the camera representative of the video sequence includes a processor configured to process the signals associated with the video sequence recorded by the camera and a display configured to display data associated with the signals. [006] The present applicant has recognised the need for an improved device for sensing patient information. SUMMARY [007] According to the present invention there is provided an apparatus, system and method as set forth in the appended claims. Other features of the invention will be apparent from the dependent claims, and the description which follows. [008] In a first approach of the present techniques there is described a computer-implemented method for tracking a user’s chest movement, the method comprising: receiving video data of the user’s chest showing the user breathing, the video data comprising a plurality of images showing the user’s chest; defining a plurality of template tracking areas in a first image of the plurality of images, each template tracking area comprising a plurality of pixels; and for each other image in the plurality of images, locating a plurality of corresponding tracking areas in the image, wherein each corresponding tracking area corresponds to one of the plurality of template tracking areas; and for each of the plurality of corresponding tracking areas, determining a difference in location between the corresponding tracking area in the image and a previous image from the plurality of images. The method comprises determining, using the determined location differences, movement of the user’s chest; and outputting information on the determined movement of the user’s chest. [009] The plurality of images may be images that are taken consecutively in time. Thus, the difference in location between tracking areas may be determined between consecutive images in the plurality of images. The plurality of images may be taken over a time frame which includes at least one breath of the user. [0010] Each tracking area comprises a plurality of pixels in the image and the number of pixels defines the size of the tracking area, for example there may be between 100 to 400 pixels. Each tracking area may have a square shape, such as 10x10 pixels or 20x20 pixels. Alternatively, the tracking areas may have any suitable shape such as an approximately circular shape, or a rectangular shape, or an approximately elliptical shape. [0011] Defining the plurality of template tracking areas may comprise defining the location of each template tracking area within the first image. This may com