Mask sizing tool using a mobile application

Patent metadata

Field	Value
Publication number	US-2018117272-A1
Application number	US-201615578440-A
Country	US
Kind code	A1
Filing date	Jun 30, 2016
Priority date	Jun 30, 2015
Publication date	May 3, 2018
Grant date	—

Abstract

Apparatus and methods automate selection of patient interface(s) according to their size, such as with processing in a processor(s) or in a server(s). Image data captured by an image sensor may be received. The captured image data may contain facial feature(s) of an intended user of the patient interface. The facial features may be captured in association with a predetermined reference feature of known dimension(s). The user's facial feature(s) and the reference feature may be detected in the captured image data. Image pixel data of the image may be processed to measure an aspect of the detected facial feature(s) based on the reference feature. A patient interface size may be detected from standard patient interface sizes based on a comparison between the measured aspect of the facial feature(s) and a data record relating sizing information of the standard patient interface sizes and the measured aspect of the facial feature(s).

First claim

1 . An automated method for selecting a patient interface according to patient interface size comprising, in one or more processors:
receiving image data captured by an image sensor, the captured image data containing one or more facial features of an intended user of the patient interface in association with a predetermined reference feature having a known dimension; detecting one or more facial features of the user in the captured image data; detecting the predetermined reference feature in the captured image data; processing image pixel data of the image to measure an aspect of the one or more facial features detected in the image based on the predetermined reference feature; and selecting a patient interface size from a group of standard patient interface sizes based on a comparison between the measured aspect of the one or more facial features and a data record relating sizing information of the group of standard patient interface sizes and the measured aspect of the one or more facial features.

2 . The method of claim 1 wherein the aspect of the one or more facial features comprises a distance between a sellion and supramenton of the user.

3 . The method of any one of claims 1 to 2 further comprising calculating a value of the measured aspect based on a scaling factor derived from the reference feature.

4 . The method of any one of claims 1 to 3 further comprising adjusting a value of the measured aspect with an anthropometric correction factor.

5 . The method of claim 4 wherein the anthropometric correction factor is calculated based on patient interface return data.

6 . The method of any one of claims 3 to 5 , further comprising calculating, in the one or more processors, the scaling factor as a function of the known dimension of the predetermined reference feature and a detected pixel count for the detected reference feature.

7 . The method of claim 1 , wherein the predetermined reference feature is a coin.

8 . The method of claim 7 , wherein the detecting the reference feature comprises applying a cascade classifier to the captured image data.

9 . The method of claim 7 , further comprising calculating a value of the measured aspect based on a scaling factor derived from the coin.

10 . The method of claim 9 , further comprising calculating, in the one or more processors, the scaling factor as a function of the known dimension of the coin in the captured image data and a detected pixel count for the coin that is detected.

11 . The method of claim 10 , wherein the detected pixel count for the coin that is detected is a width of an ellipse fitted to the coin.

12 . The method of claim 1 , wherein the predetermined reference feature is a cornea of the user.

13 . The method of any one of claims 1 to 7 further comprising, for image capture, displaying the reference feature on a display interface of a display device coupled with the image sensor.

14 . The method of claim 13 , wherein the display interface includes a targeting guide and a live action preview of content detected by the image sensor, the content including the reference feature as displayed on the display interface.

15 . The method of claim 14 , further comprising, in the one or more processors, controlling capturing of the image data to satisfy at least one alignment condition.

16 . The method of claim 15 , wherein the at least one alignment condition comprises detection of positioning of the reference feature of the live action preview within a box of the targeting guide.

17 . The method of any one of claims 15 to 16 , wherein the at least one alignment condition includes detection of a tilt condition being within about +/−10 degrees of a superior-inferior extending axis.

18 . The method of any one of claims 15 to 17 , wherein the at least one alignment condition includes detection of a tilt condition being within about +/−5 degrees of a superior-inferior extending axis.

19 . The method of any one of claims 17 to 18 , wherein detection of a tilt condition is performed by reading an inertial measurement unit (IMU).

20 . The method of any one of claims 13 to 19 , wherein the predetermined reference feature is a QR code.

21 . The method of any one of claims 1 to 20 wherein the patient interface comprises a mask.

22 . The method of claim 21 wherein the patient interface comprises a nasal mask.

23 . The method of any one of claims 1 to 22 wherein the processing image pixel data comprises counting pixels.

24 . The method of any one of claims 1 to 23 further comprising generating an automated electronic offer for a patient interface for purchase based on the selected patient interface size.

25 . The method of any one of claims 1 to 24 , further comprising calculating an average of the measured aspect of the facial feature from a plurality of captured images of the one or more facial features.

26 . A system for automatically recommending a patient interface size complementary to a particular patient's facial features comprising:
one or more servers, the one or more servers configured to communicate with a computing device over a network, the one or more servers further configured to:
receive image data captured by an image sensor, the captured image data containing one or more facial features of an intended user of the patient interface in association with a predetermined reference feature having a known dimension;
detect one or more facial features of the user in the captured image data;
detect the predetermined reference feature in the captured image data;
process image pixel data of the image to measure an aspect of the one or more facial features detected in the image based on the predetermined reference feature; and
select a patient interface size from a group of standard patient interface sizes based on a comparison between the measured aspect of the one or more facial features and a data record relating sizing information of the group of standard patient interface sizes and the measured aspect of the one or more facial features.

27 . The system of claim 26 wherein the aspect of the one or more facial features comprises a distance between a sellion and supramenton of the user.

28 . The system of any one of claims 26 to 27 wherein the one or more servers is further configured to calculate a value of the measured aspect based on a scaling factor derived from the reference feature.

29 . The system of any one of claims 26 to 28 wherein the one or more servers is further configured to adjust a value of the measured aspect with an anthropometric correction factor.

30 . The system of claim 29 wherein the anthropometric correction factor is calculated based on patient interface return data.

31 . The system of any one of claims 28 to 30 , wherein the one or more servers is further configured to calculate the scaling factor as a function of the known dimension of the predetermined reference feature and a detected pixel count for the detected reference feature.

32 . The system of claim 26 , wherein the predetermined reference feature is a coin.

33 . The system of claim 32 , wherein the one or more servers is configured to detect the reference feature by applying a cascade classifier to the captured image dat

Assignees

• Resmed Ltd

Inventors

• Fu Timothy Tsun-Fai
• Butyletskiy Denis
• Kooij Michiel
• Johnston Benjamin Peter
• Hudson Robert James

Classifications

• G06V10/7553

  based on shape, e.g. active shape models [ASM] · CPC title

• A61M2230/00

  Measuring parameters of the user · CPC title

• G16H10/60

  for patient-specific data, e.g. for electronic patient records · CPC title

• A61M2016/0661

  with customised shape · CPC title

• A61B5/1077

  Measuring of profiles · CPC title