Single channel imaging measurement of dynamic changes in heart or respiration rate

• US 10,143,377 B2
• Filed: 05/02/2012
• Issued: 12/04/2018
• Est. Priority Date: 05/02/2012
• Status: Active Grant

• Current Assignee: Banna Biomedical Research Institute
• Original Assignee: Augusta University Research Institute, Inc., Banna Biomedical Research Institute
• Inventors: Tsien, Joseph Z., Li, Meng, Zhao, Fang, Qian, Yi
• Primary Examiner(s): VANNI, GEORGE STEVEN
• Application Number:
  US13/462,524
• Publication Number:
  US 20130296660A1
• Time in Patent Office: 2,407 Days
• Field of Search: None
• CPC Class Codes: A61B 5/004 adapted for image acquisition of a particular organ or body part A61B5/0082 takes precedence; arrangements for optical scanning A61B5/0062
• CPC Class Codes: A61B 5/0077 Devices for viewing the surface of the body, e.g. camera, magnifying lens
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/0255 Recording instruments specially adapted therefor
• CPC Class Codes: A61B 5/026 Measuring blood flow A61B3/1233, A61B3/1241 take precedence
• CPC Class Codes: A61B 5/4809 Sleep detection, i.e. determining whether a subject is asleep or not
• CPC Class Codes: G06T 2207/10048 Infrared image
• CPC Class Codes: G06T 2207/30076 Plethysmography
• CPC Class Codes: G06T 7/0016 involving temporal comparison

Abstract

Methods for remotely measuring or monitoring one or more physiological parameters in a subject, such as blood volume pulse, heart rate, respiratory wave, or respiration rate, are provided. The methods include capturing a series of images of the subject, and processing the images to obtain physiological parameters of interest. These methods can be used to analyze single channel signals, including signals obtained from active night vision cameras. As a result, these methods can be used to measure or monitor one or more physiological parameters in both daylight and low-light conditions. Also provided are methods of removing false positives. Systems for remotely measuring or monitoring one or more physiological parameters in a subject, as well as methods of using thereof, are also provided.

Claims

1. A computer-implemented method for measuring one or more physiological parameters in a subject consisting of:

capturing a time series of digital single channel images of the subject with a night vision camera;

establishing a common region of interest in each of the digital images;

processing brightness of a common subset of pixels in each region of interest of each digital image and thereby producing a spatially averaged brightness of the common subset of pixels from each digital image;

combining the average brightness obtained from each digital image and thereby constructing a combined signal of average brightness over time showing changes in intensity over time;

processing the combined signal of average brightness over time using dynamical embedding and thereby constructing an embedding matrix from a series of delay vectors taken from the combined signal of average brightness over time;

processing the dynamical embedding matrix using independent component analysis and thereby identifying self-repeating rhythmicity from the combined signal of average brightness over time; and

calculating the frequency of the self-repeating rhythmicity to identify the one or more physiological parameters of interest, wherein the one or more physiological parameters are selected from the group consisting of heart and respiration rates.

2. The method of claim 1, wherein the physiological parameters are measured simultaneously.

3. The method of claim 1, wherein the region of interest in each of the digital images is an area of the skin of the subject.

4. The method of claim 1, wherein the region of interest in each of the digital images is an area of the chest or abdomen of the subject.

5. The method of claim 1, further comprising detrending the single observed time series over time.

6. The method of claim 1, further comprising normalizing the single observed time series over time.

7. The method of claim 1, each vector comprises a subset of the single observed time series.

8. The method of claim 1, further comprising the step processing the regions of interest into two subsets;

performing the method of claim 1 on the two subsets to determine intrinsic oscillatory frequencies or each subset; and

thereby determining the intrinsic oscillatory frequency of the first subset matches the intrinsic oscillatory frequency of the second subset, wherein in a mismatch indicates a false positive.