Monitoring breathing via signal strength in wireless networks

• US 9,443,419 B2
• Filed: 08/16/2012
• Issued: 09/13/2016
• Est. Priority Date: 08/16/2011
• Status: Active Grant

• Current Assignee: University of Utah Research Foundation (State of Utah)
• Original Assignee: University of Utah Research Foundation (State of Utah)
• Inventors: Wilson, Anthony Joey, Patwari, Neal K.
• Primary Examiner(s): Huynh, Dung B
• Application Number:
  US14/238,791
• Publication Number:
  US 20140313913A1
• Time in Patent Office: 1,489 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/6889 Rooms
• CPC Class Codes: A61B 5/6891 Furniture
• CPC Class Codes: G08C 17/02 using a radio link
• CPC Class Codes: H04W 4/38 for collecting sensor information
• CPC Class Codes: H04W 84/18 Self-organising networks, e.g. ad-hoc networks or sensor networks

Abstract

Systems and methods are disclosed for the use of sensor links in a network to estimate the breathing rate of a breathing subject within a structure, estimate the location of the subject within the structure, and detect if the subject is breathing. The structure may be a bed, a building, or a room in the building. The received signal strength of the sensor links is obtained and is then used in various breathing models to determine the breathing rate estimation, the location estimation, and the breathing detection.

Claims

1. A method for breathing rate estimation comprising:

arranging a plurality of radio frequency sensors in a network around a subject within a structure;

measuring received signal strengths (RSS) between the plurality of radio frequency sensors, wherein the measured RSS is at least partially indicative of breathing of the subject;

determining a breathing rate estimation model based on information related to the measured signal strengths, wherein determining a breathing rate estimation model comprises;

calculating, with a computer processor, a power spectral density versus frequency of the measured RSS, and

identifying a frequency at which the power spectral density peaks,

wherein the identified frequency correlates with the estimated breathing rate of the subject; and

displaying an estimate of a breathing rate of the subject using the breathing rate estimation model.

2. The method of claim 1, wherein the breathing rate estimation model maximizes a function of the received signal strengths of a plurality of sensor pairs of the plurality of radio frequency sensors.

3. The method of claim 1, further comprising:

estimating an amplitude of the signal strength at the estimated breathing rate using the breathing rate estimation model.

4. The method of claim 1, further comprising:

estimating a phase of the signal strength at the estimated breathing rate using the breathing rate estimation model.

5. The method of claim 4, wherein the estimated phase of the signal strength is used to estimate the number of subjects within the structure.

6. The method of claim 1, wherein the plurality of radio frequency sensors do not touch the subject within the structure.

7. The method of claim 1, wherein the structure is a bed that the subject lies in.

8. The method of claim 1, wherein the structure is a building within which the subject is located.

9. The method of claim 8, wherein the plurality of radio frequency sensors are located within one or more walls of the building.

10. The method of claim 8, wherein the plurality of radio frequency sensors are attached to one or more walls of the building.

11. The method of claim 1, wherein the plurality of radio frequency sensors comprise multiple frequency channel sensors.

12. The method of claim 1, further comprising:

determining a mean RSS value for the measured RSS;

removing the mean RSS value from the measured RSS; and

using the resultant RSS value in the breathing rate estimation model to determine the breathing rate of the subject.

13. The method of claim 12, wherein a filter is used to remove the mean RSS value.

14. The method of claim 12, wherein one or more time indices during which a RSS change occurs are used when removing the mean RSS value.

15. The method of claim 1, further comprising:

using the estimated breathing rate to estimate a location of the subject within the structure.

16. A method for breathing detection comprising:

arranging a plurality of radio frequency sensors in a network around a subject within a structure;

measuring received signal strengths (RSS) between the plurality of radio frequency sensors, the received signals strengths is at least partially indicative of breathing of the subject;

calculating a probability density function of a network-wide breathing statistic over all links of the plurality of radio frequency sensors for a given time unit, wherein the network-wide breathing statistic is calculated by a summing of RSS amplitudes over links in the network;

comparing the probability density function to a user defined breathing threshold; and

during time periods when the probability density function is below the threshold value indicating, on a digital display, that the subject is not breathing, and

during time periods when the sum of the probability density function is above the threshold value indicating, on the digital display, that the subject is breathing.

17. The method according to claim 16, wherein the network-wide breathing statistic includes a determination of a normalized sum of the squared amplitudes of the signal strengths for all links of the plurality of radio frequency sensors and the user defined breathing threshold.

18. The method according to claim 17, wherein determining whether the subject is breathing or not comprises:

comparing whether the normalized sum of the squared amplitudes is greater or less than the user defined breathing threshold, wherein when the amplitude is greater the subject is likely to be breathing and when the amplitude is less than the subject is likely not breathing.

19. The method of claim 16, wherein the plurality of radio frequency sensors do not touch the subject within the structure.

20. The method of claim 16, wherein the structure is a bed that the subject lies in.

21. The method of claim 16, wherein the structure is a building within which the subject is located.

22. The method of claim 21, wherein the plurality of radio frequency sensors are located within one or more walls of the building.

23. The method of claim 21, wherein the plurality of radio frequency sensors are attached to one or more walls of the building.

24. The method of claim 16, wherein the plurality of radio frequency sensors comprise multiple frequency channel sensors.

25. A method for estimating the location of a breathing subject within a structure comprising:

obtaining a breathing rate estimate of a subject within a structure, the breathing rate estimate based at least in part on a measured signal strength obtained from a plurality of radio frequency sensors placed within the structure;

identifying, with a breathing localization model, high amplitude links between one or more of the plurality of radio frequency sensors that generated higher amplitudes of signal strength than the other radio frequency sensors;

identifying the link distance between the receiving portion and transmitting portion of each high amplitude link;

mapping the detected high amplitude links and respective link distances to a pixel map representative of the structure;

estimating the location of the subject within the structure based on the coordinates obtained from the pixel map; and

displaying, on a digital display, an estimated location of the subject within the structure.

26. The method of claim 25, wherein the structure is a building within which the subject is located.

27. The method of claim 26, wherein the plurality of radio frequency sensors are located within one or more walls of the building.

28. The method of claim 26, wherein the plurality of radio frequency sensors are attached to one or more walls of the building.

29. The method of claim 25, wherein the plurality of radio frequency sensors comprise multiple frequency channel sensors.

30. A system for breathing estimation comprising:

a plurality of radio frequency sensors associated with a structure within which a breathing subject is located; and

a computing system including a breathing rate estimation module, the breathing rate estimation module configured to obtain information related to received signal strengths between the plurality of radio frequency sensors and to perform the following;

calculate, with a computer processor, a power spectral density versus frequency of the measured RSS; and

identify a frequency at which the power spectral density peaks,

wherein the identified frequency correlates with the estimated breathing rate of the subject;

determine a breathing rate estimation model based on the measured signal strengths, wherein determining a breathing rate estimation model comprises;

calculating, with a computer processor, a power spectral density versus frequency of the measured RSS, and

identifying a frequency at which the power spectral density peaks,

wherein the identified frequency correlates with the estimated breathing rate of the subject; and

displaying an estimate of a breathing rate of the subject using the breathing rate estimation model.

31. The system of claim 30, further comprising:

a base station sensor for collecting the information related to the received signal strengths between the plurality of radio frequency sensors, the base station sensor providing the information to the computing system.

32. The system of claim 30, wherein the plurality of radio frequency sensors comprise multiple frequency channel sensors.

33. The system of claim 30, wherein the breathing rate estimation module is further configured to perform the following:

determine a mean RSS value for the measured RSS;

remove the mean RSS value from the measured RSS; and

use the resultant RSS value in the breathing rate estimation model to determine the breathing rate of the subject.

34. The system of claim 33, further comprising a filter that is used to remove the mean RSS value.

35. The system of claim 33, the breathing rate estimation module uses one or more time indices during which a RSS change occurs when removing the mean RSS value.

36. The system of claim 30, the breathing rate estimation module uses the estimated breathing rate to estimate a location of the subject within the structure.

37. The system of claim 30, wherein the structure is a bed that the subject lies in.

38. The system of claim 30, wherein the structure is a building within which the subject is located.

39. The system of claim 38, wherein the plurality of radio frequency sensors are located within one or more walls of the building.

40. The system of claim 38, wherein the plurality of radio frequency sensors are attached to one or more walls of the building.

41. A system for breathing detection comprising:

a plurality of radio frequency sensors associated with a structure within which a breathing subject is located; and

a computing system including a breathing detection module, the breathing detection module configured to obtain information related to received signal strengths of the plurality of radio frequency sensors and to perform the following;

calculate a network-wide breathing statistic over all links of the plurality of radio frequency sensors, wherein the network-wide statistic is calculated by a summing of RSS amplitudes over links in the network;

comparing the sum of the RSS amplitudes to a user defined breathing threshold value; and

when the sum of the RSS amplitudes is below the threshold value displaying on a digital display an indication that the subject is not breathing, and

when the sum of the RSS amplitudes is above the threshold value displaying on the digital display an indication that the subject is breathing.

42. The system of claim 41, further comprising:

a base station sensor for collecting the information related to the received signal strengths between the plurality of radio frequency sensors, the base station sensor providing the information to the computing system.

43. The system of claim 41, wherein the plurality of radio frequency sensors comprise multiple frequency channel sensors.

44. The system of claim 41, wherein the structure is a bed that the subject lies in.

45. The system of claim 41, wherein the structure is a building within which the subject is located.

46. The system of claim 45, wherein the plurality of radio frequency sensors are located within one or more walls of the building.

47. The system of claim 45, wherein the plurality of radio frequency sensors are attached to one or more walls of the building.

48. A system for estimating the location of a breathing subject within a structure comprising:

a plurality of radio frequency sensors associated with a structure within which a breathing subject is located; and

a computing system including a breathing localization module, the breathing localization module configured to obtain information related to received signal strengths of the plurality of radio frequency sensors and to perform the following;

obtain a breathing rate estimate of a subject within the structure, the breathing rate estimate based at least in part on the received signal strengths obtained from the plurality of radio frequency sensors placed within the structure;

identifying high amplitude links between one or more of the plurality of radio frequency sensors that generated higher amplitudes of signal strength than the other radio frequency sensors;

identifying the link distance between the receiving portion and transmitting portion of each high amplitude link;

mapping the identified high amplitude links and respective link distances to a pixel map representative of the structure; and

estimate the location of the subject within the structure based on the coordinates obtained from the pixel map; and

displaying, on a digital display, an estimated location of the subject within the structure.

49. The system of claim 48, wherein the plurality of radio frequency sensors comprise multiple frequency channel sensors.

50. The system of claim 48, wherein the structure is a building within which the subject is located.

51. The system of claim 50, wherein the plurality of radio frequency sensors are located within one or more walls of the building.

52. The system of claim 50, wherein the plurality of radio frequency sensors are attached to one or more walls of the building.

53. The system of claim 48, wherein an image vector is used when estimating the coordinates.