Techniques for prediction and monitoring of clinical episodes

• US 7,314,451 B2
• Filed: 08/03/2005
• Issued: 01/01/2008
• Est. Priority Date: 04/25/2005
• Status: Active Grant

• Current Assignee: Hill-Rom Services Incorporated (Baxter International Inc.)
• Original Assignee: EarlySense Ltd.
• Inventors: Gross, Yosef, Halperin, Avner, Lange, Daniel H., Pinhas, Itzhak
• Primary Examiner(s): Marmor, II; Charles A.
• Assistant Examiner(s): Toth; Karen E.
• Application Number:
  US11/197,786
• Publication Number:
  US 20060241510A1
• Time in Patent Office: 881 Days
• Field of Search: 600/534
• US Class Current: 600/534
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 5/4094 Diagnosing or monitoring seizure diseases, e.g. epilepsy
• CPC Class Codes: A61B 5/6892 Mats
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

A method is provided for predicting an onset of an asthma attack. The method includes sensing at least one parameter of a subject without contacting or viewing the subject or clothes the subject is wearing, and predicting the onset of the asthma attack at least in part responsively to the sensed parameter. Also provided is a method for predicting an onset of an episode associated with congestive heart failure (CHF), including sensing at least one parameter of a subject without contacting or viewing the subject or clothes the subject is wearing, and predicting the onset of the episode at least in part responsively to the sensed parameter. Other embodiments are also described.

Claims

1. A method for predicting an onset of an asthma attack, comprising:

sensing at least one parameter of a subject without contacting or viewing the subject or clothes the subject is wearing; and

predicting the onset of the asthma attack at least in part responsively to the sensed parameter,

wherein predicting the onset comprises generating subject-specific data regarding the parameter by analyzing previous occurrences of the asthma attack, and predicting the onset at least in part responsively to the data.

2. The method according to claim 1, wherein the at least one parameter includes at least one motion-related parameter of the subject, and wherein sensing the at least one parameter comprises sensing the at least one motion-related parameter.

3. The method according to claim 1, comprising determining a measure of coughing of the subject, wherein predicting the onset comprises predicting the onset at least in part responsively to the sensed parameter and the measure of coughing.

4. The method according to claim 1, wherein sensing the at least one parameter comprises sensing the at least one parameter without requiring human compliance.

5. The method according to claim 1, wherein sensing the at least one parameter comprises sensing the at least one parameter while the subject is sleeping.

6. The method according to claim 1, wherein the at least one parameter includes at least one breathing-related parameter of the subject, and wherein sensing the at least one parameter comprises sensing the at least one breathing-related parameter.

7. The method according to claim 6, wherein predicting the onset comprises:

determining at least one breathing pattern of the subject responsively to the sensed breathing-related parameter;

comparing the breathing pattern with a baseline breathing pattern; and

predicting the onset at least in part responsively to the comparison.

8. A method for predicting an onset of an asthma attack, comprising:

sensing at least one parameter of a subject without contacting or viewing the subject or clothes the subject is wearing; and

predicting the onset of the asthma attack at least in part responsively to the sensed parameter,

wherein predicting the onset comprises determining a measure of restlessness of the subject, and predicting the onset at least in part responsively to the measure of restlessness.

9. The method according to claim 8, wherein the at least one parameter includes at least one motion-related parameter of the subject, and wherein sensing the at least one parameter comprises sensing the at least one motion-related parameter.

10. The method according to claim 8, comprising determining a measure of coughing of the subject, wherein predicting the onset comprises predicting the onset at least in part responsively to the sensed parameter and the measure of coughing.

11. The method according to claim 8, wherein sensing the at least one parameter comprises sensing the at least one parameter without requiring human compliance.

12. A method for predicting an onset of an asthma attack, comprising:

sensing at least one parameter of a subject while the subject is sleeping, without contacting or viewing the subject or clothes the subject is wearing;

predicting the onset of the asthma attack at least in part responsively to the sensed parameter; and

alerting the subject to the predicted onset only after the subject awakes.

13. The method according to claim 12, wherein predicting the onset comprises predicting the onset before the subject or a caretaker of the subject becomes aware of the onset.

14. The method according to claim 12, wherein the at least one parameter includes at least one motion-related parameter of the subject, and wherein sensing the at least one parameter comprises sensing the at least one motion-related parameter.

15. The method according to claim 12, comprising determining a measure of coughing of the subject, wherein predicting the onset comprises predicting the onset at least in part responsively to the sensed parameter and the measure of coughing.

16. The method according to claim 12, wherein sensing the at least one parameter comprises sensing the at least one parameter without requiring human compliance.

17. A method for predicting an onset of an asthma attack, comprising:

sensing at least one parameter of a subject without contacting or viewing the subject or clothes the subject is wearing; and

predicting the onset of the asthma attack at least in part responsively to the sensed parameter,

wherein the at least one parameter includes at least one breathing-related parameter of the subject,

wherein sensing the at least one parameter comprises sensing the at least one breathing-related parameter,

wherein the at least one parameter includes at least one heartbeat-related parameter of the subject,

wherein sensing the at least one parameter comprises the at least one heartbeat-related parameter, and

wherein predicting the onset of the asthma attack comprises predicting the onset of the asthma attack at least in part responsively to the breathing-related and the heartbeat-related parameters.

18. The method according to claim 17, comprising determining a measure of coughing of the subject, wherein predicting the onset comprises predicting the onset at least in part responsively to the sensed parameter and the measure of coughing.

19. The method according to claim 17, wherein sensing the at least one parameter comprises sensing the at least one parameter without requiring human compliance.

20. The method according to claim 17, wherein sensing the at least one parameter comprises sensing the at least one parameter while the subject is sleeping.

21. The method according to claim 17, wherein predicting the onset comprises:

determining at least one breathing pattern of the subject responsively to the sensed breathing-related parameter;

comparing the breathing pattern with a baseline breathing pattern; and

predicting the onset at least in part responsively to the comparison.

22. A method for predicting an onset of an episode associated with congestive heart failure (CHF), comprising:

sensing at least one parameter of a subject without contacting or viewing the subject or clothes the subject is wearing; and

predicting the onset of the episode at least in part responsively to the sensed parameter,

wherein sensing the at least one parameter comprises sensing a breathing-related parameter of the subject, and a blood pressure of the subject, and

wherein predicting the onset comprises predicting the onset at least in part responsively to the breathing-related parameter and the blood pressure.

23. The method according to claim 22, wherein the at least one parameter includes at least one motion-related parameter of the subject, and wherein sensing the at least one parameter comprises sensing the at least one motion-related parameter.

24. The method according to claim 22, wherein sensing the at least one parameter comprises measuring a pressure in, on, or under a reclining surface upon which the subject lies.

25. The method according to claim 22, wherein sensing the at least one parameter comprises sensing the at least one parameter while the subject is sleeping.

26. The method according to claim 22, wherein sensing the at least one parameter comprises sensing the at least one parameter without requiring human compliance.

27. A method for predicting an onset of a clinical episode, comprising:

sensing at least one parameter of a subject while the subject is sleeping, without requiring human compliance;

predicting the onset at least in part responsively to the sensed parameter; and

alerting the subject to the predicted onset only after the subject awakes.

28. The method according to claim 27, wherein sensing the at least one parameter comprises sensing the at least one parameter without contacting or viewing the subject or clothes the subject is wearing.

29. The method according to claim 27, wherein the at least one parameter includes at least one motion-related parameter of the subject, and wherein sensing the at least one parameter comprises sensing the at least one motion-related parameter without requiring human compliance.

30. The method according to claim 27, wherein the clinical episode is selected from the list consisting of:

an episode of abnormal autonomic nervous system activity caused by a neurological condition, an epileptic seizure, an episode of Periodic Limb Movements in Sleep (PLMS), a stroke, an episode of essential tremor, an episode of stress, an episode of fibrillation, an episode associated with chronic obstructive pulmonary disease (COPD), an episode associated with cystic fibrosis (CF), and an episode of anaphylactic shock, and wherein predicting the onset comprises predicting the onset of the selected clinical episode.

31. The method according to claim 27, wherein the at least one parameter includes at least one breathing-related parameter of the subject, and wherein sensing the at least one parameter comprises sensing the at least one breathing-related parameter without requiring human compliance.

32. Apparatus for predicting an onset of an asthma attack, comprising:

a non-contact sensor, adapted to sense at least one parameter of a subject without contacting the subject or clothes the subject is wearing; and

a control unit, adapted to;

predict the onset of the asthma attack at least in part responsively to the sensed parameter,

generate subject-specific data regarding the parameter by analyzing previous occurrences of the asthma attack, and

predict the onset at least in part responsively to the data.

33. The apparatus according to claim 32, wherein the at least one parameter includes at least one motion-related parameter of the subject, and wherein the sensor is adapted to sense the at least one motion-related parameter.

34. The apparatus according to claim 32, wherein the control unit is adapted to determine a measure of coughing of the subject, and to predict the onset at least in part responsively to the sensed parameter and the measure of coughing.

35. The apparatus according to claim 32, wherein the sensor is adapted to sense the at least one parameter without requiring human compliance.

36. The apparatus according to claim 32, wherein the sensor is adapted to sense the at least one parameter while the subject is sleeping.

37. The apparatus according to claim 32, wherein the at least one parameter includes at least one breathing-related parameter of the subject, and the sensor is adapted to sense the at least one breathing-related parameter.

38. The apparatus according to claim 37, wherein the control unit is adapted to:

determine at least one breathing pattern of the subject responsively to the sensed breathing-related parameter,

compare the breathing pattern with a baseline breathing pattern, and

predict the onset at least in part responsively to the comparison.

39. Apparatus for predicting an onset of an asthma attack, comprising:

a non-contact sensor, adapted to sense at least one parameter of a subject without contacting the subject or clothes the subject is wearing; and

a control unit, adapted to predict the onset of the asthma attack at least in part responsively to the sensed parameter,

wherein the control unit is adapted to determine a measure of restlessness of the subject, and to predict the onset at least in part responsively to the measure of restlessness.

40. The apparatus according to claim 39, wherein the at least one parameter includes at least one motion-related parameter of the subject, and wherein the sensor is adapted to sense the at least one motion-related parameter.

41. The apparatus according to claim 39, wherein the control unit is adapted to determine a measure of coughing of the subject, and to predict the onset at least in part responsively to the sensed parameter and the measure of coughing.

42. The apparatus according to claim 39, wherein the sensor is adapted to sense the at least one parameter without requiring human compliance.

43. Apparatus for predicting an onset of an asthma attack, comprising:

a user interface;

a non-contact sensor, adapted to sense at least one parameter of a subject while the subject is sleeping, without contacting the subject or clothes the subject is wearing; and

a control unit, adapted to;

predict the onset of the asthma attack at least in part responsively to the sensed parameter, and

drive the user interface to alert the subject to the predicted onset only after the subject awakes.

44. The apparatus according to claim 43, wherein the control unit is adapted to predict the onset before the subject or a caretaker of the subject becomes aware of the onset.

45. The apparatus according to claim 43, wherein the at least one parameter includes at least one motion-related parameter of the subject, and wherein the sensor is adapted to sense the at least one motion-related parameter.

46. The apparatus according to claim 43, wherein the control unit is adapted to determine a measure of coughing of the subject, and to predict the onset at least in part responsively to the sensed parameter and to measure of coughing.

47. The apparatus according to claim 43, wherein the sensor is adapted to sense the at least one parameter without requiring human compliance.

48. Apparatus for predicting an onset of an asthma attack, comprising:

a non-contact sensor, adapted to sense at least one parameter of a subject without contacting the subject or clothes the subject is wearing; and

a control unit, adapted to predict the onset of the asthma attack at least in part responsively to the sensed parameter,

wherein the at least one parameter includes at least one breathing-related parameter of the subject, and the sensor is adapted to sense the at least one breathing-related parameter,

wherein the at least one parameter includes at least one heartbeat-related parameter of the subject,

wherein the sensor is adapted to sense the at least one heartbeat-related parameter, and

wherein the control unit is adapted to predict the onset of the asthma attack at least in part responsively to the breathing-related and heartbeat-related parameters.

49. The apparatus according to claim 48, wherein the control unit is adapted to determine a measure of coughing of the subject, and to predict to onset at least in part rosponsively to the sensed parameter and the measure of coughing.

50. The apparatus according to claim 48, wherein the sensor is adapted to sense the at least one parameter without requiring human compliance.

51. The apparatus according to claim 48, wherein the sensor is adapted to sense the at least one parameter while to subject is sleeping.

52. The apparatus according to claim 48, wherein the control unit is adapted to:

determine at least one breathing pattern of the subject responsively to the sensed breathing-related parameter,

compare to breathing pattern with a baseline breathing pattern, and

predict to onset at least in part responsively to the comparison.

53. Apparatus for predicting an onset of an episode associated with congestive heart failure (CHF), comprising:

a non-contact sensor, adapted to sense at least one parameter of a subject without contacting the subject or clothes the subject is wearing; and

a control unit, adapted to predict the onset of the episode at least in part responsively to the sensed parameter,

wherein the sensor is adapted to sense a breathing-related parameter of the subject, and a blood pressure of the subject, and

wherein the control unit is adapted to predict the onset at least in part responsively to the breathing-related parameter and the blood pressure.

54. The apparatus according to claim 53, wherein the at least one parameter includes at least one motion-related parameter of the subject, and wherein the sensor is adapted to sense the at least one motion-related parameter.

55. The apparatus according to claim 53, wherein the sensor comprises a pressure gauge, configured to measure a pressure in, on, or under a reclining surface upon which the subject lies.

56. The apparatus according to claim 53, wherein the sensor is adapted to sense the at least one parameter while the subject is sleeping.

57. The apparatus according to claim 53, wherein the sensor is adapted to sense the at least one parameter without requiring human compliance.

58. Apparatus for predicting an onset of a clinical episode, comprising:

a user interface;

a sensor, adapted to sense at least one parameter of a subject while the subject is sleeping, without requiring human compliance; and

a control unit, adapted to;

predict the onset at least in part responsively to the sensed parameter, and

drive the user interface to alert the subject to the predicted onset only after the subject awakes.

59. The apparatus according to claim 58, wherein the sensor comprises a non-contact sensor, adapted to sense the at least one parameter without contacting the subject or clothes the subject is wearing.

60. The apparatus according to claim 58, wherein the at least one parameter includes at least one motion-related parameter of the subject, and wherein the sensor is adapted to sense the at least one motion-related parameter without requiring human compliance.

61. The apparatus according to claim 58, wherein the clinical episode is selected from the list consisting of:

an episode of abnormal autonomic nervous system activity caused by a neurological condition, an epileptic seizure, an episode of Periodic Limb Movements in Sleep (PLMS), a stroke, an episode of essential tremor, an episode of stress, an episode of fibrillation, an episode associated with chronic obstructive pulmonary disease (COPD), an episode associated with cystic fibrosis (CF), and an episode of anaphylactic shock, and wherein the control unit is adapted to predict the onset of the selected clinical episode.

62. The apparatus according to claim 58, wherein the at least one parameter includes at least one breathing-related parameter of the subject, and wherein the sensor is adapted to sense the at least one breathing-related parameter without requiring human compliance.