Method and apparatus for machine error detection by combining multiple sensor inputs

• US 20030128125A1
• Filed: 01/04/2002
• Published: 07/10/2003
• Est. Priority Date: 01/04/2002
• Status: Abandoned Application

• Current Assignee: Nxstage Medical Incorporated (Fresenius SE & Co. KGaA)
• Original Assignee: Nxstage Medical Incorporated (Fresenius SE & Co. KGaA)
• Inventors: Brugger, James M., Burbank, Jeffrey H.
• Application Number:
  US10/037,254
• Publication Number:
  US 20030128125A1
• Time in Patent Office: Days
• US Class Current: 340/605
• CPC Class Codes: A61M 1/14 Dialysis systems; Artificial kidneys; Blood oxygenators semi-permeable membranes characterised by the material, manufacturing processes therefor B01D71/00; Reciprocating systems for treatment of body fluids, e.g. single needle systems for hemofiltration or pheresis
• CPC Class Codes: A61M 1/1611 Weight of the patient
• CPC Class Codes: A61M 1/1692 Detection of blood traces in dialysate
• CPC Class Codes: A61M 1/34 Filtering material out of the blood by passing it through a membrane, i.e. hemofiltration or diafiltration
• CPC Class Codes: A61M 1/3403 Regulation parameters
• CPC Class Codes: A61M 1/3607 Regulation parameters
• CPC Class Codes: A61M 1/3609 Physical characteristics of the blood, e.g. haematocrit, urea
• CPC Class Codes: A61M 1/3621 Extra-corporeal blood circuits single-needle circuits A61M1/30
• CPC Class Codes: A61M 1/3626 Gas bubble detectors
• CPC Class Codes: A61M 1/3639 Blood pressure control, pressure transducers specially adapted therefor
• CPC Class Codes: A61M 1/3653 Interfaces between patient blood circulation and extra-corporal blood circuit
• CPC Class Codes: A61M 1/3655 Arterio-venous shunts or fistulae
• CPC Class Codes: A61M 1/3656 Monitoring patency or flow at connection sites; Detecting disconnections
• CPC Class Codes: A61M 1/3659 Cannulae pertaining to extracorporeal circulation
• CPC Class Codes: A61M 2205/15 Detection of leaks
• CPC Class Codes: A61M 2205/18 with alarm
• CPC Class Codes: A61M 2205/33 Controlling, regulating or measuring
• CPC Class Codes: A61M 2205/3303 Using a biosensor
• CPC Class Codes: A61M 2205/3331 Pressure; Flow
• CPC Class Codes: A61M 2205/3344 Measuring or controlling pressure at the body treatment site
• CPC Class Codes: A61M 2205/3368 : Temperature
• CPC Class Codes: A61M 2205/3375 : Acoustical, e.g. ultrasonic, measuring means
• CPC Class Codes: A61M 2205/502 : User interfaces, e.g. screens or keyboards
• CPC Class Codes: A61M 2230/06 : Heartbeat rate only
• CPC Class Codes: A61M 2230/205 : partial oxygen pressure (P-O2)
• CPC Class Codes: A61M 60/109 : incorporated within extracorporeal blood circuits or systems
• CPC Class Codes: A61M 60/113 : in other functional devices, e.g. dialysers or heart-lung machines
• CPC Class Codes: A61M 60/205 : Non-positive displacement blood pumps
• CPC Class Codes: A61M 60/515 : Regulation using real-time patient data
• CPC Class Codes: A61M 60/531 : using blood pressure data, e.g. from blood pressure sensors
• CPC Class Codes: A61M 60/538 : Regulation using real-time blood pump operational parameter data, e.g. motor current
• CPC Class Codes: G01M 3/26 : by measuring rate of loss or gain of fluid, e.g. by pressure-responsive devices, by flow detectors
• CPC Class Codes: G06F 18/211 : Selection of the most significant subset of features
• CPC Class Codes: G06F 18/24155 : Bayesian classification
• CPC Class Codes: G08B 21/02 : Alarms for ensuring the safety of persons
• CPC Class Codes: G08B 21/0211 : Combination with medical sensor, e.g. for measuring heart rate, temperature
• CPC Class Codes: G16H 30/20 : for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 40/40 : for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16Z 99/00 : Subject matter not provided for in other main groups of this subclass

Abstract

One of the most significant safety concerns in the automation of extracorporeal blood treatments such as dialysis is the risk of blood leakage. Extracorporeal blood treatment systems draw blood at such a high rate that a loss of integrity in the blood circuit can be serious. There are a number of mechanisms for detecting and preventing leaks, but none is perfect. This tends to limit the use of such equipment in unsupervised settings, such as the home will be limited. Some leak detection schemes can be made sensitive enough to detect the barest of leaks, but when this is done, they result in too many false positives. The invention combines information from multiple inputs to enhance sensitivity in leak detection and reduce the problem of false positives.

Claims

1. A method of detecting a loss of integrity in a blood circuit supplying blood to a patient, comprising the steps of:

detecting a leak in at least two independent ways to generate at least two leak detection signals;

deriving at least one composite signal responsive to said two leak detection signals;

generating an alarm signal responsively to said at least one composite signal.

2. A method as in claim 1, wherein said step of deriving includes calculating a probability of a leak responsively to said at least two detection signals.

3. A method as in claim 1, wherein said step of deriving includes combining said at least two leak detection signals such that a sensitivity of detection of a leak is enhanced.

4. A method as in claim 3, wherein said step of calculating includes applying said leak detection signals to a network classifier.

5. A method as in claim 1, wherein said step of deriving includes applying a respective weight to said at least two leak detection signals and adding them.

6. A method as in claim 1, wherein said step of detecting includes sensing a presence of fluid outside said blood circuit and detecting a presence of air inside said blood circuit.

7. A leak detection device, comprising:

a first detector sensing a first condition and generating a first signal responsive thereto;

a second detector sensing a second condition and generating a second signal responsive thereto;

a controller programmed to generate an alarm based on a probability of a leak derived, at least in part, from said first and second signals.

8. A detection device as in claim 7, wherein said first and second detectors each includes at least one of an air detector and a fluid detector.

9. A leak detection device, comprising:

a first detector outputting a first detection signal;

a second detector outputting a second detection signal;

a signal combiner connected to form a combination signal responsive to both said first and second detection signals to generate an alarm output for connection to an alarm device;

said signal combiner being such that both a sensitivity and a reliability of leak detection represented by said combination signal is greater than said first and second detection signals alone or together;

said first detector being adapted to detect a first condition that is correlated with a leak in a blood circuit;

said second detector being adapted to detect a second condition that is correlated with a leak in said blood circuit;

said first and second conditions being associated with different physical phenomena.

10. A detection device as in claim 9, wherein said combiner includes an analog summing circuit.

11. A detection device as in claim 9, wherein said combiner includes a programmable processor.

12. A detection device as in claim 9, wherein said first detector includes at least one of a detector of air in said blood circuit, a detector of fluid outside said blood circuit, a detector of pressure in said blood circuit, an image classifier connected to a camera oriented to image a patient, or a device to measure a patient heart rate, blood oxygen level, body weight, or the continuity or bioimpedance of tissue of the patient.

14. A detection device as in claim 9, wherein sa id first detector includes at least one of a detector of air in said blood circuit, a detector of fluid outside said blood circuit, a detector of pressure in said blood circuit, an image classifier connected to a camera oriented to image a patient, or a device to measure a patient heart rate, blood oxygen level, body weight, or the continuity or bioimpedance of tissue of the patient.

13. A leak detection device for detecting a leak in an extracorporeal blood treatment machine, comprising:

a first detector outputting a first detection signal;

a second detector outputting a second detection signal;

a signal combiner connected to form a combination signal responsive to both said first and second detection signals to generate an alarm output for connection to an alarm device;

said first detector being adapted to detect a first condition that is correlated with a probability of a leak in a blood circuit;

said second detector being adapted to detect a second condition that is correlated with a probability of a leak in said blood circuit.

15. A method of detecting an alarm condition in a medical treatment machine, comprising the steps of:

combining detector signals from at least two indicators of an alarm condition such that a prediction of an alarm state is generated thereby and such that said prediction possesses at least one of a higher reliability and a higher sensitivity than said detectors signals uncombined;

generating an alarm signal responsively to said prediction.

16. A method as in claim 15, wherein said medical treatment machine is a blood processing machine and said alarm condition is a leak of fluid therefrom.

17. A method as in claim 16, wherein said alarm condition is a leakage of blood from a blood circuit of said blood processing machine.

18. A method as in claim 15, wherein said at least two different indicators of a status of a patient, medical treatment machine, or environment thereof.

19. A method as in claim 18, wherein said different indicators include at least two of respective ones of a video image of a patient, a blood oxygen level of a patient, a body weight of a patient, a bioimpedance of a patient'"'"'s tissue, a body temperature of a patient, a heart rate of a patient, a blood pressure of a patient, a breathing rate of a patient, a presence of fluid, and a presence of air in a fluid circuit.

20. A method as in claim 15, wherein said step of combining includes deriving a probability of an alarm condition, said alarm signal indicating said probability.

21. A method as in claim 15, wherein said step of combining has the effect of amplifying a reliability of an estimate of said alarm condition indicated by said signal relative to any one of said detector signals alone by cumulating influence of multiple detector signals to generate a linear or non-linear combination.

22. A method as in claim 15, wherein said step of combining has the effect of amplifying a sensitivity of an estimate of said alarm condition indicated by said signal relative to any one of said detector signals alone by cumulating influence of multiple detector signals to generate a linear or non-linear combination.

23. A method as in claim 22, wherein said step of combining also has the effect of amplifying a reliability of an estimate of said alarm condition indicated by said signal relative to any one of said detector signals alone by said cumulation of influence of multiple detector signals to generate a linear or nonlinear combination.

24. A method as in claim 15, wherein said step of combining includes combining with a network classifier.

25. A method of detecting a leak from a medical treatment machine, comprising:

combining at least two respective ones of detector signals providing a video image of a patient, a blood oxygen level of a patient, a body weight of a patient, a bioimpedance of a patient'"'"'s tissue, a body temperature of a patient, a heart rate of a patient, a blood pressure of a patient, a breathing rate of a patient, a presence of fluid, and a presence of air in a fluid circuit;

said step of combining being effective to yield a prediction of a leakage of fluid from said medical treatment machine.

26. A method as in claim 25, wherein said step of combining includes deriving a probability of an alarm condition, said alarm signal indicating said probability.

27. A method as in claim 25, wherein said step of combining has the effect of amplifying a reliability of an estimate of said alarm condition indicated by said signal relative to any one of said detector signals alone by cumulating influence of multiple detector signals to generate a linear or non-linear combination.

28. A method as in claim 25, wherein said step of combining has the effect of amplifying a sensitivity of an estimate of said alarm condition indicated by said signal relative to any one of said detector signals alone by cumulating influence of multiple detector signals to generate a linear or non-linear combination.

29. A method as in claim 25, wherein said step of combining also has the effect of amplifying a reliability of an estimate of said alarm condition indicated by said signal relative to any one of said detector signals alone by said cumulation of influence of multiple detector signals to generate a linear or nonlinear combination.

30. A method as in claim 29, wherein said step of combining includes combining with a network classifier.

31. A method as in claim 25, wherein said step of combining includes combining with a network classifier.

32. A method as in claim 25, wherein said medical treatment machine includes an extracorporeal blood circuit.

33. A method as in claim 25, wherein said medical treatment machine includes a fluid circuit.

34. A device for detecting an alarm condition in a medical treatment machine, comprising:

a signal filter adapted to combine detector signals from at least two indicators of an alarm condition such that a prediction of an alarm state is generated thereby and such that said prediction possesses at least one of a higher reliability and a higher sensitivity than said detectors signals uncombined;

said signal filter being further adapted to generate an alarm signal responsive to said prediction.

35. A device as in claim 34, wherein said medical treatment machine is a blood processing machine and said alarm condition is a leak of fluid therefrom.

36. A device as in claim 35, wherein said alarm condition is a leakage of blood from a blood circuit of said blood processing machine.

37. A device as in claim 34, wherein said at least two different indicators of a status of a patient, medical treatment machine, or environment thereof.

38. A device as in claim 37, wherein said different indicators include at least two of respective ones of a video image of a patient, a blood oxygen level of a patient, a body weight of a patient, a bioimpedance of a patient'"'"'s tissue, a body temperature of a patient, a heart rate of a patient, a blood pressure of a patient, a breathing rate of a patient, a presence of fluid, and a presence of air in a fluid circuit.

39. A device as in claim 34, wherein said prediction includes a probability of an alarm condition, said alarm signal indicating said probability.

40. A device as in claim 34, wherein said signal filter combines said detector signals by cumulating influences of multiple detector signals to generate a linear or non-linear combination thereof.

41. A device as in claim 34, wherein said signal filter includes a network classifier.

42. A device for detecting a leak from a medical treatment machine, comprising:

a signal filter connected to combine at least two respective ones of detector signals providing a video image of a patient, a blood oxygen level of a patient, a body weight of a patient, a bioimpedance of a patient'"'"'s tissue, a body temperature of a patient, a heart rate of a patient, a blood pressure of a patient, a breathing rate of a patient, a presence of fluid,-and a presence of air in a fluid circuit;

said signal filter being configured such that a prediction of a leakage of fluid from said medical treatment machine is generated by combining said at least two.

43. A device as in claim 42, wherein said prediction includes a probability of an alarm condition, said alarm signal indicating said probability.

44. A device as in claim 42, said signal filter combines said detector signals by cumulating influences of multiple detector signals to generate a linear or nonlinear combination thereof.

45. A device as in claim 44, wherein said signal filter includes a network classifier.

46. A device as in claim 42, wherein said signal filter includes a network classifier.

47. A device as in claim 42, wherein said medical treatment machine includes a fluid circuit.

48. A device as in claim 42, wherein said medical treatment machine includes an extracorporeal blood circuit.