Partitioning medical binary decision diagrams for analysis optimization

• US 9,177,247 B2
• Filed: 09/23/2011
• Issued: 11/03/2015
• Est. Priority Date: 09/23/2011
• Status: Active Grant

• Current Assignee: Fujitsu Limited
• Original Assignee: Fujitsu Limited
• Inventors: Stergiou, Stergios, Jain, Jawahar
• Primary Examiner(s): Hill, Stanley K
• Application Number:
  US13/241,789
• Publication Number:
  US 20130080114A1
• Time in Patent Office: 1,502 Days
• US Class Current: 1/1
• CPC Class Codes: G05B 23/0221 Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks

Abstract

In particular embodiments, a method includes accessing a first binary decision diagram (BDD) representing data streams from sensors, selecting portions from the first BDD based on ease-of-analysis, and constructing a plurality of sub-BDDs by partitioning the first BDD, wherein the sub-BDDs comprises a first sub-BDD representing the selected portions, and second sub-BDDs representing the non-selected portions.

Claims

1. A method comprising:

by one or more computing devices,

accessing medical sensor data from one or more medical sensors measuring physiological stimulus from a person'"'"'s body, the medical sensor data being stored as a first binary decision diagram (BDD), wherein the first BDD comprises one or more rooted directed acyclic graphs representing a Boolean function, the binary decision diagram comprising a plurality of nodes and a plurality of edges connecting the nodes thereby forming a plurality of paths, each path in the first BDD representing a set of variable assignments setting the represented Boolean function, wherein;

the medical sensor data comprise a plurality of components, each component being defined based on a structural characteristic of a waveform of a signal outputted by the one or more sensors; and

the first BDD comprises a plurality of portions respectively corresponding to the plurality of components;

selecting, from the plurality of portions, one or more portions based on ease-of-analysis for increasing the speed or efficiency of analyzing the medical sensor data; and

constructing a second BDD and one or more third BDDs by partitioning the first BDD, wherein the second BDD represents the one or more selected portions, and the one or more third BDDs respectively represent one or more non-selection portions of the first BDD.

2. The method of claim 1, further comprising analyzing the second BDD.

3. The method of claim 2, wherein analyzing the second BDD is easier than analyzing the one or more selected portions included in the first BDD.

4. The method of claim 1, wherein selecting, from the plurality of portions, the one or more portions based on ease-of-analysis comprises:

identifying, from the plurality of components, one or more components relevant to an analytical process; and

selecting, from the plurality of portions, the one or more portions respectively corresponding to the one or more components relevant to the analytical process.

5. The method of claim 4, further comprising performing the analytical process using the second BDD.

6. The method of claim 1, wherein selecting, from the plurality of portions, the one or more portions based on ease-of-analysis comprises:

selecting, from the plurality of components, one or more components, such that for each of the one or more selected component, a BDD representing the selected component has a compression rate greater than the first BDD'"'"'s compression rate; and

selecting, from the plurality of portions, the one or more portions respectively corresponding to the one or more selected components.

7. The method of claim 1, further comprising identifying the plurality of components in the medical sensor data.

8. The method of claim 7, wherein the plurality of components in the medical sensor data is identified based on one or more structural characteristics of the medical sensor data.

9. The method of claim 8, wherein the one or more structural characteristics of the medical sensor data comprise one or more structural components of a waveform of a signal outputted by at least one of the one or more medical sensors.

10. The method of claim 8, wherein the one or more structural characteristics of the medical sensor data comprise a periodicity of a waveform of a signal outputted by at least one of the one or more medical sensors.

11. The method of claim 8, wherein the one or more structural characteristics of the medical sensor data comprise one or more identifiers embedded in the medical sensor data, which define one or more of the plurality of components.

12. The method of claim 7, wherein the plurality of components in the medical sensor data is identified based on one or more functional characteristics of the medical sensor data.

13. The method of claim 12, wherein the one or more functional characteristics of the medical sensor data comprise a rate of change of a waveform of a signal outputted by at least one of the one or more medical sensors.

14. The method of claim 7, wherein the plurality of components in the medical sensor data is identified based on a plurality of component definitions provided by a user.

15. The method of claim 1, further comprising optimizing the first BDD, the second BDD, and the one or more third BDDs.

16. The method of claim 1, further comprising:

storing the second BDD and the one or more third BDDs; and

deleting the first BDD.

17. The method of claim 1, wherein at least one of the one or more medical sensors is affixed to a person'"'"'s body.

18. An apparatus comprising:

one or more processors; and

a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to;

access medical sensor data from one or more medical sensors measuring physiological stimulus from a person'"'"'s body, the medical sensor data being stored as a first binary decision diagram (BDD), wherein the first BDD comprises one or more rooted directed acyclic graphs representing a Boolean function, the binary decision diagram comprising a plurality of nodes and a plurality of edges connecting the nodes thereby forming a plurality of paths, each path in the first BDD representing a set of variable assignments setting the represented Boolean function, wherein;

the medical sensor data comprise a plurality of components, each component being defined based on a structural characteristic of a waveform of a signal outputted by the one or more sensors; and

the first BDD comprises a plurality of portions respectively corresponding to the plurality of components;

select, from the plurality of portions, one or more portions based on ease-of-analysis for increasing the speed or efficiency of analyzing the medical sensor data; and

construct a second BDD and one or more third BDDs by partitioning the first BDD, wherein the second BDD represents the one or more selected portions, and the one or more third BDDs respectively represent one or more non-selection portions of the first BDD.

19. The apparatus of claim 18, wherein the processors are further operable when executing the instructions to analyzing the second BDD.

20. The apparatus of claim 19, wherein analyzing the second BDD is easier than analyzing the one or more selected portions included in the first BDD.

21. The apparatus of claim 18, wherein selecting, from the plurality of portions, the one or more portions based on ease-of-analysis comprises:

identifying, from the plurality of components, one or more components relevant to an analytical process; and

selecting, from the plurality of portions, the one or more portions respectively corresponding to the one or more components relevant to the analytical process.

22. The apparatus of claim 21, wherein the processors are further operable when executing the instructions to perform the analytical process using the second BDD.

23. The apparatus of claim 18 wherein selecting, from the plurality of portions, the one or more portions based on ease-of-analysis comprises:

selecting, from the plurality of components, one or more components, such that for each of the one or more selected component, a BDD representing the selected component has a compression rate greater than the first BDD'"'"'s compression rate; and

selecting, from the plurality of portions, the one or more portions respectively corresponding to the one or more selected components.

24. The apparatus of claim 18, wherein the processors are further operable when executing the instructions to identify the plurality of components in the medical sensor data.

25. The apparatus of claim 24, wherein the plurality of components in the medical sensor data is identified based on one or more structural characteristics of the medical sensor data.

26. The apparatus of claim 25, wherein the one or more structural characteristics of the medical sensor data comprise one or more structural components of a waveform of a signal outputted by at least one of the one or more medical sensors.

27. The apparatus of claim 25, wherein the one or more structural characteristics of the medical sensor data comprise a periodicity of a waveform of a signal outputted by at least one of the one or more medical sensors.

28. The apparatus of claim 25, wherein the one or more structural characteristics of the medical sensor data comprise one or more identifiers embedded in the medical sensor data, which define one or more of the plurality of components.

29. The apparatus of claim 24, wherein the plurality of components in the medical sensor data is identified based on one or more functional characteristics of the medical sensor data.

30. The apparatus of claim 29, wherein the one or more functional characteristics of the medical sensor data comprise a rate of change of a waveform of a signal outputted by at least one of the one or more medical sensors.

31. The apparatus of claim 24, wherein the plurality of components in the medical sensor data is identified based on a plurality of component definitions provided by a user.

32. The apparatus of claim 18, wherein the processors are further operable when executing the instructions to optimize the first BDD, the second BDD, and the one or more third BDDs.

33. The apparatus of claim 18, wherein the processors are further operable when executing the instructions to:

store the second BDD and the one or more third BDDs; and

delete the first BDD.

34. The apparatus of claim 18, wherein at least one of the one or more medical sensors is affixed to a person'"'"'s body.

35. One or more computer-readable non-transitory storage media embodying software that is operable when executed to:

access medical sensor data from one or more medical sensors measuring physiological stimulus from a person'"'"'s body, the medical sensor data being stored as a first binary decision diagram (BDD), wherein the first BDD comprises one or more rooted directed acyclic graphs representing a Boolean function, the binary decision diagram comprising a plurality of nodes and a plurality of edges connecting the nodes thereby forming a plurality of paths, each path in the first BDD representing a set of variable assignments setting the represented Boolean function, wherein;

the medical sensor data comprise a plurality of components, each component being defined based on a structural characteristic of a waveform of a signal outputted by the one or more sensors; and

the first BDD comprises a plurality of portions respectively corresponding to the plurality of components;

select, from the plurality of portions, one or more portions based on ease-of-analysis for increasing the speed or efficiency of analyzing the medical sensor data; and

construct a second BDD and one or more third BDDs by partitioning the first BDD, wherein the second BDD represents the one or more selected portions, and the one or more third BDDs respectively represent one or more non-selection portions of the first BDD.

36. The media of claim 35, wherein the software is further operable when executed to analyzing the second BDD.

37. The media of claim 36, wherein analyzing the second BDD is easier than analyzing the one or more selected portions included in the first BDD.

38. The media of claim 35, wherein selecting, from the plurality of portions, the one or more portions based on ease-of-analysis comprises:

identifying, from the plurality of components, one or more components relevant to an analytical process; and

selecting, from the plurality of portions, the one or more portions respectively corresponding to the one or more components relevant to the analytical process.

39. The media of claim 38, wherein the software is further operable when executed to perform the analytical process using the second BDD.

40. The media of claim 35 wherein selecting, from the plurality of portions, the one or more portions based on ease-of-analysis comprises:

selecting, from the plurality of components, one or more components, such that for each of the one or more selected component, a BDD representing the selected component has a compression rate greater than the first BDD'"'"'s compression rate; and

selecting, from the plurality of portions, the one or more portions respectively corresponding to the one or more selected components.

41. The media of claim 35, wherein the software is further operable when executed to identify the plurality of components in the medical sensor data.

42. The media of claim 41, wherein the plurality of components in the medical sensor data is identified based on one or more structural characteristics of the medical sensor data.

43. The media of claim 42, wherein the one or more structural characteristics of the medical sensor data comprise one or more structural components of a waveform of a signal outputted by at least one of the one or more medical sensors.

44. The media of claim 42, wherein the one or more structural characteristics of the medical sensor data comprise a periodicity of a waveform of a signal outputted by at least one of the one or more medical sensors.

45. The media of claim 42, wherein the one or more structural characteristics of the medical sensor data comprise one or more identifiers embedded in the medical sensor data, which define one or more of the plurality of components.

46. The media of claim 41, wherein the plurality of components in the medical sensor data is identified based on one or more functional characteristics of the medical sensor data.

47. The media of claim 46, wherein the one or more functional characteristics of the medical sensor data comprise a rate of change of a waveform of a signal outputted by at least one of the one or more medical sensors.

48. The media of claim 41, wherein the plurality of components in the medical sensor data is identified based on a plurality of component definitions provided by a user.

49. The media of claim 35, wherein the software is further operable when executed to optimize the first BDD, the second BDD, and the one or more third BDDs.

50. The media of claim 35, wherein the software is further operable when executed to:

store the second BDD and the one or more third BDDs; and

delete the first BDD.

51. The media of claim 35, wherein at least one of the one or more medical sensors is affixed to a person'"'"'s body.

52. A system comprising:

means for accessing medical sensor data from one or more medical sensors measuring physiological stimulus from a person'"'"'s body the medical sensor data being stored as a first binary decision diagram (BDD), wherein the first BDD comprises one or more rooted directed acyclic graphs representing a Boolean function, the binary decision diagram comprising a plurality of nodes and a plurality of edges connecting the nodes thereby forming a plurality of paths, each path in the first BDD representing a set of variable assignments setting the represented Boolean function, wherein;

the medical sensor data comprise a plurality of components, each component being defined based on a structural characteristic of a waveform of a signal outputted by the one or more sensors; and

the first BDD comprises a plurality of portions respectively corresponding to the plurality of components;

means for selecting, from the plurality of portions, one or more portions based on ease-of-analysis for increasing the speed or efficiency of analyzing the medical sensor data; and

means for constructing a second BDD and one or more third BDDs by partitioning the first BDD, wherein the second BDD represents the one or more selected portions, and the one or more third BDDs respectively represent one or more non-selection portions of the first BDD.