Physiological measurement logic engine

• US 9,693,737 B2
• Filed: 12/11/2015
• Issued: 07/04/2017
• Est. Priority Date: 10/13/2010
• Status: Active Grant

• Current Assignee: Masimo Corporation
• Original Assignee: Masimo Corporation
• Inventors: Al-Ali, Ammar
• Primary Examiner(s): WINAKUR, ERIC FRANK
• Application Number:
  US14/967,075
• Publication Number:
  US 20160166210A1
• Time in Patent Office: 571 Days
• CPC Class Codes: A61B 5/0059 using light, e.g. diagnosis by transillumination, diascopy, fluorescence A61B5/0093, A61B5/1455, A61B5/02416 and A61B5/0261 take precedence
• 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 5/02108 from analysis of pulse wave characteristics
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/0261 using optical means, e.g. infrared light
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/1455 using optical sensors, e.g. spectral photometrical oximeters
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• 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 5/7271 Specific aspects of physiological measurement analysis A61B5/316, A61B5/349 and A61B5/374 take precedence
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: A61B 7/02 Stethoscopes acoustic details thereof G10K11/00
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A patient monitor including a physiological measurement logic engine receives physiological data from a physiological sensor. The logic engine abstracts one or more features of the physiological data and determines a category for the abstracted feature. The logic engine further encodes the category of each of the one or more features and determines an action to perform based on the encoded categories.

Claims

1. A method for reducing processing load of a patient monitor, the method comprising:

emitting light from a light emitter of a physiological sensor;

detecting the light at a detector of the physiological sensor after the light has been attenuated by tissue;

receiving at a patient monitor physiological data from the physiological sensor based at least in part on the light detected at the physiological sensor, wherein the physiological data is characterized by a plurality of features including at least a first feature and a second feature;

associating a category of a first plurality of categories with the physiological data, the first feature characterized by the first plurality of categories;

associating a category of a second plurality of categories with the physiological data, the second feature characterized by the second plurality of categories;

assigning a first value to the physiological data based at least in part on the category of the first plurality of categories;

assigning a second value to the physiological data based at least in part on the category of the second plurality of categories;

determining an action from a set of actions to perform based at least in part on an aggregation of at least the first value and the second value; and

performing the determined action.

2. The method of claim 1, wherein the plurality of features comprises at least one of a standard deviation of the physiological data, a slope of the physiological data, a change in the slope of the physiological data, a correlation coefficient of the physiological data, a linear regression of the physiological data, or a comparison of outputs between different processing engines.

3. The method of claim 1, wherein the set of actions includes at least one of changing a display of a patient monitor, changing an output of the patient monitor, activating an alarm, receiving additional data from the physiological sensor, receiving additional data via a network, notifying a healthcare provider, notifying a patient, powering off, or requesting additional information from a user.

4. The method of claim 1, wherein the plurality of features are predetermined.

5. The method of claim 1, further comprising selecting the plurality of features from a predetermined set of features.

6. The method of claim 5, wherein selecting the plurality of features comprises selecting all the features of the predetermined set of features.

7. The method of claim 5, wherein selecting the plurality of features comprises selecting a subset of the predetermined set of features.

8. The method of claim 5, wherein selecting the plurality of features comprises selecting the features that use fewer processing resources.

9. The method of claim 5, wherein selecting the plurality of features comprises selecting the plurality of features based on a type of physiological data obtained.

10. The method of claim 1, wherein the physiological sensor is one of a pulse oximeter sensor and an acoustic sensor.

24. The method of claim 1, wherein the one or more features comprises a plurality of features and determining the action is based on an aggregation of the assigned values of the plurality of features.

11. A patient monitor system comprising:

a physiological sensor configured to emit light towards a tissue site and detect the light after it has been attenuated by tissue; and

a patient monitor in communication with the physiological sensor and configured to;

receive physiological data from the physiological sensor based at least in part on the light detected by the physiological sensor, wherein the physiological data is characterized by a plurality of features;

determine the plurality of features of the physiological data wherein the plurality of features includes at least a first feature and a second feature;

associate a category of a first plurality of categories with the physiological data, the first feature characterized by the first plurality of categories;

associate a category of a second plurality of categories with the physiological data, the second feature characterized by the second plurality of categories;

assign a first value to the physiological data based at least in part on the category of the first plurality of categories;

assign a second value to the physiological data based at least in part on the category of the second plurality of categories;

determine an action from a set of actions to perform based at least in part on an aggregation of at least the first value and the second value; and

perform the determined action.

12. The system of claim 11, wherein the patient monitor determines in real-time the plurality of features of the physiological data.

13. The system of claim 11, wherein the plurality of features of the physiological data comprise at least one of a standard deviation of the physiological data, a slope of the physiological data, a change in the slope of the physiological data, or a comparison of outputs between different processing engines.

14. The system of claim 11, wherein the plurality of features of the physiological data are predetermined.

15. The system of claim 11, wherein the patient monitor is further configured to select the plurality of features of the physiological data from a predetermined set of features, wherein the patient monitor determines the plurality of features of the physiological data selected from the predetermined set of features.

16. The system of claim 15, wherein the patient monitor selects the plurality of features of the physiological data by selecting all features from the predetermined set of features.

17. The system of claim 15, wherein the patient monitor selects the plurality of features of the physiological data by selecting a subset of features from the predetermined set of features.

18. The system of claim 15, wherein the patient monitor selects the plurality of features of the physiological data by selecting the features of the physiological data that use fewer processing resources.

19. The system of claim 15, wherein the patient monitor selects the plurality of features of the physiological data by selecting the plurality of features of the physiological data based on a type of physiological data obtained.

20. The system of claim 11, wherein the physiological sensor is one of a pulse oximeter sensor and an acoustic sensor.

21. A computer-implemented method for reducing processing load of a patient monitor, the method comprising:

under control of one or more computing devices of the patient monitor;

receiving physiological data from a physiological sensor configured to emit light towards a tissue site and detect the light after it has been attenuated by tissue, wherein the physiological data is characterized by a plurality of features;

determining the plurality of features of the physiological data wherein the plurality of features includes at least a first feature and a second feature;

associating a category of a first plurality of categories with the physiological data, the first feature characterized by the first plurality of categories;

associating a category of a second plurality of categories with the physiological data, the second feature characterized by the second plurality of categories;

assigning a first value to the physiological data based at least in part on the category of the first plurality of categories;

assigning a second value to the physiological data based at least in part on the category of the second plurality of categories;

determining an action from a set of actions to perform based at least in part on an aggregation of at least the first value and the second value; and

performing the determined action.

22. The method of claim 21, wherein the action is determined using an electronic lookup table.

23. The method of claim 21, wherein the determining the plurality of features of the physiological data occurs in real-time.