Systems and methods for providing sensor arrays for detecting physiological characteristics

• US 8,986,207 B2
• Filed: 11/12/2010
• Issued: 03/24/2015
• Est. Priority Date: 11/12/2009
• Status: Active Grant

• Current Assignee: Covidien LP (Medtronic Plc)
• Original Assignee: Covidien LP (Medtronic Plc)
• Inventors: Li, Youzhi, Chen, Bo, McKenna, Edward M., Addison, Paul Stanley
• Primary Examiner(s): Thomson, William
• Assistant Examiner(s): Archer, Marie
• Application Number:
  US12/944,955
• Publication Number:
  US 20110112379A1
• Time in Patent Office: 1,593 Days
• US Class Current: 600/301
• CPC Class Codes: A61B 2562/0233 Special features of optical sensors or probes classified in A61B5/00
• CPC Class Codes: A61B 2562/046 in a matrix array
• 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 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/14552 Details of sensors specially adapted therefor
• CPC Class Codes: A61B 5/6804 Garments; Clothes
• CPC Class Codes: A61B 5/72 Signal processing specially adapted for physiological signals or for diagnostic purposes character recognition, recognising digital ink, document-oriented image-based pattern recognition G06V30/00; recognition or understanding of postal images G06V30/424
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• 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: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: Y10S 128/92 Computer assisted medical diagnostics
• CPC Class Codes: Y10S 128/925 Neural network

Abstract

Systems and methods for determining physiological parameters of a subject using a sensor array. In an embodiment, a sensor array may contain sensor elements for determining multiple physiological parameters. A combination of sensor elements and the physiological parameters determined may be selected based on signals obtained from the sensor elements of the sensor array. A sensor array may be connected to a monitoring device that may select an optimal sensor element or combination of sensor elements and one or more physiological parameters to be determined. The monitoring device may then determine physiological parameters using the selected combination of sensor elements and display information associated with the parameters on a monitor for use, for example, in monitoring a medical patient.

Claims

1. A method for determining one or more physiological parameters of a subject, the method comprising:

receiving physiological signals from sensor elements coupled to the subject;

analyzing, using a processor, the physiological signals using a first metric associated with a first physiological parameter;

analyzing, using a processor, the physiological signals using a second metric associated with a second physiological parameter;

identifying, using a processor, whether the first physiological parameter can be determined based at least in part on the first metric;

identifying, using a processor, whether the second physiological parameter can be determined based at least in part on the second metric; and

determining, using a processor, at least one of the first and second physiological parameters of the subject based at least in part on the physiological signals received from the sensor elements and based at least in part on whether the first and second physiological parameters can be determined.

2. The method of claim 1, further comprising:

receiving an indication of a set of predefined measurement types; and

identifying the first and second physiological parameters from the set.

3. The method of claim 1, wherein:

analyzing the physiological signals using the first metric comprises;

correlating the physiological signals with a first model for a first available measurement type; and

determining whether the correlation between the physiological signals and the first model exceeds a threshold for the first available measurement type; and

analyzing the physiological signals using the second metric comprises;

correlating the physiological signals with a second model for a second available measurement type; and

determining whether the correlation between the physiological signals and the second model exceeds a threshold for the second available measurement type.

4. The method of claim 1, wherein further comprising:

analyzing the physiological signals using the first metric comprises;

comparing the physiological signals to the first metric, and

determining whether the physiological signals meet a threshold level for the first metric; and

analyzing the physiological signals using the second metric comprises;

comparing the physiological signals to the second metric, and

determining whether the physiological signals meet a threshold level for the second metric.

5. The method of claim 4, further comprising identifying an optimal measurement type that can be determined from the physiological signals based on the comparisons of the physiological signals to the first and second metrics.

6. A system for determining one or more physiological parameters of a subject, the system comprising:

a sensor interface capable of receiving physiological signals from sensor elements coupled to the subject; and

a processor coupled to the sensor interface, wherein the processor is capable of;

analyzing the physiological signals using a first metric associated with a first physiological parameter and a second metric associated with a second physiological parameter;

identifying whether the first physiological parameter can be determined based at least in part on the first metric;

identifying whether the second physiological parameter can be determined based at least in part on the second metric; and

determining at least one of the first and second physiological parameters of the subject based at least in part on the physiological signals received from the sensor elements and on whether the first and second physiological parameters can be determined.

7. The system of claim 6, wherein the processor is further capable of:

receiving an indication of a set of predefined measurement types; and

identifying the first and second physiological parameters from the set.

8. The system of claim 6, wherein the processor is further capable of:

correlating the physiological signals with first and second models for respective first and second available measurement types; and

determining whether the respective correlations between the physiological signals and the first and second models exceed a threshold for at least one of the first and second available measurement types.

9. The system of claim 6, wherein the processor is further capable of:

comparing the physiological signals to the first and second metrics; and

determining whether the physiological signals meet at least one threshold level for the first and second metrics.

10. The system of claim 9, wherein the processor is further capable of identifying an optimal measurement type that can be determined based on the comparisons of the physiological signals to the first and second metrics.