Systems and methods for determining whether regional oximetry sensors are properly positioned

• US 10,201,302 B2
• Filed: 01/10/2018
• Issued: 02/12/2019
• Est. Priority Date: 01/27/2014
• Status: Active Grant

• Current Assignee: Covidien LP (Medtronic Plc)
• Original Assignee: Covidien LP (Medtronic Plc)
• Inventors: Baker, Jr., Clark R.
• Primary Examiner(s): WINAKUR, ERIC FRANK
• Application Number:
  US15/867,208
• Publication Number:
  US 20180146897A1
• Time in Patent Office: 398 Days
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: A61B 5/684 Indicating the position of the sensor on the body
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence

Abstract

Methods and systems are presented for determining whether a regional oximetry sensor is properly positioned on a subject. First and second metric values may be determined based on respective first and second light signals. The first and second metric values and a relationship between the first and second metrics are used to determine whether the sensor is properly positioned on the subject. The first and second metrics may form a pair of metrics, and whether the sensor is properly positioned on the subject may be determined based on whether the pair of metrics falls within a sensor-on region. In some embodiments, a plurality of metrics may be determined based on a plurality of received physiological signals. The plurality of metrics may be combined, using, for example, a neural network, to determine whether the regional oximetry sensor is properly positioned on a subject.

Claims

1. A system comprising:

one or more inputs configured to;

receive a first signal representative of an intensity of light at a first detector of a regional oximetry sensor, and

receive a second signal representative of an intensity of light at a second detector of the regional oximetry sensor; and

one or more processors configured to;

determine a first metric value based on the first signal;

determine a second metric value based on the second signal;

determine a first combination metric value based on the first metric value and the second metric value;

determine a second combination metric value based on the second metric value, and

determine, based on the first combination metric value and the second combination metric value, that the regional oximetry sensor is properly positioned relative to a target site on a subject.

2. The system of claim 1, wherein the one or more processors are configured to determine that the regional oximetry sensor is properly positioned relative to the target site by at least comparing the first combination metric value and the second combination metric value to a distribution threshold.

3. The system of claim 1, wherein the one or more processors are configured to determine that the regional oximetry sensor is properly positioned relative to the target site by at least comparing the first combination metric value to a first distribution threshold and comparing the second combination metric value to a second distribution threshold.

4. The system of claim 3, wherein the one or more processors are configured to determine that the regional oximetry sensor is properly positioned relative to the target site in response to determining that the first combination metric value exceeds the first distribution threshold and that the second combination metric does not exceed the second distribution threshold.

5. The system of claim 1, wherein the one or more processors are configured to use a neural network to determine, based on the first combination metric value and the second combination metric value, that the regional oximetry sensor is properly positioned relative to the target site.

6. The system of claim 1, wherein the one or more processors are further configured to determine the regional oxygen saturation (rSO₂) of the subject in response to determining that the regional oximetry sensor is positioned within or at the target site.

7. The system of claim 1, wherein the first metric value is based on a near-infrared light component of the first signal, and the second metric value is based on a near-infrared light component of the second signal, and

wherein the one or more processors are configured to determine that the regional oximetry sensor is properly positioned relative to the target site by at least comparing the first combination metric value and the second combination metric value to a distribution threshold, wherein the distribution threshold is a function of the first metric value and the second metric value.

8. The system of claim 1, wherein the one or more processors are configured to determine the first metric value based on the first signal by at least normalizing the first signal based on a first calibration coefficient to generate a normalized first signal, and determining the first metric value based on the normalized first signal, and

wherein the one or more processors are configured to determine the second metric value based on the second signal by at least normalizing the second signal based on a second calibration coefficient to generate a normalized second signal, and determining the second metric value based on the normalized second signal.

9. The system of claim 8, wherein the regional oximetry sensor comprises a light source configured to emit a plurality of wavelengths of light, wherein the first and second detectors of the regional oximetry sensor are configured to receive the plurality of wavelengths of light, and wherein:

the first calibration coefficient is based on a brightness of the light source and a first sensitivity of the first detector, and

the second calibration coefficient is based on the brightness of the light source and a second sensitivity of the second detector.

10. The system of claim 8, wherein the one or more processors are configured to determine at least one of the first metric value or the second metric value by at least determining the at least one of the first metric value or the second metric value as a logarithm of a respective one of the normalized first signal or the normalized second signal.

11. The system of claim 1, wherein the one or more processors are configured to determine the first combination metric value by at least determining First Metric−

m*Second Metric+b, wherein m and b denote linear regression coefficients, wherein First Metric denotes the first metric value, and wherein Second Metric denotes the second metric value.

12. The system of claim 1, wherein the one or more processors are further configured to:

determine a first morphology metric value associated with morphology of the first signal; and

determine a second morphology metric value associated with morphology of the second signal, wherein the one or more processors are further configured to determine that the regional oximetry sensor is properly positioned relative to the target site based on the first and second morphology metric values.

13. The system of claim 12, wherein the first signal is associated with a first mean path length and the second signal is associated with a second mean path length longer than the first mean path length, and wherein the one or more processors are configured to determine the first morphology metric value based on a shape of a pulsatile modulation of the first signal.

14. The system of claim 12, wherein the first morphology metric value is based on skewness of a first derivative of the first signal, and wherein the second morphology metric value is based on the peak-to-peak modulation of the second signal.

15. A system comprising:

one or more inputs configured to;

receive a first signal representative of an intensity of light at a first detector of a regional oximetry sensor, and

receive a second signal representative of an intensity of light at a second detector of the regional oximetry sensor; and

one or more processors configured to;

determine a first metric value based on the first signal;

determine a second metric value based on the second signal,

determine a combination metric value based on the first metric value and the second metric value;

determine, based on the combination metric value, that the regional oximetry sensor is not properly positioned relative to a target site on a subject.

16. The system of claim 15, wherein the one or more processors are configured to determine that the regional oximetry sensor is not properly positioned relative to the target site by at least comparing the combination metric value to a distribution threshold.

17. The system of claim 15, wherein the one or more processors are configured to use a neural network to determine, based on the combination metric value, that the regional oximetry sensor is not properly positioned relative to the target site.

18. A method comprising:

receiving a first signal representative of an intensity of light at a first detector of a regional oximetry sensor,

receiving a second signal representative of an intensity of light at a second detector of the regional oximetry sensor;

determining, by one or more processors, a first metric value based on the first signal;

determining, by the one or more processors, a second metric value based on the second signal;

determining, by the one or more processors, a first combination metric value based on the first metric value and the second metric value;

determining, by the one or more processors, a second combination metric value based on the first metric value and the second metric value; and

determining, by one or more processors, based on the first combination metric value and the second combination metric value, that the regional oximetry sensor is properly positioned relative to a target site on a subject.

19. The method of claim 18, wherein the determining, by the one or more processors, that the regional oximetry sensor is properly positioned relative to the target site comprises comparing the first combination metric value to a first distribution threshold and comparing the second combination metric value to a second distribution threshold.

20. The method of claim 19, wherein the determining, by the one or more processors, that the regional oximetry sensor is properly positioned relative to the target site comprises determining that the first combination metric value exceeds the first distribution threshold and that the second combination metric does not exceed the second distribution threshold.

21. The method of claim 18, wherein the determining, by the one or more processors, that the regional oximetry sensor is properly positioned relative to the target site comprises using a neural network to determine that the regional oximetry sensor is properly positioned relative to the target site based on the first combination metric value and the second combination metric value.

22. A method comprising:

receiving a first signal representative of an intensity of light at a first detector of a regional oximetry sensor;

receiving a second signal representative of an intensity of light at a second detector of the regional oximetry sensor;

determining, by one or more processors, a first metric value based on the first signal;

determining, by the one or more processors, a second metric value based on the second signal;

determining, by the one or more processors, a combination metric value based on the first metric value and the second metric value; and

determining, by one or more processors, based on the combination metric value, that the regional oximetry sensor is not properly positioned relative to a target site on a subject.

23. The method of claim 22, wherein the determining, by the one or more processors, that the regional oximetry sensor is not properly positioned relative to the target site comprises comparing the combination metric value to a distribution threshold.

24. The method of claim 22, wherein the determining, by the one or more processors, that the regional oximetry sensor is not properly positioned relative to the target site comprises using a neural network to determine that the regional oximetry sensor is properly positioned relative to the target based on the combination metric value.