Functional near-infrared spectroscopy as a monitor for depth of anesthesia

• US 9,955,901 B2
• Filed: 06/17/2014
• Issued: 05/01/2018
• Est. Priority Date: 09/30/2008
• Status: Active Grant

• Current Assignee: Drexel University
• Original Assignee: Drexel University
• Inventors: Izzetoglu, Kurtulus, Izzetoglu, Meltem Alkan
• Primary Examiner(s): WINAKUR, ERIC FRANK
• Application Number:
  US14/306,809
• Publication Number:
  US 20140303464A1
• Time in Patent Office: 1,414 Days
• 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 5/14552 Details of sensors specially adapted therefor
• CPC Class Codes: A61B 5/14553 specially adapted for cerebral tissue
• CPC Class Codes: A61B 5/4821 Determining level or depth of anaesthesia A61B5/1106 takes precedence
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal

Abstract

Disclosed are methods and devices for measuring a state of anesthesia in a noninvasive manner. Optical techniques may be used to measure changes in a functional near-infrared (fNIR) signal, where the fNIR signal is received in response to directing wavelengths of light in a near-infrared range on a patient. The optical density change may be used to obtain a change in deoxyhemoglobin (deoxy-Hb) concentration and/or a change in an oxyhemoglobin concentration (oxy-Hb). The changes in the deoxy-Hb and/or the oxy-Hb may then be compared to determine a state of anesthesia.

The effect of artifacts (e.g., strong surgery room lighting, patient-table tilting, patient intubation/extubation) on the fNIR signal may be removed using a noise removal algorithm. In selecting the noise removal algorithm, a switching technique may be used to select the component analysis algorithm, such as a principal component analysis (PCA), an independent component analysis (ICA), or the like.

Claims

1. A method of removing the effect of an artifact on a functional near-infrared signal of a cortical anesthesia monitoring system to improve the system accuracy, the method comprising:

capturing a functional near-infrared signal of a patient, the functional near-infrared signal including a non-cortical signal, wherein the non-cortical signal is indicative of a signal-causing artifact;

processing the functional near-infrared signal with a principal component analysis (PCA) noise removal algorithm and an independent component analysis (ICA) noise removal algorithm,

analyzing outputs from the principal component analysis and the independent component analysis algorithms to select an artifact signal; and

removing the effect of the artifact from the functional near-infrared signal by subtracting a portion of the non-cortical signal from the functional near-infrared signal based on the selected artifact signal.

2. The method of claim 1, wherein the non-cortical signal is captured using a reference optode.

3. The method of claim 1, wherein artifacts resulting in non-cortical signals comprise at least one of a lighting level, change in lighting, table tilting, movement of a patient, patient intubation, or patient extubation.

4. The method of claim 1, wherein the functional near-infrared signal comprises light having at least three wavelengths in a near-infrared range.

5. The method of claim 4, wherein at least one wavelength is captured during a period of minimal activation to provide a reference signal intensity of the non-cortical signal.

6. The method of claim 5, further comprising receiving a functional near-infrared signal in response to at least two of the wavelengths to determine a deoxyhemoglobin concentration and an oxyhemoglobin concentration.

7. The method of claim 6, further comprising measuring an optical density change of the functional near-infrared signal for the at least two of the wavelengths that correlate to the reference signal intensity.

8. The method of claim 1, wherein the monitoring system comprises an anesthesia monitoring system.

9. The method of claim 1, wherein the monitoring system comprises a human brain monitoring system.