Functional near-infrared spectroscopy as a monitor for depth of anesthesia
First Claim
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.
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Accused Products
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.
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Citations
9 Claims
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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:
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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. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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Specification