System and method for obtaining health data using a neural network
First Claim
1. A device, comprising:
- an optical circuit including;
a plurality of light emitting diodes configured to emit light at least at a first wavelength in a range of 370 nm to 410 nm and at a second wavelength equal to or greater than 660 nm;
at least one photodetector configured to detect photoplethysmography (PPG) signals in response to pulsating blood flow, wherein the PPG signals include a first spectral response obtained from light reflected at the first wavelength from skin tissue of a patient and a second spectral response obtained from light reflected at the second wavelength from the skin tissue of the patient;
a signal processing circuit configured to generate PPG input data using the first spectral response at the first wavelength in a range of 370 nm to 410 nm and the second spectral response at the second wavelength equal to or greater than 660 nm; and
a neural network processing device implementing a machine learning algorithm, wherein one or more parameters of the machine learning algorithm are determined using a training set, wherein the training set includes training PPG input data obtained from a healthy population and corresponding known glucose levels from the healthy population, wherein the training PPG input data includes spectral responses at the first wavelength and at the second wavelength from the healthy population and wherein the neural network processing device is configured to;
determine a glucose level in blood flow of the patient from the PPG input data including the first spectral response at the first wavelength and the second spectral response at the second wavelength.
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Accused Products
Abstract
A photoplethysmography (PPG) circuit or non-contact camera obtains PPG signals at a plurality of wavelengths. A signal processing module obtains at least a first spectral response around a first wavelength and a second spectral response around a second wavelength. The signal processing device generates PPG input data using the PPG signals, wherein the PPG input data includes one or more parameters obtained from each of the first spectral response and the second spectral response. A neural network processing device generates an input vector including the PPG input data and determines an output vector including health data, wherein the health data includes for example, an oxygen saturation level, a glucose level or a blood alcohol level.
223 Citations
24 Claims
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1. A device, comprising:
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an optical circuit including; a plurality of light emitting diodes configured to emit light at least at a first wavelength in a range of 370 nm to 410 nm and at a second wavelength equal to or greater than 660 nm; at least one photodetector configured to detect photoplethysmography (PPG) signals in response to pulsating blood flow, wherein the PPG signals include a first spectral response obtained from light reflected at the first wavelength from skin tissue of a patient and a second spectral response obtained from light reflected at the second wavelength from the skin tissue of the patient; a signal processing circuit configured to generate PPG input data using the first spectral response at the first wavelength in a range of 370 nm to 410 nm and the second spectral response at the second wavelength equal to or greater than 660 nm; and a neural network processing device implementing a machine learning algorithm, wherein one or more parameters of the machine learning algorithm are determined using a training set, wherein the training set includes training PPG input data obtained from a healthy population and corresponding known glucose levels from the healthy population, wherein the training PPG input data includes spectral responses at the first wavelength and at the second wavelength from the healthy population and wherein the neural network processing device is configured to; determine a glucose level in blood flow of the patient from the PPG input data including the first spectral response at the first wavelength and the second spectral response at the second wavelength. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A device, comprising:
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a signal processing circuit configured to; receive photoplethysmography (PPG) signals, wherein the PPG signals include a first spectral response obtained from light at a first wavelength reflected from skin tissue of a patient and a second spectral response obtained from light reflected at a second wavelength reflected from skin tissue of the patient, wherein the first wavelength is between 370 nm and 410 nm and wherein the second wavelength is equal to or greater than 660 nm; generate PPG input data using the first spectral response obtained from light reflected at the first wavelength and the second spectral response obtained from light reflected at the second wavelength; and a neural network processing device configured to; pre-configure one or more parameters using a learning vector generated from a training set, wherein the training set includes additional PPG input data obtained from a healthy population and corresponding known nitric oxide (NO) levels, wherein the additional PPG input data includes additional spectral responses at the first wavelength and at the second wavelength; and determine an NO level in blood flow from the first spectral response obtained from light reflected at the first wavelength and the second spectral response obtained from light reflected at the second wavelength. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17)
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18. A device, comprising:
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a signal processing circuit including a plurality of light emitting diodes and at least one photodetector configured to; obtain photoplethysmography (PPG) signals at a first wavelength from skin tissue of a patient and at a second wavelength from skin tissue of the patient, wherein the first wavelength is in a range of 370 nm-410 nm and wherein the second wavelength is in a visible or an infrared (IR) range; generate PPG input data using the PPG signals obtained from the patient at the first wavelength in the range of 370 nm-410 nm and at the second wavelength in the visible or the IR range; and a neural network processing device configured to; obtain one or more parameters generated from a training set, wherein the training set includes PPG signals obtained from a healthy population at the first wavelength in a range of 370 nm to 410 nm and at the second wavelength in the visible or the IR range and corresponding known glucose levels obtained from the healthy population; receive the PPG input data; and determine a glucose level in blood flow of the patient from the PPG signals obtained from the patient at the first wavelength in the range of 370 nm to 410 nm and at the second wavelength in the visible or the IR range. - View Dependent Claims (19, 20, 21, 22, 23, 24)
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Specification