Measurement of water replenishment using an optical sensor

Abstract

The present disclosure provides a physiological monitoring system that can include a hardware processor. The hardware processor can access first optical data corresponding to a water-dependent radiation wavelength that is attenuated through a medium and detected by a detector. The hardware processor can access second optical data corresponding to a water-independent radiation wavelength that is attenuated through the medium and detected by the detector. The hardware processor can determine a hydration index of the medium based on the first and second optical data.

Description

Technical Field

[0001] The present disclosure relates to systems, devices, and methods for monitoring a user's hydration.

Background Art

[0002] Spectroscopy is a common technique for measuring the concentrations of organic and some inorganic components in a solution. The theoretical basis of this technique is the Beer-Lambert law, which states that the concentration c of an absorber in a solution i is related to the path length d at a specific wavelength λ λ , the intensity I of the incident light 0,λ , and the extinction coefficient ε i,λ and can be determined by the intensity of the light transmitted through the solution, provided that these values are known.

[0003] In a generalized form, the Beer-Lambert law is

Equation

Equation

[0004] Certain applications of this technique are pulse oximetry and plethysmography that utilize non-invasive sensors to measure, among other physiological parameters, oxygen saturation and pulse rate. Pulse oximetry or plethysmography outputs signals indicative of various physiological parameters, such as the patient's blood components and / or analytes, including, among other physiological parameters, the percentage value of arterial blood oxygen saturation, and depends on a sensor externally attached to the patient (typically, for example, a fingertip, foot, ear, forehead, or other measurement site). The sensor has at least one emitter that transmits light radiation of one or more wavelengths to the tissue site, and at least one detector that responds to the intensity of the light radiation (which can be reflected from or transmitted through the tissue site) after absorption by the pulsatile arterial blood flowing within the tissue site. Based on this response, the processor determines the relative concentrations of oxygenated hemoglobin (HbO2) and deoxygenated hemoglobin (Hb) in order to derive the oxygen saturation, which provides early detection of potentially dangerous decreases in the patient's oxygen supply and other physiological parameters.

[0005] The patient monitoring device can include a plethysmograph sensor. The plethysmograph sensor can calculate oxygen saturation (SpO2), pulse rate, plethysmograph waveform, perfusion index (PI), pleth variability index (PVI), methemoglobin (MetHb), carboxyhemoglobin (CoHb), total hemoglobin (tHb), respiratory rate, glucose, etc. The parameters measured by the plethysmograph sensor can be displayed on one or more monitors individually, in groups, in trends, as combinations, or as overall health status or other indicators.

[0006] The water content of tissues is also a useful diagnostic parameter. Dehydration symptoms can reduce cognitive and physical abilities. On the other hand, overhydration can be a symptom of any of several clinically relevant conditions, such as heart, liver, or kidney pathology, phlebitis, malnutrition and / or poor diet, allergies, food intolerances, pregnancy, laxatives, diuretics, and / or abuse of other drugs, use of pregnancy medications or hormone replacement therapy.

SUMMARY OF THE INVENTION

MEANS FOR SOLVING THE PROBLEM

[0007] The various implementations of the systems, methods, and devices within the scope of the appended claims each have several aspects, and no single one of them alone is the sole factor for the desirable attributes described herein. Without limiting the scope of the appended claims, the following description explains several prominent features.

[0008] Details of one or more implementations of the subject matter described herein are set forth in the accompanying drawings and the following detailed description. Other features, aspects, and advantages will become apparent from the description, drawings, and claims. Note that the relative dimensions of the following figures may not be drawn to scale.

[0009] The devices, systems, and methods of the present disclosure each have several innovative aspects, and no single one of them alone is the sole factor for their desirable attributes. Without limiting the scope of the present disclosure, its more prominent features are briefly discussed here.

[0010] Monitoring the water content of tissues can be useful for indicating the state of hydration of a person engaged in physical activity, such as exercise. Low body hydration can cause health problems and may negatively affect athletic performance. Additionally, some pathological symptoms caused by dehydration symptoms include problems related to digestion, high blood pressure, seizures, etc.

[0011] An optical sensor can provide information regarding the tissue components of a subject. The tissue components can include, among other things, hemoglobin and water. The optical sensor can use radiation of a plurality of wavelengths. Each of the wavelengths may be more sensitive to absorption, attenuation, scattering, etc. by a specific component of the tissue than other wavelengths. Thus, the various wavelengths can provide different information regarding the various tissue components. The information corresponding to the various wavelengths can facilitate determining a more accurate hydration estimation.

[0012] A physiological monitoring system can non-invasively monitor a subject's hydration in real time using an optical sensor. The physiological monitoring system can include a wearable device and one or more hardware computer processors. The wearable device can be fixed to the subject. The wearable device can include one or more light emitters and one or more optical detectors. The one or more light emitters can emit light radiation towards the subject's tissue. The light radiation can include a water-dependent wavelength and a water-independent wavelength. The one or more optical detectors can detect the light radiation emitted by the one or more light emitters after attenuation through the subject's tissue. The one or more optical detectors can generate optical data in response to detecting the light radiation. The one or more hardware computer processors can access the optical data. The one or more hardware computer processors can determine a water-dependent optical parameter based on the optical data corresponding to the water-dependent wavelength. The one or more hardware computer processors can determine a water-independent optical parameter based on the optical data corresponding to the water-independent wavelength. The one or more hardware computer processors can determine the subject's hydration index based on normalizing the water-dependent optical parameter by the water-independent optical parameter. The one or more hardware computer processors can generate user interface data for rendering a display of the hydration index on a display.

[0013] In some implementations, the wearable device can further include a device display configured to render one or more user interfaces including the subject's physiological data. The one or more hardware computer processors can generate user interface data for rendering a display of the hydration index on the device display.

[0014] In some implementations, normalizing a water-dependent optical parameter by a water-independent optical parameter can include dividing the water-dependent optical parameter by the water-independent optical parameter.

[0015] In some implementations, normalizing a water-dependent optical parameter by a water-independent optical parameter includes subtracting the water-independent optical parameter from the water-dependent optical parameter.

[0016] In some implementations, the water-dependent optical parameter corresponds to the light intensity of a water-dependent wavelength of radiation detected by one or more optical detectors, and the water-independent optical parameter corresponds to the light intensity of a water-independent wavelength of radiation detected by one or more optical detectors.

[0017] In some implementations, the water-dependent optical parameter corresponds to the absorption of radiation of a water-dependent wavelength by tissue, and the water-independent optical parameter corresponds to the absorption of radiation of a water-independent wavelength by tissue.

[0018] In some implementations, the water-dependent wavelength of the radiation is sensitive to absorption by water, and the absorption of the water-independent wavelength of the radiation is not substantially affected by water.

[0019] In some implementations, the water-dependent wavelength of the radiation is greater than 700 nm.

[0020] In some implementations, the water-dependent wavelength of the radiation is greater than 800 nm.

[0021] In some implementations, the water-dependent wavelength of the radiation is greater than 900 nm.

[0022] In some implementations, the water-dependent wavelength of the radiation is between 900 nm and 1000 nm.

[0023] In some implementations, the water-dependent wavelength of the radiation is 970 nm.

[0024] In some implementations, the water-dependent wavelength of the radiation is 905 nm.

[0025] In some implementations, the water-independent wavelength of the radiation is less than 700 nm.

[0026] In some implementations, the water-independent wavelength of the radiation is between 600 nm and 700 nm.

[0027] In some implementations, the water-independent wavelength of the radiation is 660 nm.

[0028] In some implementations, the water-independent wavelength of the radiation is 620 nm.

[0029] In some implementations, one or more hardware computer processors can adjust optical data based on wavelengths associated with the optical data, and adjusting the optical data includes increasing the magnitude of the optical data associated with wavelengths at which the detector has low sensitivity.

[0030] In some implementations, one or more hardware computer processors can determine a hydration index based on calibration data including an empirical data calibration curve.

[0031] In some implementations, the wearable device includes a wristwatch.

[0032] In some implementations, the wearable device includes an auricular device.

[0033] In some implementations, the wearable device includes a finger sensor.

[0034] In some implementations, the wearable device is configured to be fixed to the wrist area of the subject.

[0035] In some implementations, the wearable device is configured to be fixed to a subject's finger.

[0036] In some implementations, the wearable device is configured to be fixed to a subject's ear.

[0037] In some implementations, the wearable device is configured to be fixed to a subject's foot.

[0038] In some implementations, the wearable device is configured to be fixed to a subject's head.

[0039] In some implementations, the wearable device further comprises one or more hardware computer processors.

[0040] In some implementations, the one or more hardware computer processors are disposed within a computing device remote from the wearable device.

[0041] In some implementations, the computing device includes a telephone.

[0042] In some implementations, the computing device includes a server.

[0043] In some implementations, the one or more hardware computer processors can determine a hydration protocol based at least on a hydration index, the hydration protocol including a recommended amount of fluid to hydrate.

[0044] In some implementations, the one or more hardware computer processors can determine a hydration protocol based at least on a hydration index, the hydration protocol including a recommended time to hydrate.

[0045] In some implementations, one or more hardware computer processors can determine a hydration protocol based at least on a hydration index, the hydration protocol including a recommended time for exercise.

[0046] In some implementations, one or more hardware computer processors can determine a hydration protocol based at least on a hydration index, the hydration protocol including an estimated time to a dehydrated state.

[0047] In some implementations, one or more hardware computer processors can access reference optical data corresponding to other radiation attenuated through a reference medium. The other radiation can include water-dependent wavelengths and water-independent wavelengths. One or more hardware computer processors can determine a water-dependent optical parameter based on normalizing optical data corresponding to a water-dependent wavelength with reference optical data corresponding to the water-dependent wavelength. One or more hardware computer processors can determine a water-independent optical parameter based on normalizing optical data corresponding to a water-independent wavelength with reference optical data corresponding to the water-independent wavelength.

[0048] In some implementations, the optical data corresponds to an optical density of tissue and the reference optical data corresponds to an optical density of a reference medium.

[0049] In some implementations, the reference medium is air.

[0050] In some implementations, normalizing the optical data with the reference optical data includes dividing the optical data by the reference optical data.

[0051] In some implementations, one or more hardware computer processors can determine a second water-dependent optical parameter based on a second water-dependent wavelength of radiation. One or more hardware computer processors can determine a second water-independent optical parameter based on a second water-independent wavelength of radiation. One or more hardware computer processors can determine a hydration index based on normalizing the difference between the water-dependent optical parameter and the second water-dependent optical parameter by the difference between the water-independent optical parameter and the second water-independent optical parameter.

[0052] In some implementations, the second water-dependent wavelength of radiation is greater than 800 nm.

[0053] In some implementations, the second water-dependent wavelength of radiation is between 900 nm and 1000 nm.

[0054] In some implementations, the water-dependent wavelength of radiation is 970 nm and the second water-dependent wavelength of radiation is 905 nm.

[0055] In some implementations, the second water-independent wavelength of radiation is less than 700 nm.

[0056] In some implementations, the second water-independent wavelength of radiation is between 600 nm and 700 nm.

[0057] In some implementations, the water-independent wavelength of radiation is 620 nm and the second water-independent wavelength of radiation is 660 nm.

[0058] In some implementations, the water-dependent optical parameter corresponds to the estimated area integrated under the absorption curve between the water-dependent wavelength and the second water-dependent wavelength.

[0059] In some implementations, the water-independent optical parameter corresponds to an estimated area integrated under an absorption curve between a water-independent wavelength and a second water-independent wavelength.

[0060] In some implementations, one or more hardware computer processors can access reference optical data corresponding to other radiation attenuated through a reference medium, where the other radiation includes a water-dependent wavelength, a second water-dependent wavelength, a water-independent wavelength, and a second water-independent wavelength, and the radiation includes a second water-dependent wavelength and a second water-independent wavelength. One or more hardware computer processors can determine a water-dependent optical parameter based on normalizing optical data corresponding to the water-dependent wavelength by reference optical data corresponding to the water-dependent wavelength. One or more hardware computer processors can determine a second water-dependent optical parameter based on normalizing optical data corresponding to the second water-dependent wavelength by reference optical data corresponding to the second water-dependent wavelength. One or more hardware computer processors can determine a water-independent optical parameter based on normalizing optical data corresponding to the water-independent wavelength by reference optical data corresponding to the water-independent wavelength. One or more hardware computer processors can determine a second water-independent optical parameter based on normalizing optical data corresponding to the second water-independent wavelength by reference optical data corresponding to the second water-independent wavelength. One or more hardware computer processors can determine a tissue hydration index based on normalizing the difference between the water-dependent optical parameter and the second water-dependent optical parameter by the difference between the water-independent optical parameter and the second water-independent optical parameter.

[0061] In some implementations, the second water-dependent wavelength of the radiation is between 900 nm and 1000 nm, and the second water-independent wavelength of the radiation is between 600 nm and 700 nm.

[0062] In some implementations, the water-dependent wavelength of the radiation is 970 nm, the second water-dependent wavelength of the radiation is 905 nm, the water-independent wavelength of the radiation is 620 nm, and the second water-independent wavelength of the radiation is 660 nm.

[0063] A method for non-invasively monitoring a subject's hydration in real time using an optical sensor can include emitting light radiation towards the subject's tissue by one or more light emitters. The light radiation includes a water-dependent wavelength and a water-independent wavelength. The method can further include detecting, by one or more optical detectors, the emitted light radiation after attenuation through the subject's tissue. The method can further include generating optical data in response to detecting the light radiation. The method can further include determining a water-dependent optical parameter based on the optical data corresponding to the water-dependent wavelength. The method can further include determining a water-independent optical parameter based on the optical data corresponding to the water-independent wavelength. The method can further include determining a hydration index of the subject based on normalizing the water-dependent optical parameter by the water-independent optical parameter. The method can further include generating user interface data for rendering a display of the hydration index on a display. The method can further include displaying, via the display, the display of the hydration index.

[0064] A non-transitory computer-readable medium can include computer-executable instructions that, when executed by a computing system, cause the computing system to emit light radiation toward a subject's tissue by one or more light emitters, the light radiation including a water-dependent wavelength and a water-independent wavelength; detect the emitted light radiation after attenuation through the subject's tissue by one or more optical detectors; generate optical data in response to detecting the light radiation; determine a water-dependent optical parameter based on the optical data corresponding to the water-dependent wavelength; determine a water-independent optical parameter based on the optical data corresponding to the water-independent wavelength; determine a hydration index of the subject based on normalizing the water-dependent optical parameter by the water-independent optical parameter; generate user interface data for rendering a display of the hydration index on a display; and display the display of the hydration index via the display.

[0065] A physiological monitoring system can non-invasively monitor a subject's hydration in real time using an optical sensor. The physiological monitoring system can include a wearable device configured to be fixed to the subject and one or more hardware computer processors. The wearable device can include one or more light emitters and one or more optical detectors. The one or more light emitters can emit light radiation towards the subject's tissue. The light radiation can include a water-dependent wavelength between 900 nm and 1000 nm. The light radiation can include a water-independent wavelength between 600 nm and 700 nm. The one or more optical detectors can detect the light radiation emitted by the one or more light emitters after attenuation through the subject's tissue and generate optical data in response to detecting the light radiation. The one or more hardware computer processors can access the optical data, determine a water-dependent optical parameter based on the optical data corresponding to the water-dependent wavelength, determine a water-independent optical parameter based on the optical data corresponding to the water-independent wavelength, determine a hydration index of the subject based on the water-dependent optical parameter and the water-independent optical parameter, and generate user interface data for rendering a display of the hydration index on a display.

[0066] In some implementations, the wearable device can further include a device display configured to render one or more user interfaces including the subject's physiological data. The one or more hardware computer processors can generate user interface data for rendering a display of the hydration index on the device display.

[0067] A physiological monitoring system for non-invasively monitoring a subject's hydration using an optical sensor can comprise one or more light emitters, one or more optical detectors, and one or more hardware computer processors. The one or more light emitters can emit light radiation towards the subject's tissue. The light radiation can include water-dependent wavelengths between 900 nm and 1000 nm. The light radiation can include water-independent wavelengths between 600 nm and 700 nm. The one or more optical detectors can detect the light radiation emitted by the one or more light emitters after attenuation through the subject's tissue. The one or more optical detectors can generate optical data in response to detecting the light radiation. The one or more hardware computer processors can access the optical data. The one or more hardware computer processors can determine a hydration index of the subject based on the optical data corresponding to the water-dependent and water-independent wavelengths.

[0068] A physiological monitoring system for non-invasively monitoring a subject's hydration using an optical sensor can comprise one or more light emitters, one or more optical detectors, and one or more hardware computer processors. The one or more light emitters can emit light radiation towards the subject's tissue. The light radiation can include a plurality of water-dependent wavelengths and a plurality of water-independent wavelengths. The one or more optical detectors can detect the light radiation emitted by the one or more light emitters after attenuation through the subject's tissue. The one or more optical detectors can generate optical data in response to detecting the light radiation. The one or more hardware computer processors can access the optical data and determine a hydration index of the subject based on normalizing the optical data corresponding to the plurality of water-dependent wavelengths by the optical data corresponding to the plurality of water-independent wavelengths.

[0069] In some embodiments, each of the wavelengths of the plurality of water-dependent wavelengths is greater than 800 nm.

[0070] In some embodiments, each of the wavelengths of the plurality of water-dependent wavelengths is between 900 nm and 1000 nm.

[0071] In some embodiments, the plurality of water-dependent wavelengths includes a first wavelength of at least 905 nm and a second wavelength of 970 nm.

[0072] In some embodiments, the plurality of water-dependent wavelengths includes at least two wavelengths.

[0073] In some embodiments, each of the wavelengths of the plurality of water-independent wavelengths is less than 700 nm.

[0074] In some embodiments, each of the wavelengths of the plurality of water-independent wavelengths is between 600 nm and 700 nm.

[0075] In some embodiments, the plurality of water-independent wavelengths includes a first wavelength of at least 620 nm and a second wavelength of 660 nm.

[0076] In some embodiments, the plurality of water-independent wavelengths includes at least two wavelengths.

[0077] A physiological monitoring system for non-invasively monitoring a subject's hydration using an optical sensor can include one or more light emitters, one or more optical detectors, and one or more hardware computer processors. The one or more light emitters can emit light radiation towards the subject's tissue. The light radiation can include a plurality of water-dependent wavelengths and a plurality of water-independent wavelengths. The one or more optical detectors can detect the light radiation emitted by the one or more light emitters after attenuation through the subject's tissue. The one or more optical detectors can generate optical data in response to detecting the light radiation. The one or more hardware computer processors can access the optical data. The one or more hardware computer processors can determine a water-dependent optical parameter based on the optical data corresponding to the plurality of water-dependent wavelengths. The water-dependent optical parameter can correspond to at least a portion of an estimated area under a water absorption curve between the plurality of water-dependent wavelengths. The one or more hardware computer processors can determine a water-independent optical parameter based on the optical data corresponding to the plurality of water-independent wavelengths. The water-independent optical parameter can correspond to at least a portion of an estimated area under a hemoglobin absorption curve between the plurality of water-independent wavelengths. The one or more hardware computer processors can determine a hydration index of the subject based on the water-dependent optical parameter and the water-independent optical parameter.

[0078] In some implementations, the hemoglobin absorption curve includes an oxyhemoglobin absorption curve.

[0079] In some implementations, the hemoglobin absorption curve includes a deoxyhemoglobin absorption curve.

[0080] A physiological monitoring system for non-invasively monitoring a subject's hydration can comprise one or more hardware computer processors. The one or more hardware computer processors can execute a plurality of computer-executable instructions that cause the physiological monitoring system to access optical data corresponding to radiation attenuated through a medium and detected by a detector. The one or more hardware computer processors can execute a plurality of computer-executable instructions that cause the physiological monitoring system to determine a water-dependent optical parameter based on a water-dependent wavelength of the radiation. The one or more hardware computer processors can execute a plurality of computer-executable instructions that cause the physiological monitoring system to determine a water-independent optical parameter based on a water-independent wavelength of the radiation. The one or more hardware computer processors can execute a plurality of computer-executable instructions that cause the physiological monitoring system to determine a hydration index of the medium based on normalizing the water-dependent optical parameter by the water-independent optical parameter.

[0081] A computer-implemented method can include accessing optical data corresponding to radiation attenuated through a medium and detected by a detector. The computer-implemented method can include determining a water-dependent optical parameter based on a water-dependent wavelength of the radiation. The computer-implemented method can include determining a water-independent optical parameter based on a water-independent wavelength of the radiation. The computer-implemented method can include determining a hydration index of the medium based on normalizing the water-dependent optical parameter by the water-independent optical parameter.

[0082] A computing system can comprise one or more hardware computer processors. The one or more hardware computer processors can execute a plurality of computer-executable instructions that cause the computing system to access first optical data corresponding to water-dependent radiation wavelengths attenuated through a medium and detected by a detector. The one or more hardware computer processors can execute a plurality of computer-executable instructions that cause the computing system to access second optical data corresponding to water-independent radiation wavelengths attenuated through the medium and detected by the detector. The one or more hardware computer processors can execute a plurality of computer-executable instructions that cause the computing system to determine a moisture replenishment index of the medium based on the first and second optical data.

[0083] A physiological monitoring system for monitoring a subject's hydration using an optical sensor can comprise one or more light emitters, one or more optical detectors, and one or more hardware computer processors. The one or more light emitters can emit light radiation towards the subject's tissue. The light radiation can include a water-dependent wavelength and a water-independent wavelength. The one or more optical detectors can detect the light radiation emitted by the one or more light emitters after attenuation through the subject's tissue. The one or more optical detectors can generate optical data in response to detecting the light radiation. The one or more hardware computer processors can access the optical data. The one or more hardware computer processors can determine a hydration index of the subject based on the optical data corresponding to the water-dependent wavelength and the water-independent wavelength. The one or more hardware computer processors can determine a hydration protocol for the subject based at least on the hydration index. The one or more hardware computer processors can generate user interface data for rendering a display of the hydration protocol on a display.

[0084] In some implementations, the hydration protocol includes a recommended amount of fluid for the subject to consume.

[0085] In some implementations, the hydration protocol includes a recommended time for the subject to consume the fluid.

[0086] In some implementations, the hydration protocol includes a recommended time to exercise.

[0087] In some implementations, the one or more hardware computer processors can generate one or more alerts based on the hydration protocol.

[0088] In some implementations, one or more hardware computer processors can generate one or more alerts based on a hydration index.

[0089] In some implementations, the physiological monitoring system further comprises a wearable device. The wearable device can comprise a device display. One or more hardware computer processors can generate user interface data for rendering a display of a hydration protocol on the device display.

[0090] The present disclosure provides a method, system, and / or device capable of detecting a subject's hydration by optical sensing. The physiological monitoring system can include a hardware processor. The physiological monitoring system can include a device including an optical sensor configured to collect physiological data from a subject. The device may be remote from the hardware processor. The device can be portable. The device can include a wearable device. The device can be fixed to the subject. The device can be attached to the subject. The device can be a wristwatch. The device can be an adhesive patch. The adhesive patch can include an electronic device. The device can be a phone. The device can be earbuds. The device can collect physiological data from a body part of the subject, including but not limited to the head, forehead, face, ear, nose, neck, shoulder, arm, forearm, hand, finger, toe, abdomen, back, chest, torso, belly, waist, leg, thigh, calf, ankle, and toe of the foot. The device can be incorporated as part of clothing, such as a hat, shirt, pants, shorts, socks, boots, shoes, a sweatband, an armband, a headband, gloves, or other clothing items worn by the subject.

[0091] In certain aspects, the present disclosure provides a method for estimating a user's hydration that includes transmitting light of a first wavelength, a second wavelength, a third wavelength, and a fourth wavelength to the user's skin; measuring a first absorption of the user's tissue corresponding to the first wavelength, a second absorption of the user's tissue corresponding to the second wavelength, a third absorption of the user's tissue corresponding to the third wavelength, and a fourth absorption of the user's tissue corresponding to the fourth wavelength; integrating over the first absorption and the second absorption to generate a first hydration parameter; integrating over the third absorption and the fourth absorption to generate a second hydration parameter; and comparing the second hydration parameter to the first hydration parameter to generate a result.

[0092] In some implementations, the tissue absorption at the first wavelength and the second wavelength may not be substantially affected by the user's hydration. In some implementations, the tissue absorption at the third wavelength and the fourth wavelength may be substantially affected by the user's hydration. In some implementations, the method may include averaging the first absorption and the second absorption and multiplying by the difference between the first wavelength and the second wavelength, and may also include integrating the first absorption and the second absorption. In some implementations, the method includes averaging the third absorption and the fourth absorption and multiplying by the difference between the third wavelength and the fourth wavelength, and may also include integrating the third absorption and the fourth absorption. In some implementations, the method may also include projecting the first absorption and the second absorption to their respective values at 95% SpO2 if the user's SpO2 is less than 95%. In some implementations, the method may also include transmitting light of a fifth wavelength to the user's skin, where the fifth wavelength may be between the first wavelength and the second wavelength, measuring the fifth absorption of the user's tissue corresponding to the fifth wavelength, and integrating over the first absorption, the fifth absorption, and the second absorption to generate a first hydration parameter. In some implementations, the method may also include transmitting light of a fifth wavelength to the user's skin, where the fifth wavelength may be between the third wavelength and the fourth wavelength, measuring the fifth absorption of the user's tissue corresponding to the fifth wavelength, and integrating over the third absorption, the fifth absorption, and the fourth absorption to generate a second hydration parameter. In some implementations, the first wavelength may be in the range of about 400 nm to 660 nm. The first wavelength may be in the range of about 610 nm to 630 nm. The first wavelength may be about 620 nm. In some implementations, the second wavelength may be in the range of about 620 nm to 700 nm. The second wavelength may be in the range of about 650 nm to 670 nm. The second wavelength may be about 660 nm. In some implementations, the third wavelength may be in the range of about 800 nm to 970 nm.The third wavelength can be in the range of about 895 nm to 915 nm. The third wavelength can be about 905 nm. In some implementations, the fourth wavelength can be in the range of about 905 nm to 1400 nm. The fourth wavelength can be in the range of about 960 nm to 980 nm. The fourth wavelength can be about 970 nm.

[0093] In certain aspects, the present disclosure provides a method for estimating a user's hydration that includes integrating over a first pair of tissue absorbances to generate a first hydration parameter, integrating over a second pair of tissue absorbances to generate a second hydration parameter, and comparing the first hydration parameter and the second hydration parameter.

[0094] In certain aspects, the present disclosure provides a system capable of estimating a user's hydration that includes one or more light sources configured to emit light at a first wavelength, a second wavelength, a third wavelength, and a fourth wavelength, an optical sensor configured to measure a first tissue absorbance corresponding to the first wavelength, a second tissue absorbance corresponding to the second wavelength, a third tissue absorbance corresponding to the third wavelength, and a fourth tissue absorbance corresponding to the fourth wavelength, and a processor configured to receive the first, second, third, and fourth tissue absorbances, integrate the first and second tissue absorbances to generate a first hydration parameter, integrate the third and fourth tissue absorbances to generate a second hydration parameter, and compare the first hydration parameter and the second hydration parameter to generate a result.

[0095] In some implementations, the system may include a first light source configured to emit light at a first wavelength, a second light source configured to emit light at a second wavelength, a third light source configured to emit light at a third wavelength, and a fourth light source configured to emit light at a fourth wavelength. In some implementations, each of the first wavelength, the second wavelength, the third wavelength, and the fourth wavelength may be different. In some embodiments, the tissue absorption at the first wavelength and the second wavelength may not be substantially affected by the user's hydration. In some embodiments, the tissue absorption at the third wavelength and the fourth wavelength may be substantially affected by the user's hydration. In some embodiments, the first wavelength may be in the range of about 400 nm to 660 nm. The first wavelength may be in the range of about 610 nm to 630 nm. The first wavelength may be about 620 nm. In some implementations, the second wavelength may be in the range of about 620 nm to 700 nm. The second wavelength may be in the range of about 650 nm to 670 nm. The second wavelength may be about 660 nm. In some implementations, the third wavelength may be in the range of about 800 nm to 970 nm. The third wavelength may be in the range of about 895 nm to 915 nm. The third wavelength may be about 905 nm. In some implementations, the fourth wavelength may be in the range of about 905 nm to 1400 nm. The fourth wavelength may be in the range of about 960 nm to 980 nm. The fourth wavelength may be about 970 nm. In some embodiments, the system may include a display configured to show results. In some embodiments, the system may include a display configured to indicate the user's hydration level. In some embodiments, the system may be included within a wearable device.

[0096] With reference to the accompanying drawings, various implementations will be described below. These implementations are illustrated and described by way of example only and are not intended to limit the scope of the present disclosure. In the drawings, like elements may have like reference numerals.

Brief Description of the Drawings

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DETAILED DESCRIPTION OF THE INVENTION

[0098] The present disclosure will be described with reference to the accompanying drawings, where like numerals indicate like elements throughout. The following description is merely exemplary in nature and is in no way intended to limit the present disclosure, its application, or its use. It should be understood that steps within a method may be performed in a different order without changing the principles of the present disclosure. Further, the devices, systems, and / or methods disclosed herein may include several novel features, and no single one of them alone may be the sole factor for its desirable attributes or be indispensable for practicing the devices, systems, and / or methods disclosed herein.

[0099] Specific implementations and examples will be described below, but those skilled in the art will understand that the present disclosure extends beyond the specifically disclosed implementations and / or uses and their obvious modifications and equivalents based on the disclosure herein. Accordingly, the scope of the disclosure herein should not be limited by any specific implementation and / or example described below.

[0100] A subject's hydration level can be evaluated by measuring impedance and / or conductance to assess the concentration of electrolytes in sweat that can indicate the hydration level. Alternatively, changes in the body's electrical impedance can be used to monitor changes in hydration. However, impedance and / or conductance may be partially dependent on the anthropometric characteristics of the subject, such as body weight, age, gender, race, shoulder width, waist circumference, waist-hip ratio, and body mass index. Further, impedance and / or conductance may be partially dependent on the subject's electrolyte levels, which can change independently of hydration. Models incorporating measurements of impedance and / or conductance to estimate hydration may not be able to account for these variables and may result in inaccurate measurements.

[0101] To evaluate water replenishment, magnetic resonance imaging (MRI) can be used. However, MRI requires equipment that is not easily movable and bulky. In addition, MRI equipment is expensive and requires operation by a skilled technician. In addition, an MRI scan can take longer than one hour.

[0102] Another method of estimating water replenishment is the dilution method, which involves orally administering a dose of tracer to a subject. Typically, two blood or urine samples are collected, one immediately before the administration of the tracer and one after a sufficient time, usually from a few minutes to a few hours later. Water replenishment is estimated by correlating the dose of the tracer with the dilution of the tracer in the second sample. The dilution method is time-consuming and inconvenient for the subject.

[0103] The present disclosure provides devices, systems, and methods that can accurately, portably, conveniently, rapidly, and / or non-invasively optically measure a subject's water replenishment. The optical attenuation or absorbance by a medium such as the subject's tissue can be measured at wavelengths that are not substantially affected by the tissue's water content and / or at wavelengths that are affected by the tissue's water content. These absorbances can be analyzed to generate a quantitative indicator of the subject's water replenishment.

[0104] FIG. 1A is a perspective view of an exemplary wearable device 100. The wearable device 100 can be a wristwatch such as a smartwatch. The wearable device 100 can perform one or more physiologically related functions. The wearable device 100 can perform one or more non-physiologically related functions. The wearable device 100 can perform functions such as time tracking and display, execution of data communication, and reproduction of audio sound. The wearable device 100 can include a display configured to display information such as physiological information to the user.

[0105] The wearable device 100 can include one or more straps 102. The strap 102 is adjustable and can removably secure the wearable device 100 to a part of a subject, such as the wrist. In some embodiments, the wearable device 100 can be secured to other parts of the body, such as the ear, finger, arm, leg, ankle, neck, etc. The wearable device 100 can include one or more sensors, such as physiological sensors. The wearable device 100 can include an optical sensor.

[0106] The wearable device 100 can include one or more emitters 104. The emitter 104 can include one or more light-emitting diodes (LEDs). The emitter 104 can emit light radiation of various wavelengths, such as light that can penetrate the tissue of the user of the wearable device 100.

[0107] The wearable device 100 can include one or more detectors 106. The detector 106 can form a ring around the emitter 104. The detector 106 can detect light radiation, such as the light emitted by the emitter 104. The detector 106 can generate one or more signals based at least in part on the detected radiation emitted by the emitter 104. The detector 106 can generate data regarding spectroscopy. The detector 106 can generate data regarding the hydration status of the user. The detector 106 can generate data regarding the blood oxygen saturation of the user of the wearable device 100. The light emitter and detector can be configured in a reflectance sensor configuration or a transmittance sensor configuration. For example, non-limiting examples are discussed below for different types of sensor configurations and measurement sites.

[0108] Sensors of the wearable device 100, such as the emitter 104 and / or the detector 106, can be disposed on the housing of the wearable device 100. In some embodiments, one or more of the sensors of the wearable device 100 can be disposed in a part of the housing of the wearable device 100 that is not easily accessible to the user. For example, the user may not be able to access one or more sensors with the user's finger, and / or the sensors may not be visible to the user when worn. For example, the sensors can be disposed in the lower portion of the wearable device 100 such that the wearable device 100 covers the sensors with respect to the user, such as when the wearable device 100 is worn by the user on the user's wrist area. In various implementations, the emitter 104 and the detector 106 can be disposed around the user's tissue such that the detector 106 can detect light transmitted through the user's tissue. In some embodiments, the emitter 104 and the detector 106 can be disposed on the opposite side of the user's tissue, such as on the opposite side of the finger. In other implementations, the emitter 104 and the detector 106 can be disposed on the same side of the tissue, such as on the same side of the wrist.

[0109] Figure 1B shows another exemplary wearable device 120. The wearable device 120 can be an auricle device. The wearable device 120 can be an earbud, earphone, headset, etc. The wearable device 120 can be fixed to the ear 122 of the user 121. The wearable device 120 can be fixed to the concha, helix, tragus, antitragus, earlobe, etc. of the ear 122 of the user 121. The wearable device 120 can be disposed adjacent to the ear canal of the user 121. The wearable device 120 can be disposed within the ear canal of the user 121. A part of the wearable device 120 can be disposed within the ear canal of the user 121. The entire wearable device 120 can be disposed within the ear canal of the user 121. The wearable device 120 can emit an audio signal such as music through a speaker. The wearable device 120 can include one or more physiological sensors such as an optical sensor. The wearable device 120 can include a light emitter and an optical detector. The light emitter of the wearable device 120 can emit light radiation such as light to the ear 122 of the user 121 to collect physiological data of the user 121. The optical detector can detect the radiation that has passed through the ear 122 of the user 121. The wearable device 120 can include any of the structural and / or operational features illustrated and / or described herein as any of the other exemplary wearable devices such as the wearable device 100.

[0110] Figure 1C shows another exemplary wearable device 140. The wearable device 140 can be fixed to a user's finger or toe, such as a finger, thumb, or toe of the foot. The wearable device 140 can be a ring. The wearable device 140 can include one or more physiological sensors, such as optical sensors. The wearable device 140 can include a light emitter and an optical detector. The light emitter of the wearable device 140 can emit light radiation, such as light, to the user's finger or toe to collect the user's physiological data. The optical detector can detect the radiation that has passed through the user's finger or toe. The wearable device 140 can include any of the structural and / or operational features illustrated and / or described herein as any of the other exemplary wearable devices, such as the wearable device 100.

[0111] Figure 1D shows another example of a wearable device 160. The wearable device 160 can be fixed to the user's foot 162, such as the leg or ankle. The wearable device 160 can include one or more physiological sensors, such as optical sensors. The wearable device 160 can include a light emitter and an optical detector. The light emitter of the wearable device 160 can emit light to the user's foot 162 to collect the user's physiological data. The optical detector can detect the radiation that has passed through the user's foot 162. The wearable device 160 can include any of the structural and / or operational features illustrated and / or described herein as any of the other exemplary wearable devices, such as the wearable device 100.

[0112] Figure 1E shows another example of the wearable device 170. The wearable device 170 can be fixed to the user's nose 172. The wearable device 170 can be fixed to the nostrils, nasal bridge, etc. of the user's nose 172. The wearable device 170 may include one or more physiological sensors such as an optical sensor. The wearable device 170 can include a light emitter and an optical detector. The light emitter of the wearable device 170 can emit light to the user's nose 172 to collect the user's physiological data. The optical detector can detect the radiation that has passed through the user's nose 172. The wearable device 170 can include any of the structural and / or operational features illustrated and / or described herein as any of the other exemplary wearable devices such as the wearable device 100.

[0113] Figure 1F shows another example of the wearable device 180. The wearable device 180 can be fixed to a finger or toe of a subject such as a finger or thumb. The wearable device 180 may include one or more physiological sensors such as an optical sensor. The wearable device 180 can include a light emitter and an optical detector. The light emitter of the wearable device 180 can emit light to the finger or toe of the subject to collect the subject's physiological data. The optical detector can detect the radiation that has passed through the finger or toe of the subject. The wearable device 180 can include any of the structural and / or operational features illustrated and / or described herein as any of the other exemplary wearable devices such as the wearable device 100.

[0114] Figure 1G shows another example of the wearable device 190. The wearable device 190 can include a sensor unit 193 and a control unit 191. The sensor unit 193 can be separated from the control unit 191. The sensor unit 193 can be remote from the control unit 191. The sensor unit 193 can be connected to the control unit 191 via one or more cables 195. In some implementations, the sensor unit 193 can be wirelessly connected to the control unit 191. The control unit 191 can include a display. The control unit 191 can display physiological data of the subject. The wearable device 190 can be fixed to the subject, such as the subject's arm, forearm, wrist, hand, finger, thumb, etc. The control unit 191 can be fixed to the subject's wrist. The sensor unit 193 can be fixed to the subject's finger, such as a finger or thumb. The sensor unit 193 can include one or more physiological sensors, such as an optical sensor. The sensor unit 193 can include a light emitter and an optical detector. The light emitter of the sensor unit 193 can emit light to the subject's finger to collect the subject's physiological data. The optical detector can detect the radiation that has passed through the subject's finger. The wearable device 190 can include any of the structural and / or operational features illustrated and / or described herein as any of the other exemplary wearable devices, such as the wearable device 100.

[0115] Figures 1A - 1G are provided by way of example and are not intended to be limiting. A variety of wearable devices that can be attached to various parts of a user's body can be implemented. In some implementations, the wearable device can be a headband, hat, helmet, glasses, etc., and can be attached to the user's head. In some implementations, the wearable device can be a wristband, armband, glove, etc., and can be attached to a part of the user's arm or hand. In some implementations, the wearable device can be a necklace, etc., and can be attached to the user's neck. In some implementations, the wearable device can be attached to a part of the body different from the part of the body that collects physiological data. For example, the wearable device can be worn around the user's neck and can collect physiological data from the user's hand. In some implementations, the wearable device can be fixed to the user via one or more of adhesion, straps, frictional force, elastic force, spring force, etc.

[0116] Figure 2 is a block diagram showing an exemplary implementation of a physiological monitoring system 250. The physiological monitoring system 250 can include a hardware processor 201, a memory device 203, a communication module 205, a power supply 207, one or more optical emitters 209, and one or more optical detectors 213. The physiological monitoring system 250 can optionally include a display 211 and one or more other sensors 215. In some implementations, the physiological monitoring system 250 can include fewer components than all of the components shown in FIG. 2.

[0117] In some implementations, one or more components of the physiological monitoring system 250 may be implemented in a wearable device, such as any of the exemplary wireless devices illustrated and / or described herein with reference to FIGS. 1A-1E. For example, the wearable device 100 may include one or more components of the physiological monitoring system 250 within the housing of the wearable device 100. In some implementations, the physiological monitoring system 250 may be implemented as a single integrated unit, such as within the same device. In some implementations, one or more components of the physiological monitoring system 250 may be implemented on separate devices. For example, the light emitter 209 and / or the optical detector 213 may be implemented on the wearable device, and the hardware processor 201 may be located remotely from the wearable device, such as on a remote server or a remote computing device.

[0118] The hardware processor 201 can be configured to execute program instructions for causing the physiological monitoring system 250 to perform one or more operations. The hardware processor 201 can be configured to, among other things, process data, execute instructions to perform one or more functions, and / or control the operation of the physiological monitoring system 250 or its components. For example, the hardware processor 201 can process physiological data obtained from a physiological sensor and execute instructions for performing functions related to the storage, processing, analysis, and / or transmission of such physiological data. In some implementations, the hardware processor 201 can be remote from other components of the physiological monitoring system 250. The hardware processor 201 can be implemented on a remote computing device that is remote from other components of the physiological monitoring system 250. The remote computing device can include, for example, a server, a phone, a computer, another wearable device, a physiological sensor, a physiological monitoring hub, and the like. The hardware processor 201 can receive and process data from the optical detector 213 and / or other sensors 215 in real time, such as when the data is collected and / or after a length of time imperceptible to human senses after the data is collected. The hardware processor 201 can access and process data stored in the memory device 203, such as data previously generated by the optical detector 213 and / or other sensors 215.

[0119] The memory device 203 can include one or more memory devices for storing data, including, but not limited to, dynamic and / or static random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), and the like. Such stored data can include processed and / or unprocessed physiological data obtained from a physiological sensor.

[0120] The communication module 205 can facilitate communication (via a wired connection and / or a wireless connection) between the physiological monitoring system 250 (and / or its components) and a separate device, such as a separate device, sensor, system, server, etc. For example, the communication module 205 can be configured to enable the hardware processor 201 to communicate wirelessly with other devices, systems, and / or networks via any of a variety of communication protocols. The communication module 205 can be configured to use any of a variety of wireless communication protocols, such as Wi-Fi (802.11x), Bluetooth®, ZigBee®, Z-wave®, cellular phone, infrared, near field communication (NFC), RFID, satellite transmission, its own protocol, combinations thereof, etc. The communication module 205 can enable data and / or instructions to be transmitted and / or received between the hardware processor 201 and a separate computing device. The communication module 205 can be configured to transmit and / or receive (e.g., wirelessly) processed and / or unprocessed physiological data with a separate computing device, including a physiological sensor, other monitoring hubs, remote servers, etc. The communication module 205 can be embodied in one or more components that communicate with each other. The communication module 205 can include near field communication (NFC) components, such as a wireless transceiver, antenna, and / or transponder.

[0121] The power supply 207 can supply power to the components of the physiological monitoring system 250. The power supply 207 can include a battery. The power supply 207 can include a dual battery configuration having a main battery and a backup battery. The power supply 207 can include energy from a commercial power line, such as a cable connected to a 110V outlet. The power supply 207 can include solar power generation.

[0122] The hardware processor 201 can generate display data for display on the display 211 or to render a user interface. The display 211 can be a digital display. The display 211 can be an LED display. The display 211 can be an ultra-low power display. The display 211 can be an electronic paper display. The display 211 can display physiological data such as physiological parameters.

[0123] The light emitter 209 can be configured to emit light radiation such as light. The light emitter 209 can include one or more light emitting diodes (LEDs). The light emitter 209 can also include one or more groups or clusters of emitters. In some implementations, each group or cluster of emitters can include five emitters. In some implementations, each group or cluster of emitters can include more than five emitters. In some implementations, each group or cluster of emitters can include four emitters. In some implementations, each group or cluster of emitters can include less than four emitters, such as three or two emitters. Each group of the light emitter 209 can be configured to emit a plurality of different wavelengths as described herein. The light emitter 209 can be configured to emit radiation at a plurality of wavelengths. The light emitter 209 can be configured to emit radiation within the visible spectrum.

[0124] The optical detector 213 can include a photosensitive optical detector. The optical detector 213 can include a photodiode. The optical detector 213 can include two or more groups or clusters of detectors. In some implementations, each group or cluster of the optical detector 213 can include a single detector. In some implementations, each group or cluster of the optical detector 213 can include two or more detectors.

[0125] The light emitter 209 can be configured to emit light of a first wavelength. The first wavelength can be in the range of about 400 nm to 660 nm. The first wavelength can be in the range of about 610 nm to 630 nm. The first wavelength can be less than 700 nm. The first wavelength can be less than 650 nm. The first wavelength can be about 620 nm.

[0126] The light emitter 209 can be configured to emit light of a second wavelength. In some implementations, the second wavelength can be in the range of about 620 nm to 700 nm. The second wavelength can be in the range of about 650 nm to 670 nm. The second wavelength can be less than 700 nm. The second wavelength can be less than 680 nm. The second wavelength can be about 660 nm.

[0127] The light emitter 209 can be configured to emit light of a third wavelength. In some implementations, the third wavelength can be in the range of about 800 nm to 970 nm. The third wavelength can be in the range of about 895 nm to 915 nm. The third wavelength can exceed 800 nm. The third wavelength can exceed 890 nm. The third wavelength can be about 905 nm.

[0128] The light emitter 209 can be configured to emit light of a fourth wavelength. In some implementations, the fourth wavelength can be in the range of about 905 nm to 1400 nm. The fourth wavelength can be in the range of about 960 nm to 980 nm. The fourth wavelength can exceed 900 nm. The fourth wavelength can exceed 950 nm. The fourth wavelength can be about 970 nm.

[0129] Light of the first and / or second wavelength may be more sensitive to the hemoglobin content of tissues such as oxygenated hemoglobin and / or deoxygenated hemoglobin than light of the third and / or fourth wavelength. Light of the first and / or second wavelength may be more readily absorbed by hemoglobin such as oxygenated hemoglobin and / or deoxygenated hemoglobin than light of the third and / or fourth wavelength. Light of the third and / or fourth wavelength may be more sensitive to the water content of tissues than light of the first and / or second wavelength. Light of the third and / or fourth wavelength may be more readily absorbed by water than light of the first and / or second wavelength.

[0130] As an exemplary example, an implementation of the optical detector 213 can include a first LED capable of emitting light at a wavelength of 620 nm, a second LED capable of emitting light at a wavelength of 660 nm, a third LED capable of emitting light at a wavelength of 905 nm, and a fourth LED capable of emitting light at a wavelength of 970 nm.

[0131] The hardware processor 201 can process signals to determine a plurality of physiological parameters. The hardware processor 201 can be configured to drive the light emitter 209 to emit radiation of different wavelengths and / or process signals from the optical detector 213 of the radiation attenuated after absorption by the subject's body tissue. Absorption of the light may occur via transreflectance by the wearer's body tissue. Absorption of the light may be pulsatile arterial blood flowing through capillaries (and optionally arteries) within the tissue site. As used herein, "attenuation" and "absorption" may be used interchangeably.

[0132] The physiological monitoring system 250 can be configured to measure indicators of the wearer's physiological parameters. This can include, for example, heart rate, respiratory rate, SpO2, pulse wave variability index (PVI), perfusion index (PI), respiratory rate (RRp: Respiration from the pleth), total hemoglobin (SpHb), hydration, glucose, blood pressure, and / or other parameters. The physiological monitoring system 250 can perform intermittent and / or continuous monitoring of the measured parameters. The physiological monitoring system 250 can additionally and / or alternatively perform extraction tests of the measured parameters, for example, in response to the wearer's request.

[0133] The other sensors 215 can include one or more sensors. The other sensors 215 can be remote from the hardware processor 201, the light emitter 209, and / or the optical detector 213. The other sensors 215 can include physiological sensors. The other sensors 215 can include one or more of an acoustic sensor, a voltage sensor, an impedance sensor, a capacitance sensor, an inertial sensor, and the like.

[0134] The hardware processor 201 can determine the subject's hydration status. The hardware processor 201 can determine the subject's hydration index. The hardware processor 201 can determine the subject's hydration status based on data obtained from a light sensor such as the light emitter 209 and / or the optical detector 213. The hardware processor 201 can determine the subject's hydration status based on data obtained from other sensors 215. The hardware processor 201 can determine the subject's hydration status based on a combination of data obtained from the light emitter 209, the optical detector 213, and other sensors 215. For example, the hardware processor 201 can determine the subject's hydration status based on data from the optical sensor in combination with data from a sweat sensor, an impedance sensor, an inertial sensor, or an acoustic sensor. The hardware processor 201 can calculate the mean or weighted mean of the hydration index values calculated based on signals from different sensors, and / or can rely on different hydration monitoring sensors for redundancy.

[0135] Figure 3 is a diagram 300 showing how various components of physiological tissue attenuate or absorb radiation of various wavelengths. The tissue may include physiological components such as melanin, hemoglobin, and water. Hemoglobin may include oxyhemoglobin, deoxyhemoglobin, carboxyhemoglobin, and / or methemoglobin. Water may be intracellular or extracellular. Extracellular water may be interstitial or intravascular. Intravascular water may be in the plasma. As shown, water may absorb less radiation at shorter wavelengths than at longer wavelengths. For example, water may absorb minimal or negligible amounts of radiation at wavelengths less than about 700 nm and more radiation at wavelengths greater than about 700 nm. The amount of radiation absorbed by water may depend on the wavelength of the radiation. The amount of radiation absorbed by water may increase as the wavelength increases.

[0136] As shown, hemoglobin, such as oxygenated hemoglobin, may absorb less radiation at longer wavelengths than at shorter wavelengths. For example, hemoglobin may absorb minimal or negligible amounts of radiation at wavelengths greater than about 800 nm, 900 nm, or 1000 nm, and may absorb more radiation at wavelengths less than about 800 nm, 900 nm, or 1000 nm. The amount of radiation absorbed by hemoglobin may depend on the wavelength of the radiation. The amount of radiation absorbed by hemoglobin may increase as the wavelength decreases.

[0137] Figure 300 includes three absorption curves for various tissue water contents. Curve 333A shows the absorption of radiation over various wavelengths due to a high tissue water content. Curve 333B shows the absorption of radiation over various wavelengths due to a medium tissue water content. Curve 333C shows the absorption of radiation over various wavelengths due to a low tissue water content. As shown, a change in tissue water content can affect the amount of radiation absorbed by the tissue. For example, a decrease in tissue water content can result in a decrease in the absorbance of radiation in the tissue, such as for radiation at wavelengths greater than about 700 nm. As another example, an increase in tissue water content can result in an increase in the absorbance of radiation in the tissue, such as for radiation at wavelengths greater than about 700 nm. As shown, a change in tissue water content can affect the amount of radiation absorbed by the tissue at wavelengths greater than about 700 nm. As shown, a change in tissue water content can have a minimal effect, an insignificant effect, or no effect on the amount of radiation absorbed by the tissue at wavelengths less than about 700 nm.

[0138] Figure 300 includes an exemplary first parameter 301 and an exemplary second parameter 302. The first parameter 301 represents the absorption of light integrated under the oxyhemoglobin curve 341. The first parameter 301 may depend on hemoglobin content such as oxyhemoglobin content. For example, the area of the first parameter 301 may increase as the oxyhemoglobin content increases and may decrease as the oxyhemoglobin content decreases. The first parameter 301 may not be affected, substantially unaffected, or minimally affected by tissue water content. For example, a change in tissue water content may have little or no effect on the first parameter 301. The first parameter 301 may be independent of tissue water content. The first parameter 301 may be unrelated to tissue water content. The first parameter 301 may include wavelengths that are independent of water. The first parameter 301 may not be sensitive to water.

[0139] The second parameter 302 represents the absorption of light integrated under a water absorption curve such as curve 333B. The second parameter 302 may depend on tissue water content. For example, the area of the second parameter 302 may increase as the tissue water content increases and may decrease as the tissue water content decreases. The second parameter 302 may be affected by hemoglobin such as the content of deoxyhemoglobin or oxyhemoglobin. For example, as shown, the deoxyhemoglobin curve 343 and the oxyhemoglobin curve 341 may intersect the second parameter 302. The second parameter 302 may correspond to the amount of water in the tissue that may correspond to the subject's hydration level. The second parameter 302 may depend more directly on tissue water content than on hemoglobin content.

[0140] As described herein, the second parameter 302 can be used to determine a subject's hydration level. In some implementations, the second parameter 302 can be used in combination with the first parameter 301 to determine a subject's hydration level. For example, the systems or methods described herein can compare the first parameter 301 to the second parameter 302. A second parameter 302 that is greater than the first parameter 301 may indicate a high tissue water content. A second parameter 302 that is less than the first parameter 301 may indicate a low tissue water content. Considering how non-water components, such as hemoglobin, affect the absorption of radiation within the second parameter 302 may improve the determination of the tissue water content.

[0141] The first parameter 301 can be bounded by an upper wavelength and a lower wavelength. The first parameter 301 can include the lower wavelength λ1. The first parameter 301 can include the upper wavelength λ2. The lower wavelength λ1 is not affected or minimally affected by the water content of the tissue. The lower wavelength λ1 is not absorbed or minimally absorbed by water. The lower wavelength λ1 may be referred to as a water-independent wavelength. The lower wavelength λ1 may be less sensitive to absorption, attenuation, scattering, etc. by water than the lower wavelength λ3 and / or the upper wavelength λ4. The lower wavelength λ1 may be less sensitive to absorption, attenuation, scattering, etc. by water. The lower wavelength λ1 can be less than 700 nm, less than 680 nm, less than 660 nm, less than 640 nm, less than 620 nm, less than 610 nm, less than 600 nm, less than 500 nm, etc. In some implementations, the lower wavelength λ1 can be 620 nm. The lower wavelength λ1 may be smaller than the upper wavelength λ2. The difference between the lower wavelength λ1 and the upper wavelength λ2 can be less than 100 nm, less than 80 nm, less than 60 nm, less than 40 nm, less than 30 nm, etc. In some implementations, the difference between the lower wavelength λ1 and the upper wavelength λ2 can be 40 nm. The lower wavelength λ1 can be disposed in a portion of the oxygenated hemoglobin curve 341 that has a steeper absolute value slope than other portions of the oxygenated hemoglobin curve 341. The lower wavelength λ1 can be disposed in a portion of the oxygenated hemoglobin curve 341 that has the maximum or nearly maximum absolute value slope. The lower wavelength λ1 can be separated from the upper wavelength λ2 such that the difference between the absorption of the lower wavelength λ1 by deoxygenated hemoglobin or oxygenated hemoglobin and the absorption of the upper wavelength λ2 by deoxygenated hemoglobin or oxygenated hemoglobin is maximized or nearly maximized for a wavelength range between about 400 nm and about 1000 nm, or between about 500 nm and about 1000 nm, or between about 600 nm and 1000 nm.

[0142] The upper limit wavelength λ2 may not be affected by the tissue water content or may be affected only minimally. The upper limit wavelength λ2 may not be absorbed by water or may be absorbed by water only minimally. The upper limit wavelength λ2 may be referred to as a water-independent wavelength. The upper limit wavelength λ2 may be less sensitive to absorption, attenuation, scattering, etc. by water than the lower limit wavelength λ3 and / or the upper limit wavelength λ4. The upper limit wavelength λ2 may be less sensitive to absorption, attenuation, scattering, etc. by water. The upper limit wavelength λ2 may be less than 700 nm, less than 680 nm, less than 660 nm, less than 650 nm, less than 640 nm, etc. In some implementations, the upper limit wavelength λ2 may be 660 nm. The upper limit wavelength λ2 may be greater than the lower limit wavelength λ1.

[0143] The second parameter 302 can be bounded by an upper wavelength and a lower wavelength. The second parameter 302 can include the lower wavelength λ3. The second parameter 302 can include the upper wavelength λ4. The lower wavelength λ3 may depend on the tissue water content. The lower wavelength λ3 may be absorbed by water. The lower wavelength λ3 may be referred to as a water-dependent wavelength. The lower wavelength λ3 may be sensitive to absorption, attenuation, scattering, etc. by water. The lower wavelength λ3 may be more sensitive to absorption, attenuation, scattering, etc. by water than the lower wavelength λ1 and / or the upper wavelength λ2. The lower wavelength λ3 may be referred to as being sensitive to water. The lower wavelength λ3 may be greater than 700 nm. The lower wavelength λ3 may be less than 880 nm, less than 900 nm, less than 910 nm, less than 920 nm, less than 940 nm, etc. In some implementations, the lower wavelength λ3 may be 905 nm. The lower wavelength λ3 may be less than the upper wavelength λ4. The difference between the lower wavelength λ3 and the upper wavelength λ4 may be less than 100 nm, less than 90 nm, less than 80 nm, less than 70 nm, less than 60 nm, less than 50 nm, etc. In some implementations, the difference between the lower wavelength λ3 and the upper wavelength λ4 may be 65 nm. The lower wavelength λ3 may be disposed in a portion of the water curve 333 that has a steeper absolute value slope than other portions of the water curve 333. The lower wavelength λ3 may be disposed in a portion of the oxygenated hemoglobin curve 341 that has the maximum or nearly maximum absolute value slope. The lower wavelength λ3 may be separated from the upper wavelength λ4 such that the difference between the absorption of the lower wavelength λ3 by water and the absorption of the upper wavelength λ4 by water is maximized or nearly maximized for a wavelength range between about 800 nm and about 1300 nm, or between about 800 nm and about 1000 nm.

[0144] The upper limit wavelength λ4 may depend on the tissue water content. The upper limit wavelength λ4 may be absorbed by water. The upper limit wavelength λ4 may be called a water-dependent wavelength. The upper limit wavelength λ4 may be sensitive to absorption, attenuation, scattering, etc. by water. The upper limit wavelength λ4 may be more sensitive to absorption, attenuation, scattering, etc. by water than the lower limit wavelength λ1 and / or the upper limit wavelength λ2. The upper limit wavelength λ4 may be called sensitive to water. The upper limit wavelength λ4 may be greater than 700 nm. The upper limit wavelength λ4 may be less than 950 nm, less than 960 nm, less than 970 nm, less than 980 nm, less than 990 nm, less than 1000 nm, etc. In some implementations, the upper limit wavelength λ4 may be 970 nm. The upper limit wavelength λ4 may be greater than the lower limit wavelength λ3.

[0145] As shown with respect to the first parameter 301, the lower limit wavelength λ1 may correspond to the absorption parameter μ1, and the upper limit wavelength λ2 may correspond to the absorption parameter μ2. As shown with respect to the second parameter 302, the lower limit wavelength λ3 may correspond to the absorption parameter μ3, and the upper limit wavelength λ4 may correspond to the absorption parameter μ4. The absorption parameter may indicate the amount of radiation absorbed by the medium at that wavelength when the radiation passes through the medium. For example, the absorption parameter μ1 may indicate the amount of light having a wavelength of λ1 absorbed by the tissue. The absorption parameter may correspond to the intensity of the radiation detected by a detector such as a light sensor, a photodiode, etc. For example, a high absorption parameter may correspond to a small light intensity detected by the detector, which may indicate that much of the light at that wavelength was absorbed when passing through the medium. As another example, a small absorption parameter may correspond to a large light intensity detected by the detector, which may indicate that a small amount of light at that wavelength was absorbed when passing through the medium. The absorption parameter and / or intensity of the detected radiation may correspond to the brightness of the detected light. The absorption parameter μ1 may be greater than the absorption parameter μ2. The absorption parameter μ4 may be greater than the absorption parameter μ3.

[0146] The absorption parameter μ1 may correspond to the absorption of radiation by hemoglobin such as oxygenated hemoglobin. The absorption by hemoglobin such as oxygenated hemoglobin may account for a major part of the absorption parameter μ1. Water may not affect or may have only a minimal effect on the absorption parameter μ1. The absorption parameter μ2 may correspond to the absorption of radiation by hemoglobin such as oxygenated hemoglobin. The absorption by hemoglobin such as oxygenated hemoglobin may account for a major part of the absorption parameter μ2. Water may not affect or may have only a minimal effect on the absorption parameter μ2. The absorption parameter μ3 may correspond to the absorption of radiation by water. The absorption parameter μ3 may correspond to the absorption of radiation by non-water tissue components such as hemoglobin. Most of the absorption parameter μ3 may correspond to the absorption of radiation by water. As shown in the figure, the absorption parameter μ3 may not exactly correspond to the water curve 333. For example, the absorption parameter μ3 may be greater than the water curve 333 because at least both water and non-water tissue components such as deoxygenated hemoglobin or oxygenated hemoglobin absorb radiation at the lower limit wavelength λ3. The absorption parameter μ4 may correspond to the absorption of radiation by water. The absorption parameter μ4 may correspond to the absorption of radiation by non-water tissue components such as deoxygenated hemoglobin or oxygenated hemoglobin. Most of the absorption parameter μ4 may correspond to the absorption of radiation by water. As shown in the figure, the absorption parameter μ4 may not exactly correspond to the water curve 333. For example, the absorption parameter μ4 may be greater than the water curve 333 because at least both water and non-water tissue components such as deoxygenated hemoglobin or oxygenated hemoglobin absorb radiation at the upper limit wavelength λ4.

[0147] The absorption parameter μ3 can provide an indicator of the amount of water in the subject's tissue. The absorption parameter μ4 can provide an indicator of the amount of water in the subject's tissue. The estimation of water replenishment based only on the absorption parameter μ3 and / or the absorption parameter μ4 may not accurately correspond to the subject's water replenishment because the absorption parameter μ3 and / or the absorption parameter μ4 may be affected by non-aqueous tissue components. A system or method as described herein can improve the estimation of water replenishment by taking into account absorption by non-aqueous components, such as by combining with the absorption parameter μ3 and / or the absorption parameter μ4, or by considering the absorption parameter μ1 and / or the absorption parameter μ2. Variations in the subject's hemoglobin levels, such as SpO2 levels, may have little or no effect on the estimation of water replenishment. In some implementations, when the subject's SpO2 is less than 95%, the second parameter 302 can be normalized by projecting its lower and upper absorbances to their respective values if the subject's SpO2 was 95% or greater.

[0148] The hardware processor can estimate the subject's water replenishment level, which may sometimes be referred to as a water replenishment index. The water replenishment index can be based on the amount of water in the subject's tissue. The hardware processor can determine the amount of water in the subject's tissue. The processor can be any of the exemplary processors illustrated and / or described herein, such as the hardware processor 201. The processor can be implemented in a wearable device. The processor can be remote from the wearable device.

[0149] The hardware processor can estimate the hydration index alone or in combination with 301 of the first parameter based on the second parameter 302. The second parameter 302 can include the area of the second parameter 302, the lower wavelength λ3, the upper wavelength λ4, the absorption parameter μ3 (which may correspond to the light intensity detected by the detector), and / or the absorption parameter μ4 (which may correspond to the light intensity detected by the detector). The first parameter 301 can include the area of the first parameter 301, the lower wavelength λ1, the upper wavelength λ2, the absorption parameter μ1 (which may correspond to the light intensity detected by the detector), and / or the absorption parameter μ2 (which may correspond to the light intensity detected by the detector).

[0150] The hardware processor may take into account the absorption by non-aqueous tissue components within the second parameter 302, such as by normalizing the second parameter 302 with the first parameter 301. The hardware processor may take into account the absorption by non-aqueous tissue components within the second parameter 302, such as by subtracting the first parameter 301 or a part thereof from the second parameter 302 or a part thereof. The hardware processor may take into account fluctuations in the sensitivity of the detector. The sensitivity of a detector such as a photodiode may vary depending on the wavelength of the radiation being detected. For example, the detector may be less sensitive to the detection of radiation at a wavelength of μ4 or around it, and may be more sensitive to the detection of radiation at a wavelength of μ3 or around it. The hardware processor can adjust the output received from the detector based on the wavelength in order to correct the wavelength-based detector sensitivity. For example, the hardware processor may amplify the magnitude of the detector signal corresponding to those wavelengths in order to account for the reduced ability of the detector to detect wavelengths with low sensitivity. As another example, the hardware processor may reduce or not change the magnitude of the detector signal corresponding to wavelengths at which the detector has high or average sensitivity. In one exemplary implementation, the hardware processor may amplify the detector signal corresponding to a wavelength of μ4 or around it, and may reduce or not change the detector signal corresponding to wavelengths at μ3 or around it. Tests during manufacturing can be used to determine when and at what level compensation may be required. The compensation level can be stored in the memory incorporated in each individual device or sensor.

[0151] The hardware processor can estimate the area of the first parameter 301. The area of the first parameter 301 can approximately correspond to the area bounded by the lower wavelength λ1, the upper wavelength λ2, and the oxyhemoglobin curve 341. The hardware processor can estimate the area of the second parameter 302. The area of the second parameter 302 can approximately correspond to the area bounded by the lower wavelength λ3, the upper wavelength λ4, and the water curve 333. In some implementations, the hardware processor can determine the area of the first parameter 301 according to Equation (3) as follows.

Number

[0152] In some implementations, the hardware processor can determine the area of the second parameter 302 according to Equation (4) as follows.

Number

[0153] The hardware processor can estimate a part of the area of the first parameter 301. The area of a part of the first parameter 301 may be smaller than the area bounded by the lower wavelength λ1, the upper wavelength λ2, and the oxyhemoglobin curve 341. The hardware processor can estimate a part of the area of the second parameter 302. The area of a part of the second parameter 302 may be smaller than the area bounded by the lower wavelength λ3, the upper wavelength λ4, and the water curve 333. In some implementations, the hardware processor can determine a part of the area of the first parameter 301 according to Equation (5) as follows.

Number

[0154] In some implementations, the hardware processor may determine a portion of the area of the second parameter 302 according to Equation (6) as follows.

Number

[0155] The hardware processor can determine the area of the first parameter 301. The hardware processor may determine the area of the first parameter 301 by integrating the oxyhemoglobin curve 341 between the lower wavelength λ1 and the upper wavelength λ2. In some implementations, the processor may determine the absorption of radiation at additional wavelengths within the first parameter 301, such as wavelengths between the lower wavelength λ1 and the upper wavelength λ2. Measuring the absorption at one or more additional wavelengths may improve the accuracy of estimating the area under the absorption curve. In some implementations, the hardware processor may integrate the area under the oxyhemoglobin curve 341 based on the absorption at at least one or more additional wavelengths between the lower wavelength λ1 and the upper wavelength λ2.

[0156] The hardware processor can determine the area of the second parameter 302. The hardware processor may determine the area of the second parameter 302 by integrating the oxyhemoglobin curve 341 between the lower wavelength λ3 and the upper wavelength λ4. In some implementations, the processor may determine the absorption of radiation at additional wavelengths within the second parameter 302, such as wavelengths between the lower wavelength λ3 and the upper wavelength λ4. Measuring the absorption at one or more additional wavelengths may improve the accuracy of estimating the area under the absorption curve. In some implementations, the hardware processor may integrate the area under the water curve 333 based on the absorption at at least one or more additional wavelengths between the lower wavelength λ3 and the upper wavelength λ4.

[0157] The hardware processor can determine the subject's hydration index based only on the area or a part of the area of the second parameter 302, or in combination with the area or a part of the area of the first parameter 301. The hardware processor can determine the hydration index by subtracting the area or a part of the area of the first parameter 301 from the area or a part of the area of the second parameter 302. As an example, the hardware processor can calculate the subject's hydration index by subtracting the area of the first parameter 301 calculated according to Equation (3) from the area of the second parameter 302 calculated according to Equation (4). As another example, the hardware processor can calculate the subject's hydration index by subtracting a part of the area of the first parameter 301 calculated according to Equation (5) from a part of the area of the second parameter 302 calculated according to Equation (6).

[0158] The hardware processor can determine the hydration index by normalizing the area or a part of the area of the second parameter 302 with the area or a part of the area of the first parameter 301. As an example, the hardware processor can calculate the subject's hydration index by dividing the area of the second parameter 302 calculated according to Equation (4) by the area of the first parameter 301 calculated according to Equation (3). As another example, the hardware processor can calculate the subject's hydration index by dividing a part of the area of the second parameter 302 calculated according to Equation (6) by a part of the area of the first parameter 301 calculated according to Equation (5).

[0159] The hardware processor can determine a hydration index based on the intensity of light measured through a medium such as the tissue of a subject. The hardware processor can determine a hydration index based on the intensity of light at a plurality of wavelengths measured through the tissue of the subject. The hardware processor can determine a hydration index based on the ratio of the intensity of light measured through the tissue of the subject to the intensity of light measured through a reference material. The reference material can be air. The hardware processor can determine a hydration index based on the difference in the ratio of the intensity of light.

[0160] The difference in the intensity of light observed through two materials may be proportional to the difference in their respective optical densities. The hardware processor can determine the change or difference in optical density between two materials according to Equation (7) as follows.

Equation

[0161] As discussed herein, I β or I α parameters such as may correlate with the intensity of light measured through a medium. The I parameter may correlate with the attenuation or absorption of radiation by the medium through which the radiation passes. The I parameter may be inversely proportional to the attenuation or absorption of radiation. The I parameter may correlate with the intensity of light detected by a detector. The I parameter may be directly related to the brightness of the light detected by the detector. The I parameter may correspond to a parameter generated by a detector such as a DC value. The I parameter may be normalized by a current. Thus, it may be independent of the current. The I parameter may be normalized by a gain. Thus, the I parameter may be independent of the gain. The I parameter may be independent of the emitter operation, such as being normalized to account for such differences when one LED emits light brighter than another.

[0162] Iβ can be the measured intensity of light through a medium such as a subject's tissue. The hardware processor, for example, determines I at a plurality of different times each time it performs a measurement to determine a subject's hydration level β can be determined. I β changes as the subject's hydration level changes. In some implementations, the processor can adjust I based on a known or determined detector sensitivity based on wavelength. For example, the processor can increase or amplify I if the corresponding wavelength falls within a certain threshold β can be adjusted. For example, the processor can increase or amplify I if the corresponding wavelength falls within a certain threshold β can be increased or amplified. As another example, the processor can reduce or decrease I if the corresponding wavelength falls within a certain threshold β can be reduced or decreased. As another example, the processor may not change I if the corresponding wavelength falls within a certain threshold β

[0163] I α can be the intensity of light measured through a reference material. The reference material can be air. In some implementations, the hardware processor can use the same I each time it performs a measurement to determine a subject's hydration level α may be used. The value of I α may not change. The hardware processor can determine I by accessing data such as data stored in memory. In some implementations, I α can be determined. In some implementations, I α can be the average light intensity measured through a reference material using a plurality of sensors. In some implementations, I α is I β can be the light intensity measured through a reference material using a specific sensor such as the same sensor used to determine I α For example, a wearable device can perform calibration to determine the value of I corresponding to each of the sensors on a particular wearable device. The wearable device can perform I α ​A single calibration can be performed to determine the value of. The wearable device can perform multiple calibrations to determine or update the value of I, for example, periodically or upon request. α In some implementations, the measured intensity can be based on the current divided by the gain.

[0164] The hardware processor can determine the hydration index based on normalizing the water-dependent optical parameter with the water-independent optical parameter. The optical parameter can be based on the light intensity of the detected wavelength. The optical parameter can be based on the absorption of the detected wavelength in the medium. In some implementations, the hardware processor can determine the hydration index of the subject according to Equation (8.1) as follows.

Number

[0165] The water-dependent optical parameter

Number

Number

[0166] The hardware processor can determine a hydration index based on normalizing the normalized water-dependent optical parameters to the normalized water-independent optical parameters. The normalized optical parameters can be based on the detected light intensity at the detected wavelength. The normalized optical parameters can be based on the absorption at the detected wavelength in the medium. In some implementations, the hardware processor can determine the hydration index of a subject according to Equation (8.2) as follows.

Number

[0167] The processor can normalize the optical parameters by normalizing the measured value of the radiation through the tissue material with the measured value of the radiation through the reference material. The normalized water-dependent optical parameters

Number

[0168] can be based on wavelength λ3, or wavelength λ4, or any wavelength in between, which can correspond to wavelength λ3 or λ4 as described with reference to Figure 3. The normalized water-independent optical parameters

Number

[0169] can be based on wavelength λ1, or wavelength λ2, or any wavelength in between, which can correspond to wavelength λ1 or λ2 as described with reference to Figure 3. C can be a constant as described in more detail below.

[0170] The hardware processor can determine the hydration index based on normalizing the difference in water-dependent optical parameters to the difference in water-independent optical parameters. The optical parameters can be based on the light intensity of the detected wavelength. The optical parameters can be based on the absorption of the detected wavelength in the medium. In some implementations, the hardware processor can determine the hydration index of the subject according to Equation (8.3) as follows.

Number

[0171] Water-dependent optical parameter

Number

Number

Number

Number

[0172] can be based on a wavelength λ2 that can correspond to the wavelength λ2 described with reference to FIG. 3. C can be a constant as will be explained in more detail below.

[0173] The hardware processor can determine a hydration index based on normalizing the difference in normalized water-dependent optical parameters to the difference in normalized water-independent optical parameters. The optical parameters can be based on the detected light intensity at the detected wavelength. The optical parameters can be based on the absorption of the detected wavelength in the medium. The hardware processor can determine a hydration index based on the difference in the change in the optical density of a radiation wavelength sensitive to water normalized to the difference in the change in the optical density of a radiation wavelength not sensitive to water. The hardware processor can determine a hydration index based on the change in the difference in the optical density of an infrared radiation wavelength normalized to the difference in the change in the optical density of a red radiation wavelength.

[0174] In some implementations, the hardware processor can determine the hydration index of the subject according to Equation (8.4) as follows.

Number

[0175] Water-dependent optical parameter

Number

Number

Number

Number

[0176] It can be obtained based on a wavelength λ2 that can correspond to the wavelength λ2 described with reference to FIG. 3. C can be a constant as will be described in more detail below.

[0177] For any of equations (8.1) to (8.4), the hydration index (Hi) can be a percentage of the total body water content. The hydration index can be an amount of water. For any of equations (8.1) to (8.4), C can be a specific value for male subjects and a different value for female subjects. C can be based on the subject and may vary from subject to subject or may vary with time for a single subject. C can represent the total body water content of the subject. C can be based on the age, height, and / or weight of the subject. In some implementations, the hardware processor can determine the value of C according to equation (9) or equation (10) as follows. C = 2.447 - (0.09516 * age) + (0.1074 * height) + (0.3362 * weight) (9) C = -2.097 + (0.1069 * height) + (0.2466 * weight) (10)

[0178] Equation 9 may correspond to the C value for males. Equation 10 may correspond to the C value for females. Age can be measured in years. Height can be measured in centimeters. Weight can be measured in kilograms.

[0179] In some implementations, the absorption parameter in any of equations (3) to (6) may correspond to the optical parameter described in any of equations (8.1) to (8.4), and vice versa.

[0180] FIG. 4 is a flowchart illustrating an exemplary process 400 for determining a subject's hydration using an optical sensor. Process 400, or a portion thereof, can be implemented in one or more devices such as a wearable device, a computing device, a physiological sensor, etc. One or more hardware processors can execute program instructions to execute process 400 or a portion thereof. In some implementations, the physiological monitoring system 250 illustrated and / or described herein can execute process 400 or a portion thereof. In some implementations, the hardware processor 201 illustrated and / or described herein can execute process 400 or a portion thereof. Process 400 is provided by way of example and is not intended to limit the present disclosure. In some implementations, a computing device and / or a hardware processor executing process 400 can omit a portion of the process, add additional operations, and / or rearrange the order in which the operations of process 400 are executed.

[0181] The processor can execute process 400 or a portion thereof for individual data points. The processor can execute process 400 or a portion thereof for a plurality of data points. The processor can execute process 400 or a portion thereof for a window of data. The window of data can include data within a time period such as a window of 1 minute, 5 minutes, 10 minutes, 15 minutes, 20 minutes, 30 minutes, 60 minutes, etc. By way of example, the processor can determine a hydration index based on a 15-minute data window in block 409. The processor can update the window of data by taking a new measurement of the data. The processor can update the window of data periodically, such as every 0.5 seconds, 1 second, 2 seconds, 5 seconds, 10 seconds, 60 seconds, etc. By way of example, the processor can cause the sensor to take a new measurement every 1 second.

[0182] In block 401, the processor can cause the light emitter to transmit light radiation to a medium such as the subject's tissue. The light radiation can include light. The light radiation can include radiation of multiple wavelengths. The subject's tissue can include the subject's skin. The subject's tissue can be, by way of non-limiting example, a finger, wrist, ear, nose, ankle, toe of the foot, foot, leg, arm, head, neck. In some implementations, one or more LEDs can emit light radiation. In some implementations, the processor can cause the light emitter to emit radiation periodically. In some implementations, the processor can cause the light emitter to emit radiation in response to conditions, such as in response to a user request.

[0183] In block 403, one or more optical detectors can detect the radiation. The radiation can detect the light radiation emitted from the emitter in block 401. The optical detector can include a photodetector, a photodiode, etc. The radiation detected by the detector in block 403 may have passed through the subject's tissue. Since at least a portion of the radiation may be attenuated or absorbed by the subject's tissue, less than all of the radiation emitted by the emitter can be detected by the detector in block 403.

[0184] In block 405, the processor can determine the intensity of the detected water-independent radiation wavelength. The water-independent wavelength can include the wavelengths of radiation that are minimally absorbed by water. The water-independent wavelength can include one or more wavelengths. In some implementations, the water-independent wavelength can include two wavelengths. The water-independent wavelength can include radiation at less than 700 nm, less than 680 nm, less than 660 nm, less than 640 nm, less than 620 nm, less than 600 nm, etc. The water-independent wavelength can include radiation at 620 nm. The water-independent wavelength can include radiation at 660 nm.

[0185] In block 407, the processor can determine the intensity of the detected water-dependent radiation wavelength. The water-dependent wavelength can include the wavelengths of radiation absorbed by water. The water-dependent wavelength can include one or more wavelengths. In some implementations, the water-dependent wavelength can include two wavelengths. The water-dependent wavelength can include radiation with a wavelength greater than 700 nm. The water-dependent wavelength can include radiation at less than 1400 nm, less than 1200 nm, less than 1000 nm, etc. The water-dependent wavelength can include radiation at less than 990 nm, less than 970 nm, less than 950 nm, less than 930 nm, less than 910 nm, less than 900 nm, etc. The water-dependent wavelength can include radiation at 970 nm. The water-dependent wavelength can include radiation at 905 nm.

[0186] The intensity of the detected wavelengths may correspond to the absorption of those wavelengths by the medium. For example, a high intensity of detected radiation at a particular wavelength may correspond to low absorption of radiation at that wavelength. As another example, a low intensity of detected radiation at a particular wavelength may correspond to high absorption of radiation at that wavelength. Determining the intensity can include determining the absorption, and vice versa.

[0187] In block 409, the processor can determine a hydration index. The processor can determine the hydration index based on the detected radiation intensity determined in block 405 and / or block 407. The processor can determine the hydration index based on the absorption determined in block 405 and / or block 407. The hydration index may indicate the amount or percentage of water in the subject's body. The processor can determine the hydration index according to any of the exemplary equations described herein. The processor can determine the hydration index based on equation (3) and / or equation (4). For example, the processor can subtract the area of the water-independent parameter from the area of the water-dependent parameter. As another example, the processor can normalize the area of the water-dependent parameter by the area of the water-independent parameter. The processor can determine the hydration index based on equation (5) and / or equation (6). For example, the processor can subtract a portion of the area of the water-independent parameter from a portion of the area of the water-dependent parameter. As another example, the processor can normalize a portion of the area of the water-dependent parameter by a portion of the area of the water-independent parameter. The processor can determine the hydration index based on equation (7) and / or any of equations (8.1)-(8.4). For example, a hardware processor can determine the hydration index based on the difference in the normalized detection intensity.

[0188] The processor can execute block 409 for individual measurements of data. The processor can execute block 409 for multiple data measurements. The processor can execute block 409 for multiple data measurements within a time window such as a 15-window. The hydration index can be based on multiple measurements. The hydration index can be based on the trend, average, and / or weighted average of multiple measurements.

[0189] In block 411, the processor can optionally determine the subject's baseline hydration. Baseline hydration may also be referred to as reference hydration. The processor may determine the baseline hydration based on accessing information from memory, such as a previously determined baseline hydration. The processor may determine the baseline hydration based on a single measurement. For example, the processor can determine the baseline hydration based on a measurement taken when the subject first uses the system for optical hydration measurement. As an illustrative example, the system can take measurements within the first 24 hours that the subject uses the system and generate a baseline. As another example, the processor can determine the baseline hydration based on measurements taken at a specific time. As an illustrative example, the processor can determine the subject's baseline hydration based on measurements taken at 12:00 AM, 1:00 AM, 2:00 AM, 3:00 AM, 4:00 AM, 5:00 AM, 6:00 AM, 8:00 AM, 9:00 AM, 10:00 AM, 11:00 AM, 12:00 PM, 1:00 PM, 2:00 PM, 3:00 PM, 4:00 PM, 5:00 PM, 6:00 PM, 7:00 PM, 8:00 PM, 9:00 PM, 10:00 PM, 11:00 PM, or other times between these times may be appropriate times for measurements used in calculating the user's baseline hydration. In some implementations, the processor can calculate the baseline hydration when the hydration measurements are substantially constant. In some implementations, the processor can calculate the baseline hydration based on information from other sensors. For example, the processor can determine the baseline hydration when information from motion sensors, such as inertial sensors, accelerometers, and / or gyroscopes, indicates that the motion is substantially constant or has a minimum or zero acceleration.

[0190] In some implementations, the processor can determine the baseline hydration once. In some implementations, the processor can determine or update the baseline hydration periodically, such as once a day.

[0191] In some implementations, the processor can determine a baseline hydration for a subject based on multiple measurements. The multiple measurements can be at set intervals within a time period. The time period can be within minutes, within hours, within days, or within weeks. As an illustrative example, the processor can use a series of measurements taken hourly over the span of a day to generate a baseline hydration. As another illustrative example, the processor can use a series of measurements taken every few hours over the course of a week to generate a baseline hydration. Other measurement frequencies and periods can also be appropriate.

[0192] The processor can determine a subject's baseline hydration based on averaging the multiple measurements. In some implementations, the average can be a weighted average. In some implementations, the weights for the weighted average can be based on a confidence score associated with the measurement. In some implementations, the weights for the weighted average can be based on factors related to the measurement, such as measurement time, the subject's activity level during the measurement, information from other sensors such as movement data from an inertial sensor, and the rate of change of hydration during the measurement. The processor can determine a subject's baseline hydration based on the mean of the multiple measurements. The processor can determine a subject's baseline hydration based on the median of the multiple measurements. The processor can determine a subject's baseline hydration based on the standard deviation of the multiple measurements. The processor can determine a subject's baseline hydration based on the trend of the multiple measurements. The processor can determine a subject's baseline hydration based on multiple previously determined hydration baselines, such as the mean, median, or average of past hydration baselines.

[0193] In some implementations, the processor can determine a baseline hydration for a subject in response to a user request. For example, the user may request to determine the baseline hydration before starting physical activity. In some implementations, the processor can determine a baseline hydration for a subject in response to one or more conditions.

[0194] In some implementations, the processor can determine the baseline hydration based on a dataset of hydration information. The dataset can be publicly available. The processor can access the dataset. The dataset can be stored in memory. The dataset can include hydration data from multiple subjects. The dataset can include hydration data from a single subject such as the user.

[0195] The processor can update a hydration index based on the hydration baseline. The processor can determine or update the hydration index as a function of the baseline hydration. The processor can determine or update the hydration index by normalizing the hydration index to the baseline hydration. The processor can determine the hydration index as a percentage of the baseline hydration. As an example, if the processor determines that the value of the hydration index determined in block 409 is 94% of the baseline hydration, the processor can determine that the hydration index is 0.94, or 94%, or 94.

[0196] In block 413, the processor can optionally determine the subject's hydration index or the trend of the hydration state. The processor can access the past hydration index based on previous measurements. The processor can compare the past hydration index with the current or most recent hydration index. The processor can determine the trend of the hydration index. The processor can predict the future hydration index. The processor can predict the future hydration index based on the trend of the past hydration index. The processor can monitor the trend of the hydration index.

[0197] In block 414, the processor can determine a hydration protocol. The hydration protocol can be based on one or more of the hydration index, baseline hydration, and / or hydration trend. The hydration protocol can be based on information from other sensors such as motion data from an inertial sensor. The hydration protocol can be based on user input such as an indication of when and how the subject exercises. The hydration protocol can include one or more recommendations for the subject. The hydration protocol can indicate the amount of water or fluid consumed by the subject. The hydration protocol can indicate the time at which the subject consumes the fluid. The hydration protocol can facilitate the subject in maintaining or achieving an optimal hydration level for a particular activity such as exercise. The hydration protocol can indicate the estimated time until a threshold is exceeded, such as when the hydration index exceeds a threshold or falls below a threshold. The hydration protocol can indicate the estimated time until the subject becomes dehydrated. The hydration protocol can indicate the estimated time until the subject is rehydrated or properly hydrated.

[0198] In block 415, the processor can optionally generate one or more alerts. The processor can generate an alert based on one or more of a hydration index, a baseline hydration, a hydration trend, and / or a hydration protocol. In some implementations, the alert can be based on other information such as time, the subject's activity, etc. The alert can indicate to the subject information related to the subject's hydration status. The alert can indicate that the subject's hydration index is below a threshold. The alert can indicate that the subject's hydration index is below the baseline hydration. The alert can indicate that a plurality of hydration indices are below a threshold, such as being below the baseline hydration. The alert can indicate that the subject's predicted future hydration status is below a threshold, such as being below the baseline hydration. The alert can indicate a hydration protocol. The alert can indicate a recommended amount of water for the subject to consume. The alert can indicate a recommended time for the subject to consume water. The alert can indicate that a hydration measurement is being performed. The alert can indicate that a hydration baseline measurement is being performed. The alert can indicate an amount of predicted time until the subject's hydration index exceeds a threshold, such as being below the baseline hydration. The alert can indicate a predicted amount of water the subject needs to consume to change the hydration index by a specific amount.

[0199] In block 417, the processor can optionally generate display data for rendering a display on a display interface. The display can include one or more of a hydration index, a past hydration index, a baseline hydration, a hydration trend, and / or an alert. The display interface can include a display on a wearable device. The display interface can be a display remote from the optical sensor used to perform the hydration measurement. The display interface can be the display 211 illustrated and / or described herein.

[0200] FIG. 5 is a block diagram illustrating an exemplary implementation of the determination of water replenishment. One or more hardware processors, such as the hardware processor 201 or any of the other exemplary processors described herein, may perform the operations and / or processes shown and / or described in FIG. 5. The pre-processor 501 can receive one or more signals corresponding to one or more wavelengths of radiation. The pre-processor 501 can receive a signal from a detector in response to the detector detecting radiation that has passed through a medium such as the tissue of a subject. The wavelengths λ1, λ2, λ3, λ4 may correspond to the wavelengths λ1, λ2, λ3, λ4 illustrated and / or described with reference to FIG. 3. The wavelengths λ1, λ2, λ3, λ4 can include any of the exemplary wavelengths discussed with reference to FIG. 3. In some implementations, the pre-processor 501 can receive information related to more than four wavelengths or less than four wavelengths. The pre-processor 501 can filter the received data. The pre-processor 501 can discard some of the received data. The pre-processor 501 can decimate the received data. The pre-processor 501 can normalize the received data. In some implementations, the pre-processor 501 can normalize the data based on reference data, such as by dividing the received data by the reference data. In some implementations, the pre-processor 501 can normalize the data according to equation (7). The pre-processor 501 can output one or more signals indicating the optical density (OD) associated with various wavelengths. The optical density can be based on filtering, decimating, and / or normalizing the data received at the pre-processor 501.

[0201] The water replenishment engine 503 can receive the signal output from the pre-processor 501, including the optical density (OD) associated with various wavelengths. The water replenishment engine 503 can determine the raw water replenishment index based on the signal received from the pre-processor 501. The water replenishment engine 503 can determine the raw water replenishment index based on comparing the signal associated with the water-dependent wavelength and the signal associated with the water-independent wavelength. The water replenishment engine 503 can determine the raw water replenishment index according to any of the exemplary formulas described herein. The water replenishment engine 503 can determine the raw water replenishment index based on Equation (3) and / or Equation (4). For example, the water replenishment engine 503 can subtract the area of one parameter from the area of another parameter. As another example, the water replenishment engine 503 can normalize the area of one parameter by the area of another parameter. The water replenishment engine 503 can determine the raw water replenishment index based on Equation (5) and / or Equation (6). For example, the water replenishment engine 503 can subtract a part of the area of one parameter from a part of the area of another parameter. As another example, the water replenishment engine 503 can normalize a part of the area of one parameter by a part of the area of another parameter. The water replenishment engine 503 can determine the raw water replenishment index based on Equation (7) and / or any of Equations (8.1)-(8.4). For example, the water replenishment engine 503 can determine the raw water replenishment index based on the difference in the normalized optical density.

[0202] The water replenishment engine 503 can determine a raw water replenishment index (Hi) based on adjusting the signal received from the detector. The sensitivity of a detector such as a photodiode may vary depending on the wavelength of the detected radiation. The detector may be more sensitive to radiation of a specific wavelength and less sensitive to radiation of another wavelength. The water replenishment engine 503 can adjust the output of the detector based on the wavelength to account for the wavelength-based detector sensitivity. For example, the water replenishment engine 503 may amplify the detector signal corresponding to a wavelength at which the detector has low sensitivity. As another example, the water replenishment engine 503 may not change the detector signal corresponding to a wavelength at which the detector has average sensitivity.

[0203] The water replenishment engine 503 can determine the raw water replenishment index based on reference water replenishment information, sometimes referred to as baseline water replenishment. The water replenishment engine 503 can further improve the raw water replenishment index by comparing the raw water replenishment index with the reference water replenishment information. The reference water replenishment information can include a plurality of water replenishment information. The reference water replenishment information can be derived from or associated with a subject. The raw Hi can be a percentage of the reference water replenishment or proportional to the reference water replenishment. The water replenishment engine 503 can index the raw Hi to the reference water replenishment information to further improve the raw Hi. The water replenishment engine 503 can determine the raw Hi based on a transfer function. The transfer function can be based on the reference water replenishment information.

[0204] The water replenishment engine 503 can perform measurements periodically and / or determine the raw water replenishment index. The water replenishment engine 503 can perform measurements at a specific time and / or determine the raw water replenishment index. The water replenishment engine 503 can perform measurements and / or determine the raw water replenishment index in response to a user request. The water replenishment engine 503 can output the raw water replenishment index.

[0205] In some implementations, the water replenishment engine 503 may implement one or more mathematical models to determine the raw Hi. The water replenishment engine 503 may use artificial intelligence to train the mathematical model. The water replenishment engine 503 may use one or more of machine learning, neural networks, deep learning, transformation functions, etc. to train the mathematical model.

[0206] The post-processor 505 can receive the raw Hi from the water replenishment engine 503. The post-processor can further refine the raw Hi to determine the final water replenishment index (Hi). The post-processor 505 can process the data received from the water replenishment engine 503, such as a plurality of raw water replenishment indices, to determine the final Hi. The post-processor 505 can average, filter, discard, and / or clean the data received from the water replenishment engine 503 to determine the final Hi. The post-processor 505 can determine the mean, median, average value, weighted average of the data received from the water replenishment engine 503. By way of example, the final Hi can be the mean, or weighted average, of the raw water replenishment indices.

[0207] The post-processor 505 can determine the final Hi from the raw Hi, based at least on calibration data. The post-processor 505 can compare the data received from the water replenishment engine 503 with the calibration data. The calibration data can include a transfer function. The post-processor 505 can apply the transfer function to the raw Hi to determine the final Hi. The calibration data can include a calibration curve. The post-processor 505 can apply the calibration curve to the raw Hi to determine the final Hi. The calibration data can include weights. The post-processor 505 can apply the weights to the raw Hi to determine the final Hi. The calibration data can include an empirical data set. The empirical data set can include water replenishment information of a plurality of subjects. The empirical data set can include water replenishment data from a plurality of subjects under controlled conditions such that the information corresponds to known water replenishment levels. The empirical data set can include water replenishment data from a single subject such as a user. The post-processor 505 can access the calibration data. The calibration data can be stored in a memory. The post-processor 505 can access the calibration data from a remote computing device such as a remote server.

[0208] Figures 6A and 6B show exemplary displays 600A and 600B. The displays 600A and 600B can include various physiological parameters of a subject. The displays 600A and 600B can include water replenishment information such as water replenishment indices (Hi) 602A and 602B. The water replenishment index 602A can indicate that the subject is relatively well hydrated. The water replenishment index 602B can indicate that the subject is in a relatively dehydrated state. The display 600A or 600B and / or the water replenishment index 602A or 602B can change color based on the subject's hydration. For example, if the user is in a dehydrated state, the number of the water replenishment index 602B can be displayed in red, and if the user is hydrated, the number of the water replenishment index 602A can be displayed in white.

[0209] Term As used herein, the terms "real-time" or "substantially real-time" may refer to events (e.g., reception, processing, transmission, display, etc.) that occur simultaneously or substantially simultaneously (e.g., ignoring any small delays such as delays that are imperceptible and / or insignificant to a human, such as those resulting from electrical conduction or transmission). By way of non-limiting example, "real-time" may refer to events that occur within a time frame of milliseconds, seconds, tens of seconds, or minutes of each other. In some implementations, "real-time" may refer to an event that occurs at the same time as, or during, another event.

[0210] As used herein, the terms "system", "apparatus", "device", and "equipment" generally include both hardware (e.g., mechanical and electronic) and, in some implementations, associated software (e.g., a dedicated computer program for graphics control) components.

[0211] It should be understood that not all objectives or advantages may necessarily be achieved in accordance with any particular implementation described herein. Thus, for example, one of ordinary skill in the art will recognize that a particular implementation may be configured to operate in a manner that achieves or optimizes one advantage or group of advantages taught herein without necessarily achieving other objectives or advantages that may be taught or suggested herein.

[0212] Each of the processes, methods, and algorithms described in the previous section may be embodied in code modules executed by one or more computer systems or computer processors including computer hardware, and may be fully or partially automated by such code modules. The code modules may be stored in any type of non-transitory computer-readable medium or computer storage device, such as a hard drive, solid-state memory, optical disk, etc. The systems and modules may also be transmitted on various computer-readable transmission media, including wireless-based and wired / cable-based media, as generated data signals (e.g., as part of a carrier wave or other analog or digital propagated signal), and may take various forms (e.g., as part of a single or multiplexed analog signal, or as multiple discrete digital packets or frames). The processes and algorithms may be implemented partially or fully in application-specific circuitry. The results of the disclosed processes and process steps may be stored persistently or otherwise in any type of non-transitory computer storage, such as volatile or non-volatile storage.

[0213] Many other variations besides those described herein will be apparent from this disclosure. For example, depending on the implementation, any particular activity, event, or function of any of the algorithms described herein may be performed in a different order, may be added, integrated, or completely omitted (e.g., not all activities or events described are necessary for the implementation of the algorithm). Further, in certain implementations, actions or events may be performed concurrently rather than sequentially, via, for example, multithreaded processing, interrupt processing, or via multiple processors or processor cores, or in other parallel architectures. Additionally, various tasks or processes may be performed by various machines and / or computing systems that can function together.

[0214] The various illustrative logical blocks, modules, and algorithm elements described in connection with the implementations disclosed herein can be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, and elements are described generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. The described functionality can be implemented in various ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

[0215] The various features and processes described herein can be used independently of each other or can be combined in various ways. All possible combinations and sub-combinations are intended to fall within the scope of the present disclosure. In addition, in some implementations, certain methods or process blocks may be omitted. The methods and processes described herein are also not limited to any particular order, and the associated blocks or states can be executed in other suitable orders. For example, the described blocks or states can be executed in orders other than those specifically disclosed, or multiple blocks or states can be combined into a single block or state. The illustrative blocks or states can be executed in series, in parallel, or in some other manner. Blocks or states can be added to or removed from the disclosed illustrative implementations. The illustrative systems and components described herein can be configured differently from those described. For example, elements can be added, removed, or rearranged compared to the disclosed illustrative implementations.

[0216] The various illustrative logical blocks and modules described in connection with the implementations disclosed herein can be implemented or executed by a general-purpose processor, a digital signal processor ("DSP"), an application specific integrated circuit ("ASIC"), a field programmable gate array ("FPGA") or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine, combinations thereof, etc. The processor may include an electrical circuit configured to process computer-executable instructions. In another implementation, the processor may include an FPGA or other programmable device that performs logical operations without processing computer-executable instructions. The processor may also be implemented as a combination of computing devices, such as, for example, a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in combination with a DSP core, or any other such configuration. Although this disclosure primarily describes digital technologies, the processor may include primarily analog components in some cases. For example, some or all of the signal processing algorithms described herein may be implemented in an analog circuit, or in a mixed analog and digital circuit. The computing environment may include any type of computer system including, but not limited to, a computer system based on a microprocessor, mainframe computer, digital signal processor, portable computing device, device controller, or computational engine within an electrical appliance.

[0217] The elements of a method, process, or algorithm described in connection with the implementations disclosed in this specification can be embodied directly in hardware, in software modules stored in one or more memory devices and executed by one or more processors, or in a combination of the two. A software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of non-transitory computer-readable storage medium, medium, or physical computer storage known in the art. An exemplary storage medium can be coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium can be integral to the processor. The storage medium can be either volatile or non-volatile. The processor and the storage medium can reside in an ASIC. The ASIC can reside in a user terminal. In the alternative, the processor and the storage medium can reside as discrete components within the user terminal.

[0218] In particular, conditional language such as "can," "could," "might," or "may," unless specifically stated otherwise, or otherwise understood within the context in which it is used, is generally intended to convey that certain implementations include, while other implementations do not include, a particular feature, element, and / or step. Thus, such conditional language is generally not intended to imply that a feature, element, and / or step is in any way required for one or more implementations or that one or more implementations necessarily include logic for determining, with or without user input or prompting, whether such a feature, element, and / or step should be present or should be performed in any particular implementation.

[0219] Disjunctive language such as the phrase "at least one of X, Y, or Z" is generally understood in the context in which it is used, unless otherwise specified, to indicate that items, terms, etc. may be any one of X, Y, or Z, or any combination thereof (e.g., X, Y, and / or Z). Thus, such disjunctive language is generally not intended to, and should not, imply that a particular implementation requires each of at least one of X, at least one of Y, or at least one of Z to be present.

[0220] Language such as the terms "substantially", "about", "generally", "essentially", etc. as used herein refers to values, amounts, or characteristics that are close to the recited values, amounts, or characteristics that still perform the desired function or achieve the desired result. For example, the terms "substantially", "about", "generally", and "essentially" may refer to amounts within a range of less than 10%, less than 5%, less than 1%, less than 0.1%, and less than 0.01% of the recited amount. As another example, in certain implementations, the terms "substantially parallel" and "essentially parallel" refer to values, amounts, or characteristics that deviate from exact parallel by 10 degrees or less, 5 degrees or less, 3 degrees or less, or 1 degree or less. As another example, in certain implementations, the terms "substantially perpendicular" and "essentially perpendicular" refer to values, amounts, or characteristics that deviate from exact perpendicular by 10 degrees or less, 5 degrees or less, 3 degrees or less, or 1 degree or less.

[0221] Any description, element, or block in a flowchart described herein and / or depicted in the accompanying figures should be understood to potentially represent a module, segment, or portion of code that includes one or more executable instructions for implementing a particular logical function or step within a process. Alternative implementations are included within the scope of the implementations described herein, and in alternative implementations, elements or functions may be deleted, executed in an order different from the order illustrated or discussed, including in a substantially simultaneous or reverse order, depending on the relevant functions, as would be understood by one of ordinary skill in the art.

[0222] Unless otherwise expressly stated, articles such as "a" or "an" are generally to be construed as including one or more of the recited items. Thus, phrases such as "a device configured to" are intended to include one or more of the recited devices. Such one or more recited devices can also be collectively configured to perform the recited listing. For example, "a processor configured to perform the listing of A, B, and C" can include a first processor configured to perform the listing of A in cooperation with a second processor configured to perform the listing of B and C.

[0223] All of the methods and processes described herein can be embodied in software code modules executed by one or more general purpose computers and can be partially or fully automated by such software code modules. For example, the methods described herein can be executed by a computing system and / or any other suitable computing device. The methods can be executed on a computing device in response to the execution of software instructions or other executable code read from a tangible computer-readable medium. A tangible computer-readable medium is a data storage device capable of storing data readable by a computer system. Examples of computer-readable media include read-only memory, random access memory, other volatile or non-volatile memory devices, CD-ROMs, magnetic tapes, flash drives, and optical data storage devices.

[0224] Numerous variations or modifications may be made to the embodiments described herein, and it should be emphasized that the elements thereof should be understood to be among other acceptable examples. All such modifications and variations are intended to be included within the scope of the present disclosure. The section headings used herein are provided solely for readability enhancement and are not intended to limit the scope of the embodiments disclosed in a particular section to the features or elements disclosed in that section. The foregoing description has detailed particular embodiments. However, it will be understood that the system and method can be practiced in many ways, however detailed the foregoing may be in text. As also stated herein, the use of particular terms when describing specific features or aspects of the system and method should not be construed as redefining the term to mean so as to be limited to any particular properties of the features or aspects of the system and method to which the term relates.

[0225] Those skilled in the art will understand that information, messages, and signals can be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips, which may be referred to throughout the above description, may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

Description of Reference Numerals

[0226] 100 Wearable device 102 Strap 104 Emitter 106 Detector 120 Wearable device 121 User 122 Ear 140 Wearable device 160 Wearable device 162 Foot 170 Wearable device 172 nose 180 wearable device 190 wearable device 191 control unit 193 sensor unit 195 cable 201 hardware processor 203 memory device 205 communication module 207 power supply 209 light emitter 211 display 213 optical detector 215 sensor 250 physiological monitoring system 300 figure 301 first parameter 302 second parameter 333 water curve 333A curve 333B curve 333C curve 341 oxygenated hemoglobin curve 343 deoxygenated hemoglobin curve 501 preprocessor 503 water replenishment engine 505 postprocessor 600A display 600B display 602A water replenishment index (Hi), water replenishment index 602B water replenishment index (Hi), water replenishment index

Claims

1. A physiological monitoring system for non-invasively monitoring a subject's hydration in real time using an optical sensor, wherein the physiological monitoring system is One or more photoemitters configured to emit light radiation toward the tissue of the subject, wherein the light radiation comprises a water-dependent wavelength, a second water-dependent wavelength, a water-independent wavelength, and a second water-independent wavelength. One or more optical detectors, To detect the photoradiation emitted by one or more photoemitters after attenuation through the tissue of the subject, To generate optical data in response to the detection of the aforementioned light radiation, One or more optical detectors configured to do so, One or more hardware computer processors, Accessing the aforementioned optical data, Based on the optical data corresponding to the water-dependent wavelength, water-dependent optical parameters are determined. Based on the optical data corresponding to the second water-dependent wavelength, a second water-dependent optical parameter is determined, Based on the optical data corresponding to the water-independent wavelength, water-independent optical parameters are determined. Based on the optical data corresponding to the second water-independent wavelength, a second water-independent optical parameter is determined, The hydration index of the subject is determined based on the water-dependent optical parameter, the second water-dependent optical parameter, the water-independent optical parameter, and the second water-independent optical parameter. One or more hardware computer processors configured to do so, A physiological monitoring system equipped with [the following features].

2. The physiological monitoring system according to claim 1, wherein the water-dependent optical parameter corresponds to the light intensity of the water-dependent wavelength of the light radiation detected by the one or more optical detectors, and the water-independent optical parameter corresponds to the light intensity of the water-independent wavelength of the light radiation detected by the one or more optical detectors.

3. The physiological monitoring system according to claim 1, wherein the water-dependent optical parameter corresponds to the absorption of the light radiation at the water-dependent wavelength by the tissue, and the water-independent optical parameter corresponds to the absorption of the light radiation at the water-independent wavelength by the tissue.

4. The physiological monitoring system according to claim 1, wherein the water-dependent wavelength of the light radiation is sensitive to absorption by water, and the absorption of the water-independent wavelength of the light radiation is substantially unaffected by water.

5. The physiological monitoring system according to claim 1, wherein the water-dependent wavelength of the light radiation is greater than 700 nm.

6. The physiological monitoring system according to claim 1, wherein the water-independent wavelength of the light radiation is less than 700 nm.

7. The one or more hardware computer processors Accessing reference optical data corresponding to other radiation attenuated through a reference medium, wherein the other radiation includes the water-dependent wavelength and the water-independent wavelength. The water-independent optical parameters are determined based on normalizing the optical data corresponding to the water-dependent wavelength with the reference optical data corresponding to the water-dependent wavelength. The water-independent optical parameters are determined based on normalizing the optical data corresponding to the water-independent wavelength with the reference optical data corresponding to the water-independent wavelength, The physiological monitoring system according to claim 1, further configured to perform the following:

8. The physiological monitoring system according to claim 7, wherein the optical data corresponds to the optical density of the tissue, and the reference optical data corresponds to the optical density of the reference medium.

9. The physiological monitoring system according to claim 1, wherein the water-dependent wavelength of the light radiation is 905 nm to 1400 nm, and the second water-dependent wavelength of the light radiation is 800 nm to 970 nm.

10. The physiological monitoring system according to claim 1, wherein the water-dependent wavelength of the light radiation is 905 nm to 1400 nm, and the second water-dependent wavelength of the light radiation is 900 nm to 1000 nm.

11. The physiological monitoring system according to claim 1, wherein the water-independent wavelength of the light radiation is 600 nm to 700 nm, and the second water-independent wavelength of the light radiation is 600 nm to 700 nm.

12. The physiological monitoring system according to claim 1, wherein the water-dependent optical parameter corresponds to the estimated area integrated under the absorption curve between the water-dependent wavelength and the second water-dependent wavelength.

13. The physiological monitoring system according to claim 1, wherein the water-independent optical parameter corresponds to the estimated area integrated under the absorption curve between the water-independent wavelength and the second water-independent wavelength.

14. The one or more hardware computer processors Accessing reference optical data corresponding to other radiation attenuated through a reference medium, wherein the other radiation includes the water-dependent wavelength, the second water-dependent wavelength, the water-independent wavelength, and the second water-independent wavelength. The water-dependent optical parameters are determined based on normalizing the optical data corresponding to the water-dependent wavelength with the reference optical data corresponding to the water-dependent wavelength, The second water-dependent optical parameter is determined by normalizing the optical data corresponding to the second water-dependent wavelength with the reference optical data corresponding to the second water-dependent wavelength, The water-independent optical parameters are determined based on normalizing the optical data corresponding to the water-independent wavelength with the reference optical data corresponding to the water-independent wavelength, The second water-independent optical parameter is determined by normalizing the optical data corresponding to the second water-independent wavelength with the reference optical data corresponding to the second water-independent wavelength, The physiological monitoring system according to claim 1, further configured to perform the following:

15. The physiological monitoring system according to claim 1, wherein the water-dependent wavelength of the light radiation is 960 nm to 980 nm, the second water-dependent wavelength of the light radiation is 895 nm to 915 nm, the water-independent wavelength of the light radiation is 610 nm to 630 nm, and the second water-independent wavelength of the light radiation is 650 nm to 670 nm.

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