Patent Publication Number: US-2023157572-A1

Title: Continuous Self-Recalibrating System and Method for Monitoring Oxygen Saturation

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     The present application is a Continuation-in-Part of U.S. patent application Ser. No. 17/153,451, titled “Wearable System and Method for Measuring Oxygen Saturation,” filed on Jan. 20, 2021. U.S. patent application Ser. No. 17/153,451 is a Continuation of U.S. patent application Ser. No. 16/132,224, titled “System and Method for Monitoring Respiratory Rate and Oxygen Saturation,” filed on Sep. 14, 2018, now U.S. Pat. No. 10,952,638, issued on Mar. 23, 2021, which is a Continuation-in-Part of U.S. patent application Ser. No. 14/738,666, titled “Monitoring Health Status of People Suffering from Chronic Diseases,” filed on Jun. 12, 2015, now U.S. Pat. No. 11,160,459, issued on Nov. 2, 2021, a Continuation-in-Part of U.S. patent application Ser. No. 14/738,636, titled “Wearable Device Electrocardiogram,” filed on Jun. 12, 2015, a Continuation-in-Part of U.S. patent application Ser. No. 14/738,711, titled “System for Performing Pulse Oximetry,” filed on Jun. 12, 2015, now U.S. Pat. No. 10,470,692, issued on Nov. 12, 2019, and a Continuation-in-Part of U.S. patent application Ser. No. 14/983,118, titled “Using Invariant Factors for Pulse Oximetry,” filed on Dec. 29, 2015, now U.S. Pat. No. 10,687,742, issued on Jun. 23, 2020. U.S. patent application Ser. No. 14/983,118 is a Continuation-in-Part of U.S. patent application Ser. No. 14/738,666, titled “Monitoring Health Status of People Suffering from Chronic Diseases,” filed on Jun. 12, 2015, now U.S. Pat. No. 11,160,459, issued on Nov. 2, 2021, a Continuation-in-Part of U.S. patent application Ser. No. 14/738,636, titled “Wearable Device Electrocardiogram,” filed on Jun. 12, 2015, and a Continuation-in-Part of U.S. patent application Ser. No. 14/738,711, titled “System for Performing Pulse Oximetry,” filed on Jun. 12, 2015, now U.S. Pat. No. 10,470,692, issued on Nov. 12, 2019. All the disclosures of the aforementioned applications are incorporated herein by reference for all purposes, including all references cited therein. 
    
    
     FIELD 
     The present application relates to systems and methods for monitoring medical parameters of people, and more specifically to systems and methods for monitoring respiratory rate and continuous monitoring oxygen saturation with system self-recalibration. 
     BACKGROUND 
     It should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section. 
     Monitoring chronic diseases, which includes measuring medical parameters, is central to providing appropriate and timely treatment to patients suffering from such chronic diseases as chronic heart failure, cardiac arrhythmia, chronic obstructive pulmonary disease, asthma, and diabetes. Traditionally, monitoring is carried out and measurements are taken while a patient is hospitalized or in other clinical settings. Appropriate treatment regimens can be based on these measurements, and thus it is highly beneficial to monitor medical parameters of the patient after the patient is released from the hospital. Therefore, the patient can be asked to visit the hospital or clinic periodically for monitoring and adjustment of treatment, if necessary. 
     However, most often, no measurements are carried out between visits, usually due to the need for trained examiners and medical devices. This is unfortunate, because, between visits, the chronic disease from which the patient suffers can worsen and result in emergency treatment and hospitalization. Furthermore, after receiving repeated courses of emergency hospital treatment, the patient&#39;s health condition may degrade and never return to the pre-hospitalization level. Therefore, a technology that allows for at-home measurements of medical parameters can be essential to managing chronic diseases or even saving a patient&#39;s life. Early warnings of worsening conditions associated with chronic diseases may prevent unnecessary hospitalizations by providing a preventive treatment and, as a result, reduce financial and human costs of the hospitalization and treatment. 
     SUMMARY 
     This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter. 
     According to one embodiment of the present disclosure, a system for monitoring medical parameters of a patient is provided. The system may include a wearable device configured to be disposed around a wrist of the patient. The wearable device may include a gyroscope configured to provide a gyroscope signal indicative of a motion of the patient. The system may further include a processor communicatively coupled to the gyroscope. The processor can be configured to perform a spectral analysis of the gyroscope signal to obtain a spectrum in a pre-determined range. The pre-determined range can cover a normal respiratory rate range. The processor can be configured to determine a position of a peak in the spectrum to obtain a value for the respiratory rate. The processor can be configured to provide, based on the value of the respiratory rate, a message regarding a health status of the patient. 
     Based on the determination that the value of the respiratory rate is outside the normal respiratory range, the processor can provide an alert message regarding the health status of the patient. The spectral analysis can be performed by a method of averaged periodograms. A normal respiratory rate range may include 6 to 18 breaths per minute. 
     The processor can be configured to determine the strongest amplitude peak in the spectrum to obtain a value for the respiratory rate. The processor can determine that the spectrum includes one or more further peaks with descending amplitudes. The further peaks correspond to frequencies n*ω, wherein ω is a frequency corresponding to the strongest amplitude peak, and n is a natural number. Based on the determination, the processor may assign w to the value of the respiratory rate. 
     The wearable device may further include a first optical sensor configured to measure, at a palmar surface of the wrist, a first red wavelength photoplethysmography (PPG) signal and a first infrared wavelength PPG signal. The wearable device may further include a second optical sensor configured to measure, at a dorsal surface of the wrist, a second red wavelength PPG signal and a second infrared wavelength PPG signal. The first optical sensor and the second optical sensor can be communicatively coupled to the processor. 
     The processor can be configured to determine a continuous monitoring of an oxygen saturation of a patent that includes recalibration of the wearable device. The oxygen monitoring system is based on the first red wavelength PPG signal and the first infrared wavelength PPG signal, a first ratio for obtaining an oxygen saturation. The processor can be further configured to determine, based on the second red wavelength PPG signal and the second infrared wavelength PPG signal, a second ratio for obtaining the oxygen saturation and can include the determining of a perfusion index. The processor can be further configured to determine, based on the first ratio and the second ratio, a third ratio to be used for obtaining an oxygen saturation. The processor can be further configured to determine, based on the third ratio, a value of the oxygen saturation. The processor can be further configured to provide, based on the value of the oxygen saturation, a message regarding a health status of the patient. 
     Based on changes in different measurements, the system can use the signals from the second optical sensor to recalibrate the oxygen level indicated in the first optical sensor. Thus, the recalibration provides the capability to continuously monitor a patent&#39;s oxygen level. Recalibration requires a sufficiently strong signal for recalibration. A sufficient profusion index above 0.4% provides for a sufficiently strong signal. Various changes in the indicated oxygen level based on the first ratio provides for an indication that the system needs recalibration. A change in detected oxygen level based on the first ration will be an indication for recalibration. If the signal strength from the second sensor is insufficient, the system can generate an indication to patient to make a physical change that can improve the perfusion at the second sensor. This can include, but is not limited to, a message to warm themselves, hydrate, rest, or reposition the wearable device. 
     The third ratio can be determined by formula R=α R a +(1−α)R b , wherein the a is a weight between 0 and 1, the R a  is the first ratio, and the R b  is the second ratio. The weight α can be a function of a perfusion index. The perfusion index can be determined based on the second red wavelength PPG signal or the second infrared wavelength PPG signal. The weight α increases when the perfusion index increases. A shape of the function is pre-determined during a calibration process. 
     The first optical sensor can be configured to measure the first red wavelength PPG signal and the first infrared wavelength PPG signal substantially near a radial artery of the wrist. 
     According to another example embodiment of the present disclosure, a method for monitoring medical parameters of a patient is provided. The method may include providing, by a gyroscope integrated into a wearable device configured to be worn around a wrist of a patient, a gyroscope signal indicative of a motion of the patient. The method may further include performing, by the processor communicatively coupled with the gyroscope, a spectral analysis of the gyroscope signal to obtain a spectrum in a pre-determined range. The pre-determined range may cover a normal respiratory rate range. The method may further include determining, by the processor, a position of a peak in the spectrum to obtain a value for a respiratory rate. The method may further include providing, by the processor and based on the value of the respiratory rate, a message regarding a health status of the patient. 
     The method can include measuring at a palmar surface of the wrist of the patient, by a first optical sensor of the wearable device, a first red wavelength PPG signal and a first infrared wavelength PPG signal. The method may include measuring at a dorsal surface of the wrist, by a second optical sensor of the wearable device, a second red wavelength PPG signal and a second infrared wavelength PPG signal. The first optical sensor and the second optical sensor can be communicatively connected to the processor. 
     The method may further include determining, by a processor and based on the first red wavelength PPG signal and the first infrared wavelength PPG signal, a first ratio for obtaining an oxygen saturation. 
     The method may include determining, by the processor and based on the second red wavelength PPG signal and the second infrared wavelength PPG signal, a second ratio to be used for obtaining the oxygen saturation. The method may further include determining, by the processor and based on the first ratio and the second ratio, a third ratio for obtaining an oxygen saturation. The method may further include determining, by the processor and based on the third ratio, a value of the oxygen saturation. The method may further include providing, by the processor based on the value of the oxygen saturation, a message regarding a health status of the patient. 
     According to another example embodiment of the present disclosure, the steps of the method for monitoring medical parameters of a patient can be stored on a non-transitory machine-readable medium comprising instructions, which when implemented by one or more processors perform the recited steps. 
     Other example embodiments of the disclosure and aspects will become apparent from the following description taken in conjunction with the following drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like references indicate similar elements and in which: 
         FIG.  1    is a block diagram showing an example system for monitoring medical parameters of a patient. 
         FIG.  2    is a block diagram showing components of an example device for monitoring medical parameters of a patient. 
         FIG.  3    is a block diagram illustrating example sensors, example medical parameters, and example chronic diseases. 
         FIGS.  4 A and  4 B  are schematic diagrams illustrating an example device for monitoring medical parameters of a patient. 
         FIG.  4 C  is a schematic diagram illustrating an example optical sensor. 
         FIG.  5    is a block diagram showing an example system for monitoring medical parameters of a patient. 
         FIG.  6 A  is a plot of an example PPG signal. 
         FIG.  6 B  shows an example function  600  for determining the weight α based on the value of a perfusion index. 
         FIG.  7    shows plots of a gyroscope signal, spectrum of the gyroscope signal, reference signal, and spectrum of the reference signal. 
         FIG.  8    shows plots of another gyroscope signal, spectrum of another gyroscope signal, another reference gyroscope signal, and spectrum of another reference gyroscope signal. 
         FIG.  9    is a flow chart showing steps of an example method for monitoring a respiratory rate. 
         FIG.  10    is a flow chart diagram illustrating an example method for monitoring respiratory rate of a patient. 
         FIGS.  11 A and  11 B  is a flow chart showing steps of continuous recalibrating of monitoring a patients oxygen levels. 
     
    
    
     DETAILED DESCRIPTION 
     The following detailed description includes references to the accompanying drawings, which form a part of the detailed description. The drawings show illustrations in accordance with exemplary embodiments. These exemplary embodiments, which are also referred to herein as “examples,” are described in enough detail to enable those skilled in the art to practice the present subject matter. The embodiments can be combined, other embodiments can be utilized, or structural, logical and electrical changes can be made without departing from the scope of what is claimed. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope is defined by the appended claims and their equivalents. 
     The present disclosure provides systems and methods for monitoring medical parameters of people suffering from chronic diseases. Embodiments of the present disclosure can allow measuring medical parameters of a patient in a non-intrusive manner while, for example, the patient is at home, at work, outdoors, traveling, and at other stationary or mobile environments. Some example embodiments can provide for a wearable device (e.g., a wristband, a watch, or a bracelet) that includes sensors configured to measure medical parameters such as, for example, oxygen saturation, respiratory rate, and the like. The measurements can be taken during daytime and nighttime for days, weeks, months, and years. The medical parameters can be analyzed to determine trends in the medical parameters and to determine whether the severity of the patient&#39;s chronic disease (e.g., a heart disease, diabetes, lung disease, and so on) worsens or improves. Embodiments of the present technology may facilitate a rapid reaction to provide an appropriate and timely treatment for the patient. The early treatment may allow taking timely preventive measures to avoid worsening of the patient&#39;s condition to the point of requiring an emergency hospitalization and associated expensive medical treatment. 
     Described in further detail, this disclosure includes the continuous monitoring of a patient with the wearable device. Continuous monitoring can include monitoring at periodic intervals, by a set time schedule, using a random time schedule, as fast as processing allows, or according to a physiological or outside trigger. Continuous monitoring requires the ability to self-recalibrate a wearable device where the device used a radial artery or another artery to determine blood oxygen levels. 
     The benefit of using the radial artery in measuring blood oxygen levels is that it provides a strong signal for photoplethysmography. However, because the signal is comprised of both the arterial reflected signal and the reflected signal from surrounding tissues, this signal requires calibration. Calibration can be provided by other photoplethysmography sensors placed on a patient&#39;s skin in a location with a more uniform blood supply, like the top of the wrist or the traditionally used finger. However, these locations typically have lower perfusion and thus the signals coming off these sensors are weaker. This may cause limitations when this sensor can be used for calibration. Specifically, the signal from this sensor used for calibration needs to provide a perfusion index of 0.4% or greater. 
     The perfusion index “PI” is calculated by measurement of the constant amount of light reflected by non-pulsatile blood and other tissue (DC) and the variable amount of light reflected by pulsating arterial inflow (AC) and use of the following equation: PI=(AC/DC)×100%. 
     Indications that recalibration is needed of the data from the radial artery sensor includes a change in the sensor&#39;s reading of the palmar red and infrared signals. The change can be according to a predetermined amount, percentage, or an amount indicative of a potential change in the health status of the patient wearing the device. To verify the accuracy of the oxygen reading from the arterial sensor, a recalibration reading is needed from the dorsal sensor on the other side of the wrist. The recalibration reading is used to optimize the shifting parameters of Eq. 2. Further, changes can be caused by repositioning the wearable device including but not limited to taking it off and putting it back on or moving the wearable device&#39;s position on the patient&#39;s wrist. These changes may cause the need for self-recalibration of the palmar signals to achieve continuous accurate monitoring of blood oxygen levels. 
     Further, the need for recalibration can occur when physiological changes occur. These changes can occur when a patient gets cold and the blood flow to the wrist decreases. Dehydration can also reduce the perfusion index in a person&#39;s arm. 
     Additionally, the invention includes feedback to the user to help with the recalibration process. If the dorsal positioned sensor signal is too low with a low perfusion index, then it can not be used for calibrating the arterial sensor. 
     According to various example embodiments, a method for monitoring medical parameters of a patient can include measuring at a palmar surface of a wrist of the patient, by a first optical sensor of a wearable device configured to be disposed around the wrist of the patient, a first red wavelength PPG signal and a first infrared wavelength PPG signal. The method may include measuring from a dorsal surface of the wrist, by a second optical sensor, a second red wavelength PPG signal and a second infrared wavelength PPG signal. The method may also include determining, by a processor communicatively connected to the first optical sensor and the second optical sensor and based on the first red wavelength PPG signal and the first infrared wavelength PPG signal, a first ratio for obtaining an oxygen saturation. 
     The method may include determining, by the processor and based on the second red wavelength PPG signal and the second infrared wavelength PPG signal, a second ratio to be used to obtain the oxygen saturation. The method may further include determining, by the processor and based on the first ratio and the second ratio, a third ratio to be used to obtain an oxygen saturation. The method may further include determining, by the processor and based on the third ratio, a value of the oxygen saturation. The method may further include providing, by the processor based on the value of the oxygen saturation, a message regarding a health status of the patient. 
     The method may further include providing, by a gyroscope communicatively coupled with the processor and disposed in the wearable device, a gyroscope signal indicative of motion of the patient. The method may further include performing, by the processor, a spectral analysis of the gyroscope signal to obtain a spectrum in a pre-determined range. The pre-determined range may cover a normal respiratory rate range. The method may further include determining, by the processor, a position of a peak in the spectrum to obtain a value for a respiratory rate. The method may further include determining, by the processor, that the value of the respiratory rate is outside of the normal respiratory rate range. If the value of the respiratory rate is outside of the normal respiratory rate range, the method may further include providing, by the processor, an alert message regarding the health status of the patient. 
     Referring now to  FIG.  1   , an example system  100  for monitoring a patient&#39;s health status is shown. The system  100  includes at least a wearable device  110 . The wearable device may include sensors  120 . In some embodiments, the wearable device  110  can be worn by a patient  130 , for example on a wrist, for an extended period of time. The wearable device  110  can be carried out as a watch, a bracelet, a wristband, and the like. 
     The wearable device  110  can be configured to constantly collect, via sensors  120 , sensor data from a patient  130 . In some embodiments, based on the sensor data, a processor of the wearable device  110  can be configured to obtain, based on the sensor data, medical parameters associated with the patient  130 . The medical parameters can be analyzed to obtain changes (trends) in medical parameters over time. Based on the changes, one or more conclusions regarding severity of one or more chronic diseases can be obtained. The processor of the wearable device  110  can be configured to send, via a communication module of the wearable device  110 , messages regarding a current health status to a computing device of the patient, a relative, a caretaker of the patient, or a doctor treating the patient. The message to the patient may include advice to see a doctor and/or take medicine. The processor of the wearable device  110  can display the message on a graphical display system of the wearable device  110 . 
     In some embodiments, the system  100  includes a mobile device  140 . The mobile device  140  can be communicatively coupled to the wearable device  140 . In various embodiments, the mobile device  140  is operable to communicate with the wearable device  110  via a wireless connection such as, for example, Wi-Fi, Bluetooth, Infrared (IR), and the like. The mobile device  140  can include a mobile phone, a smart phone, a phablet, a tablet computer, a notebook, and so forth. The mobile device  140  can be configured to receive the sensor data and medical parameters from the mobile device  110 . In certain embodiments, a processor of the mobile device can be configured to perform analysis of the received sensor data to determine medical parameters. The mobile device  140  can be further configured to provide, via a graphic display system of the mobile device  140 , a report regarding current health status. In various embodiments, the mobile device  140  runs one or more applications that provide, via the graphical display system of the mobile device  140 , charts and graphics concerning medical parameters of the patient. 
     In some embodiments, the mobile device  140  can be configured to determine the severity of a health status resulting from the chronic disease from which the patient suffers. The mobile device can be configured to provide the patient with advice to see a medical professional or to take medicine. An alert message regarding health status of the patient can be sent, by the mobile device  140 , to a computing device of a doctor, relative, or caretaker of the patient. 
     In further embodiments, the system  100  may further include a cloud-based computing resource (also referred to as a computing cloud  150 ). In some embodiments, the cloud-based computing resource includes one or more server farms/clusters comprising a collection of computer servers and is co-located with network switches and/or routers. In certain embodiments, the mobile device  140  and/or wearable device  110  can be communicatively coupled to the computing cloud  150 . The mobile device  140  and/or wearable device  110  can be operable to send the sensor data and medical parameters to the computing cloud  150  for further analysis. The computing cloud  150  can be configured to store historical data concerning patient health status including sensor data and medical parameters collected over days, weeks, months, and years. The computing cloud  150  can be configured to run one or more applications to provide reports regarding health status of the patient. A doctor  170  treating the patient may access the reports, for example via a computing device  160 , using the Internet or a secure network. In some embodiments, the results of the analysis of the medical parameters can be sent back to the mobile device  140  and/or wearable device  110 . 
     The severity of the health status resulting from a chronic disease can be estimated by computing a deviation or divergence from normal medical parameters of one or more medical parameters being measured at the moment. The normal medical parameters can be specific to the patient and can be derived based on historical data concerning the patient&#39;s health status recorded over an extended time period. If the deviation in the medical parameters becomes sufficiently large, the patient can be advised, via a message to the mobile device  140 , to take medicine or contact a doctor. In some situations, when the deviation becomes substantial, an alert message can be sent by the mobile device  140  and/or the wearable device  110  to a computing device of a relative, a doctor, or a caretaker of the patient. 
     It may be desirable for the patient to be assured that the current medical parameters are within an acceptable deviation of the normal medical parameters. For example, when the current medical parameters are normal, the wearable device  110  and/or mobile device  140  can be operable to periodically alert the patient using a pleasant sound. The signal can be provided, for example, every 30 minutes, once every hour, and the like. In certain embodiments, when the medical parameters are within normal values, the mobile device  140  may provide a text message assuring the patient of normal conditions. A haptic feedback component can be used to alert the patient to a health condition, to warn the patient about a specific event concerning treatment of a chronic disease, to remind the patient to take a medicine, if the patient has failed to take the medicine within a pre-determined period of time, and so forth. The wearable device  110  may include a haptic feedback functionality for providing the patient with haptic feedback, for example, a tap-in device, to apply a force or vibration to skin of the patient. In further embodiments, the haptic alert can be provided by the mobile device  140 . The mobile device  140  can vibrate when the mobile device is in a pocket of the patient or when the mobile device  140  is located on a surface (e.g., a table). 
       FIG.  2    is a block diagram illustrating components of wearable device  110 , according to an example embodiment. The example wearable device  110  may include sensors  120 , a communication unit  210 , a processor  220 , memory  230 , and a battery  240 . 
     The communication unit  210  can be configured to communicate with a network such as the Internet, a Wide Area Network (WAN), a Local Area Network (LAN), a cellular network, and so forth, to send a data stream, for example sensor data, medical parameters, and messages concerning the health condition of a patient. 
     The processor  220  can include hardware and/or software, which is operable to execute computer programs stored in memory  230 . The processor  220  can use floating point operations, complex operations, and other operations, including processing and analyzing sensor data. 
     In some embodiments, the battery  240  is operable to provide electrical power for operation of other components of the wearable device  110 . In some embodiments, the battery  240  is a rechargeable battery. In certain embodiments, the battery  240  is recharged using inductive charging technology. 
     The wearable device  110  may include additional or different components to provide a particular operation or functionality. Similarly, in other embodiments, the wearable device  110  includes fewer components that perform similar or equivalent functions to those depicted in  FIG.  2   . For example, the wearable device  110  may further include a graphical display system to provide an alert message and display current values of the medical parameters to the patient. The wearable device  110  may also include a haptic device to alert the patient with vibrations. The wearable device  110  may also include an audio signaling device, for example, a beeper or a speaker, to provide sound alerts to the patient. 
       FIG.  3    is a block diagram showing a list of example sensors  120 , a list of example medical parameters  310 , and a list of example chronic diseases  320 . In various embodiments, the sensors  120  may include optical sensors  222   a  and  222   b , electrical sensors  224 , and motion sensors  226 . The medical parameters  310 , determined based on the sensor data, include, but are not limited to, SpO 2  oxygen saturation, tissue oxygen saturation, cardiac output, vascular resistance, pulse rate, blood pressure, respiration, electrocardiogram (ECG) data, respiratory rate, and motion data. The chronic diseases  320 , the progression of which can be tracked based on changes of the medical parameters, include but are not limited to congestive heart failure (CHF), hypertension, arrhythmia, asthma, chronic obstructive pulmonary disease (COPD), hypoglycemia, sleep apnea, and Parkinson&#39;s disease. 
     The optical sensors  222   a  and  222   b  can be operable to measure medical parameters associated with blood flow in blood vessels using changing absorbance of light at different wavelengths in blood and skin. The data from optical sensors  222   a  and  222   b  can be used to determine multiple medical parameters, including but not limited to: SpO 2  oxygen saturation, cardiac output, vascular resistance, pulse rate, and respiratory rate. Based on the measurements obtained from optical sensors  222   a  and  222   b , abnormal cardiac rhythms (for example, atrial fibrillation, rapid rhythms, and slow rhythms) can be detected. 
     In some embodiments, respiratory rate can be derived from a sinus arrhythmia waveform. The sinus arrhythmia waveform can be obtained based on intervals between subsequent heart beats (RR intervals) measured by the optical sensors  222   a  and  222   b  using the fact that the rhythm of the heart beats is modulated by human breathing. 
     The electrical sensors  224  can be operable to obtain ECG activity data of the patient. The ECG activity data includes a characteristic electrically-derived waveform of a heart activity. The ECG data can include a number of components, whose characteristics (timing, amplitude, width, and so forth), alone or in combination, can provide a picture of cardiac and overall health. The ECG data is typically derived by measurements from one or more sets of leads (groups of electrodes comprising grounded circuits), such that the exact characteristics of the resulting waveforms is a function of the electrical and spatial vectors of the electrode positions relative to the heart. While the details of interpretation of the ECG data are too involved to describe succinctly in this disclosure, consideration of each of the component parameters can indicate health status, physical or psychological stress, or trends of disease conditions. Various cardiovascular parameters can be extracted from the ECG alone (such as a heart rate for example), or in combination with other physiological measurements. 
     According to example embodiments of present disclosure, ECG of the patient can be measured via the electrical sensors  224 . Since measurements are taken from a wrist of the patient, electrodes of the electrical sensors  224  should be located very close to each other on a wearable device. Therefore, the ECG data may contain noise. Averaging of several subsequent intervals of the ECG data between heart beats can be used to cancel out noise in ECG data. To determine intervals between two subsequent heart beats, the PPG signals as measured by optical sensors  222   a  and  222   b  can be used as a reference. In some embodiments, an arrhythmia analysis can be carried out using the ECG data and data concerning cardiac output and pulse rate. 
     In some embodiments, motion sensors  226  include an accelerometer, a gyroscope, and an Inertial Measurement Unit (IMU). The motion data obtained via motion sensors  226  can provide parameters of body movement and tremor. The motion data can allow tracking the progression or remission of a motor disease, Parkinson&#39;s disease, and physical condition of the patient. In some embodiments, the motion data can be analyzed to determine whether the patient is likely to fall. In some embodiments, the motion data can be analyzed in time domain and frequency domain. By tracking amplitudes of movement of the patient it can be determined if the patient&#39;s movements become slower (i.e., the patient becomes sluggish) or the patient is not moving at all. Additionally, according to example embodiments of the present disclosure, the motion data can be analyzed to determine a respiratory rate of the patient. 
       FIG.  4 A  and  FIG.  4 B  are schematic diagrams illustrating an example wearable device  110 . In the examples of  FIG.  4 A  and  FIG.  4 B , the wearable device  110  can be carried out in a shape of an open bangle. The  FIG.  4 A  shows a dorsal side of a patient&#39;s hand  410  and the wearable device  110  placed on the patient&#39;s wrist.  FIG.  4 B  shows a palmar side of the patient&#39;s hand  410  and wearable device  110 . The wearable device  110  can be designed to apply pressure at an area of skin surface covering a radial artery  420 . In comparison to wristbands and straps, an open bangle may be more comfortable to wear by a patient since no pressure is applied to the middle area inside the wrist. 
     The wearable device  110  can include optical sensors  222   a  and  222   b  located on an inner side of the wearable device  110 . When the wearable device  110  is worn on the patient&#39;s hand, the inner side of the wearable device  110  can be in continuous contact with a surface of the skin of the patient&#39;s hand  410 . 
     When the wearable device  110  is disposed around a wrist of patient&#39;s hand  410 , the optical sensor  222   a  is located as close as possible to cover the skin area covering an artery of the wrist, for example the radial artery  420 . When the wearable device  110  is disposed around a wrist of patient&#39;s hand  410 , the optical sensor  222   b  is located on the dorsal side of the wrist. The optical sensors  222   a  and  222   b  can be configured to be in a continuous contact with the skin of the patient  130 . 
     As shown in  FIG.  4 C , the optical sensors  222   a  may include multiple light sensors  440  (photodetectors), to measure the reflected light, and multiple light transmitters  450  (for example, Light Emission Diodes (LEDs)). The number and location of the light sensors  440  and light transmitters  450  can be chosen such that in case of an accidental displacement of the wearable device, at least one of the light sensors is still located sufficiently close to the radial artery. In some embodiments, when measuring the light reflected from the skin and radial artery, a signal from those photoelectric cells that provides the strongest or otherwise determined best output can be selected for further processing in order to obtain medical parameters using methods of pulse (reflectance) oximetry. In certain embodiments, the wearable device  110  can be configured to apply a pre-determined amount of pressure to the wrist each time the user wears the wearable device to allow the same conditions for the reflection of the light from the skin. The optical sensor  222   b  may include elements analogous to the elements of the optical sensor  222   a . The signals measured by optical sensors  222   a  and  222   b  can be used to determine oxygen saturation, heart rate, cardiac output, and other parameters using pulse oximetry methods. 
     Oxygen saturation is the relative proportion (typically expressed as percentage) of oxygen dissolved in blood, as bound to hemoglobin, relative to non-oxygen-bound hemoglobin. Oxygen saturation is important in clinical monitoring of surgical anesthesia, and in monitoring and assessment of various clinical conditions such as COPD and asthma. In healthy individuals, oxygen saturation is over 95%. Direct measurement can be made from arterial blood sample, but drawing blood is an invasive procedure, and, except for a few controlled environments (e.g., during a surgery) cannot be easily performed continuously. Pulse oximetry can yield a quantity called SpO2 (saturation of peripheral oxygen), an accepted estimate of arterial oxygen saturation, derived from optical characteristics of blood using transmission of light through a thin part of a human body (for example, a fingertip or an earlobe (in the most common transmissive application mode)). Reflectance pulse oximetry can be used to estimate SpO2 using other body sites. The reflectance pulse oximetry does not require a thin section of the person&#39;s body and is therefore suited to more universal application such as the feet, forehead, and chest, but it has some serious issues due to the light reflected from non-pulsating tissues. When oxygen saturation cannot be measured directly from arterial blood, an indirect measurement can be performed by tracking tissue oxygen saturation. The measurement of oxygen saturation is commonly used to track progression of heart disease or lung disease. When the heart or lungs are not functioning properly, the saturation of oxygen drops in both arterial blood and tissue around the artery. Therefore, tissue oxygen saturation can be measured by sensing the skin color near the radial artery. For example, if the wearable device  110  moves so that optical sensor  222   a  is not covering the radial artery, measurements of tissue saturation near the radial artery can be used as a backup to provide values for oxygen saturation. 
     The optical sensor  222   a  can be configured to measure an infrared wavelength PPG signal I a   ir  and a red wavelength PPG signal I a   red  near a blood artery of the wrist of the patient (for example, the radial artery  420 ). The infrared wavelength PPG signal can be obtained by emitting, by the light transmitters  450 , an infrared wavelength light and detecting, by the light sensor  440 , intensity of infrared light reflected from the skin and blood vessels of the patient. The red wavelength PPG signal can be obtained by emitting, by the light transmitters  450 , a red wavelength light and detecting, by the light sensor  440 , intensity of red light reflected from the skin and blood vessels of the patient. Similarly, the optical sensor  222   a  can be configured to measure an infrared wavelength PPG signal I b   ir  and a red wavelength PPG signal I b   red  from the palmar side of the wrist of patient. 
     The wearable device  110  can include a gyroscope  430 . The gyroscope  430  can be located at any point within the wearable device  110 . The gyroscope may include a triple axis Micro Electro-Mechanical Systems (MEMS) gyroscope. The gyroscope  430  can measure rotation around three axes: x, y, and z. 
     In some embodiments, a gyroscope signal measured by the gyroscope  430  can be analyzed to determine a respiratory rate of a patient. The respiratory rate, which is a vital sign, is typically expressed as the number of breaths per minute. Typical adult resting respiratory rate is about 16-20 breaths per minute. Extreme variations can result from physical or psychological stress. The respiratory rate is often affected in chronic disease states, particularly in pulmonary and cardiovascular disease. Extreme short-term changes may be associated with acute disease episodes, particularly in chronically ill patients. 
       FIG.  5    is a block diagram showing components of a system  500  for monitoring health status of people suffering from chronic diseases, according to an example embodiment. The system  500  can include a sensor data acquisition module  510 , an oxygen saturation estimation module  520 , a respiratory rate estimation module  530 , and an output module  540 . In some embodiments, the modules  510 - 540  are implemented as chipsets included in the wearable device  110 . In other embodiments, the modules  520 ,  530 , and  540  can be stored as instructions in memory of the wearable device  110 , mobile device  140 , or computing cloud  150 , and executed by a processor. 
     In some embodiments, the sensor acquisition module  510  is configured to receive and digitize the sensor data. The sensor data acquisition module  510  can include one or more analog-to-digital converters to transform the electrical signals from sensors  120  to digital signals and provide the digital signal to modules  520 - 540  for further analysis. 
     In some embodiments, the data processing module is configured to analyze the infrared wavelength PPG signals and the red wavelength PPG signals recorded by the optical sensor  222   a  and  222   b  to obtain oxygen saturation using the methods of pulse oximetry. 
     The methods for pulse oximetry are based on the fact that oxygenated hemoglobin absorbs more infrared light while deoxygenated hemoglobin absorbs more red light. Typically, the methods of the pulse oximetry include calculation of a ratio R defined as follows: 
     
       
         
           
             
               
                 
                   R 
                   = 
                   
                     
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                       ⁡ 
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     wherein I max   red  and I min   red  are maximum and minimum of red wavelength PPG signal and I max   ir  and I min   ir  are maximum and minimum of infrared wavelength PPG signal. The ratio R can indicate a ratio between oxygenated hemoglobin and deoxygenated hemoglobin. The ratio R can be converted to a corresponding oxygen saturation (SpO 2 ) value via an empirically-derived look-up table. 
     In some embodiments, to take into account contributions due to interaction of light with non-pulsatile tissue, the infrared wavelength PPG signal can be shifted by a parameter L ir  and the red wavelength PPG signal can be shifted by a parameter L red . The ratio R 1  can be then determined as 
     
       
         
           
             
               
                 
                   
                     
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     The ratio R 1  can be further used to obtain the oxygen saturation via an empirically-derived look-up table or function. The parameters L red  and L ir  can be pre-determined in a calibration process. The calibration process may include optimization of L red  and L ir  to fulfill the equation R 1 (L red , L ir )=R true , wherein the R true  is a true value for the ratio R found by a “gold standard” measurement. 
     Using the infrared wavelength PPG signal I a   ir  and the red wavelength PPG signal I a   red  recorded by the optical sensor  222   a  from palmar side of a wrist near a blood artery, the oxygen saturation estimation module  520  may be configured to calculate a ratio R a . Using the infrared wavelength PPG signal I b   ir  and red wavelength PPG signal I b   red  recorded by the optical sensor  222   b  from dorsal side of the wrist, the oxygen saturation estimation module  520  may be configured to calculate a ratio R b . The PPG signals I a   ir , I a   red , I b   ir , and I b   red  can be recorded substantially simultaneously. 
     Since the ratio R a  is determined from PPG signals recorded by optical sensor  222   a  from the palmar side of the wrist near a blood artery, the value of the ratio R a  may be sensitive to location of light transmitters  450  and light sensors  440  relative to the blood artery. Typically, error of value oxygen saturation (SpO 2 ) determined based on ratio R a  decreases with increase of values for oxygen saturations. However, the optical sensor  222   a  located at the radial artery on the palmar side of the wrist may provide a PPG signals with a Signal-to-Noise Ratio (SNR) higher than the SNR of the PPG signal for optical sensor  222   b  located on the dorsal side of the wrist. Therefore, a location of an optical sensor near the radial artery is preferable over locations near fingertip or dorsal side of the wrist. Optical sensors located at a fingertip or on the dorsal side of the wrist can measure PPG signals received from small blood vessels. The quality of the PPG measurements received from the small blood vessels may be decreased due to several factors. One of the factors causing decrease in the quality of the PPG measurements includes possible constriction of small vessels due to low ambient temperatures. Another factor causing decrease in the quality of the PPG measurements includes a darker color of the skin covering the small blood vessels, which may lead to a decrease of the SNR in the PPG signals. 
     The ratio R b  is determined from PPG signals recorded at dorsal side of the wrist, which does not include pulsatile blood vessels. Therefore, the ratio R b  can be assumed to be independent on location of the light transmitters and light sensors of the optical sensor  222   b  relative to the surface of the dorsal side of the wrist. When PPG signals I b   ir , and I b   red  recorded by the optical sensor  222   b  are of a good quality, that is having a high SNR (as defined above), then the ratio R b  obtained using the PPG signals I b   ir , and I b   red  can be used to calibrate the PPG signals I a   ir  and I a   red  recorded by the optical sensor  222   a.    
     In some embodiments, the ratio R a  can be found by using the formula (2) and the ratio R b  can be found by using formula (1). The ratio R b  can be further used as R true  (the “gold standard” measurement) to optimize the parameters L red  and L ir  in formula (2). Thus, the PPG signals measured by the optical sensor  222   b  on the dorsal side of the wrist can be used to calibrate the optical sensor  222   a  on the palmar side. The calibration process can be carried out each time the patient wears the wearable device  110 . The calibration process can be also performed if a value of the oxygen saturation determined by using the PPG signals measured by the optical sensor  222   a  is outside a pre-determined range. 
     In some embodiments, the ratio R b  can be used to correct a value for ratio R a . For example, the ratio R a  and ratio R b  can be fused to obtain a ratio R. The ratio R can be further used to determine value of the oxygen saturation via an empirically-derived look-up table. 
     In some embodiments, a ratio R can be determined as 
         R=αR   a +(1−α) R   b   (3)
 
     wherein α is a weight, 0&lt;α≤1. The weight α can be determined as a function of SNR of PPG signal I b   ir  or PPG signal I b   red  measured at the palmar side of the wrist. Higher values of the weight α may correspond to higher values of the SNR of PPG signals I b   ir , or I b   red  since a higher SNR signal is more reliable for determining ratio R. A weighted average of the ratio R a  and ratio R b  can provide a better estimate for the ratio R because measurement errors of the optical sensor  222   a  and  222   b  are independent of each other. At the same time, the ratio R a  can be given a larger weight because a measurement obtained on the palmar side of the wrist and near the radial artery may provide more information for core blood pressure and oxygen saturation than a measurement obtained from small vessels on the dorsal side of the wrist. 
     In some other embodiments, weight α can be determined as a function of a perfusion index. The perfusion index is a ratio of the pulsatile blood flow to the non-pulsatile static blood flow in patient&#39;s peripheral tissue. The perfusion index can be estimated based on a PPG signal I b   ir  or a PPG signal I b   red  measured at the dorsal side of the wrist. 
       FIG.  6 A  shows a plot  600 A of an example PPG signal  610  which represents an amount of light received by a photodetector of optical sensor  222   b . The perfusion index can be calculated as a ratio of difference  620  of the amount of light received by the photodetector between vasoconstriction and vascular dilation to the total amount  630  of light received by the photodetector. Typically, the larger the perfusion index, the more accurate the measurement of oxygen saturation. Therefore, the perfusion index can be used as an indicator of quality of the PPG signal. 
     If the perfusion index determined based on PPG signals PPG signal I b   ir  and PPG signal I b   red  measured at the dorsal side of the wrist are higher than a pre-determined threshold, the ratio R b  obtained using the PPG signals I b   ir  and I b   red  can be used to correct the ratio R a  using formula (3). Furthermore, if the perfusion index determined based on the PPG signal I b   ir  and PPG signal I b   red  measured at the dorsal side of the wrist are higher than a pre-determined threshold, the ratio R b  can be also used to determine parameters L red  and L ir  in formula (2) for shifting PPG signals I a   red  and I a   ir  and, thereby, calibrate the optical sensor  222   a  disposed at the palmar side of the wrist. 
       FIG.  6 B  shows an example function  600 B for determining the weight α based on the value of perfusion index. The value of the perfusion index can be found based on the PPG signal I b   ir  or the PPG signal I b   red  measured at the dorsal side of wrist of a patient. The shape of function  600  can be determined in a calibration process. The weight α increases with an increase of the value for the perfusion index. 
     In some embodiments, the respiratory rate estimation module  530  is configured to analyze the gyroscope signal (rotation around three axes x, y, and z) measured by the gyroscope  430  at a wrist to obtain respiratory rate of a patient. It was found in tests performed by inventor that the gyroscope signal measured at the wrist of the patient includes data due to a cyclical motion of the chest of the patient. During the tests, a gyroscope signal measured by a gyroscope disposed at a wrist of a patient and a reference gyroscope signal measured by a gyroscope disposed in a chest strap at the chest of the patient were recorded simultaneously. A spectral analysis of the gyroscope signal measured at the wrist and the reference gyroscope signal measured at the chest were performed. A comparison of the spectra of the signals shows that the gyroscope signal measured at the wrist contains a frequency corresponding to the number of breaths of patient as determined based on the reference gyroscope signal measured at the chest. 
       FIG.  7    shows plot  700  of example gyroscope signal  710  measured at a wrist, spectrum  720  of the gyroscope signal  710 , reference gyroscope signal  730  measured at the chest, and spectrum  740  of the reference gyroscope signal  730 . The spectrum  720  of the gyroscope signal  710  includes a peak  750 , which corresponds to a peak  760  in spectrum  740  of the reference gyroscope signal  730 . The frequency at the peak  750  corresponds to the respiratory rate. 
       FIG.  8    shows plot  800  of example gyroscope signal  810  measured at a wrist, spectrum  820  of the gyroscope signal  810 , reference gyroscope signal  830  measured at the chest, and spectrum  840  of the reference gyroscope signal  830 . The SNR of gyroscope signal  810  is higher than SNR of the gyroscope signal  710  shown in  FIG.  7   . The spectrum  820  of the gyroscope signal  810  includes a peak  850  which corresponds to peak  860  in spectrum  840  of the reference gyroscope signal  830 . The frequency at the peak  850  corresponds to the respiratory rate. 
     The respiratory rate estimation module  530  may receive the gyroscope signal measured by the gyroscope  430  at the wrist of the patient and perform the spectral analysis of the gyroscope signal to obtain a spectrum of the gyroscope signal in a pre-determined range. The pre-determined range can be selected to cover a range of typical values for the respiratory rate of a human (for example, 6-18 breaths per minute). For example, the pre-determined range may include a range of 0 to 50 breaths per minute. In some embodiments, the spectral analysis may include fast Fourier transform, averaged periodograms (Bartlett&#39;s method), Welch&#39;s method, least-squares spectral analysis, and so forth. 
     The respiratory rate estimation module  530  can be further configured to determine a position of a peak in the spectrum that corresponds to the number of breaths of a patient per minute (the respiratory rate). In some embodiments, the respiratory rate estimation module  530  can be configured to select the strongest peak in the pre-determined range. As seen in  FIG.  7    and  FIG.  8   , the spectrum of the gyroscope signal can be contaminated by a noise caused by movement of the patient. Typically, the noise is of a low frequency. Therefore, in the spectrum, the frequencies caused by the noise may interfere with the frequency corresponding to the respiratory rate. 
     The signal s(t) representing motion of breathing can be described by formula: 
         s ( t )=Σ n=1   ∞   A   n ƒ( n*ω*t )  (4)
 
     wherein ƒ is a periodic function, ω is a fundamental frequency, and A n  are descending amplitudes. In a frequency domain, the signal s(t) is represented by peaks at frequencies n*ω, wherein amplitudes of the peaks descend with the increase of n. This pattern can be searched in a spectrum of the gyroscope signal measured by the gyroscope at a wrist of patient to confirm that a correct peak was assigned to the respiratory rate. 
     After determining the strongest peak, the module respiratory rate estimation  530  can confirm that the strongest peak in the spectrum represents breathing of the patient and not caused by movement noise of the patient. The module respiratory rate estimation  530  can be configured to determine that the spectrum includes one or more further peaks with descending amplitudes, such as the further peaks corresponding to frequencies n*ω, wherein ω is a frequency corresponding to the strongest peak, and n is a natural number. Based on the determination, the respiratory rate estimation module  530  can assign value w to the value of the respiratory rate. 
     In some embodiments, the output module  540  is configured to provide reports and alert messages regarding a health status of the patient. The output module  540  may be configured to display via a graphical display system of the wearable device  110  or the mobile device  140 . The output module  540  may determine that the respiratory rate of the patient is near or outside of a typical range (for example, 6-18 breaths per minute). The output module  540  may also determine that the value of oxygen saturation of the patient is below a pre-determined threshold. In response to the determination, the output module  540  may provide an alert message to the patient via a graphical display system of the wearable device  110  or/and mobile device  140 . The alert message may include an advice to take medication or contact a doctor. The output module may also send a warning message, via the communication unit of the wearable device  110  and/or mobile device  140 , to a computing device of a relative, a doctor, or a caretaker of the patient. 
       FIG.  9    is a flow chart diagram showing example method  900  for monitoring oxygen saturation of a patient. The method  900  may be implemented in system  100 . In block  910 , the method  900  may commence with measuring at a palmar surface of a wrist of the patient, by a first optical sensor, a first red wavelength PPG signal and a first infrared wavelength PPG signal. The first optical sensor can be embedded into a wearable device disposed around the wrist of the patient. 
     In block  920 , the method  900  may proceed with measuring, at a dorsal surface of the wrist, by a second optical sensor disposed in the wearable device, a second red wavelength PPG signal and a second infrared wavelength PPG signal. The second red wavelength PPG signal and the second infrared wavelength PPG signal can be measured substantially simultaneously with the first red wavelength PPG signal and the first infrared wavelength PPG signal. 
     In block  930 , the method  900  may continue with determining, by a processor communicatively connected to the first optical sensor and the second optical sensor and based on the first red wavelength PPG signal and the first infrared wavelength PPG signal, a first ratio for obtaining an oxygen saturation. In block  940 , the method  900  may determine, by the processor and based on the second red wavelength PPG signal and the second infrared wavelength PPG signal, a second ratio for obtaining the oxygen saturation. 
     In block  950 , the method  900  may determine, by the processor and based on the first ratio and the second ratio, a third ratio for obtaining an oxygen saturation. In block  960 , the method  900  may determine, by the processor and based on the third ratio, a value of the oxygen saturation. In block  970 , the method  900  may include providing, by the processor and based on the value of the oxygen saturation, a message regarding a health status of the patient. The message may include a warning against upcoming episode or worsening of a chronic disease of the patient, for which the oxygen saturation is one of the indicators. Upon receiving such a warning, preventive measures can be taken to reduce the severity of upcoming or worsening of the chronic disease. The message may include an advice to take a medicine or to contact a doctor. 
       FIG.  10    is a flow chart diagram showing an example method  1000  for monitoring respiratory rate of a patient. The method  1000  may be implemented in system  100 . In block  1010 , the method  1000  may commence with providing, by a gyroscope of a wearable device disposed on a wrist of a patient, a gyroscope signal indicative of a motion of the patient. The gyroscope can be communicatively coupled with a processor. In block  1020 , the method  1000  may proceed with performing, by the processor, a spectral analysis of the gyroscope signal to obtain a spectrum in a pre-determined frequency range, the pre-determined frequency range covering a normal respiratory rate range. 
     In block  1030 , the method  1000  may determine, by the processor, a position of a peak in the spectrum to obtain a value for a respiratory rate. In block  1040 , the method  1000  may provide, by the processor and based on the value of the respiratory rate, a message regarding the health status of the patient. In some embodiments, the method  1000  may determine, by the processor, that the value of the respiratory rate is outside of the normal respiratory rate range and provide, by the processor, an alert message regarding the health status of the patient based on the determination that the value of the respiratory rate is outside of the normal respiratory rate range. The alert message may include a warning against upcoming or worsening of a chronic disease from which the patients suffers, for which respiratory rate is one of the indicators. Upon receiving the message, preventive measures can be taken to reduce the severity of upcoming or worsening of a chronic disease. The message may include an advice to take a medication or to contact a doctor. 
       FIG.  11    is a flow chart diagram showing example method  1100  for continuous self-recalibration monitoring of a patient&#39;s oxygen saturation. The method  1100  may be implemented in system  100 . In block  1110 , the method  1100  may commence with measuring at a palmar surface of a wrist of the patient, by a first optical sensor, a first red wavelength PPG signal and a first infrared wavelength PPG signal. The first optical sensor can be embedded into a wearable device disposed around the wrist of the patient. 
     In block  1120 , the method  1100  may proceed with measuring, at a dorsal surface of the wrist, by a second optical sensor disposed in the wearable device, a second red wavelength PPG signal and a second infrared wavelength PPG signal. The second red wavelength PPG signal and the second infrared wavelength PPG signal can be measured substantially simultaneously with the first red wavelength PPG signal and the first infrared wavelength PPG signal. 
     In block  1130 , the method  1100  continues with determining repeatedly, first the conditions needed to be able to recalibrate and if recalibration needs to be performed. An oxygen saturation level at the dorsal sensor by the second sensor is determined and a profusion index determined. A sufficiently strong signal and profusion index is required from the dorsal sensor because this information is used to calibrate the readings from the first sensor. Based on the second red wavelength PPG signal and the second infrared wavelength PPG signal, a first ratio for obtaining the oxygen saturation and a perfusion index is determined. 
     In block  1140 , the method  1100  determines if the conditions for recalibration of the first optical sensor are satisfied. These conditions include a sufficient perfusion index determination based on the second sensor. 
     In block  1150 , the method  1100  determines if the perfusion index is too weak, below 0.4% then recalibration can not be performed. Optionally, a indication can be sent to a patient in the form of a message to take physical actions that could improve the perfusion index. These messages could include but are not limited to asking the patient to sit down, move to a warmer location, reposition the wearable device, or hydrate themselves. The process waits until the perfusion index is greater than 0.4% indicating that the reading level off the dorsal sensor can be used in the recalibration process. 
     In block  1160 , the method  1100  may determine, by the processor and based on based on the first ratio, a first parameter for modifying the first red wavelength PPG signal and a second parameter for modifying the first infrared wavelength PPG signal. 
     In block  1170 , the method  1100  may determine, by the processor, a second ratio for obtaining the oxygen saturation, the second ratio being determined based on the first red wavelength PPG signal, the first infrared wavelength PPG signal, the first parameter for modifying the first red wavelength PPG signal, and the second parameter for modifying the first infrared wavelength PPG signal. 
     In block  1180 , the method  1100  may provide based on the second ratio, a value of the oxygen saturation. This value is the oxygen reference of the first sensor. The process of recalibration can occur repeatedly when conditions indicate the need for self-recalibration are detected. Taking off and on the wearable device may cause the need for recalibration in that the calibrated value (oxygen saturation level) from the palmer sensor will change. Further, the recalibration will not occur until a perfusion index from the dorsal sensor above 0.4% occurs which will not happen until the wearable device is put back on the patient. 
     In block  1190 , the method  1100  may provide by the processor a message may include a warning against upcoming episode or worsening of a chronic disease of the patient, for which the oxygen saturation is one of the indicators. Upon receiving such a warning, preventive measures can be taken to reduce the severity of upcoming or worsening of the chronic disease. The message may include an advice to take a medicine or to contact a doctor. 
     The present technology is described above with reference to example embodiments. Therefore, other variations upon the example embodiments are intended to be covered by the present disclosure.