KR20210024412A - Electronic apparatus and method to provide personalized information based on biometric information - Google Patents

Abstract

The disclosure provides a method for operating an electronic device. The method includes the steps of: obtaining first information related to a user photoplethysmogram (PPG) at a first time; obtaining second information related to at least one of the user physical activity, heart rate, blood oxygenation level, or sleep quality during a first period; providing personalized information for the user, based on the first information and the second information; obtaining additional information related to the customized information during a second period; obtaining third information related to the PPG at a second time; and maintaining or altering the customized information based on the additional information and the third information.

Description

Electronic devices and methods that provide personalized information based on biometric information {ELECTRONIC APPARATUS AND METHOD TO PROVIDE PERSONALIZED INFORMATION BASED ON BIOMETRIC INFORMATION}

The present disclosure relates to an electronic device and method for providing personalized information based on biometric information.

The concept of a healthy lifestyle encompasses the total range of components. It's not just a diet or sports, it's a lifestyle that aims to energize the whole body, give up bad habits, and achieve a daily diet that includes good rest, productive work and physical activity.

The results of numerous studies show that human health at any age is more than 50% dependent on lifestyle. Experts highlight a number of advantages by answering the question of what is useful about a healthy lifestyle. This is the achievement of healthy longevity, reducing the risk of developing chronic diseases, dealing with bad mood, depression and stress, and obtaining desired levels.

Market Demand: Estimation of health status and eating patterns for quality control of lifestyle.

Most modern people have smart watches and smart phones. They need recommendations on how to improve the user's own health conditions, monitor compliance with the physician's recommendations, and, if necessary, adjust and periodically monitor changes in the health condition.

It is known that health state estimation can be performed on the basis of data from the accelerometer/gyroscope of an accelerometer/photoplethysmogram sensor (PPG) from the user devices in particular (US 20170249445; US 9402597).

One of the methods of estimating the health state is to estimate the health state of the vascular system based on photoplethysmography (PPG analysis).

The condition of the blood vessels determines how long and active a person will live. Most serious complications occur due to problems with the blood vessels, and vice versa, many diseases affect the condition of the blood vessels. Optical volume pulse wave measurement is a method of recording blood flow parameters using a near-infrared or visible wavelength radiation source and a photo detector. The greater the amount of blood in the tissue at a given moment, the more radiation is absorbed, and thus less radiation is obtained at the photo detector.

Both smartwatches and smart phones include optical volumetric pulse wave sensors. The smartphone is a major component of the claimed invention because a smartphone comprising an optical optical volumetric pulse wave sensor makes it possible to obtain a better signal from the finger. With respect to the smartwatch, the signal is obtained from the wrist.

The heart moves blood in the blood vessels. The photovoltaic pulse wave measurement makes it possible to measure the volumetric pulse of blood that is caused by periodic changes in blood volume according to each heart rate, heart rate, and heart rate variability. Due to a decrease in the ventricular myocardium, blood under pressure enters the aorta and pulmonary arteries from the heart. The rhythmic contractions of the myocardium form a rhythmic expansion of the vessel wall (pulse), which generates pulse waves under the influence of propagation of pressure waves from the first part of the aorta to arteries and capillaries.

As a result of the interaction between the left ventricle and the pulmonary circulation vessels, the contour of the volume pulse wave (Fig. 3A) is formed. The finger optical volume pulse wave reflects the merging between two volume pulse waves (sawtooth). The first teeth are formed by cardiac contractions, direct waves, which are formed by blood flow to the systolic phase, and are sent from the left ventricle to the fingers of the upper limbs (anacrotic stage). The second tooth is formed by the reflected wave generated by the reflection of blood flow from the periphery to the heart, and is sent to the lower limbs through the aorta and large major aorta, and is sent to the ascending aorta and additionally to the fingers of the upper limbs. Loses (dicrotic phase). The propagation speed of the pulse wave through the blood vessels does not depend on the blood flow rate, but is determined not only by the density of the blood, but also by the diameter of the blood vessel, the thickness of the blood vessel wall, and the elasticity of the blood vessel. Thus, photovoltaic measurement helps to identify the features of the stenosis (stenosis and sclerosis) to assess vascular tone and heart function.

It is determined that the frequency and duration of the pulse wave depend on the action of the heart muscle, and the size and shape of the peaks of the photovoltaic pulse wave depend on the state of the blood vessel wall. FIG. 3A shows the photovoltaic pulse wave of the blood vessel of a healthy person, and FIG. 3B shows the photovoltaic pulse wave of the blood vessel of the person affected by atherosclerosis, which is characterized by the waveform of the photovoltaic pulse wave. For a healthy person, the pulse wave is steeper and has a relatively high reflected wave. The constriction of the aorta leads to smoothing of the elevation, prolongation of the intermediate phase and a decrease in the height of the reflected wave. When the blood vessel is severely constricted, the reflected wave may be absent at all.

Factors that increase vascular stiffness and cause changes in the shape of the photovoltaic wave curve are: age, atherosclerotic diseases, cerebral infarction, coronary artery disease, chronic kidney disease, diabetes, hypertension. , Metabolic syndrome, and other diseases.

The shape of the photovoltaic pulse wave curve in a healthy person must correspond to that age. Thus, deviations indicate health problems. Accordingly, it is possible to evaluate the state of the vascular system and the vascular age according to the waveform of the optical volumetric pulse wave. This may differ from your actual age; Thus, the health condition can be assessed.

Another way is to estimate your health by detecting eating habits. The main data sources in this case are the accelerometer and gyroscope, which are some of the inertial measuring modules (IMUs) built into the smartwatch, i.e. the acceleration of the smartwatch along three axes. And some of the sensors that detect the rotational speed along the three axes.

The signals of the accelerometer and the gyroscope are different signals, and the signals may be determined when the user performs various actions such as walking, working with a keyboard, eating, and the like. At the same time, movements related to meals are better defined if the smartwatch is on the mainly used hand (right-handed, left-handed), and not well defined if the smartwatch is on the non-primarily used hand.

For example, mobile applications for wellness monitoring such as Samsung Health and Apple Activity appear widely in the market, and they track activity level, heart rate, PPG signal, stress level, food intake, sleep, and sports activities. However, it requires manual input of information from the user (eg, food intake time), and also has low accuracy for data input because it depends on the user's memory and honesty. That is, the currently available mobile applications for wellness monitoring do not have solutions for measuring health status. The current market fails to provide solutions for PPG analysis. Therefore, there is no objective method for evaluating the health status of users using electronic devices available in the market.

Mobile vascular health assessment processes are disclosed in US 9,402,597 (published August 2, 2016). The method includes: receiving data indicative of one or more physiological metrics or parameters of the body from a portable physiological measurement device configured to be temporarily attached to a human body; Vascular function for the body from one or more Doppler vascular sensors configured to be temporarily attached to locations of the peripheral artery of the body and a portable Doppler vascular signal measuring device connected to the Doppler vascular sensors The process of receiving information; Determining medical condition data indicating one or more medical conditions of the patient based on the analysis and correlations of the vascular function information and the patient physiological metrics; The above recommendations for actions that the individual or health care provider should take in response to recommendations, or parameters; Or creating and providing output records specifying one or more of one or more reports, animations, or numbers.

While the physician is involved in the evaluation, one or more computing devices perform the method. The patient must continuously enter information, ie the device requires manual data entry. The doctor monitors the received data and continuously inserts corrections; It is necessary to constantly monitor whether changes are present. The device is intended for clinical patients (not healthy users) and is not designed for the general consumer, as it cannot simultaneously monitor eating habits, assess the health status with relevant recommendations, and adjust the recommendations. to be.

US 20170249445 (published August 31, 2017) discloses a system for monitoring nutritional intake. The system comprises: a wearable housing configured to be releasably attached to a user; A biosensor supported by the wearable housing for placement adjacent to a blood vessel; The biosensor is configured to collect pulse profile data; Output device; And a processing circuit coupled to the biosensor and output device. The processing circuitry: receives the pulse profile data from the biosensor; Generate a nutritional intake value from the received pulse profile data; And an output device is configured to control outputting the nutritional intake value.

The estimation of food consumption is performed according to the light volume pulse wave. However, the device does not contain any recommendation system. An evaluation algorithm is initiated when a person eats or does not. The system is configured to estimate Kcal, for example 400 g of food corresponds to 700 kcal. The system does not simultaneously provide monitoring of eating habits, assessing health status with relevant recommendations, and encouraging recommendations.

In US 2017340219 (published on November 30, 2017) a smartwatch and human-to-computer interface for monitoring food consumption are disclosed. The wrist worn device (the smartwatch) non-invasively measures a pulse transit time and operates to calculate a blood pressure value using the pulse transit time. The wrist worn device is a wrist worn extension band, at least four EKG or ICG electrodes connected to the wrist worn device to detect ventricular discharge of the heart, and connected to the wrist worn device to detect the arrival of a blood pressure pulse wave at the user's wrist. A photoplethysmogram (PPG) sensor, and a controller configured to calculate a pulse transit time (PTT) for the blood pressure pulse. The controller calculates one or more blood pressure values for the user based on the PPG.

The system includes specific sensors in the smart watch that are not available in the market. The description does not specify which parameters will be measured and how nutrition will be evaluated according to the sensor signals. The system does not provide recommendations for physical activity, nutrition and sleep. The system is not a self-calibrating recommendation system and does not provide automatic nutrition monitoring. The system does not simultaneously provide monitoring of eating habits, assessing health status using relevant recommendations and recommendations, and coordinating recommendations.

US 7953613 (published July 3, 2008) discloses a health maintenance system for comprehensive health assessment, abnormality detection, health monitoring, health pattern and trend detection, health strategy development and health history storage.

The health maintenance system includes a subscriber segment and a system segment communicatively connected. The subscriber segment obtains subscriber personalization and health data from at least one subscriber, and analyzes the data; Identifying specific health anomalies; Define at least one customized subscriber health product, instruct the subscriber to implement the prescribed health product, compile and preserve health history data of the subscriber including abnormalities and prescribed health products, and , Conduct monitoring of subscriber health conditions. The subscriber segment acquires subscriber data from the subscriber segment, stores and maintains the data, facilitates data retrieval by the subscriber, and enables emergency medical personnel to analyze subscriber patterns and trends, and provide new health products. Develop and modify existing health products, and monitor the effectiveness of these health products.

The system engages the physician to monitor the parameters of the user, ie targets clinical patients. The system is more automatic than the systems mentioned above. Doctors observe, examine, and correct. However, automatic nutrition monitoring does not exist and requires manual data entry.

The system does not provide simultaneous monitoring of dietary habits and the use of relevant recommendations to assess health status and to adjust the recommendations.

US 2014136226 (published April 15, 2014) discloses a system for managing cardiovascular health, i.e., calculating a patient's disease risk score based on recommendations of treatment or lifestyle changes. The system receives risk parameter values for calculating the disease risk score according to a risk score algorithm, and an input device that receives recommendations for treatment or lifestyle changes, and recommendations for treatment or lifestyle changes. Based on the items, an analyzer for calculating at least one risk parameter value for calculating the disease risk score, a risk calculator for calculating the disease risk score based on the received risk parameter values and the calculated risk parameter value And an output device that communicates the calculated disease risk score. Thanks to the interpreter, the recommended treatment or lifestyle change is "translated" to the value of the risk parameter for calculating the disease risk score, thus calculating the risk score due to the treatment or lifestyle change. Can be allowed.

The system has the following drawbacks: no estimate of the user's vascular condition; No self-correcting recommendations system; No automatic nutrition monitoring.

The system does not simultaneously provide monitoring of eating habits and adjustment of recommendations and assessment of health status using relevant recommendations.

US 2014349256 (published on November 27, 2014) discloses a smartwatch and human-to-computer interface for monitoring food consumption. The system for monitoring a person's food consumption comprises: a wearable sensor that automatically collects data to detect possible eating events; A spontaneous human-to-computer interface used by the person to input food consumption data, wherein the person is prompted to enter food consumption data when a meal event is detected by the wearable sensor, and food consumption And a data analysis component that analyzes the data to estimate the types and amounts of ingredients, nutrients and/or calories consumed by the person. In one example, the wearable sensor may be a part of a smart watch or a smart bracelet. In one example, the spontaneous human-to-computer interface may be part of a smartphone. The integrated operation of the wearable sensor and the spontaneous human-to-computer interface, disclosed in this invention, provides an accurate measurement of food consumption with little intrusion to the privacy of the person.

The system has the following disadvantages: The system involves a physician for monitoring the parameters of the user, ie targeting clinical patients, there is no automatic nutrition monitoring, and requires manual data entry.

The system does not simultaneously provide monitoring of eating habits and adjustment of recommendations and assessment of health status using relevant recommendations.

An aspect of the present disclosure is to provide an electronic device and method for providing personalized information based on biometric information.

Another aspect of the present disclosure is to provide an electronic device and method for generating recommendations for a user for a healthy lifestyle.

Another aspect of the present disclosure is to provide an electronic device and method for providing personalized information for generating recommendations for a user for a healthy lifestyle.

The technical result achieved by the present disclosure includes improving the accuracy of estimating the health status of the user through real-time monitoring of eating habits and physical activity, and additionally, when correcting the user's behavior, the user It is possible to detect the association between the user's behavior and physiological changes that occur with respect to. The user's behavior is measured using signals from the smartwatch and smartphone. Based on the measurement, the most appropriate recommendations are provided, ie personalized recommendations for the user for eating habits and physical activity.

The proposed system is effective when the smartwatch is worn on both the user's primary hand (right-handed, left-handed) and non-primarily used hand.

The proposed system and method makes it possible to provide personalized recommendations on lifestyle change and lifestyle control with minimal user participation in order to develop user habits leading to a better health condition.

According to an aspect of the present disclosure, a method of operating an electronic device is provided. The method includes obtaining first information related to a photoplethysmogram (PPG) of a user at a first time point; Acquiring second information related to at least one of the user's physical activity, heart rate, blood oxygenation level, and sleep quality during the first period; Providing personalized information for the user based on the first information and the second information; Obtaining additional information related to the personalized information during a second period; Acquiring third information related to the PPG at a second point in time; And maintaining or changing the personalized information based on the additional information and the third information.

According to another aspect of the present disclosure, an electronic device is provided. The electronic device may include a display; At least one processor connected to the display; The memory includes a memory connected to the at least one processor, wherein the processor at the time of execution: acquires first information related to the user's photoplethysmogram (PPG) at a first time point, and during a first period Obtaining second information related to at least one of the user's physical activity, heart rate, blood oxygenation level, and sleep quality, and personalized information for the user based on the first information and the second information Controls the display to provide, obtains additional information related to the personalized information during a second period, obtains third information related to PPG at a second time point, and obtains the third information related to the PPG, based on the additional information and the third information. It stores instructions that allow you to maintain or change personalized information.

According to another aspect of the present disclosure, the technical result is achieved by providing a personalized system that forms recommendations for users when implementing a healthy lifestyle, the system:

An accelerometer, a gyroscope, and a photoplethysmogram (PPG) configured to sense and provide signals related to the user's physical activity, heart rate, blood oxygenation level, and sleep quality. A smartwatch including a sensor; The data, the data of the location based on the user's profile and geolocation, consider the time of food intakes, eating habits and patterns of physical activity in consideration of the right-handed or left-handed person. Is used to estimate,

A smart phone including a PPG sensor that forms an optical volume pulse wave signal by touching it with the user's finger, and a processing unit that processes signals of the PPG sensor that measures vascular stiffness that defines a blood vessel age ( smartphone), and

Generates recommendations for the user during food intakes and physical activity, detects the relationship between the user behavior and user physiological changes based on signals received from a smart watch and/or smartphone, and makes the most appropriate recommendation And a unit configured to select items and display the recommendations.

Advantageously, the personalized system further comprises a smart scale configured to generate signals of the user's weight dynamics and transmit the food intakes and recommendations upon physical activity to the unit that generates them.

Preferably, the unit generating recommendations for the user upon food intakes and physical activity is further configured to determine other types of deviations from the user's daily behavior, in particular to eat while on the move. do.

According to another embodiment of a personalized system that forms recommendations for users when implementing a healthy lifestyle, the system includes:

An accelerometer, a gyroscope, and a photoplethysmogram (PPG) configured to sense and provide signals related to the user's physical activity, heart rate, blood oxygenation level, and sleep quality. A smartwatch including a sensor; The data, the data of the location based on the user's profile and geolocation, consider the time of food intakes, eating habits and patterns of physical activity in consideration of the right-handed or left-handed person. Is used to estimate,

The PPG sensor is positioned on a display side of the smart watch, and is configured to form an optical volume pulse wave signal by touching it with the user's finger,

A unit processing signals of the PPG sensor that estimates vascular stiffness that defines vascular age, and

Generate recommendations for the user in the eating habit pattern, detect the association between the user's behavior and the user's physiological changes based on signals received from the smartwatch, and select the most appropriate recommendations. And a unit configured to display recommendations on the watch display.

Preferably, the personalized system further comprises a smart scale configured to generate signals of the user's weight dynamics and transmit the food intakes and recommendations for the user upon physical activity to the unit. do.

Preferably, the personalized system includes an ECG sensor including two electrodes, one of which is located on the display side of the smartwatch, and a second electrode is located on the rear surface of the smartwatch, and the The sensor is configured to generate ECG signals and transmit them to the unit that generates recommendations for the user during the food intakes and physical activity.

Preferably, the personalized system generates signals of the dynamics of changes in the user's blood glucose level, and transmits the signals to a unit that generates recommendations for the user during the food intakes and physical activity. It further includes an invasive/non-invasive glucose sensor configured.

The technical result is achieved by providing a method of forming recommendations for users in the implementation of a healthy lifestyle, the method being:

Measuring a photoplethysmogram on a smartphone by touching with the user's finger to estimate the blood vessel age based on the determination of the user's health condition;

Based on observations on user behavior and collected data, detect unhealthy eating habits including physical activity and rules including time, duration, time periods and intensity of the food intakes, and the health status Forming recommendations for the user on how to change their eating habits and physical activity to improve them;

Based on the dynamics of the changes in the health state being estimated based on the estimation of the blood vessel age, measuring the optical volume pulse wave repeatedly, and if necessary, changing the recommendations based on individual characteristics of the user's habits process;

Perform periodic monitoring of compliance with the recommendations and, if necessary, adjust or modify the recommendations to achieve a positive dynamic of the user's health status based on an estimate of the vascular age. Includes the process.

According to another embodiment of the method of forming recommendations for users in implementing a healthy lifestyle, the method includes:

Measuring a photoplethysmogram on a smart watch by touching with the user's finger to estimate the blood vessel age based on the determination of the user's health state;

Based on observations on user behavior and collected data, detect unhealthy eating habits including physical activity and rules including time, duration, time periods and intensity of the food intakes, and the health status Forming recommendations for the user on how to change their eating habits and physical activity to improve them;

Based on the dynamics of the changes in the health state being estimated based on the estimation of the blood vessel age, measuring the optical volume pulse wave repeatedly, and if necessary, changing the recommendations based on individual characteristics of the user's habits process;

Perform periodic monitoring of compliance with the recommendations and, if necessary, adjust or modify the recommendations to achieve a positive dynamic of the user's health status based on an estimate of the vascular age. Includes the process.

Preferably, in the method, the dynamics of the user's body weight are taken into account when adjusting or changing the recommendations to achieve a positive dynamics of the user's health status.

Preferably, in the method, the user's electrocardiogram ECG is taken into account when adjusting or changing the recommendations to achieve a positive dynamic of the user's health status.

Preferably, in the method, the dynamics of changes in glucose content are taken into account when adjusting or changing the recommendations to achieve a positive dynamics of the user's health status.

The technical result is realized due to the fact that in addition to the data obtained from the accelerometer and gyroscope, the data of the optical volume pulse wave signal is used. As a result, a significant improvement in the validity of the recommendations for the user is achieved. In addition, compared to known systems, the proposed system does not allow the use of manual user input. Notwithstanding the taboos that the user may have, known solutions are recommendations that are common to all users, for example, it is recommended to run on the user to lose weight.

Existing systems monitor a number of parameters, but the user has to wear a series of special sensors and constantly wear them, which causes inconvenience and results in refusal to use the system. The claimed invention does not require additional sensors and does not require modification of existing smartwatches and smartphones.

Using an accelerometer/gyroscope and a photovoltaic pulse wave sensor allows a complete estimation of the user's lifestyle (nutrition/activity/sleep) without interacting with the user.

The recommendations for improving the personalized healthy lifestyle of the user include a database of standard recommendations approved by those skilled in the art of healthy lifestyle, and the personalized recommendations include the user's behavioral characteristics and individual It is selected from the database by identifying health and lifestyle characteristics.

The present invention can detect a wide range of applications in health monitoring, particularly wellness management using the recommendations of personalized healthy lifestyle users.

Additional aspects of the invention will become apparent from the following description, which is given by way of example only, and is also given with reference to the accompanying drawings:
1 is a block diagram of an electronic device in a network environment according to various embodiments of the present disclosure.
2 illustrates steps in a method of generating recommendations for a user in implementing a healthy lifestyle, according to various embodiments of the present disclosure;
3 illustrates the body pulse wave according to various embodiments of the present disclosure, FIG. 3A illustrates a photoplethysmogram of a healthy human blood vessel, and FIG. 3B illustrates atherosclerosis. ) It shows the photovoltaic pulse wave of human blood vessels;
4 is a diagram illustrating an embodiment of a personalized system that generates recommendations for users when implementing a healthy lifestyle according to various embodiments of the present disclosure, wherein the system includes a smart watch and a smart phone. includes (smartphone);
5 illustrates an embodiment of a personalized system for generating recommendations for users when implementing a healthy lifestyle according to various embodiments of the present disclosure, wherein the system includes a smart watch, a smart phone, and a smart scale. Includes;
6 illustrates an embodiment of a personalized system for generating recommendations for users when implementing a healthy lifestyle according to various embodiments of the present disclosure, the system being a display side of a smart watch And a second PPG sensor positioned on the smart watch and configured to form an optical volume pulse wave signal by touching it with the user's finger;
7 illustrates an embodiment of a personalized system that generates recommendations for users when implementing a healthy lifestyle, according to various embodiments of the present disclosure, the system: located on the display side of a smart watch The smart watch comprising a second PPG sensor that is configured to form an optical volume pulse wave signal by touching it with the user's finger; Smart scale, one electrode is located on the display side of the smart watch, the second electrode is an ECG sensor located on the rear surface of the smart watch, and an invasive/non-invasive glucose sensor (invasive/non-invasive glucose sensor). sensor);
8 is based on analysis of PPG signals of 40000 users divided into three classes of Poor/Good/Excellent vascular conditions according to various embodiments of the present disclosure. It shows the estimation result of the vascular state;
9 is a test of an algorithm for automatically detecting meals of 50 users based on signals from the accelerometer, the gyroscope, and the smart watch photovoltaic pulse wave sensor according to various embodiments of the present disclosure. The results are shown;
10 shows an example of possible results of analyzes of optical volume pulse wave signals from a user of the age of 40 and corresponding recommendations according to various embodiments of the present disclosure.
11A is a diagram illustrating an example of a photovoltaic pulse wave signal acquired using the photophobic pulse wave sensor according to various embodiments of the present disclosure.
11B illustrates an example of a signal processed using the acquired optical volumetric pulse wave signal according to various embodiments of the present disclosure.
11C shows an accelerometer and an accelerometer/gyroscope signal acquired using the gyroscope.
11D shows an example of a signal processed using the acquired accelerometer/gyroscope signal.
11E is a diagram for describing information related to an average oxygenation level, HRV, and blood vessel stiffness obtained from a processed optical volumetric pulse wave signal according to various embodiments of the present disclosure.
11F is a diagram for describing information obtained from a processed accelerometer/gyroscope/optical volume pulse wave signal according to various embodiments of the present disclosure.
12 illustrates an example of a method of estimating whether an electronic device consumes food according to various embodiments of the present disclosure.
13 illustrates an example of a method of estimating whether an electronic device consumes food, according to various embodiments of the present disclosure.
14 illustrates an example of a method for generating personalized recommendations by an electronic device according to various embodiments of the present disclosure.

1 is a block diagram of an electronic device 101 in a network environment 100 according to various embodiments. Referring to FIG. 1, in a network environment 100, the electronic device 101 communicates with the electronic device 102 through a first network 198 (for example, a short-range wireless communication network), or a second network 199 It is possible to communicate with the electronic device 104 or the server 108 through (eg, a long-distance wireless communication network). According to an embodiment, the electronic device 101 may communicate with the electronic device 104 through the server 108. According to an embodiment, the electronic device 101 includes a processor 120, a memory 130, an input device 150, an audio output device 155, a display device 160, a sensor module 176, and an interface 177. ), a power management module 188, a battery 189, a communication module 190, a subscriber identification module 196, or an antenna module 197. In some embodiments, at least one of these components (for example, the display device 160) may be omitted or one or more other components may be added to the electronic device 101. In some embodiments, some of these components may be implemented as a single integrated circuit. For example, the sensor module 176 (eg, a fingerprint sensor, an iris sensor, or an illuminance sensor) may be implemented while being embedded in the display device 160 (eg, a display).

The processor 120, for example, executes software (eg, a program 140) to implement at least one other component (eg, a hardware or software component) of the electronic device 101 connected to the processor 120. It can be controlled and can perform various data processing or operations. According to an embodiment, as at least a part of data processing or operation, the processor 120 may transfer commands or data received from other components (eg, the sensor module 176 or the communication module 190) to the volatile memory 132 It is loaded into, processes commands or data stored in the volatile memory 132, and the result data may be stored in the nonvolatile memory 134. According to an embodiment, the processor 120 includes a main processor 121 (eg, a central processing unit or an application processor), and an auxiliary processor 123 (eg, a graphic processing unit, an image signal processor) that can be operated independently or together. , A sensor hub processor, or a communication processor). Additionally or alternatively, the coprocessor 123 may be set to use lower power than the main processor 121 or to be specialized for a designated function. The secondary processor 123 may be implemented separately from the main processor 121 or as a part thereof.

The co-processor 123 is, for example, in place of the main processor 121 while the main processor 121 is in an inactive (eg, sleep) state, or the main processor 121 is active (eg, executing an application). ) While in the state, together with the main processor 121, at least one of the components of the electronic device 101 (for example, the display device 160, the sensor module 176, or the communication module 190) It is possible to control at least some of the functions or states associated with it. According to an embodiment, the coprocessor 123 (eg, an image signal processor or a communication processor) may be implemented as a part of another functionally related component (eg, the communication module 190).

The memory 130 may store various data used by at least one component of the electronic device 101 (eg, the processor 120 or the sensor module 176). The data may include, for example, software (eg, the program 140) and input data or output data for commands related thereto. The memory 130 may include a volatile memory 132 or a nonvolatile memory 134.

The program 140 may be stored as software in the memory 130, and may include, for example, an operating system 142, middleware 144, or an application 146.

The input device 150 may receive a command or data to be used for a component of the electronic device 101 (eg, the processor 120) from outside (eg, a user) of the electronic device 101. The input device 150 may include, for example, a microphone, a mouse, a keyboard, or a digital pen (eg, a stylus pen).

The sound output device 155 may output an sound signal to the outside of the electronic device 101. The sound output device 155 may include, for example, a speaker or a receiver. The speaker can be used for general purposes such as multimedia playback or recording playback, and the receiver can be used to receive incoming calls. According to an embodiment, the receiver may be implemented separately from or as a part of the speaker.

The display device 160 may visually provide information to the outside of the electronic device 101 (eg, a user). The display device 160 may include, for example, a display, a hologram device, or a projector and a control circuit for controlling the device. According to an embodiment, the display device 160 may include a touch circuitry set to sense a touch, or a sensor circuit (eg, a pressure sensor) set to measure the strength of a force generated by the touch. have.

The sensor module 176 detects an operating state (eg, power or temperature) of the electronic device 101, or an external environmental state (eg, a user state), and generates an electrical signal or data value corresponding to the detected state. can do. According to an embodiment, the sensor module 176 is, for example, a gesture sensor, a gyro sensor, an atmospheric pressure sensor, a magnetic sensor, a light volume pulse wave sensor 171, an accelerometer sensor 172, a gyroscope 173 sensor, It may include an ECG sensor 174, a grip sensor, a proximity sensor, a color sensor, an infrared (IR) sensor, a biometric sensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

The interface 177 may support one or more designated protocols that may be used for the electronic device 101 to directly or wirelessly connect with an external electronic device (eg, the electronic device 102). According to an embodiment, the interface 177 may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

The connection terminal 178 may include a connector through which the electronic device 101 can be physically connected to an external electronic device (eg, the electronic device 102). According to an embodiment, the connection terminal 178 may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (eg, a headphone connector).

The power management module 188 may manage power supplied to the electronic device 101. According to an embodiment, the power management module 388 may be implemented as at least a part of, for example, a power management integrated circuit (PMIC).

The battery 189 may supply power to at least one component of the electronic device 101. According to an embodiment, the battery 189 may include, for example, a non-rechargeable primary cell, a rechargeable secondary cell, or a fuel cell.

The communication module 190 includes a direct (eg, wired) communication channel or a wireless communication channel between the electronic device 101 and an external electronic device (eg, the electronic device 102, the electronic device 104, or the server 108). It is possible to support establishment and communication through the established communication channel. The communication module 190 operates independently of the processor 120 (eg, an application processor) and may include one or more communication processors supporting direct (eg, wired) communication or wireless communication. According to an embodiment, the communication module 190 is a wireless communication module 192 (eg, a cellular communication module, a short-range wireless communication module, or a global navigation satellite system (GNSS) communication module) or a wired communication module 194 (eg : A local area network (LAN) communication module, or a power line communication module) may be included. Among these communication modules, a corresponding communication module is a first network 198 (for example, a short-range communication network such as Bluetooth, WiFi direct or IrDA (infrared data association)) or a second network 199 (for example, a cellular network, the Internet, or It can communicate with external electronic devices through a computer network (for example, a telecommunication network such as a LAN or WAN). These various types of communication modules may be integrated into one component (eg, a single chip), or may be implemented as a plurality of separate components (eg, multiple chips). The wireless communication module 192 uses subscriber information stored in the subscriber identification module 196 (eg, International Mobile Subscriber Identifier (IMSI)) in a communication network such as the first network 198 or the second network 199. The electronic device 101 can be checked and authenticated.

The antenna module 197 may transmit a signal or power to the outside (eg, an external electronic device) or receive from the outside. According to an embodiment, the antenna module may include one antenna including a conductor formed on a substrate (eg, a PCB) or a radiator formed of a conductive pattern. According to an embodiment, the antenna module 197 may include a plurality of antennas. In this case, at least one antenna suitable for a communication method used in a communication network such as the first network 198 or the second network 199 is, for example, provided by the communication module 190 from the plurality of antennas. Can be chosen. The signal or power may be transmitted or received between the communication module 190 and an external electronic device through the at least one selected antenna. According to some embodiments, other components (eg, RFIC) other than the radiator may be additionally formed as part of the antenna module 197.

At least some of the components are connected to each other through a communication method (e.g., a bus, general purpose input and output (GPIO), serial peripheral interface (SPI), or mobile industry processor interface (MIPI))) between peripheral devices and a signal ( E.g. commands or data) can be exchanged with each other.

According to an embodiment, the command or data may be transmitted or received between the electronic device 101 and the external electronic device 104 through the server 108 connected to the second network 199. Each of the electronic devices 102 and 104 may be a device of the same or different type as the electronic device 101. According to an embodiment, all or part of the operations executed by the electronic device 101 may be executed by one or more of the external electronic devices 102, 104, or 108. For example, when the electronic device 101 needs to perform a function or service automatically or in response to a request from a user or another device, the electronic device 101 In addition or in addition, it is possible to request one or more external electronic devices to perform the function or at least part of the service. One or more external electronic devices receiving the request may execute at least a part of the requested function or service, or an additional function or service related to the request, and transmit a result of the execution to the electronic device 101. The electronic device 101 may process the result as it is or additionally and provide it as at least a part of a response to the request. For this, for example, cloud computing, distributed computing, or client-server computing technology may be used.

An electronic device according to various embodiments disclosed in this document may be a device of various types. The electronic device may include, for example, a portable communication device (eg, a smart phone), a computer device, a portable multimedia device, a portable medical device, a camera, a wearable device, or a home appliance. The electronic device according to the exemplary embodiment of the present document is not limited to the above-described devices.

Various embodiments of the present document and terms used therein are not intended to limit the technical features described in this document to specific embodiments, and should be understood to include various modifications, equivalents, or substitutes for the corresponding embodiment. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of the above items unless clearly indicated otherwise in a related context. In this document, “A or B”, “at least one of A and B”, “at least one of A or B,” “A, B or C,” “at least one of A, B and C,” and “A Each of the phrases such as "at least one of, B, or C" may include any one of the items listed together in the corresponding one of the phrases, or all possible combinations thereof. Terms such as "first", "second", or "first" or "second" may be used simply to distinguish the component from other Order) is not limited. Some (eg, a first) component is referred to as “coupled” or “connected” to another (eg, a second) component, with or without the terms “functionally” or “communicatively”. When mentioned, it means that any of the above components can be connected to the other components directly (eg by wire), wirelessly, or via a third component.

The term "module" used in this document may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic blocks, parts, or circuits. The module may be an integrally configured component or a minimum unit of the component or a part thereof that performs one or more functions. For example, according to an embodiment, the module may be implemented in the form of an application-specific integrated circuit (ASIC).

Various embodiments of the present document include one or more commands stored in a storage medium (eg, internal memory 136 or external memory 138) that can be read by a machine (eg, electronic device 101). It may be implemented as software (for example, the program 140) including them. For example, the processor (eg, the processor 120) of the device (eg, the electronic device 101) may call and execute at least one command among one or more commands stored from a storage medium. This enables the device to be operated to perform at least one function according to the at least one command invoked. The one or more instructions may include code generated by a compiler or code executable by an interpreter. A storage medium that can be read by a device may be provided in the form of a non-transitory storage medium. Here,'non-transitory' only means that the storage medium is a tangible device and does not contain a signal (e.g., electromagnetic waves), and this term refers to the case where data is semi-permanently stored in the storage medium. It does not distinguish between temporary storage cases.

According to an embodiment, a method according to various embodiments disclosed in this document may be provided by being included in a computer program product. Computer program products can be traded between sellers and buyers as commodities. Computer program products are distributed in the form of a device-readable storage medium (e.g., compact disc read only memory (CD-ROM)), or through an application store (e.g., Play Store ^TM ) or two user devices (e.g., compact disc read only memory (CD-ROM)). It can be distributed (e.g., downloaded or uploaded) directly between, e.g. smartphones). In the case of online distribution, at least some of the computer program products may be temporarily stored or temporarily generated in a storage medium that can be read by a device such as a server of a manufacturer, a server of an application store, or a memory of a relay server.

According to various embodiments, each component (eg, module or program) of the above-described components may include a singular number or a plurality of entities. According to various embodiments, one or more components or operations among the above-described corresponding components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (eg, a module or program) may be integrated into one component. In this case, the integrated component may perform one or more functions of each component of the plurality of components in the same or similar to that performed by the corresponding component among the plurality of components prior to the integration. . According to various embodiments, operations performed by a module, program, or other component may be sequentially, parallel, repeatedly, or heuristically executed, or one or more of the operations may be executed in a different order or omitted. , Or one or more other actions may be added.

According to an embodiment, a personalized system 400 for forming recommendations to a user when implementing a healthy lifestyle (FIG. 4) includes: the user's physical activity, heart rate, and blood oxygenation level (blood oxygenation level), and an accelerometer configured to sense and provide signals related to sleep quality, a gyroscope 411, a photoplethysmogram (PPG) sensor 412 (smartwatch) 410. The data, the data of the location based on the user's profile and geolocation, is used to estimate the eating time, eating habits and patterns of physical activity in consideration of the right-handed or left-handed person. Is used.

The system 400 includes a PPG sensor 421 that provides an optical volume pulse wave signal by touching it with a user's finger, and processes the signals of the PPG sensor to measure vascular stiffness that defines the vascular age. It includes a smartphone (smartphone) including a unit.

The system 400 also generates recommendations for the user during food intakes and physical activity, and based on the signals received from the smartwatch 410 and/or smartphone 420, the user behavior and user physiology. It includes a unit attached to a smartwatch and/or smartphone, configured to detect the association between the changes, select the most appropriate recommendations, and display the recommendations.

In one embodiment, the personalized system 500 for forming recommendations (FIG. 5) is a unit that generates the food intakes and recommendations for physical activity by generating signals of the user's weight dynamics. And a smart scale 530 that is configured to transmit.

The unit that generates recommendations for the user upon the food intakes and physical activity is further configured to identify other types of deviations from the user's daily behavior, in particular eating while traveling.

According to another embodiment of the claimed invention, a personalized system 600 (FIG. 6) that generates recommendations for a user when implementing a healthy lifestyle includes the user's physical activity, heart rate, and blood oxygenation level. ), and a smartwatch 610 including an accelerometer, a gyroscope 611, and a photoplethysmogram (PPG) sensor 612, configured to sense and provide signals related to sleep quality; The data, the data of the location based on the user's profile and geolocation, consider the time of food intakes, eating habits and patterns of physical activity in consideration of the right-handed or left-handed person. It is used to estimate.

According to the embodiment, the smart watch 610 is positioned on the display side of the smart watch 610 and is configured to generate a light volume pulse wave signal by touching it with the user's finger ( In addition, a photoplethysmogram (PPG) sensor 613 is included.

A unit (not shown in the drawings) for processing signals of the PPG sensor measuring vascular stiffness that defines the level of blood oxygenation and vascular age is attached to the smart watch 610 have.

The system 600 further comprises a unit that generates eating habit patterns, recommendations for the user in physical activity, and is attached to the smartwatch 610; The unit detects a relationship between the user's behavior and the user's physiological changes based on signals received from the smart watch, selects the most suitable recommendations, and displays the recommendations on the watch display. Is configured to

In a preferred embodiment, the personalized system 700 (FIG. 7) that forms recommendations for the user generates signals of the user's weight dynamics to the user during the food intakes and physical activity. It further comprises a smart scale 730, configured to transmit the recommendations for the generating unit.

In one embodiment, the personalized system 700 (FIG. 7) for generating recommendations for the user further includes an ECG sensor 714 including two electrodes, one of which is Located on the display side, the second electrode is located on the back surface of the smartwatch, and the sensor generates ECG signals and transmits them to the unit that generates recommendations for the user during the food intakes and physical activity. Is configured to

In one embodiment, a personalized system 700 (FIG. 7) that forms recommendations for the user generates signals of the dynamics of changes in the user's blood glucose level, and converts the signals to the food intakes and It further comprises an invasive/non-invasive glucose sensor 715, which is configured to transmit recommendations for the user upon physical activity to the generating unit.

According to the present invention, the method 200 (FIG. 2) of generating recommendations for users when implementing a healthy lifestyle is performed in the following manner.

In the first step 201, the user wears the smartwatch and touches it with the user's finger to estimate the (excellent/good/poor) health condition, thereby making the optical volume on the smartphone. It carries out measuring the pulse wave. The optical volume pulse wave signal of the user is analyzed by comparing the received optical volume pulse wave signal of the user with a signal received for a healthy person of the same age as the given user's age (Fig. 3), and is associated with the stiffness of the blood vessels. Waveforms and coefficients calculated from the signals being processed are compared.

In a second step 202, after a short period of time, such as a week after the first measurement, the system determines unhealthy eating habits (meal time, duration) based on observations and collected data on user behavior. Time), physical activity (durations and intensity), and generates recommendations for the user on how to change eating habits and physical activity to improve health.

Personalized recommendations are selected from a set of standard recommendations approved by those skilled in the healthy lifestyle. Recommendations are selected according to the user's goals, in particular the user can choose to maintain a form of health, ie maintain a healthy lifestyle, lose weight or gain weight. Recommendations are selected based on the current health status of the user. For example, when the user has a problem related to blood vessels, the physical activity is restricted.

In addition, the system automatically monitors the user's behavior and estimates compliance with the recommendations, especially over a long period, of about 3 months.

Food intakes are detected based on signals from the gyroscope and accelerometer together with the analysis of the light volume pulse wave signals, and the durations and intensity of the user's physical activity are calculated based on the signals from the accelerometer and the gyroscope.

In a third step (203), after a time interval of about 3 months after the first measurement, the user determines the different of the optical volume pulse wave signal based on the system estimating the role of the health state according to the age of the vascular system. Carry out the measurement. The condition of the vascular system is not improved or altered as a result of compliance with the recommendations, if the condition of the vascular system was initially excellent. In the case of deterioration of the vascular condition when implementing the recommendations, a decision is made to change the recommendations.

Thereafter, weekly, monitoring 204 of compliance with the recommendations is performed, and in case of improvement of the healing status, the user is motivated to follow the recommendations; In the case where the user does not follow the recommendations, for example, if the user has a habit of sleeping 5 hours a day, the recommendations can be replaced with less stringent recommendations, and sleep 8 hours. Recommendations are so difficult that it is necessary to provide recommendations to continuously increase sleep time.

Since the state of the vascular system changes after 3 to 4 months after a lifestyle change, frequent measurement of the optical volume pulse wave is impractical.

The algorithm for determining the blood vessel age from the optical volume pulse wave signal is a vascular stiffness index calculated using the amplitude characteristics, first and second derivatives, and other parameters of the optical volume pulse wave. index).

In order to more accurately determine the blood vessel age, a machine learning algorithm is used, for example a trained random forest for the state of the blood vessel age and the signals of the photovoltaic wave of 40,000 people. And the algorithm is used to process the pre-prepared (filtered and normalized) signals of the optical volume pulse wave. The result of estimating the blood vessel age is shown in FIG. 8, and the estimation corresponds to three classes: poor/good/excellent state of the blood vessel age.

The user's eating habits are deep machine learning algorithms (recurrent neural networks) trained to recognize movement patterns corresponding to 50 people's food intakes and 1100 food intakes. It is identified by analyzing the signals of the accelerometer, gyroscope and photovoltaic pulse wave sensor after the pre-processing steps including filtering and normalizing using a. The deep machine learning algorithm uses the XGboost algorithm. A method of analyzing the user's eating habits will be described later in detail.

The light volume pulse wave signal is recorded in four spectral ranges of red, infrared, green, and blue. The signals recorded on different channels are compared to each other. The result of the comparison is a spectral scattering coefficient that can be used to determine whether the chemical composition of the blood has changed.

After a meal, the user's blood composition is changed, and the scattering coefficients at different wavelengths are changed accordingly, and the oxygen saturation of the blood is determined by the spectral scattering characteristics, which is also the spectral scattering characteristics. Together with the catering coefficients, it is used as an input parameter to an algorithm based on a neural network.

One or more parameters used by the algorithm based on the neural network to determine the eating process are in heart rate variability associated with the activity of the autonomous regulatory systems of the digestive system in response to food intakes. It's a change.

9 shows the results of detection of the food intakes. For the main hand, the boxplot is shown on the right. The F-measurement is used (the F1-score is an estimate of the accuracy, precision and completeness, the joint of the recall, and on average is 0.7. The picture box on the right above is primarily for the hands that are not in use. For; where the F-measure is less than or equal to 0.63.

An example of forming recommendations for a 40-year-old user is provided in FIG. 10.

In the first case (FIG. 10A), the algorithm estimates that the user's blood vessel age is 29 years old, which is much less than the user's actual age, so it is recommended that the user maintain a healthy lifestyle continuously. The recommended period for measuring the optical volume pulse wave signal is 4 months; Minimal user interaction is required.

In both cases (Fig. 10b), the algorithm estimates that the user's blood vessel age is 45 years old, which is similar to the user's actual age, and thus maintains and develops habits to maintain a healthier lifestyle that is better for the user. Motivated to do it. The recommended period for measuring the optical volume pulse wave signal is 3 months; The system, if present, notifies the user of non-compliance with the recommendations.

In the third case (FIG. 10C), the algorithm estimates that the user's blood vessel age is 60 years old, which is much higher than the user's actual age, so it is recommended that the user undergo examination at a hospital.

First, according to various embodiments of the present disclosure, the electronic device may estimate a user's eating habit in various ways. Hereinafter, a method of estimating a user's eating habit by an electronic device according to various embodiments of the present disclosure will be described with reference to FIGS. 11A to 11F.

11A is a diagram illustrating an example of an optical volume pulse wave signal obtained by an electronic device using an optical volume pulse wave sensor according to various embodiments of the present disclosure.

Referring to FIG. 11A, first, signal 1110 represents a light volume pulse wave signal obtained by using a red channel of a red wavelength sensor and before a user consumes food. The 1120 signal represents a light volume pulse wave signal obtained by using the red channel and after ingestion of food. Signal 1130 represents a light volume pulse wave signal obtained by using an infrared channel before the user consumes food. The 1140 signal represents a light volume pulse wave signal obtained by using an infrared channel and after a user ingests food.

By performing a smoothing operation on the acquired optical volumetric pulse wave signal, noise included in the acquired optical volumetric pulse wave signal, that is, noise of the optical volumetric pulse wave sensor, may be removed. Here, the smoothing operation may be performed using a low pass filter (LPF), or may be performed based on an exponential moving average method, and the smoothing operation is not limited thereto. . The optical volume pulse wave signal from which the noise is removed is filtered using a high pass filter (HPF), and thus motion artifacts may be reduced.

11B is a diagram illustrating a signal obtained by processing an optical volume pulse wave signal obtained by an electronic device according to various embodiments of the present disclosure. Here, the electronic device acquires parameters of 11e to be described later by using the processed optical volume pulse wave signal. The electronic device estimates whether a food intake event has occurred using a machine learning (ML) algorithm based on the acquired parameters.

11C is a diagram illustrating an accelerometer/gyroscope signal acquired by an electronic device using an accelerometer/gyroscope according to various embodiments of the present disclosure.

Referring to FIG. 11C, first, the electronic device may smooth the accelerometer/gyroscope signal by removing noise from the accelerometer/gyroscope by applying an exponential moving average method to the acquired accelerometer/gyroscope signal. In addition, the electronic device reduces the computation cost of a machine learning algorithm by performing down sampling on the smoothed accelerometer/gyroscope signal, and the smoothed accelerometer/gyroscope signal has a value between 0 and 1. In order to have it, a normalization operation is performed on the smoothed accelerometer/gyroscope signal.

11D is a diagram illustrating an accelerometer/gyroscope signal generated by processing an acquired accelerometer/gyroscope signal by an electronic device according to various embodiments of the present disclosure.

Referring to FIG. 11D, the electronic device acquires parameters of FIG. 11F to be described later using a processed accelerometer/gyroscope signal, and estimates whether a food intake event occurs using a machine learning algorithm based on the acquired parameters. .

In various embodiments of the present invention, a set time, for example, a plurality of food intake events divided into an accelerometer/gyroscope/optical volume pulse wave signal sensed for 32000 hours or more and the accelerometer/gyroscope/optical volume pulse wave signal For example, it can be assumed that more than 4200 food intake events are data based on a number of people, for example 106 people, and are stored in a database for a machine learning algorithm.

The signals and parameters described in FIGS. 11A-11F may be obtained using an infrared wavelengths sensor and a red wavelength sensor, and the like.

FIG. 12 is an example of a process of processing an optical volume pulse wave signal shown in FIGS. 11A to 11F and a process of estimating whether a food intake event occurs based on the processed optical volume pulse wave signal, according to various embodiments of the present disclosure. Is shown.

Referring to FIG. 12, firstly, the electronic device acquires an optical volumetric pulse wave signal from the optical volumetric pulse wave sensor (1200). The obtained optical volume pulse wave signal is processed by performing a smoothing operation (1210). Here, the smoothing operation may be performed using a low-pass filter or may be performed based on an exponential moving average method. The electronic device may obtain information related to an average oxygenation level, heart rate variability (HRV), and vascular stiffness) from the processed optical volumetric pulse wave signal, and the average oxygenation level, HRV And information related to vascular stiffness is shown in FIG. 11E (1220). The electronic device obtains food intake-related probabilities by using a machine learning algorithm based on information related to the average oxygenation level, HRV, and vascular stiffness (1230). The electronic device estimates whether a food intake event has occurred based on the obtained food intake-related probabilities. (1240). Here, the electronic device generates and provides a personalized recommendation for a user based on a result of whether the food intake event occurs.

13 is a process of processing the accelerometer/gyroscope signal shown in FIGS. 11A to 11F and estimating whether a food intake event occurs from the processed accelerometer/gyroscope/optical volume pulse wave signal according to various embodiments of the present disclosure. An example of the process is shown.

Referring to FIG. 13, first, the electronic device acquires an accelerometer/gyroscope signal from an accelerometer/gyroscope sensor (1300). A smoothing operation is performed on the obtained accelerometer/gyroscope signal to provide noise and smooth the signal. Here, the smoothing operation may be performed using a low-pass filter or may be performed based on an exponential moving average method. In addition, the processed accelerometer/gyroscope signal is down-sampled to reduce the computational cost of the algorithm, and normalization is performed so that the processed accelerometer/gyroscope signal has a value between 0 and 1. The accelerometer/gyroscope signal is processed by performing the (Normalization) operation (1310). The electronic device obtains the information shown in FIG. 11F from the processed accelerometer/gyroscope signal and the processed optical volume pulse wave signal (1320). The electronic device acquires food intake-related probabilities using a machine learning algorithm based on the obtained information (1330). The electronic device estimates whether a food intake event has occurred based on the obtained food intake-related probabilities (1340). Here, the electronic device generates and provides a personalized recommendation for a user based on a result of whether the food intake event occurs.

14 illustrates an example of a method of operating an electronic device according to various embodiments of the present disclosure.

Referring to FIG. 14, the electronic device first measures the optical volumetric pulse wave, and acquires biometric information such as vascular stiffness based on the measured optical volumetric pulse wave (1400). The electronic device acquires user health information (eg, the user's physical activity, heart rate, blood oxygenation level, sleep quality, etc.) for a set first period, eg, a week or so (1410). The electronic device generates a personalized recommendation based on the obtained biometric information and user health information, and provides the generated personalized recommendation (1420). Here, the personalized personalized recommendation may be provided to a user through a device device included in the electronic device, for example. Thereafter, for a second set period, for example, about three months, the electronic device monitors whether or not the provided personalized recommendation has been observed (1430). The electronic device measures the optical volumetric pulse wave and acquires biometric information such as vascular stiffness based on the optical volumetric pulse wave (1440).

The electronic device checks whether or not the state of the vascular system has improved based on the biometric information acquired in step 1440 and whether to comply with the personalized recommendation (1450). The electronic device determines and provides whether to maintain or change the provided personalized recommendations based on whether or not the vascular system is improved. When it is determined that the state of the vascular system is improved, the electronic device maintains the personalized recommendation (1460). In contrast, when it is determined that the state of the vascular system has not improved, the electronic device changes the personalized recommendation. (1470).

Then, the electronic device monitors whether the maintained personal-customized recommendations or the changed personal-customized recommendations have been observed for a set third period, for example, a week, and returns to operation 1450 to improve the state of the vascular system. Performs an operation to check whether it is successful (1480).

In one aspect of the present disclosure, a personalized system for forming recommendations for users when implementing a healthy lifestyle is provided. Here, the personalized system is a smart watch including an accelerometer, a gyroscope, and a PPG sensor configured to sense and provide signals related to the user's physical activity, heart rate, blood oxygenation level, and sleep quality (here, the data , The data of the location based on the user's profile and geolocation is used to estimate the time of food intakes, eating habits and patterns of physical activity in consideration of the right-handed or left-handed), and the user's finger A smartphone including a PPG sensor that forms a photovoltaic pulse wave signal by touching it, and a processing unit that processes the signals of the PPG sensor that measures blood vessel stiffness that defines blood vessel age, and food intakes and during physical activity. Generate recommendations for the user, detect the relationship between the user behavior and user physiological changes based on signals received from the smart watch and/or smartphone, select the most appropriate recommendations, and the recommendations And a unit configured to display them.

Here, the personalized system further includes a smart scale configured to generate signals of the user's weight dynamics and transmit the food intakes and recommendations for physical activity to the unit.

Here, the unit for generating recommendations for the user upon the food intakes and physical activity is further configured to determine other types of deviations from the user's daily behavior, in particular to eat while on the move.

In another aspect of the present disclosure, a personalized system that forms recommendations for users is implemented when implementing a healthy lifestyle. The personalized system includes an accelerometer, a gyroscope, and a PPG sensor configured to sense and provide signals related to the user's physical activity, heart rate, blood oxygenation level, and sleep quality. The location data based on the user's profile and geolocation is used to estimate the time of food intakes, eating habits, and patterns of physical activity in consideration of right-handed or left-handed people, and the PPG sensor It is located on the side of the display and is configured to form an optical volume pulse wave signal by touching it with the user's finger); A unit that processes signals of the PPG sensor for estimating vascular stiffness that defines vascular age, and generates recommendations for the user in a eating habit pattern, and the user's behavior based on signals received from the smartwatch. And a unit configured to detect the association between the user's physiological changes, select the most suitable recommendations, and display recommendations on the watch display.

Here, the personalized system further includes a smart scale configured to generate signals of the user's weight dynamics and transmit the food intakes and recommendations for the user during physical activity to the unit.

Here, the personalized system further includes an ECG sensor including two electrodes, one of which is located on the display side of the smart watch, the second electrode is located on the rear surface of the smart watch, and the The sensor is configured to generate ECG signals and transmit them to the unit that generates recommendations for the user during the food intakes and physical activity.

Here, the personalized system is configured to generate signals of the dynamics of changes in the user's blood glucose level, and to transmit the signals to a unit that generates recommendations for the user during the food intakes and physical activity. And an invasive/non-invasive glucose sensor.

In another aspect of the present disclosure, a method of forming recommendations for a user in implementing a healthy lifestyle is provided. The method includes: measuring PPG on a smartphone by touching with the user's finger to estimate the blood vessel age based on the determination of the user's health condition; Based on observations on user behavior and collected data, detect unhealthy eating habits including physical activity and rules including time, duration, time periods and intensity of the food intakes, and the health status Forming recommendations for the user on how to change their eating habits and physical activity to improve them; Based on the dynamics of the changes in the health state being estimated based on the estimation of the blood vessel age, measuring the optical volume pulse wave repeatedly, and if necessary, changing the recommendations based on individual characteristics of the user's habits process; Including the process of performing periodic monitoring of compliance with the recommendations and, if necessary, adjusting or changing the recommendations to achieve a positive dynamic of the user's health status based on the estimation of the vascular age. do.

In another aspect of the present disclosure, a method of forming recommendations for a user in implementing a healthy lifestyle is provided. The method includes: measuring PPG on a smart watch by touching the user's finger to estimate the blood vessel age based on the determination of the user's health state; Based on observations on user behavior and collected data, detect unhealthy eating habits including physical activity and rules including time, duration, time periods and intensity of the food intakes, and the health status Forming recommendations for the user on how to change their eating habits and physical activity to improve them; Based on the dynamics of the changes in the health state being estimated based on the estimation of the blood vessel age, measuring the optical volume pulse wave repeatedly, and if necessary, changing the recommendations based on individual characteristics of the user's habits process; Including the process of performing periodic monitoring of compliance with the recommendations and, if necessary, adjusting or changing the recommendations to achieve a positive dynamic of the user's health status based on the estimation of the vascular age. do.

Here, the method further includes taking into account the dynamics of the user's body weight when adjusting or changing the recommendations to achieve a positive dynamics of the user's health status.

Here, the method further includes taking into account the user's ECG when adjusting or changing the recommendations to achieve a positive dynamic of the user's health status.

Here, the method further includes taking into account the dynamics of changes in glucose content when adjusting or changing the recommendations to achieve a positive dynamics of the health status of the user.

In addition, in the method of operating an electronic device according to the present disclosure, a photoplethysmogram (PPG) as a method for inferring or predicting information on a user's physical activity, heart rate, blood oxygenation level, and ingested food. Related information or an artificial intelligence model using an accelerometer and a gyroscope can be used. The processor may perform a preprocessing process on the data and convert it into a form suitable for use as an input of an artificial intelligence model. Artificial intelligence models can be created through learning. Here, to be made through learning means that a basic artificial intelligence model is learned using a plurality of learning data by a learning algorithm, so that a predefined motion rule or artificial intelligence model set to perform a desired characteristic (or purpose) is created. Means Jim. The artificial intelligence model may be composed of a plurality of neural network layers. Each of the plurality of neural network layers has a plurality of weight values, and a neural network operation is performed through an operation result of a previous layer and a plurality of weights.

Reasoning prediction is a technology that logically infers and predicts information by judging information, and includes knowledge based reasoning, optimization prediction, preference-based planning, and recommendation. Includes.

While the present invention has been described in connection with several exemplary embodiments, it should be understood that the invention is not limited to these specific embodiments. On the contrary, it is assumed that the present invention includes all alternatives, modifications and equivalents that may be included in the essence and scope of the claims.

Further, the present invention retains all equivalents of the claimed invention, even if the claims change during the examination procedure.

Meanwhile, each of the aforementioned components of the electronic device may be composed of one or more components, and the names of the corresponding components may vary according to the type of the electronic device. In various embodiments of the present disclosure, the electronic device may include at least one of the above-described components, and some components may be omitted or additional other components may be further included. In addition, some of the components of the electronic device according to various embodiments of the present disclosure are combined to form a single entity, so that the function of the corresponding component before the combination may be performed in the same manner.

In addition, the embodiments of the present disclosure are presented for description and understanding of the disclosed and technical content, and do not limit the scope of the present disclosure. Accordingly, the scope of the present disclosure should be construed as including all changes or various other embodiments based on the technical idea of the present disclosure.

Claims (21)

In the method of operating an electronic device,
Acquiring first information related to a user's photoplethysmogram (PPG) at a first time point;
Acquiring second information related to at least one of the user's physical activity, heart rate, blood oxygenation level, and sleep quality during the first period;
Estimating third information related to food intake based on the first information and the second information;
Providing personalized information for the user based on the first information, second information, and third information;
Obtaining additional information related to the personalized information during a second period;
Acquiring fourth information related to the PPG at a second point in time;
And maintaining or changing the personalized information based on the additional information and the fourth information. The method of claim 1,
The user's PPG is sensed through a PPG sensor included in the electronic device,
At least one of the user's physical activity, heart rate, blood oxygenation level, and sleep quality of the user is sensed by an accelerometer and a gyroscope included in the electronic device. The method of claim 1,
At least one of the first information and the second information is received from another electronic device outside the electronic device. The method of claim 1,
The third information is information obtained by estimating information related to food intake by comparing with data in a database based on processed information of the first information and the second information. The method of claim 4,
The third information includes information related to the time and number of times the user consumes food. The method of claim 1,
The additional information includes information related to the user's weight dynamics, information related to the user's physical activity, information related to the user's electrocardiogram (ECG), and information related to the user's glucose level. A method comprising at least one of. The method of claim 6,
When the additional information is information related to the user's glucose level, the information related to the user's glucose level includes information related to a change in the glucose level during the second period. The method of claim 1,
The first information includes information related to vascular stiffness. The method of claim 8,
The information related to the vascular stiffness is obtained based on a comparison result of the user's PPG and the set PPG. The method of claim 9,
Further comprising the process of providing the maintained or changed personal customized information,
The personalized information is provided so that the user's physical activity is restricted according to the user's vascular stiffness. In the electronic device,
display;
At least one processor connected to the display;
Including a memory connected to the at least one processor,
When the memory is executed, the processor:
Acquires first information related to the user's photoplethysmogram (PPG) at the first time point,
Acquiring second information related to at least one of the user's physical activity, heart rate, blood oxygenation level, or sleep quality during the first period,
Estimating third information related to food intake based on the first information and the second information,
Controlling the display to provide personalized information for the user based on the first information, second information, and third information,
Acquire additional information related to the personalized information during the second period,
Acquires the fourth information related to the PPG at the second time point,
An electronic device that stores instructions for maintaining or changing the personalized information based on the additional information and the fourth information. The method of claim 11,
A PPG sensor that senses the user's PPG;
An electronic device further comprising an accelerometer and a gyroscope for sensing at least one of the user's physical activity, heart rate, blood oxygenation level, and sleep quality. The method of claim 11,
The electronic device further comprises a receiver configured to receive at least one of the first information and the second information from another electronic device outside the electronic device. The method of claim 11,
The third information is information obtained by estimating information related to food intake by comparing with data in a database based on processed information of the first information and the second information. The method of claim 14,
The third information includes information related to a time and a number of times the user consumes food. The method of claim 11,
The additional information includes information related to the user's weight dynamics, information related to the user's physical activity, information related to the user's electrocardiogram (ECG), and information related to the user's glucose level. Electronic device including at least one of. The method of claim 16,
When the additional information is information related to the user's glucose level, the information related to the user's glucose level includes information related to a change in the glucose level during the second period. The method of claim 16,
An ECG sensor that senses the user's ECG;
An electronic device further comprising an invasive/non-invasive glucose sensor for sensing the user's glucose level. The method of claim 11,
The first information includes information related to vascular stiffness. The method of claim 19,
The information related to the vascular stiffness is obtained based on a comparison result of the user's PPG and a set PPG. The method of claim 19,
Further comprising the process of providing the maintained or changed personal customized information,
The personalized information is provided to limit the user's physical activity according to the user's blood vessel stiffness.

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