Predictive system and predictive computer program for hyperthyroidism using wearable device

Abstract

To provide a system and a computer program for managing and predicting hyperthyroidism using a wearable device.SOLUTION: The predictive system is a system for predicting hyperthyroidism using a resting heart rate, the system including: a wearable device for measuring the heart rate of a patient at regular intervals; and a bio-signal computing device for receiving heart rate information from the wearable device, the bio-signal computing device outputting a warning alarm when the patient has a resting heart rate greater than a reference heart rate in a normal state.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a system and computer program for predicting hyperthyroidism, and more particularly to a system and computer program for managing and predicting hyperthyroidism using a wearable device. [Background technology]

[0002] Hyperthyroidism is a condition in which the thyroid gland secretes too much hormones for any reason, causing thyrotoxicosis. This can lead to weight loss or fatigue, and in severe cases, breathing difficulties or fainting. Hyperthyroidism is a common disease with a prevalence of about 2%, and in Korea, most patients are diagnosed with Graves' disease and treated with antithyroid drugs. In the case of antithyroid drugs, compliance with the drug intake, that is, taking the drug according to the prescription, is very important for treatment. In the past, hyperthyroidism was only managed in outpatient clinics, so even if patients were prescribed drugs and took them, after a certain period of time, they would often stop taking the drugs on their own accord without receiving additional medical treatment if their symptoms improved. Even if continuous treatment was performed, the medical team would usually try to stop taking the drugs after one to two years of taking the drugs, at the discretion of the medical team. In any case, if the drug is stopped, the recurrence rate reaches 50%, which is a problem. Even in cases of recurrence, symptoms are initially mild, so patients continue to live normally without feeling any major inconvenience, but it is only when symptoms worsen and the patient is in a state of severe thyrotoxicosis that they visit the hospital. In such cases, hospitalization is often unavoidable, and in severe cases, it can even result in death.

[0003] Until now, hyperthyroidism has relied solely on outpatient care to manage the disease and predict recurrence. The rule is that once a patient is diagnosed with hyperthyroidism, they should visit the hospital periodically for the rest of their life, but in reality this rule is not followed well, especially after medication is discontinued. Therefore, there is an urgent need to develop a system that can actively manage hyperthyroidism and predict recurrence without the need for outpatient care. Summary of the Invention [Problem to be solved by the invention]

[0004] The problem to be solved by the present invention is to provide a system capable of managing hyperthyroidism and predicting recurrence by utilizing a patient's vital signs, in particular resting heart rate, measured from a wearable device.

[0005] Another problem to be solved by the present invention is to provide a prediction computer program utilizing such a system.

[0006] The problems to be solved by the present invention are not limited to those mentioned above, and other problems not mentioned above will be clearly understood by those skilled in the art from the following description. [Means for solving the problem]

[0007] To achieve the above object, one embodiment of the present invention provides a system for predicting hyperthyroidism using a wearable device, which is a system for predicting hyperthyroidism using resting heart rate, and includes a wearable device that measures a patient's heart rate at regular intervals, and a biosignal calculation device that receives heart rate information from the wearable device and outputs a warning alarm to the patient if the resting heart rate is higher than a reference heart rate in a normal state.

[0008] The wearable device measures the patient's number of steps and transmits the measured number of steps to the biosignal calculation device, which extracts periods during a certain time period each day during which the number of steps is zero and calculates the resting heart rate using the heart rate measured in each period.

[0009] The biosignal calculation device calculates a median of the heart rate measured in each section, and The median of the medians is defined as the resting heart rate.

[0010] The biosignal calculation device calculates the median of the heart rates measured in each interval, and calculates the resting heart rate by weighting the median measured in the sleep interval more heavily than the median measured in the wake interval.

[0011] The baseline heart rate is defined as the average resting heart rate measured over a given number of euthyroid days.

[0012] The biological signal calculation device outputs the warning alarm if the average value of the resting heart rate for a predetermined number of consecutive days is greater than the reference heart rate.

[0013] The biosignal calculation device calculates the median of the heart rates measured in each section during a day when the number of steps is zero for at least 15 minutes, defines the median of the calculated medians as the resting heart rate for the relevant date, and outputs a warning alarm if the average resting heart rate for five consecutive days is 10 or more times higher than the reference heart rate.

[0014] To achieve the other object, a computer program stored in a medium according to one embodiment of the present invention is stored in a medium to execute the steps of receiving heart rate and step count information from a wearable device that is combined with a biosignal calculation device for predicting hyperthyroidism using the resting heart rate and measures a patient's heart rate and step count at a regular interval, extracting sections during a certain time period in a day in which the number of steps is below a certain value and defining the resting heart rate using the heart rate measured in each section, defining an average value of the resting heart rates measured during a predetermined number of days when thyroid function is normal as a reference heart rate, and outputting a warning alarm if the resting heart rate is higher than the reference heart rate.

[0015] Specific details of other embodiments are included in the detailed description and drawings. Effect of the Invention

[0016] As described above, according to the present invention, the patient can continuously monitor the treatment response, progress prediction, and recurrence prediction of hyperthyroidism by simply wearing a wearable device, which can be utilized for early diagnosis and treatment of recurrence after discontinuing medication. In addition, the wearable device can be used to continuously monitor the change in the patient's heart rate along with the amount of exercise, thereby improving the patient's compliance with medication and effectively predicting recurrence in patients who have discontinued medication.

[0017] Until now, the management of hyperthyroidism has relied solely on outpatient care, and there is currently no electronic device or computer software that can proactively manage the disease and predict recurrence. The inventors of the present invention have developed the prediction system and computer program of the present invention by analyzing the results of a one-year clinical study, and we hope that this development will be the first case of using digital healthcare in the management of hyperthyroidism. [Brief description of the drawings]

[0018] [Figure 1] FIG. 1 is a schematic diagram illustrating a system for predicting hyperthyroidism according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a schematic diagram of the biological signal calculation device of FIG. 1. [Diagram 3] 1 is a flow chart sequentially illustrating a method for predicting hyperthyroidism according to an embodiment of the present invention. [Figure 4] FIG. 1 is a schematic diagram showing a clinical method using the prediction system of the present invention. [Diagram 5] FIG. 5 shows thyroid hormone concentrations measured at patient visits during the course of the clinical study of FIG. 4. [Figure 6] FIG. 5 shows the resting heart rate measured in the clinical study of FIG. 4. [Figure 7] FIG. 5 is a graph showing the correlation between thyroid hormone concentrations and resting heart rate measured in the clinical study of FIG. 4. [Figure 8] This is a graph showing the correlation between changes in resting heart rate measured by a wearable device and hyperthyroidism in the clinical study of Figure 4. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0019] The advantages and features of the present invention, as well as the methods for achieving them, will become apparent from the following detailed description of the embodiments in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, and may be embodied in various different forms. However, the embodiments are provided to fully disclose the present invention, and to fully inform those skilled in the art of the scope of the invention, and the present invention is defined only by the claims. The same reference numerals refer to the same elements throughout the specification.

[0020] Hereinafter, a system for predicting hyperthyroidism according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings.

[0021] Fig. 1 is a schematic diagram of a hyperthyroidism prediction system according to an embodiment of the present invention. Fig. 2 is a schematic diagram of a biological signal calculation device of Fig. 1. The prediction system of the present invention is a system for predicting hyperthyroidism using a patient's resting heart rate, and includes a wearable device 20 that measures the patient's biological signal, and a biological signal calculation device 30 that communicates with the wearable device 20 to receive and calculate the biological signal.

[0022] The wearable device 20 communicates with the biosignal calculation device 30 via a network, measures the biosignals of the patient 10, such as the heart rate and the number of steps, and transmits the measured biosignals to the biosignal calculation device 30. The wearable device 20 is connected to the biosignal calculation device 30 via wired or wireless communication, and is preferably an electronic device that performs wireless communication functions such as Wi-Fi and Bluetooth (registered trademark (bluetooth)). For example, various devices such as a smart watch and a smart band may be used as the wearable device 20. The wearable device 20 includes a communication module for wired and wireless communication, and a sensor for measuring the heart rate and the number of steps. The sensor built into the wearable device 20 includes one or more sensing means for grasping the shape and movement of the body of the patient 10, and may include, for example, a heart rate sensor, a gravity sensor, an acceleration sensor, a gyroscope, a GPS sensor, or a combination thereof.

[0023] It is preferable that the patient 10 always wears the wearable device 20, and the wearable device 20 measures the heart rate of the patient 10 at regular intervals, for example, 5 to 10 times per minute. In addition, the wearable device 20 measures the number of steps based on the movement of the patient 10 whenever such movement occurs.

[0024] The biosignal calculation device 30 is an electronic device that receives a biosignal from the wearable device 20 and calculates it to manage and predict hyperthyroidism. The biosignal calculation device 30 is an electronic device that performs a communication function via wireless communication while the user is moving, and may be, for example, a mobile phone including a smartphone, a tablet PC, a PDA, a wearable device, a smart watch, a smart band, or the like.

[0025] The biological signal calculation device 30 includes a communication unit 31, a processor 32, a calculation unit 33, an input unit , an output unit 35, and a memory .

[0026] The communication unit 31 of the biosignal calculation device 30 performs wired and wireless communication with an external electronic device. The communication unit 31 is responsible for transmitting and receiving data with the wearable device 20, and also for data communication and voice communication with a communication carrier.

[0027] The calculation unit 33 of the biosignal calculation device 30 manages and predicts hyperthyroidism of the patient 10 using the biosignal received from the wearable device 20. In detail, the calculation unit 33 defines a reference heart rate and a resting heart rate from the measured heart rate. Here, <heart rate> is a value measured by the wearable device 20, and <reference heart rate> and <resting heart rate> are values ​​calculated from the heart rate. The process of calculating the reference heart rate and the resting heart rate is as follows.

[0028] First, the calculation unit 33 extracts a section in which the number of steps is zero for a certain period of time (e.g., 15 minutes or more) during a day from the data measuring the number of steps of the patient. The extracted section is considered to be one in which the patient does not move or exercise, and the resting heart rate is calculated using the heart rate measured in each section. In detail, the calculation unit 33 calculates the median (referred to as the "section median") of the multiple heart rates measured within each section, and defines the median of the section medians calculated throughout the day (e.g., from 0:00 to 24:00) as the "resting heart rate." Since there is a possibility that the heart rate may change significantly at the boundaries of sections, such errors can be reduced as much as possible by selecting the median rather than the average value.

[0029] As a modified example, the calculation unit 33 may calculate the resting heart rate by applying different weights to the median values ​​for each section calculated throughout the day. In more detail, the section with zero steps can be divided into a <wake-up section> and a <sleep section>, where the <wake-up section> is defined as a section with zero steps for a certain period of time when the patient is awake, and the <sleep section> is defined as a section with zero steps for a certain period of time when the patient is asleep. For example, a method of calculating the resting heart rate by applying weights is expressed as in the following formula (1). According to formula (1), the correlation with hyperthyroidism can be further increased by calculating the resting heart rate by applying a weight to the heart rate in the sleep section more than the heart rate in the wake-up section.

[0030] Formula (1) Resting heart rate = [A x (median of the medians for each section for the wake-up section) + B x (median of the medians for each section for the sleep section)] / (A + B) (However, 0 <A<B) The baseline heart rate, on the other hand, is defined as the average resting heart rate measured over a given number of days while the patient is in a normal state (i.e., euthyroid).

[0031] In this way, the calculation unit 33 defines the reference heart rate and the resting heart rate from the measured heart rate, and then outputs a warning alarm via the output unit 35 or the wearable device 20 if the resting heart rate is greater than the reference heart rate. Preferably, the calculation unit 33 outputs a warning alarm if the average value of the resting heart rate for a predetermined number of consecutive days (e.g., 5 or more consecutive days) is greater than the reference heart rate by a predetermined value (e.g., 10 times) or more. In the present invention, the difference between the resting heart rate and the reference heart rate is used to manage and predict hyperthyroidism, and the correlation between the resting heart rate, the resting heart rate, and hyperthyroidism will be described in detail later.

[0032] The input unit 34 of the biosignal calculation device 30 includes a software or hardware input device, and the output unit 35 includes a speaker and a display. The display includes a user interface as a means for sensing a user's touch input in the UI / UX of the operating system software and the UI / UX of the application software. The display is a means for outputting a screen, and is also a touch screen that performs the function of an input means for sensing a user's touch event.

[0033] The memory 36 of the biosignal processing device 30 generally provides a place to store computer code and data used in the device. The memory 36 stores various applications and the resources required to run and manage them, as well as firmware for any device including a basic input / output system, operating system, various programs, applications, or user interface functions executed in the device, processor functions, etc.

[0034] The processor 32 of the biosignal processing device 30 executes computer code together with the operating system to perform operations for generating and using data. The processor 32 also uses a series of commands to receive and process input and output data between components of the biosignal processing device 30. The processor 32 also serves as a controller that executes the functions of the operating system software and various application software installed in the biosignal processing device 30.

[0035] Although additional or conventional components of the biosignal processing device 30, such as a power supply, a communication modem, a GPS, an I / O device, and hardware and software modules such as a camera module, are not shown, the biosignal processing device 30 of the present invention includes various internal and external components that contribute to the function of the device. Additionally, the biosignal processing device 30 may include hardware elements (including circuitry), software elements (including computer code stored on a computer readable medium), or a combination of these two elements.

[0036] In this embodiment, the wearable device 20 and the biosignal processing device 30 are physically separated, but the present invention is not limited to this. In other words, the biosignal processing device 30 may be physically included in the wearable device 20. In this case, the wearable device 20 and the biosignal processing device 30 should be regarded as one integrated physical electronic device.

[0037] Hereinafter, a method for predicting hyperthyroidism according to an embodiment of the present invention will be described in detail with reference to Fig. 3. Fig. 3 is a flow chart sequentially illustrating a method for predicting hyperthyroidism according to an embodiment of the present invention.

[0038] First, the wearable device 20 periodically measures the heart rate and the number of steps of the patient 10, and transmits these to the biosignal calculation device 30 (S10).

[0039] The biosignal calculation device 30 receives the heart rate and the number of steps from the wearable device 20 and calculates the resting heart rate S20. In detail, the biosignal calculation device 30 extracts a section in which the number of steps is zero for a certain period of time (e.g., 15 minutes or more) in a day from the patient's step count data. The biosignal calculation device 30 calculates the section-by-section median for the heart rate in each section, and defines the median of the section-by-section median for the day as the "resting heart rate". As a variant, the biosignal calculation device 30 may calculate the resting heart rate by weighting the heart rate in the sleep section more heavily than the heart rate in the wake section, as in Equation (1).

[0040] Furthermore, the biological signal calculation device 30 defines the average value of the resting heart rate measured during a predetermined number of days when the patient's thyroid function is normal as the "reference heart rate" (S30).

[0041] Next, the biosignal calculation device 30 compares the resting heart rate with the reference heart rate S40, and if the resting heart rate is greater than the reference heart rate, outputs a warning alarm S50 via its own output unit or the wearable device 20. For example, the biosignal calculation device 30 may output a warning alarm if the average value of the resting heart rate for a predetermined number of consecutive days (e.g., 5 or more consecutive days) is greater than the reference heart rate by a predetermined value (e.g., 10 times) or more.

[0042] Hereinafter, the contents of a clinical study on the correlation between heart rate and hyperthyroidism, on which the prediction system of the present invention is based, will be described in detail with reference to FIGS.

[0043] FIG. 4 is a schematic diagram showing a clinical method using the prediction system of the present invention. In this clinical study, in order to confirm the correlation between thyroid function and heart rate, 30 hyperthyroid patients (including new and recurrent patients) were recruited and had to wear a wearable device to continuously monitor their heart rate. The wearable device used in this clinical study was the Fitbit Charge HR. TM and Fitbit Charge 2 TM The patient wearing the wearable device visited the hospital three times, and while undergoing treatment with antithyroid drugs, the changes in thyroid hormone concentration during treatment were compared with the changes in heart rate measured by the wearable device. In order to compare the degree of correlation between changes in heart rate measured by the wearable device and changes in thyroid function with conventional methods, the heart rate measured by an automatic blood pressure monitor and the Hyperthyroid Symptom Scale (HSS) were simultaneously measured and analyzed at each visit to the hospital.

[0044] Figure 5 shows the thyroid hormone concentrations measured at the time of the patient's visit during the clinical study process shown in Figure 4. In Figure 5, BMI is Body Mass Index, SBP is Systolic Blood Pressure, DBP is Diastolic Blood Pressure, HR is Heart Rate, HSS is Hyperthyroid Symptom Scale, free T4 is thyroid hormone, TSH is Thyroid Stimulating Hormone, TB is Total Bilirubin, ALP is Alkaline Phosphates, AST is Aspartate Transaminase, ALT is Alamine Transaminase, and WBC is White Blood Cells. It was found that the more antithyroid drug treatment is administered to hyperthyroid patients, that is, the thyroid hormone (free T4) values ​​measured at the second and third visits compared to the first visit gradually decrease and enter the normal range (0.8-1.8ng / dL).

[0045] FIG. 6 shows the resting heart rate measured in the clinical study of FIG. 4. In detail, FIG. 6 shows the change in resting heart rate measured by the wearable device over time. It was found that the more antithyroid drug treatment was administered to hyperthyroid patients, the more the resting heart rate measured by the wearable device gradually decreased.

[0046] The correlation between the measured heart rate and the concentration of thyroid hormone was examined. Figure 7 is a graph showing the correlation between the concentration of thyroid hormone measured in the clinical study in Figure 4 and the resting heart rate. In Figure 7, WD-rHR is the resting heart rate obtained through the wearable device, HSS is the value obtained by adding up the scores of 10 representative symptoms of hyperthyroidism scored from 0 to 5 points through a questionnaire survey, and on-site HR (or HR) is the heart rate measured with a blood pressure monitor at the hospital when the patient visited the hospital, that is, on the day of the blood test. To compare the heart rate data (WD-rHR and on-site HR) with the HSS data, the standard deviation for the average of each index was used for comparison. In this case, the resting heart rate (WD-rHR) measured with the wearable device showed the greatest correlation.

[0047] Figure 8 is a graph showing the correlation between changes in resting heart rate measured by a wearable device and hyperthyroidism in the clinical study shown in Figure 4. In detail, Figure 8 shows the probability of being classified as hyperthyroidism when each index increases by 1 SD (standard deviation) by dividing the data in Figure 7 into two groups: when thyroid hormone (free T4) is greater than 1.8 ng / dL (i.e., greater than the upper limit of normal and falling into the range of hyperthyroidism) and when it is not, respectively. In the case of resting heart rate (WD-HR) measured by a wearable device, the probability of being classified as hyperthyroidism increases threefold when resting heart rate increases by 1 SD (about 10 beats). These results show that the single index of resting heart rate (WD-HR) measured by a wearable device showed a stronger predictive power than the index (HSS) that scores various symptoms of hyperthyroidism, and that heart rate (HR) measured by the conventional method at a hospital did not show a statistically significant predictive power of hyperthyroidism.

[0048] In this way, it has been found that the change in resting heart rate measured by the wearable device is closely related to the prevalence or recurrence rate of hyperthyroidism, and by using the prediction system of the present invention, the degree of hyperthyroidism control can be evaluated and recurrence can be easily predicted from the change in resting heart rate, without the patient having to visit the hospital in person, simply by wearing the wearable device. If the resting heart rate shows signs of abnormally increasing compared to the reference heart rate, the prediction system can warn the patient of abnormal thyroid function and notify them to undergo a blood test.

[0049] Although the embodiments of the present invention have been described with reference to the attached drawings, those skilled in the art will understand that the present invention can be embodied in other specific forms without changing the technical concept or essential features of the present invention. Therefore, it should be understood that the above-described embodiments are illustrative in all respects and are not limiting.

Claims

1. 1. A method for providing an alert of a potential thyroid abnormality, comprising: acquiring a heart rate and movement of the person using a wearable device worn by the person to provide data including the heart rate and movement of the person; calculating a first resting heart rate for the person using data acquired by the wearable device during a first set of consecutive days during which the person is euthyroid; calculating a second resting heart rate for the person using data acquired by the wearable device for a second set of consecutive days; and outputting an alert to the person if the second resting heart rate is greater than the first resting heart rate by a predetermined value or more; the first resting heart rate is calculated using data acquired during the first set of consecutive days, and the person's free T4 is measured during the first set of consecutive days to confirm that the person is euthyroid; wherein the second resting heart rate is calculated using data obtained on the second set of consecutive days without the person visiting a medical facility.

2. 10. The method of claim 1, wherein the alert suggests that the person take a blood test.

3. 2. The method of claim 1, wherein the first set of consecutive days is a predetermined number of consecutive days.

4. 2. The method of claim 1, wherein the second set of consecutive days is a predetermined number of consecutive days.

5. Calculating the first resting heart rate includes identifying time intervals during which the person is not moving during the first set of consecutive days and obtaining a heart rate value for each of the identified time intervals; 2. The method of claim 1, wherein calculating the second resting heart rate comprises identifying time intervals during the second set of consecutive days during which the person is not moving and obtaining a heart rate value for each identified time interval.

6. Calculating the first resting heart rate includes identifying time intervals during which the person is not moving during the first set of consecutive days and obtaining a heart rate value for each of the identified time intervals; the heart rate value being a median heart rate value for each of the identified time intervals; 2. The method of claim 1, wherein the first resting heart rate is a median or mean heart rate value for the identified time interval.

7. Calculating the second resting heart rate includes identifying time intervals during which the person is not moving during the second set of consecutive days and obtaining a heart rate value for each of the identified time intervals; the heart rate value being a median heart rate value for each of the identified time intervals; 2. The method of claim 1, wherein the second resting heart rate is a median or mean heart rate value for the identified time interval.

8. 2. The method of claim 1, wherein the first resting heart rate is calculated using data obtained on the first set of consecutive days, and wherein measuring the person's free T4 on the first set of consecutive days while the person is undergoing antithyroid drug therapy that reduces free T4 over time confirms that the person is euthyroid.

Images