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 excessive secretion of hormones from the thyroid gland, for any reason, leads to thyrotoxicosis. This can result in weight loss, fatigue, and in severe cases, shortness of breath or fainting. Hyperthyroidism is a common condition with a prevalence of approximately 2%. In Korea, most patients are diagnosed with Graves' disease and treated with antithyroid drugs. Medication compliance—taking the medication as prescribed—is crucial for treatment. Traditionally, hyperthyroidism was managed solely through outpatient care. Patients often discontinued medication without further medical care if their symptoms improved after a certain period of time. Even with sustained treatment, discontinuation of medication is typically attempted one to two years after the initial drug administration, at the discretion of the medical team. Regardless of the circumstances, discontinuing medication presents a problem, as the recurrence rate reaches 50%. Even in cases of recurrence, symptoms are initially mild, so patients continue to live their lives without major inconvenience, but it is only when symptoms worsen and they develop severe thyroid toxicity that they visit the hospital. In such cases, hospitalization is often unavoidable, and in severe cases, it can even lead to death.

[0003] Until now, hyperthyroidism has relied solely on outpatient care to manage the disease and predict recurrence. While the general rule is that patients diagnosed with hyperthyroidism should visit the hospital periodically throughout their lives, this rule is often not followed in reality, especially after medication is discontinued. Therefore, there is a pressing need for a system that can actively manage hyperthyroidism and predict recurrence without outpatient care. This research was supported by the Community-Based Software Service Business Commercialization Support Project (No. S2001-24-1007) by the National Institute of Information and Communications Technology (NIPA), Korea, funded by the Ministry of Science and ICT, Korea. 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 that can manage hyperthyroidism and predict recurrence by utilizing a patient's biosignals, particularly 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 that utilizes such a system.

[0006] The problems to be solved by the present invention are not limited to those described above, and other problems not described 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 when 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 where the number of steps is zero for at least 15 minutes in a day, defines the median of the calculated medians as the resting heart rate for the corresponding date, and outputs a warning alarm if the average resting heart rate for five consecutive days is 10 times or more higher than the reference heart rate.

[0014] To achieve the other object, according to one embodiment of the present invention, a computer program stored in a medium is stored in a medium to execute the following steps: receiving heart rate and step count information from a wearable device that is combined with a biosignal calculation device that predicts hyperthyroidism using the resting heart rate and measures the patient's heart rate and step count at regular intervals; extracting intervals during a certain time period in a day when the number of steps is below a certain value and defining the resting heart rate using the heart rate measured in each interval; 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 specific content and drawings. [Effects of the Invention]

[0016] As described above, according to the present invention, by simply having a patient wear a wearable device, it is possible to continuously monitor the treatment response, progress prediction, and recurrence prediction of hyperthyroidism, which can be utilized for early diagnosis and treatment of recurrence after discontinuing medication. In addition, by continuously monitoring changes in the patient's heart rate along with the amount of exercise using the wearable device, it is possible to improve the patient's compliance with medication and effectively predict recurrence in patients who have discontinued medication.

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

[0018] [Figure 1] FIG. 1 is a diagram illustrating a system for predicting hyperthyroidism according to an embodiment of the present invention. [Figure 2] FIG. 2 is a schematic diagram of the biological signal calculation device of FIG. 1. [Figure 3] 1 is a flowchart sequentially illustrating a method for predicting hyperthyroidism according to an embodiment of the present invention. [Figure 4] FIG. 1 is a diagram illustrating a clinical method using the prediction system of the present invention. [Figure 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] 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 with a wearable device and hyperthyroidism in the clinical study shown in Figure 4. DETAILED DESCRIPTION OF THE INVENTION

[0019] The advantages and features of the present invention, as well as 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, these embodiments are provided so that the disclosure of the present invention will be complete and will fully convey the scope of the invention to those skilled in the art. The present invention is defined only by the claims. Like reference numerals refer to like 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 diagram schematically illustrating a system for predicting hyperthyroidism according to an embodiment of the present invention. Fig. 2 is a diagram roughly illustrating the configuration of the 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 signals, and a biological signal calculation device 30 that communicates with the wearable device 20 to receive and calculate the biological signals.

[0022] The wearable device 20 communicates with the biosignal processing device 30 via a network, measures biosignals of the patient 10, such as heart rate and step count, and transmits the measured biosignals to the biosignal processing device 30. The wearable device 20 is connected to the biosignal processing device 30 via wired or wireless communication, and is preferably an electronic device that has a wireless communication function such as Wi-Fi or Bluetooth (registered trademark). For example, various devices such as a smart watch or 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 sensors for measuring heart rate and step count. The sensors built into the wearable device 20 include one or more sensing means for determining the shape and movement of the patient 10's body, 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 periodically, for example, 5 to 10 times per minute. The wearable device 20 also measures the number of steps taken by the patient 10 based on any movement of the patient 10.

[0024] The biosignal calculation device 30 is an electronic device that receives biosignals from the wearable device 20, calculates them, and manages and predicts hyperthyroidism. The biosignal calculation device 30 is an electronic device that performs communication functions 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, etc.

[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 external electronic devices. The communication unit 31 is responsible for sending and receiving data to and from the wearable device 20, as well as data communication and voice communication with telecommunications carriers.

[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 intervals during a certain period of time (e.g., 15 minutes or more) during which the number of steps is zero from the data measuring the patient's number of steps. The extracted intervals are considered to be periods during which the patient does not move or exercise, and the resting heart rate is calculated using the heart rate measured in each interval. Specifically, the calculation unit 33 calculates the median (referred to as the "interval median") of the multiple heart rates measured within each interval, and defines the median of the interval medians calculated for an entire day (e.g., from midnight to midnight) as the "resting heart rate." Because heart rate may fluctuate significantly at interval boundaries, selecting the median rather than the average value can minimize such errors.

[0029] As a variant, the calculation unit 33 may calculate the resting heart rate by assigning different weights to the median values ​​for each section calculated throughout the day. More specifically, sections with zero steps can be divided into a <wake-up section> and a <sleep section>. A <wake-up section> is defined as a section with zero steps for a certain period of time while the patient is awake, and a <sleep section> is defined as a section with zero steps for a certain period of time while the patient is asleep. For example, a method of assigning weights to calculate the resting heart rate is expressed as in the following equation (1). According to equation (1), by assigning a weight to the heart rate in the sleep section more than to the heart rate in the wake-up section to calculate the resting heart rate, the correlation with hyperthyroidism can be further improved.

[0030] Formula (1) Resting heart rate = [A × (median of the medians for each section of the wake-up section) + B × (median of the medians for each section of the sleep section)] / (A + B) (However, 0 <A<B) On the other hand, the baseline heart rate is defined as the average resting heart rate measured over a given number of days when 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 if the resting heart rate is higher than the reference heart rate, it outputs a warning alarm via the output unit 35 or the wearable device 20. Preferably, the calculation unit 33 outputs a warning alarm if the average resting heart rate over a predetermined number of consecutive days (e.g., five or more consecutive days) is higher than the reference heart rate by a predetermined value (e.g., 10 times) or more. In the present invention, hyperthyroidism is managed and predicted using the difference between the resting heart rate and the reference heart rate, and the correlation between the resting heart rate, the resting heart rate, and hyperthyroidism will be described in detail below.

[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 also includes a touch screen that functions as an input means for sensing a user's touch event.

[0033] The memory 36 of the biosignal processing device 30 generally provides a storage location for computer code and data used by 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 and processor functions executed by the device.

[0034] The processor 32 of the biosignal processing device 30 executes computer code together with the operating system to generate and use 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 control unit 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 such as a power supply, a communications modem, a GPS, I / O devices, 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. The biosignal processing device 30 may also 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, an example is described in which 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 within the wearable device 20. In this case, the wearable device 20 and the biosignal processing device 30 should be considered as a single 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 flowchart 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 biological signal calculation device 30 (S10).

[0039] The biosignal calculation device 30 receives the heart rate and step count from the wearable device 20 and calculates the resting heart rate S20. Specifically, the biosignal calculation device 30 extracts sections of the patient's step count data where the step count is zero for a certain period of time (e.g., 15 minutes or more) during one day. The biosignal calculation device 30 calculates the section-by-section median of the heart rate for each section, and defines the median of the section-by-section medians for one 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 during the sleep section more heavily than the heart rate during the wake section, as shown in Equation (1).

[0040] Furthermore, the biological signal calculation device 30 defines the average value of the resting heart rate measured over 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., five or more consecutive days) is greater than the reference heart rate by a predetermined value (e.g., 10 times) or more.

[0042] Hereinafter, with reference to FIGS. 4 to 8, 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.

[0043] Figure 4 is a diagram illustrating a clinical method using the prediction system of the present invention. In this clinical study, to confirm the correlation between thyroid function and heart rate, 30 hyperthyroidism patients (including new and recurrent cases) were recruited and had their heart rate continuously monitored by wearing a wearable device. The wearable device used in this clinical study was the Fitbit Charge HR. TM and Fitbit Charge 2 TM The patients wearing the wearable device visited the hospital three times and were treated with antithyroid drugs. Changes in thyroid hormone levels during treatment were compared with changes in heart rate measured by the wearable device. To compare the correlation between changes in heart rate measured by the wearable device and changes in thyroid function with conventional methods, heart rate measured with an automated blood pressure monitor and the Hyperthyroid Symptom Scale (HSS) were simultaneously measured and analyzed at each hospital visit.

[0044] Figure 5 shows thyroid hormone levels measured at patient visits during the clinical study 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 phosphate, AST is aspartate transaminase, ALT is alamine transaminase, and WBC is white blood cells. As hyperthyroid patients received antithyroid drug treatment, their thyroid hormone (free T4) levels measured at the second and third visits gradually decreased compared to the first visit, falling within the normal range (0.8-1.8 ng / dL).

[0045] Figure 6 shows the resting heart rate measured in the clinical study in Figure 4. In detail, Figure 6 shows the change in resting heart rate measured by the wearable device over time. It was found that the resting heart rate measured by the wearable device gradually decreased as the hyperthyroidism patients received more antithyroid drug treatment.

[0046] We investigated the correlation between the measured heart rate and thyroid hormone concentrations. Figure 7 shows the correlation between thyroid hormone concentrations measured in the clinical study (Figure 4) and resting heart rate. In Figure 7, WD-rHR is the resting heart rate obtained via the wearable device, HSS is the sum of scores for 10 representative symptoms of hyperthyroidism, which were scored from 0 to 5 via a questionnaire survey, and on-site HR (or HR) is the heart rate measured with a blood pressure monitor at the hospital on the day of the blood test. To compare the heart rate data (WD-rHR and on-site HR) with the HSS data, we used the standard deviation of each index's mean. In this case, the resting heart rate (WD-rHR) measured via 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. Specifically, Figure 8 shows the probability of being classified as hyperthyroidism when each indicator increases by 1 standard deviation (SD), dividing the data from Figure 7 into two groups: those with thyroid hormone (free T4) levels above 1.8 ng / dL (i.e., above the upper limit of normal and falling into the hyperthyroidism range) and those without. In the case of resting heart rate (WD-HR) measured by a wearable device, a 1 SD increase (approximately 10 beats) in resting heart rate was associated with a three-fold increase in the likelihood of being classified as hyperthyroidism. These results indicate that the single indicator, resting heart rate (WD-HR) measured by a wearable device, exhibited stronger predictive power than the HSS, which scores various symptoms of hyperthyroidism. However, conventional hospital-based heart rate (HR) measurements did not demonstrate statistically significant predictive power for hyperthyroidism.

[0048] As such, it has been found that changes in resting heart rate measured by a wearable device are 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 changes in resting heart rate, without the patient having to visit a hospital in person, simply by wearing a wearable device. If the resting heart rate shows signs of abnormally increasing compared to the baseline heart rate, the prediction system can warn the patient of abnormal thyroid function and recommend that they undergo a blood test.

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

Claims

1. 1. A method of 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 when the person is euthyroid; and 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 when 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 obtained on the first set of consecutive days, and the person's free T4 is measured on 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 which the person is not moving during the second set of consecutive days 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 is 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 is 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 the person's free T4 is measured on the first set of consecutive days while the person is undergoing antithyroid drug treatment that reduces free T4 over time to confirm that the person is euthyroid.

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