Apparatus for diagnosing abnormalities by measuring minute changes in muscle

Abstract

According to an embodiment, an apparatus for diagnosing an abnormality by measuring a slight change in a muscle includes a vibration unit that provides a vibration to a body part of a user, a measurement unit that detects a slight change in the muscle by measuring a change in elasticity of the body part according to the vibration, and a processing unit that calculates an abnormality of the body part based on the change in elasticity of the body part, wherein the processing unit calculates the abnormality of the body part by using an algorithm that detects a degree to which a specific value of the muscle deviates from a distribution map by analyzing a data distribution or an abnormality detection algorithm that detects whether an abnormality is present in a variable.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to Korean Patent Application No. 10-2021-0192377, filed on December 30, 2021, which is hereby incorporated by reference in its entirety for all purposes. Technical Field

[0003] The present invention relates to a device for diagnosing abnormalities by measuring minimal changes in muscles, and more particularly, to a device capable of providing vibrations to a body part of a user and simultaneously calculating abnormalities of the body part based on changes in muscles of the body part.

[0004] This research was conducted under the supervision of the Korea Institute of Science and Technology and Korea University Ansan Hospital with support from the KUMedicine-KISTTRC Joint Research Project (Project Title: Development of an Early Diagnosis and Monitoring System for Deep Vein Thrombosis in the Limbs Using Sensor Fusion Technology, Project Identification Number: 2E3115J). Background Art

[0005] Deep vein thrombosis (DVT) is a condition that occurs due to blood clots in the veins. It occurs when blood stagnates in the veins of a body part (primarily the lower extremities) and forms blood clots in the deep veins, often caused by prolonged periods of stationary position or in situations where blood clots may develop. It's also known as "economy class syndrome" because it's a common condition among passengers sitting in cramped seats during long-haul flights. If left untreated, DVT can lead to limb necrosis, pulmonary embolism, and respiratory distress, leading to death. Therefore, it's crucial to diagnose these symptoms early and prevent the condition from worsening.

[0006] Traditionally, deep vein thrombosis is mainly diagnosed by examining the patient's body through ultrasound or blood tests. Such diagnostic methods may be effective when the patient can undergo periodic ultrasound or blood tests in hospitals, clinics, etc., but if it is caused by long-distance flights or driving, early diagnosis is difficult. There are preemptive methods such as mechanical prevention (compression stockings, air compression equipment, etc.) or pharmacological prevention (taking anticoagulants, etc.), but in many cases, practical application is difficult, resulting in a large number of patients with deep vein thrombosis every year.

[0007] Related Literature

[0008] (Patent Document 1) KR Patent Publication No. 10-2010-0049382 SUMMARY

[0009] Accordingly, an object of the present application is to provide a diagnostic apparatus that is capable of not only calculating an abnormality of a body part based on a change in a muscle of the body part, but also diagnosing deep vein thrombosis (DVT) at an early stage.

[0010] The apparatus for diagnosing an abnormality by measuring a slight change in a muscle according to an embodiment includes a vibration unit that provides a vibration to a body part of a user, a measurement unit that detects a slight change in a muscle by measuring a change in elasticity of the body part according to the vibration, and a processing unit that calculates an abnormality of the body part based on the change in elasticity of the body part, wherein the processing unit calculates the abnormality of the body part by using an algorithm that detects a degree to which a specific value of the muscle deviates from a distribution map by analyzing a data distribution or an abnormality detection algorithm that detects whether an abnormality is present in a variable.

[0011] According to an embodiment, the processing unit can calculate a risk of thrombosis based on the abnormality of the body part.

[0012] According to an embodiment, the apparatus can further include a display unit that displays the risk of thrombosis.

[0013] According to an embodiment, the apparatus can further include a control unit that controls an operation of the vibration unit.

[0014] According to an embodiment, the vibration unit can receive a control signal from the control unit and provide a vibration of a specific frequency through a vibrator attached to the body part.

[0015] According to an embodiment, the apparatus can further include a pressure sensor positioned between the vibrator and the body part of the user to sense a pressure according to the vibration, wherein the processing unit can be configured to indicate the pressure according to the vibration through the display unit.

[0016] According to an embodiment, the measurement unit can include an accelerometer that detects a reflected vibration generated in the body part in response to the vibration.

[0017] According to an embodiment, the measurement unit can include an electromyograph that measures an electromyograph signal of the body part.

[0018] According to an embodiment, the processing unit can obtain an approximate function of each of the reflected vibration of the body part and the measured value of the EMG signal using a distribution of Bayesian probability values based on a change in the reflected vibration of the body part and the measured value of the EMG signal over time, and can convert each of the reflected vibration of the body part and the measured value of the EMG signal to a value in a range of 0 to 1 by using the calculated approximate function.

[0019] According to an embodiment, the anomaly detection algorithm used by the processing unit can include an Isolation Forest algorithm that detects anomalies by cutting the tree based on the anomaly data.

[0020] According to an embodiment, the display unit can indicate the risk of thrombus formation in a numerical manner through the display device.

[0021] According to an embodiment, the display unit can be configured to turn on the LED element when the risk of thrombus formation is greater than or equal to a threshold value.

[0022] According to an embodiment, the device can be implemented to be detachably wearable as a wearable patch.

[0023] According to an embodiment, the processing unit can use one or more of radio frequency (RF), Wi-Fi, cellular, Bluetooth, Bluetooth Low Energy (BLE), personal area network (PAN), short wave UHF, and combinations thereof to connect to wirelessly communicate with the display unit.

[0024] According to an embodiment of the present application, a device for early diagnosis of an anomaly of a body part provides a vibration of a specific frequency by using a vibrator attached to a user's body and measures a reflected vibration of a muscle sensed in response to the vibration and an EMG signal.

[0025] The diagnosis device according to an embodiment determines that the incidence of deep vein thrombosis is higher when there is an abnormal change in the reflected vibration measured by the accelerometer and / or the EMG signal measured by the electromyograph, and informs the user of an anomaly of the body part or a risk of thrombus formation in real time.

[0026] The diagnosis device according to an embodiment includes a vibrator attached to a body part and a sensor (accelerometer, electromyograph, etc.) capable of detecting a change in the body part, so that it is easy to install and use. For example, a vibrator and a sensor provided under an airplane seat can be used to measure the risk of thrombus formation at regular intervals. Thus, it is possible to diagnose deep vein thrombosis earlier than a conventional ultrasound or blood test method. BRIEF DESCRIPTION OF DRAWINGS

[0027] Figure 1 is a block diagram illustrating a concept of a device for diagnosing an anomaly by measuring a slight change in a muscle according to an embodiment.

[0028] Figures 2A to 2D A process in which the processing unit calculates a degree to which a reflected vibration or an EMG signal of a body part deviates from a data distribution by using a Bayesian algorithm according to an embodiment is illustrated.

[0029] Figures 3A to 3C A process in which the processing unit calculates an abnormality of a reflection vibration or an EMG signal of a body part using an abnormality detection algorithm according to an embodiment is illustrated.

[0030] Figure 4 A device for diagnosing an abnormality according to an embodiment is illustrated, which is implemented as a wearable patch and measures an abnormality by measuring a slight change in a muscle.

[0031] Figure 5 A process in which the processing unit calculates a risk of thrombus formation and the display unit warns a user through wireless communication according to an embodiment is illustrated. DETAILED DESCRIPTION

[0032] The terms used in the present specification are selected as general terms that are used as widely as possible in consideration of their functions, but can be different according to the intention or custom of the person skilled in the art or the appearance of new technology. Also, in a specific case, there are terms arbitrarily selected by the applicant, and in this case, the meaning thereof will be described in the corresponding description of the specification. Therefore, it is intended to clarify that the terms used in the present specification are not just the names of the terms, but should be interpreted based on the actual meaning of the terms and the contents of the entire specification.

[0033] Hereinafter, embodiments will be described in detail with reference to the accompanying drawings and the contents described in the drawings, but the scope of the claims is not limited or bound by the embodiments.

[0034] Figure 1 is a block diagram illustrating a concept of a device for diagnosing an abnormality by measuring a slight change in a muscle according to an embodiment. Referring to Figure 1 A device 10 for diagnosing an abnormality by measuring a slight change in a muscle according to an embodiment (hereinafter, "diagnosis device") is configured to include a vibration unit 110, a measurement unit 120, and a processing unit 130, a display unit 140, and a control unit 150.

[0035] Although the above-described components are separately illustrated for the convenience of conceptual description, they do not necessarily have to be implemented as independent devices or programs. For example, each of the components can be implemented by one processing unit or program, or can be implemented by an organic combination of two or more independent processing units or programs.

[0036] The vibration unit 110 receives a control signal from the control unit 150 and provides a vibration of a specific frequency through the vibrator 111 attached to the body part. The vibration unit 110 receives a control signal, for example, an input of the intensity, frequency, and form of the vibration to be provided to the user, from the control unit 150 and transmits it to the vibration unit 110 through a wire or wirelessly.

[0037] The vibrator 111 is a device having a power device such as a motor that converts electric energy into physical vibration, and is not limited to a specific shape or size. The vibrator 111 can be connected to the diagnostic device 10 through a wire or through a wireless network (Bluetooth, WiFi, infrared communication, etc.). Also, the vibrator 111 can be powered by a motor through a wire, or can be powered by a built-in battery. In one embodiment, the vibrator 111 can be attached to the user's body part (arm, leg, etc.) through a fixing part such as a band or an adhesive band that can be worn on the user's body part.

[0038] According to an embodiment, a pressure sensor (not shown) for sensing pressure according to vibration between the vibrator 111 and the user's body part can be further provided. The processing unit 130 to be described later can display a pressure change according to vibration on the display unit 140. This allows the user to know in real time whether the vibrator provides a proper pressure level of vibration. Accordingly, when the pressure is too low or too high, the operation of the vibration unit 110 and the vibrator 111 can be controlled by the control unit 150.

[0039] The measurement unit 120 can measure a change in elasticity of the body part according to the vibration provided by the vibration unit 110 to detect a slight change in the muscle. For example, when deep vein thrombosis (DVT) occurs, a blood clot is formed in the vein, which causes muscle stiffness, and the measurement unit 120 measures a change in elasticity of the muscle to detect these symptoms.

[0040] The measurement unit 120 detects a change in elasticity of the body part through the accelerometer 121 and / or the electromyograph 122 and warns the user by calculating the risk of abnormality or thrombosis of the body part when an abnormal change occurs.

[0041] According to an embodiment, the measurement unit 120 can sense a reflex vibration generated in the user's body part through the accelerometer 121. The reflex vibration refers to a tremor that occurs in the surrounding muscle when an arbitrary vibration stimulus is applied to the muscle. Generally, in an environment having the same muscle mass or blood flow, when a vibration stimulus of the same characteristics (intensity, frequency, stimulus interval) is applied, a reflex vibration of a corresponding characteristic occurs at a constant level. In contrast, when deep vein thrombosis occurs and the muscle becomes stiff or the blood flow changes, the characteristics of the reflex vibration sensed in the muscle rapidly change. The accelerometer 121 is a device for converting a minute movement of the muscle into an electrical signal, and detects a change in the vibration characteristics due to muscle atrophy or thrombosis and transmits it to the processing unit 130. After muscle atrophy or deep vein thrombosis occurs, the measured value of the reflex vibration is significantly changed.

[0042] According to an embodiment, the measurement unit 120 can measure an electromyography (EMG) signal of the user's body part through an electromyograph. The electromyograph is a device that records electrical activity according to muscle contraction using an electrode attached to or inserted into the body part. As with the above-described reflex vibration, when deep vein thrombosis occurs and the muscle is stiff or there is a change in the blood flow, the EMG signal also changes. The EMG 122 detects a change in the EMG signal and transmits it to the processing unit 130. After deep vein thrombosis occurs, the measured value of the EMG signal is significantly changed.

[0043] The processing unit 130 calculates an abnormality of the body part based on a change in elasticity of the body part. The processing unit 130 can calculate the abnormality of the body part by using an algorithm that analyzes a data distribution to detect how far a specific value of the muscle is from the distribution or an abnormality detection algorithm that detects whether there is an abnormality in a variable. In an embodiment, the abnormality of the body part calculated by the processing unit 130 can mean a risk of thrombosis.

[0044] The processing unit 130 combines and simultaneously uses the measurement results of the reflex vibration and the EMG signal (in this case, each measurement result can be given a weight), or independently uses each result to calculate an abnormality of the muscle or a risk of thrombosis.

[0045] The display unit 140 displays the risk of thrombosis calculated by the processing unit 130 to the user through an external device. According to an embodiment, the display unit 140 can display the calculation result as a numerical value on the display device 141 (refer to FIG. 2). Figure 1 According to another embodiment, the display unit 140 can warn the user by turning on an LED element (not shown) when the risk of muscle abnormality or thrombosis is greater than or equal to a threshold value (for example, if the risk of deep vein thrombosis is high, a red light is turned on, and if the risk is low, a green, etc. is turned on).

[0046] Figures 2A to 2D A process in which the processing unit calculates the degree to which the reflection vibration or EMG signal of the body part deviates from the data distribution by using a Bayesian algorithm is shown according to an embodiment.

[0047] Referring to Figures 2A to 2D , the processing unit 130 can calculate the abnormality of the body part using an algorithm that detects the degree to which a specific value of the muscle has deviated from the distribution chart by analyzing the data distribution of the measured results of the reflection vibration and the measured results of the EMG signal of the body part. The algorithm can follow the distribution of the Bayesian probability value. The processing unit 130 obtains an approximate function of each of the measured values of the reflection vibration and the EMG signal of the body part based on the change in the measured values of the reflection vibration and the EMG signal of the body part over time, and converts each of the measured values of the reflection vibration and the EMG signal of the body part using the obtained approximate function into a value in the range of 0 to 1. Here, the measured value of the reflection vibration or the EMG signal of the body part converted into a value in the range of 0 to 1 can refer to a value indicating the probability that a thrombus will be measured when the patient has muscle atrophy or thrombus formation, but the embodiment is not limited thereto.

[0048] Figures 3A to 3C A process in which the processing unit 130 calculates the abnormality of the reflection vibration or EMG signal of the body part using an anomaly detection algorithm is shown according to an embodiment.

[0049] Referring to Figures 3A to 3C , the processing unit 130 can calculate the abnormality in the reflection vibration or EMG signal of the body part by using an isolation forest algorithm that detects an anomaly based on a tree isolating abnormal data. The anomaly detection refers to detecting data that is significantly different from most data or unique data. Here, the anomaly can be expressed as noise, bias, or exception. The anomaly detection is to find outliers, which are data that show different patterns in the collected data. The isolation forest technique represents a data set in the form of a decision tree, and follows the depth direction of the decision tree in the case of cutting normal values and uses the characteristics of cutting at the top of the decision tree in the case of cutting outliers. Using these characteristics, the isolation forest makes it possible to cut normal values and outliers based on the number of times the decision tree descends and cuts. If the frequency component of the reflection vibration measured by the accelerometer and / or the frequency component of the EMG signal measured by the EMG signal suddenly changes, it is cut as an outlier. The more the number of cuts, the higher the possibility of muscle atrophy or deep vein thrombosis.

[0050] Figure 4A device for diagnosing an abnormality according to an embodiment is shown, which is implemented as a wearable patch detachably and measures a slight change in a muscle.

[0051] Referring to Figure 4 , recently, many wearable devices using Internet of Things technology have emerged. Due to the characteristics of the wearable device, it should be easy to carry, and it should be light in weight and capable of long-time operation. A small device such as a wearable device is used in a form of being in direct contact with a person's body or being attached to a clothes or other accessories without being in direct contact with the body.

[0052] In particular, in a wearable device, a wearable multi-bio-signal measurement device such as a wearable electromyography device is a device that measures a bio-signal such as electromyography using a sensor such as a patch-type electrode to form a contact point with various body parts (chest, wrist, ankle, etc.) of a subject. The device is used to predict or diagnose the occurrence of an abnormality or a disease such as thrombus formation in the body part by monitoring the bio-signal.

[0053] By implementing the diagnostic device of the present application as a wearable patch in a detachable manner, a bio-signal such as electromyography can be easily monitored in daily life. Accordingly, medical personnel can be continuously provided with a patient's condition through the motor unit, the measurement unit, and the processing unit installed on the wearable patch, and can quickly diagnose and treat a predicted disease, thereby reducing the risk of death.

[0054] Figure 5 A process according to an embodiment in which the processing unit 130 calculates a risk of an abnormality or thrombus formation of a muscle and the display unit warns a user through wireless communication is shown.

[0055] The processing unit 130 can be connected using one or more of radio frequency (RF), Wi-Fi, cellular, Bluetooth, Bluetooth Low Energy (BLE), Personal Area Network (PAN), short wavelength UHF, and combinations thereof, to communicate wirelessly with the display unit 140.

[0056] Referring to Figure 5 , the display unit 140 displays a risk of thrombus formation calculated by the processing unit 130 to a user through an external device. According to an embodiment, the display unit 140 can display the calculation result as a numerical value on the display device 141. According to another embodiment, the display unit 140 can warn a user by turning on an LED element (not shown) when the risk of thrombus formation is greater than or equal to a threshold value (for example, if the risk of deep vein thrombosis is high, a red light is turned on, and if the risk of deep vein thrombosis is low, a green light is turned on).

[0057] According to the diagnostic apparatus as described above, a vibrator attached to a user's body provides a vibration of a certain frequency, and muscle atrophy or deep vein thrombosis is diagnosed by measuring a reflected vibration of a muscle sensed in response to the vibration and an EMG signal. The diagnostic apparatus according to the embodiment is configured to include a vibrator attached to a body part and a sensor capable of sensing a change in the body part, so that it is easy to install and use. For example, by using a vibrator and a sensor disposed under an airplane seat, it is possible to automatically measure and warn of an abnormality of a body part or a risk of thrombosis of a traveler. According to this, it makes it possible to diagnose muscle atrophy and deep vein thrombosis at an earlier stage compared to a conventional ultrasonography method or a blood test method.

[0058] While the above has been described with reference to the embodiments, it is understood that various modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the present application as set forth in the following claims.

Claims

1. A device for diagnosing an abnormality by measuring a slight change in a muscle, comprising, a vibration unit that provides a vibration to a body part of a user; a measurement unit that detects a slight change in a muscle by measuring a change in elasticity of the body part according to the vibration; and a processing unit that calculates an abnormality of the body part based on the change in elasticity of the body part, wherein the measurement unit includes an electromyograph that measures an electromyographic signal of the body part, wherein the processing unit calculates the abnormality of the body part by using an abnormality detection algorithm that detects whether there is an abnormality in a detection variable, wherein the measurement unit includes an accelerometer that detects a reflected vibration generated in the body part in response to the vibration, wherein the abnormality detection algorithm used by the processing unit includes an isolation forest algorithm that detects an abnormality by cutting abnormal data by a decision tree, wherein, if a frequency component of the reflected vibration measured by the accelerometer and a frequency component of the electromyographic signal measured by the electromyograph suddenly change, it is cut as an outlier.

2. The apparatus of claim 1, wherein, The abnormality of the body part calculated by the processing unit is a risk of thrombus formation. 3.The device of claim 1, further comprising a display unit that displays the abnormality of the body part. 4.The device of claim 1, further comprising a control unit that controls an operation of the vibration unit.

5. The apparatus of claim 4, wherein, The vibration unit receives a control signal from the control unit and provides a vibration of a specific frequency through a vibrator attached to the body part. 6.The device of claim 5, further comprising a pressure sensor positioned between the vibrator and the body part of the user to sense a pressure generated according to the vibration, wherein The processing unit is configured to indicate the pressure generated according to the vibration through a display unit.

7. The apparatus of claim 3, wherein, The display unit displays the abnormality of the body part in a numerical manner through a display device.

8. The apparatus of claim 3, wherein, The display unit is configured to turn on an LED element when the abnormality of the body part is greater than or equal to a threshold value.

9. The apparatus of claim 1, wherein, The device is detachable as a wearable patch.

10. The apparatus of claim 3, wherein, The processing unit is connected to communicate wirelessly with the display unit using one or more of Wi-Fi, cellular, personal area network (PAN), short wavelength UHF.

11. The apparatus of claim 3, wherein, The processing unit is connected to communicate wirelessly with the display unit using Bluetooth.

12. The apparatus of claim 11, wherein, The Bluetooth is Bluetooth low energy (BLE).

13. The apparatus of claim 3, wherein, The processing unit is connected to communicate wirelessly with the display unit using radio frequency (RF). The processing unit is connected to communicate wirelessly with the display unit using radio frequency (RF).

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