KR20100008832A - Remote health care system and method using the supersonic wave - Google Patents

Abstract

PURPOSE: A remote health care system and method using a supersonic wave are provided to diagnose a health state by analyzing the measured signal at a remote plate and supply the diagnose results in real time. CONSTITUTION: A central center(20) analyzes a second ultrasonic Doppler signal measured in a portable terminal(10) based on a training set, and diagnoses the health state. The central center transmits the class information to the portable terminal as the diagnosis result. When the class information is classified as dangerous group, the central center requests an emergency rescue based on a position signal transmitted from the portable terminal.

Description

Remote health care system using ultrasound and its method {REMOTE HEALTH CARE SYSTEM AND METHOD USING THE SUPERSONIC WAVE}

The present invention relates to a remote health care system using ultrasound and a method thereof, and more particularly, to configure a training set through a pattern recognition technique, and based on the signal measured from the mobile terminal (ultrasound Doppler signal) The present invention relates to a remote health care system and a method for diagnosing a health condition and providing a diagnosis result in real time by analyzing a remote location.

Recently, the incidence of adult diseases and cancers has increased due to the pollution caused by industrialization along with the improvement of living standards, and thus the public's interest in health care is increasing. In particular, cardiovascular diseases such as high blood pressure, low blood pressure, heart attack and arrhythmia are not diseases that continue to cause pain to patients but are temporary diseases. Patients with these diseases usually live every day with anxiety that may worsen when they do not have any abnormalities and cannot be admitted to the hospital. In addition, to check their physical condition, they had to visit a hospital regularly for medical checkups.

Thanks to efforts to improve this inconvenience and the development of the Internet, a remote health care system has been introduced. The remote health management system is a system that allows the diagnosis of one's own health condition without having to go to the hospital. The patient receives basic biometric information such as body temperature and heart rate measured by the remote care device, and diagnoses it. It is a system that informs the patient of the diagnosis result data.

However, the remote health care system remains a simple online conversion of the form that doctors and patients face to face. In other words, doctors who have received this by converting the examination results from X-ray imaging or ultrasound diagnosis into digital and simply transmitting them using a communication network make a diagnosis and generate a prescription based on this. Most of the medicine was based on the way.

The remote medical care device used in such a conventional remote health care system is provided in the home, and there is a problem in that the remote medical care cannot be received when the patient goes out. In particular, the conventional The remote health care system transmits the data measured through the remote medical device to a specialist (doctor) located in a remote location and receives the diagnosis result from the specialist. Therefore, the diagnosis result cannot be received in real time in the absence of the specialist. there is a problem. In addition, even if the result of the remote diagnosis indicates that the patient's health is abnormal and an emergency situation that requires immediate evacuation (for example, an emergency situation in which a person loses his mind due to a sudden heart attack or arrhythmia) occurs, There is a problem that no action can be taken.

An object of the present invention is to construct a training set through a pattern recognition technique, and based on this, analyze the signal (ultrasound Doppler signal) measured from the mobile terminal from a remote location without the help of an expert to diagnose the state of health and the diagnosis result To provide a remote health care system and a method that can provide in real time.

In addition, another object of the present invention to provide a remote health care system and method that can accurately identify the location of the patient in an emergency, and can support a faster and more accurate location-based emergency rescue services.

According to an aspect of the present invention, a remote health care system and method using ultrasound are disclosed. According to the present invention, a training set is configured by grouping values that can be analyzed in the first ultrasonic Doppler signal by class using a pattern recognition technique. The central center analyzes the second ultrasonic Doppler signal measured by the portable terminal based on the training set to diagnose the state of health, and transmits class information to the portable terminal as a diagnosis result.

According to one embodiment of the present invention, when the diagnosis results, class information is classified as a danger and an emergency situation occurs, the central center requests an emergency rescue based on the location signal transmitted from the mobile terminal.

According to the present invention, it is possible to receive the diagnosis result anytime and anywhere without the help of a specialist, which allows attention and prevention of a specific disease, and provides an emergency rescue service based on location more quickly and accurately in case of an emergency. There is this.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, in the following description, when there is a risk of unnecessarily obscuring the gist of the present invention, a detailed description of well-known functions and configurations will be omitted.

1 is a view showing the configuration of a remote health care system according to an embodiment of the present invention.

In veterinary medicine and oriental medicine, you can look at the number of pulses, rhythm, size, and duration to determine heart function, arterial condition, and general health. As a representative method for observing the vein, there is a method of pulsating the wrist in oriental medicine, and there is a method using ultrasound in veterinary medicine.

The remote health care system of the present invention analyzes the ultrasonic Doppler signal (ultrasound Doppler video signal or ultrasonic Doppler audio signal) measured by the mobile terminal 10 based on the training set by the central center 20 of the remote location. The user's health condition is diagnosed (eg, normal, caution, danger, absolute risk, etc.), and the diagnosis result is transmitted to the mobile terminal 10 in real time and displayed. In addition, by accurately identifying the location of the mobile terminal 10 in the central center 20, when the emergency situation (eg, absolute risk) occurs as a diagnosis result, it supports a faster and more accurate location-based emergency rescue services.

As shown in FIG. 1, the portable terminal 10 includes a controller 14 for overall control of the operation of the portable terminal 10, an ultrasonic measuring unit 11 for measuring a heartbeat of a user using ultrasonic waves, A body temperature / breathing / blood pressure detector 12 for detecting a body temperature / breathing / blood pressure of the user, a positioning unit 13 for receiving a GPS signal transmitted from a GPS satellite, a measured ultrasonic Doppler signal, Temperature / breathing / blood pressure signals (some or all of which may be optional), wirelessly transmit position signals to the central center 20 and wirelessly transmit diagnostic results from the central center 20. A wireless transceiver 15 for receiving and a display 16 for outputting a diagnosis result.

The ultrasonic measuring unit 11 of the portable terminal 10 is used to measure the heartbeat (pulse) of the patient. The measurement signal (ultrasound Doppler signal) transmitted to the central center 20 is a value measured by the ultrasonic measuring unit 11 by scanning the ultrasonic wave on the human body by the piezoelectric effect of the probe and returning the information (the Doppler signal) on the ultrasonic wave. The frequency spectrum display data (ultrasound Doppler video signal) obtained by Fourier transforming the ultrasonic Doppler signal or the heartbeat listening data (ultrasound Doppler audio signal) obtained by Hilbert transforming the ultrasonic Doppler signal. The central center 20 analyzes the ultrasonic Doppler signal based on a training set to diagnose the state of health of the terminal user.

Here, the heart rate can be measured using ultrasonic waves, and the moving heart is distinguished from other organs by using the Doppler principle that the reflected sound reflected from the moving object is different from the reflected sound reflected by the non-moving object. . The heart rate (pulse) is obtained from the ultrasound according to the Doppler principle, and the heart rate (pulse) is obtained by using an autocorrelation function that only obtains periodic components included in the original signal and cancels noise components having no period. do.

Although not shown in the drawing, the ultrasonic measuring unit 11 includes a pulse voltage generator, an ultrasonic vibrator, a preprocessor, a digital signal processor (DSP), and the like. Looking at this in detail.

The pulse voltage generator generates pulse voltages under the control of the controller 14 and applies them to the transducer array, that is, the respective ultrasonic vibrators. For example, the controller 14 controls transmission and reception timing of the entire portable terminal. In general, in the case of the B mode display, the controller 14 generates a timing signal that is a reference of about 4 KHz and controls the transmission of the ultrasonic signal.

The ultrasonic vibrators generate and transmit ultrasonic waves according to the pulse voltage applied from the pulse voltage generator, and receive a reflected echo signal (Doppler signal) from the target. Such ultrasonic vibrators may be composed of piezoelectric materials such as PZT (lead zirconate titanate) ceramics, for example. In addition, the ultrasonic vibrators are arranged in an annular array structure at one end of the ultrasonic probe, and have a structure in which the transmitter and the receiver are spaced apart from each other by an insulator. The reason why the transmitter and the receiver are arranged with the insulator interposed therebetween is to minimize the shadow area by matching the beam pattern of the transmitter and the receiver as much as possible.

The preprocessor performs preprocessing to digitally process the reflected echo signal (Doppler signal) received from the ultrasonic vibrator. This preprocessor first amplifies the received echo signal (Doppler signal) using a preamp and then amplifies the signal from the preamplifier while varying the gain over time using a TGC amplifier. The output of the TGC amplifier is converted into a digital signal by the A / D converter, demodulated by the quadrature demodulator, and then output to the DSP.

The DSP Hilbert transforms the preprocessed reflected echo signal (Doppler signal) and outputs the Doppler voice signal (heartbeat listening data). The heartbeat listening data is wirelessly transmitted to the central center 20 at a remote location through the wireless transceiver 15 under the control of the controller 14. In addition, the DSP may Fourier transform the preprocessed reflected echo signal (Doppler signal) to output frequency spectrum display data. The frequency spectrum display data is also wirelessly transmitted to the center center 20 under the control of the controller 14. .

The body temperature / breathing / blood pressure detection unit 12 detects the body temperature / breathing / blood pressure of the user through a sensor and outputs A / D conversion, and the body temperature / breathing / blood pressure signal is remotely controlled by the control unit 14. Wireless transmission to the central center 20. However, some of the body temperature / breath / blood pressure signal may be optional.

The location positioning unit 13 receives and outputs location information transmitted from a satellite through a location antenna, that is, a GPS antenna, and the location signal is also wirelessly transmitted to the central center 20 under the control of the controller 14. Or, for more accurate positioning, the positioning unit 13 corrects the position data received from the GPS satellite network (or broadcasting network) using the D-GPS (Differential Global Positioning System), generates an accurate position signal, and generates a center center. 20 may be transmitted. That is, the GPS correction value is set based on the coordinate set as the absolute measurement value, and the correct position information is generated by comparing and correcting the error of the position data.

The portable terminal 10 is configured to be easily carried on a human body. For example, the shape of the mobile terminal 10 may be a wristwatch, a sticker, a bracelet, an anklet, a necklace, a band to be attached, and the like, and the heart rate (pulse) is measured by ultrasound, and optionally, body temperature, breathing, It is enough to measure blood pressure. In particular, the mobile terminal 10 wirelessly transmits an ultrasonic Doppler signal, a body temperature / breathing / blood pressure signal (the body temperature / breathing / blood pressure signal may be optional or partially all of them), and a position signal to the central center 20. And display a diagnosis result (for example, normal, caution, danger, absolute risk, etc.) from the central center 20. In this case, an alarm function (buzzer, etc.) indicating a health risk may be added to the 'risk' and 'absolute risk'.

On the other hand, as shown in Figure 1, the central center 20 is a DB 23 that stores the training set (Training Set) configured through the pattern recognition technique, ultrasonic Doppler signal and body temperature / breath from the portable terminal 10 Ultrasonic Doppler signal and body temperature / breath / blood pressure signal measured by the wireless transceiver 21 for receiving the blood pressure signal and the position signal and wirelessly transmitting the diagnosis result to the mobile terminal 10 (temperature / Respiration / blood pressure signal may be optional part or all of them) based on the training set (Training Set) signal analysis unit 22 for diagnosing the state of health of the terminal user, diagnostic result emergency (eg As an absolute risk) includes an emergency rescue unit 25 for contacting a rescue center (eg, hospital, fire station, police station, guardian, etc.) 30 to provide emergency rescue services based on location signals.

In particular, the training set is a value that can be analyzed in the ultrasonic Doppler signal (Resistance Index (RI) = (SD) / S), and Pulsatility Index (PI) = (S / D) / mean, Systolic / Diastolic (S / D: Systolic / Diastolic) ratio, S is the systolic maximum blood flow rate, D is the maximum diastolic blood flow rate] and other features using body temperature, respiration and blood pressure. Various diseases are defined for the combination of these characteristics and composed of a classification map. Based on the training set (detailed map), the ultrasonic state Doppler signal (ultrasonic Doppler image signal and / or the ultrasonic Doppler voice signal) may be analyzed to diagnose the state of health.

The feature for classifying the training set by disease is automatically extracted by analyzing an ultrasound Doppler image signal (frequency spectrum display data) or an audio signal (heartbeat listening data). Other features include body temperature, breathing, and blood pressure.

Then, the implementation plan of the training set (or detailed map) will be described in more detail.

The central center 20 analyzes the ultrasonic Doppler signal and the body temperature / breathing / blood pressure signal measured by the mobile terminal 10 (the temperature / breathing / blood pressure signal may be optional in part or all of them), Or a detailed map) to diagnose whether the person is normal or abnormal. At this time, for fast and accurate diagnosis, a training set (detailed map) is implemented using a pattern recognition technique.

The pattern recognition problem considers what class (class) to assign when data comes in. For example, it may be about whether or not this person is in a dangerous state (classes of normal, caution, danger, absolute risk, etc.). This way of knowing whether or not this person is at risk is determined by the degree or value of the selected features, which can be ultrasound Doppler signals, body temperature, breathing, and blood pressure. For example, people with low body temperature and slow pulses are diagnosed as dangerous. For example, "breath: 16-22 / min, pulse: 60-100 / min, blood pressure: 120/80 mmHg, body temperature: 36.5 degrees to 37 degrees" is diagnosed as 'normal'. In addition, "breath: 28 times / minute, pulse: 105 times / minute, blood pressure: 100 / 60mmHg, body temperature 36.0 degrees" is diagnosed as 'danger'. In addition, if "breathing: 30 times / 1 minute, less than 10 times / 1 minute, pulse: 200 times / minute, blood pressure: less than 90mmHg, body temperature: 38.2 degrees" is diagnosed as "absolute risk".

The range of values for each feature is made statistically for the condition of patients with a known illness. As an example, FIG. 3 shows a training set as a two-dimensional graph of pulse and body temperature. In FIG. 3, the distribution of 1000 people (risk group) that reached the degree of occurrence of the risk warning was investigated. Persons with body temperature and pulse in the lung curve where the risk group is distributed are considered to be at risk. In this way, three or more features (for example, pulse, blood pressure, body temperature) can be expanded and displayed, which can be represented graphically. This also classifies people with body temperature, pulse and blood pressure in the lung curve where the risk group is distributed.

In this way, the training set breaks down the classes you want to know about (for example, groups of normal, ambient, risk, and absolute risk), and then places them on the graph where you think they are certain about those classes. And grouping the corresponding people (closed curve of Figure 3). Various pattern recognition techniques (Support Vector Machine, SVN (k-Nearest Neighbors), neural network, etc.) may be used for grouping. This training set (detailed map) examines the characteristics of a person who does not know the state in practice and tells what class (eg normal, ambient, dangerous, absolute risk, etc.) this person belongs to.

The central center 20 trains an ultrasound Doppler signal and a body temperature / breathing / blood pressure signal measured by the mobile terminal 10 (the body temperature / breathing / blood pressure signal may be optional in part or all of them). As a result of diagnosing the state of health of the terminal user based on the analysis, the terminal is inquired by using the location signal (GPS or D-GPS information) transmitted from the portable terminal 10 in case of an emergency (eg, absolute risk). Accurately identify the user's location by linking road names, administrative district names, and streets on the map. That is, the exact location of the subscriber is identified by mapping the subscriber information on the map and the predefined rescue center information.

The central center 20 identifies the rescue centers (hospitals, fire departments, police stations, etc.) 30 that are closest to the area where the terminal user is located based on the predefined DB, and calls the identified rescue centers 30. (Outbound call) is connected to make an emergency rescue request. Of course, the central center 20 may use the ARS or a resident counselor to inform the emergency rescue center 30 of the emergency (type of emergency), the location and telephone number of the emergency target by using a voice call. have.

2 is a flowchart illustrating a remote health care method according to an embodiment of the present invention.

First, as described above, features that can be analyzed in the ultrasonic Doppler signal (RI, PI S / D Ratio, etc.) and other body temperature, respiration, blood pressure, etc. are used to create a feature, and a combination of these features Define and construct a detailed map (Classification Map) to DB (201). That is, the training set is configured by grouping values that can be analyzed in the ultrasonic Doppler signal and other body temperature, respiration, and blood pressure by class (normal group, attention group, risk group, and absolute risk group).

The portable terminal 10 measures the heartbeat (pulse) of the terminal user periodically (for example, every hour) or at the request of the terminal user (202). In this case, the measurement signal (ultrasound Doppler signal) is a value obtained by measuring the information (Doppler signal) carried on the ultrasound wave after scanning the ultrasonic wave to the human body by the piezoelectric effect of the probe, and the frequency spectrum display data obtained by Fourier transforming the ultrasonic Doppler signal. (Ultrasound Doppler video signal) or heartbeat listening data (Doppler voice signal) obtained by Hilbert transforming the ultrasonic Doppler signal.

In addition, the mobile terminal 10 may receive a location information signal (GPS) transmitted from a GPS satellite network (or a broadcast network), grasp the location (correct the received location data using D-GPS, and perform precise positioning). (203), body temperature / breathing / blood pressure (some or all of which may be optional).

The mobile terminal 10 may measure the measured ultrasonic Doppler signal (frequency spectrum display data, heartbeat listening data), body temperature / breathing / blood pressure signal (body temperature / breathing / blood pressure signal may be optional in part or all thereof), location The signal is wirelessly transmitted to the central center 20 (204).

The central center 20 analyzes the ultrasonic Doppler signal and the body temperature / breathing / blood pressure signal measured by the mobile terminal 10 (the temperature / breathing / blood pressure signal may be optional in part or all thereof). The health state of the terminal user is diagnosed by determining the class (normal, caution, danger, absolute risk) of the corresponding signal in the training set (206). The diagnosis result of the central center 20 (eg, normal, caution, danger, absolute risk, etc., which eventually becomes class information) is transmitted to the mobile terminal 10 (207) and displayed on the terminal. In this case, an alarm (buzzer, etc.) indicating a health risk may also be output for the 'risk' and 'absolute risk'.

In particular, as a result of diagnosing the state of health of the terminal user in the central center 20, when an emergency situation (eg, absolute risk) occurs (208), the exact position of the terminal user is determined using the position signal transmitted from the portable terminal 10. Identify the rescue centers (hospitals, fire departments, police stations, etc.) 30 adjacent to the area where the user of the terminal is located, and make an emergency rescue request by connecting an outbound call to the identified rescue center 30 ( 209). At this time, the emergency rescue request can be automatically sent to the rescue center 30 by including the user's location in the emergency rescue request message (emergency degree, emergency occurrence message, etc.) (for example, ARS, SMS, MMS, E -mail, etc.)

While the invention has been described in connection with some embodiments herein, it should be understood that various changes and modifications can be made therein without departing from the spirit and scope of the invention as would be understood by those skilled in the art. something to do. Also, such modifications and variations are intended to fall within the scope of the claims appended hereto.

1 is a view showing the configuration of a remote health care system according to an embodiment of the present invention.

2 is a flow diagram illustrating a remote healthcare method in accordance with an embodiment of the present invention.

3 is a two-dimensional graph of pulse and body temperature to illustrate a training set in accordance with an embodiment of the present invention.

* Explanation of symbols for the main parts of the drawings

10: mobile terminal 11: the ultrasonic measuring unit

12: body temperature / breathing / blood pressure detection unit 13: position location

14,24: control unit 15,21: wireless transceiver

16 display unit 20 center center

22: signal analysis unit 23: DB

25: emergency rescue 30: rescue center

Claims (9)

As a remote healthcare system, The training set is configured by grouping values that can be analyzed in the first ultrasound Doppler signal by class using a pattern recognition method, The central center analyzes the second ultrasonic Doppler signal measured by the portable terminal based on the training set to diagnose a health state, and transmits class information to the portable terminal as a diagnosis result. The method of claim 1, And, when the emergency information occurs because the class information is classified as a danger as a result of the diagnosis, the central center requests an emergency rescue based on the location signal transmitted from the mobile terminal. The method of claim 2, The portable terminal measures the heartbeat (pulse) of the terminal user, locates the terminal, transmits the second ultrasonic Doppler signal and the position signal to the central center, and receives the class information from the central center. Displayed, remote healthcare system. The method according to any one of claims 1 to 3, When configuring the training set, the remote health care system further comprises at least one of body temperature, respiration, blood pressure information. The method of claim 4, wherein The training set uses a value that can be analyzed in the first ultrasonic Doppler signal and at least one of body temperature, respiration, and blood pressure to create a feature, and defines a variety of diseases for the combination of these features to form a detailed map. Management system. The method of claim 5, The second ultrasonic Doppler signal is one of frequency spectrum display data obtained by Fourier transforming the Doppler signal obtained by generating ultrasonic waves and heartbeat listening data obtained by Hilbert transforming the Doppler signal obtained by generating ultrasonic waves. As a remote healthcare method, Constructing a training set by grouping values that can be analyzed in an ultrasonic Doppler signal by class using a pattern recognition technique; A central center diagnosing a health state by analyzing an ultrasonic Doppler signal measured by a mobile terminal based on the training set; And And transmitting, by the central center, class information to the portable terminal as a diagnosis result. The method of claim 7, wherein And in the event that an emergency occurs due to the class information being classified as dangerous, the central center requesting an emergency rescue based on the location signal transmitted from the mobile terminal. The method according to claim 8 or 9, And receiving, by the portable terminal, the class information from the central center, and displaying the class information.

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