KR-20260067279-A - BLOOD PRESSURE PREDICTION SYSTEM AND OPERATING METHOD OF BLOOD PRESSURE PREDICTION SYSTEM

KR20260067279AKR 20260067279 AKR20260067279 AKR 20260067279AKR-20260067279-A

Abstract

A blood pressure prediction system according to an embodiment of the present invention includes a sensing element comprising a plurality of first electrodes for measuring an electrocardiogram signal from a user and a second electrode for measuring a ballistocardiogram signal from a user, and a blood pressure prediction device for generating prediction data for a user's blood pressure based on the electrocardiogram signal and the ballistocardiogram signal. The blood pressure prediction device includes a communication device for receiving the electrocardiogram signal and the ballistocardiogram signal from the sensing element, and a processor for acquiring first sampling data and second sampling data corresponding to the electrocardiogram signal and the ballistocardiogram signal, respectively, detecting R peaks and J peaks from the first sampling data and the second sampling data, calculating interval data based on the R peaks and J peaks, and generating prediction data for a user's blood pressure based on a blood pressure prediction formula and the interval data.

Inventors

홍찬화
김혜진

Assignees

한국전자통신연구원

Dates

Publication Date: 20260512
Application Date: 20250226
Priority Date: 20241105

Claims (20)

A sensing element comprising a plurality of first electrodes for measuring an electrocardiogram signal from a user and a second electrode for measuring a ballistocardiogram signal from the user; and A blood pressure prediction device that generates prediction data for the user's blood pressure based on the electrocardiogram signal and the ballistocardiogram signal, wherein The above blood pressure prediction device is: A communication device that receives the electrocardiogram signal and the ballistocardiogram signal from the sensing element; and A blood pressure prediction system comprising a processor that acquires first sampling data and second sampling data corresponding to the electrocardiogram signal and the ballistocardiogram signal, respectively, detects R peak and J peak from the first sampling data and the second sampling data, calculates interval data based on the R peak and the J peak, and generates prediction data for the user's blood pressure based on a blood pressure prediction formula and the interval data.
In Article 1, The processor determines whether the first sampling data and the second sampling data satisfy normal conditions, and In response to determining that the above normal conditions are satisfied, the processor is a blood pressure prediction system that detects the R peak and the J peak.
In Article 2, The above processor is a blood pressure prediction system that determines that the normal condition is satisfied when the standard deviation of the first samples included in the first sampling data is included within the first normal range and the standard deviation of the second samples included in the second sampling data is included within the second normal range.
In Paragraph 3, The above processor is: Among the first samples above, a first sample having a maximum value, exceeding a first threshold value, and having a distance from an adjacent peak longer than the minimum inter-peak distance is detected as the R peak; and A blood pressure prediction system that detects as the J peak a second sample among the above second samples that has a maximum value, exceeds a second threshold value, and has a distance from an adjacent peak longer than the minimum peak distance.
In Article 4, The processor determines whether the interval data satisfies a validity condition, and In response to determining that the above valid conditions are satisfied, the processor is a blood pressure prediction system that generates the above prediction data.
In Article 5, A blood pressure prediction system in which the processor determines that the validity condition is satisfied when the interval data is included within a valid time range.
In Article 6, The above blood pressure prediction device further includes a blood pressure measuring device that acquires measurement data for the blood pressure, and The above processor is a blood pressure prediction system that derives the blood pressure prediction formula based on the above measurement data and the above interval data.
In Article 7, The above processor generates biosignal data including the above prediction data, and The blood pressure prediction device described above is a blood pressure prediction system further comprising a multimedia output device that provides the biosignal data to the user.
In Article 8, The above-mentioned sensing element is a blood pressure prediction system attached in the direction of the heart, based on the central sternum of the user.
In Article 8, The above biosignal data is a blood pressure prediction system that further includes at least one of the electrocardiogram signal, the ballistocardiogram signal, and the measurement data.
In the method of operation of a blood pressure prediction device, A step of receiving the user's electrocardiogram signal and ballistocardiogram signal from an external sensing element; A step of acquiring first sampling data and second sampling data based on the electrocardiogram signal and the ballistocardiogram signal; A step of determining whether the first sampling data and the second sampling data satisfy normal conditions; In response to the determination that the above normal conditions are satisfied, a step of detecting R peaks and J peaks based on the first sampling data and the second sampling data; A step of calculating interval data based on the above R peak and the above J peak; A step of determining whether the above interval data satisfies a validity condition; and A method of operation comprising the step of generating predicted data for the user's blood pressure based on a blood pressure prediction formula and the interval data.
In Article 11, The step of determining whether the first sampling data and the second sampling data satisfy normal conditions is: A step of determining whether the standard deviation of the first samples included in the first sampling data is included within a first normal range; and A method of operation comprising the step of determining whether the standard deviation of the second samples included in the second sampling data is included within a second normal range.
In Article 12, The above R peak is a first sample among the first samples that has a maximum value, exceeds a first threshold value, and has a distance from an adjacent peak longer than the minimum inter-peak distance, and A method of operation in which the above J peak is a second sample having a maximum value among the second samples, exceeding a second threshold value, and having a distance from an adjacent peak longer than the minimum peak distance.
In Article 13, A method of operation comprising the step of determining whether the interval data satisfies a valid condition, and the step of determining whether the interval data is included within a valid time range.
In Article 14, The step of generating predicted data for the user's blood pressure based on the above blood pressure prediction formula and the above interval data is: A step of acquiring measurement data for the above blood pressure; and A method of operation comprising the step of deriving the blood pressure prediction formula based on the above measurement data and the above interval data.
In Article 15, A step of generating biosignal data including the above-mentioned prediction data; and A method of operation comprising the step of outputting the biosignal data through a multimedia output device.
A communication device that receives the user's electrocardiogram signal and ballistocardiogram signal from an external sensing element; and A blood pressure prediction device comprising a processor that acquires first sampling data and second sampling data corresponding to the electrocardiogram signal and the ballistocardiogram signal, respectively, detects R peak and J peak from the first sampling data and the second sampling data, calculates interval data based on the R peak and the J peak, and generates prediction data for the user's blood pressure based on a blood pressure prediction formula and the interval data.
In Article 17, The processor determines whether the first sampling data and the second sampling data satisfy normal conditions, and In response to determining that the above normal conditions are satisfied, the processor is a blood pressure prediction device that detects the R peak and the J peak.
In Article 18, The processor determines whether the interval data satisfies a validity condition, and In response to determining that the above valid conditions are satisfied, the processor is a blood pressure prediction device that generates the above prediction data.
In Article 19, It further includes a blood pressure measuring device for acquiring measurement data for the above blood pressure, The above processor is a blood pressure prediction device that derives the blood pressure prediction formula based on the above measurement data and the above interval data.

Description

Blood Pressure Prediction System and Operating Method of Blood Pressure Prediction System The present invention relates to biosignal processing technology, and more specifically, to a blood pressure prediction system based on biosignal processing and a method of operation of the blood pressure prediction system. Blood pressure is an important indicator of cardiovascular health and is essential for the early detection and management of chronic diseases such as hypertension. Currently, blood pressure measurement largely relies on cuff-type blood pressure monitors. However, this method makes continuous measurement difficult and can cause inconvenience during use. BCG and ECG are non-invasive methods that measure cardiac activity based on the heart's minute movements and electrical signals, respectively; the time difference between the major peaks of the two signals (the R peak of the ECG and the J peak of the BCG) correlates with blood pressure. Conventional peak detection was performed by predicting blood pressure through the analysis of stored data after acquiring data over a certain period. This method has the problem that real-time blood pressure prediction is difficult, and analysis is time-consuming because it requires calculating the time difference for a large number of R-J values. FIG. 1 shows a blood pressure prediction system according to an exemplary embodiment of the present invention. FIG. 2 shows a sensing element according to an exemplary embodiment of the present invention. Figure 3 shows an example of the attachment of the sensing element of Figure 2. Figure 4 shows an example of the operation method of the sensing element of Figure 2. FIG. 5 shows a blood pressure prediction device according to an exemplary embodiment of the present invention. Figure 6 shows examples of the R peak and J peak. Figure 7 shows an example of the operation method of the blood pressure prediction device of Figure 5. Figure 8 shows an example of an operation method for deriving a blood pressure prediction equation of the blood pressure prediction device of Figure 5. Figure 9 shows an example of biosignal data. Figure 10 shows another example of biosignal data. In the following, embodiments of the present invention will be described clearly and in detail so that a person skilled in the art can easily practice the present invention. Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. The advantages and features of the present invention, and the methods for achieving them, will become clear by referring to the embodiments described below in detail together with the accompanying drawings. However, the present invention is not limited to the embodiments described herein and may be embodied in different forms. Rather, the embodiments introduced herein are provided to ensure that the disclosed content is thorough and complete and to ensure that the spirit of the present invention is sufficiently conveyed to those skilled in the art, and the present invention is defined only by the scope of the claims. Throughout the entire specification, the same reference numerals refer to the same components. The terms used herein are for the purpose of describing embodiments and are not intended to limit the invention. In this specification, the singular form includes the plural form unless specifically stated otherwise in the text. As used in this specification, 'comprises' and/or 'comprising' do not exclude the presence or addition of one or more other components, operations, and/or elements to the mentioned components, operations, and/or elements. Furthermore, as they are based on preferred embodiments, the reference numerals presented in the order of description are not necessarily limited to that order. Furthermore, the embodiments described herein will be explained with reference to cross-sectional and/or plan views, which are exemplary illustrations of the present invention. In the drawings, the thicknesses of films and regions are exaggerated for effective explanation of the technical content. Accordingly, the shapes of the exemplary illustrations may be modified due to manufacturing techniques and/or tolerances, etc. Therefore, the embodiments of the present invention are not limited to the specific shapes depicted but include variations in shape produced according to the manufacturing process. Components described by reference to terms such as part or unit, module, block, ~or, ~er as used herein, and functional blocks illustrated in the drawings may be implemented in the form of software, hardware, or a combination thereof. For example, software may be machine code, firmware, embedded code, and application software. For example, hardware may include electrical circuits, electronic circuits, processors, computers, integrated circuits, integrated circuit cores, pressure sensors, inertial sensors, microelectromechanical systems (MEMS), passive compo