WO2020232604A1 - 一种心脏舒张功能评估方法、设备和系统 - Google Patents
一种心脏舒张功能评估方法、设备和系统 Download PDFInfo
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Classifications
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- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/1126—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb using a particular sensing technique
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- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
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- A61B2562/0261—Strain gauges
Definitions
- the invention belongs to the field of heart monitoring, and in particular relates to a method, equipment and system for non-invasive cardiac diastolic function assessment.
- Heart failure (abbreviated as heart failure) is a clinical syndrome with multiple causes and pathogenesis.
- Heart failure is a clinical syndrome with multiple causes and pathogenesis.
- Heart failure With the aging of the population and the increasing survival rate of patients with acute myocardial infarction, the number of patients with chronic heart failure is increasing rapidly.
- Patients with heart failure transition from a chronic state to an acute worsening state, accompanied by an increase in cardiac filling pressure. High filling will cause the heart function to enter a rapid vicious circle, but the patient itself will have to continue to increase the filling pressure for about 20 days before feeling the symptoms and need to be admitted to the hospital urgently.
- the heart injury has occurred and is irreversible.
- timely intervention is required to avoid further deterioration of the patient. This has become the consensus of clinicians.
- the purpose of the present invention is to provide an evaluation method, device, system and computer-readable storage medium that can evaluate the diastolic function of a measurement object, aiming to realize non-invasive evaluation of diastolic function.
- the present invention provides a method for evaluating diastolic function of the heart, the method comprising:
- the first parameter and the second parameter are determined based on the hemodynamic related information, where the first parameter is used to characterize the early diastolic ventricular filling event, and the second parameter is used to characterize the end-diastolic atrial contraction event.
- An indicator parameter is generated based on the first parameter and the second parameter, and the diastolic function of the subject is evaluated based on the indicator parameter.
- the present invention provides a computer-readable storage medium that stores a computer program that, when executed by a processor, implements the steps of the above-mentioned diastolic function assessment method.
- the present invention provides a diastolic function assessment device, including: one or more processors; a memory; and one or more computer programs, wherein the one or more computer programs are stored in the memory And is configured to be executed by the one or more processors, and when the processor executes the computer program, the steps of the above-mentioned diastolic function evaluation method are realized.
- the present invention provides a diastolic function assessment system, the system comprising:
- One or more vibration sensors for obtaining vibration information on the thoracic surface of the subject.
- the invention monitors the diastolic function of the heart by collecting the vibration information of the user, without intruding the human body, passively measuring, and can realize continuous monitoring, the user only needs to lie on the measuring device to perform the measurement without the assistance of professionals, and It has the advantages of high measurement accuracy and simple operation, can improve the comfort of the tester, and can be applied to scenes such as hospitals and homes.
- the diastolic function evaluation system provided by the present invention can evaluate the diastolic function of the user, and then warn the user in advance when signs of deterioration appear, and help the user avoid the consequences of deterioration.
- FIG. 1 is a flowchart of a method for evaluating diastolic function according to the first embodiment of the present invention
- FIG. 2 is a schematic diagram of the waveform of the vibration information of the object A collected by the optical fiber sensor
- Figure 3 is a schematic diagram of time-domain waveforms of hemodynamic related information
- FIG. 4 is a schematic diagram of time-domain waveforms in which hemodynamic related information, first high-frequency component information, and second high-frequency component information are located on the same time axis;
- FIG. 5 is a schematic diagram of the first wave group, the second wave group and the third wave group of hemodynamic related information, vibration energy information, first high frequency component information and second high frequency component information in a cardiac cycle;
- FIG. 6 is a schematic diagram of time-domain waveforms in which electrocardiogram information, hemodynamic related information, vibration energy information, first high-frequency component information, and second high-frequency component information are placed on the same time axis in a cardiac cycle;
- 7A and 7B are schematic diagrams of the values of the first parameter and the second parameter based on the vibration information of the object B;
- 7C is a schematic diagram of the values of the first parameter and the second parameter based on the vibration information of the object C;
- 8A and 8B are schematic diagrams of the values of the first parameter and the second parameter based on the vibration information of the object D;
- 9A is a schematic diagram of the values of the first parameter and the second parameter based on the vibration information of the object E;
- 9B, 9C, and 9D are ROC curve diagrams indicating parameters
- FIG. 10 is a structural block diagram of a diastolic function assessment device according to the third embodiment of the present invention.
- Fig. 11 is a structural block diagram of a system for monitoring the cardiac filling pressure state according to the fourth embodiment of the present invention.
- a diastolic function evaluation method 100 provided in the first embodiment of the present invention includes the following steps: It should be noted that if there are substantially the same results, the diastolic function evaluation method of the present invention does not refer to FIG. The sequence of the processes shown is limited.
- the non-invasive acquisition of the body surface vibration information of the thoracic cavity of the subject may be acquired through one or more vibration sensors.
- Vibration sensors can be acceleration sensors, speed sensors, displacement sensors, pressure sensors, strain sensors, and stress sensors. In addition, they can also be sensors that convert physical quantities equivalently based on acceleration, speed, displacement, or pressure (such as electrostatic charge sensitive Sensors, inflatable micro-motion sensors, radar sensors, etc.).
- the strain sensor can be an optical fiber sensor.
- the non-invasive acquisition of the body surface vibration information of the thoracic cavity of the subject may also be acquired by other means, such as a photoelectric sensor.
- the body surface vibration information of the chest cavity of the subject is collected by an optical fiber sensor, and the optical fiber sensor can be placed under the subject's body.
- the subject can be in a posture such as supine, prone, side-lying, etc.
- the optical fiber sensor can be placed on the bed, and the subject is supine (prone or side) on it.
- the fiber optic sensor can be configured to be placed under the subject's back.
- the fiber optic sensor is configured to be placed under the area between the subject's left and right shoulder blades, which means that Below the shoulder, generally, for the convenience of description, the body surface area corresponding to the subject's left and right shoulder blades is defined as the middle shoulder.
- the measurement position corresponds to the measurement position when the subject is in the supine posture, for example, the measurement position corresponding to the back is the subject's chest.
- the optical fiber sensor can also be placed on the contact surface behind the supine human body at a certain tilt angle, the contact surface behind the reclining human body on a wheelchair or other objects that can lean on, and so on to collect vibration information.
- the vibration sensor can also be placed above the body of the subject in a supine posture, for example, the acceleration sensor can be placed on the body surface area of the chest corresponding to the apex of the heart of the subject.
- each sensor works independently and synchronously.
- the size of each sensor can be the same, or it can be designed with different sizes, such as a 20cm*30cm sensor or a 5cm*4cm sensor , Sensors of any size can be arranged and combined in any way. For example, in some embodiments, a thinner object can be equipped with one large sensor or two small sensors, while a wider object can be equipped with two large sensors or a combination of two small sensors and one large sensor.
- a fiber optic sensor is used as the vibration sensor, at least one fiber optic sensor is placed on the right shoulder of the subject. The fiber optic sensor can be placed directly under the subject's body or placed under the mattress in indirect contact with the subject.
- the sensing area of the optical fiber sensor is at least 20 square centimeters, where the sensing area refers to the area where the vibration sensor actually senses vibration (for example, the sensing area of the optical fiber sensor refers to the area where the optical fibers are distributed in the optical fiber sensor) .
- Fig. 2 is a schematic diagram of the waveform of the vibration information of an object collected by the optical fiber sensor.
- the horizontal axis of the curve 21 represents time
- the vertical axis represents normalized vibration information, which is dimensionless.
- the vibration information collected by the vibration sensor includes the respiratory signal components of the measured object, the hemodynamic signal components, as well as the micro-vibration of the environment, the interference caused by the body movement of the measured object, and the noise signal of the circuit itself.
- the large outline of the signal at this time is the signal envelope produced by human respiration, and the hemodynamic signal and other interference noises are superimposed on the respiratory envelope curve.
- S102 Perform preprocessing on the vibration information to generate hemodynamic related information.
- the vibration information obtained by different sensors contains different amounts of information, and some contain more information, so it needs to be preprocessed to capture relevant signals.
- the vibration information obtained when the vibration sensor adopts an optical fiber sensor also includes signals such as the breathing signal, body movement signal, hemodynamic signal, and some inherent noise of the sensor.
- S102 may specifically include:
- At least one of filtering, denoising, and signal scaling is performed on vibration information to obtain hemodynamic related information; specifically, it can be: IIR filter, FIR filter, wavelet filter, One or more combinations of zero-phase two-way filter, polynomial fitting smoothing filter, integral transformation, and differential transformation are used to filter and denoise vibration information. For example, filtering the vibration information below 2 Hz can filter out breathing signals and body motion signals.
- the preprocessing may also include: judging whether the vibration information carries a power frequency interference signal, and if so, filtering the power frequency noise through a power frequency notch filter. It is also possible to denoise some high-frequency noise (for example, above 45Hz), and the processed information can be scaled according to the situation to obtain hemodynamic related information.
- the filter interval can also be set directly, for example, the filter interval can be any interval between 1Hz-50Hz.
- Fig. 3 is a schematic diagram of the time-domain waveform of the hemodynamic related information after preprocessing the vibration information obtained by the optical fiber sensor shown in Fig. 2, and the filter interval of the curve 31 is selected to be 9 Hz-45 Hz.
- Each waveform of curve 31 has obvious characteristics and good consistency, regular periodicity, clear outline, and stable baseline, that is, the signal quality is better.
- S103 Determine the first parameter and the second parameter based on the hemodynamic related information.
- the first parameter is used to characterize the early diastolic ventricular filling event
- the second parameter is used to characterize the end-diastolic atrial contraction event.
- S103 may specifically include:
- S1031. Process the hemodynamic related information to generate first high frequency component information, second high frequency component and vibration energy information.
- the first high-frequency component information is used to characterize the speed signal;
- the second high-frequency component information is used to characterize the acceleration signal; and
- the vibration energy information is used to characterize the energy signal.
- the cyclical beating of the heart will cause various changes of periodic phenomena, such as intracardiac pressure and cardiovascular pressure, the volume of the atria and ventricles, and intracardiac valves (including mitral valve, tricuspid valve, aortic valve, pulmonary valve) Periodic changes in opening and closing, blood flow speed, etc. These changes drive blood to flow in a certain direction in the blood vessel. Hemodynamics is the study of the mechanics of blood flowing in the cardiovascular system, and the deformation and flow of blood and blood vessels are the research objects.
- hemodynamic related information refers to any information related to hemodynamics, which may include, but is not limited to, information related to blood flow (for example, the contraction and relaxation of the heart causes ejection), and blood flow Flow-related information (such as cardiac output CO (cardiac output), left ventricular ejection impacting the aortic arch), blood flow pressure-related information (such as arterial systolic blood pressure, diastolic blood pressure, mean arterial pressure), blood vessel-related information ( For example, one or more of vascular elasticity).
- the cyclical beating of the heart can maintain blood circulation.
- various parameters related to the beating of the heart such as the opening and closing of the heart valve, the change of the volume of the atrium and ventricle, the change of the pressure of the atrium and the ventricle, the flow velocity of the blood flow in the atrium and the ventricle And direction, etc., are all information related to hemodynamics.
- the vibration information acquired by the optical fiber sensor essentially corresponds to the displacement change information.
- the displacement change information is relatively smooth. Some acceleration or speed change details are difficult to identify in the displacement change information. For example, the speed gradually increases from zero to a certain peak value, and then gradually decreases from the peak value to zero.
- the speed change curve forms a waveform that first rises and then drops, but the displacement change curve is a monotonous waveform. Therefore, compared to the signal component corresponding to the displacement, the peak-to-valley time width of the signal component corresponding to the velocity and acceleration is narrower, which is called high-frequency component information.
- the high-frequency component extraction method can be a polynomial fitting smoothing filtering method, and it can also perform differentiation processing on hemodynamic related information to generate high-frequency component information.
- S1031 can specifically perform first-order differentiation on hemodynamic related information
- the processing generates the first high-frequency component information and the second-order differential processing is performed to generate the second high-frequency component information.
- Vibration energy information can be generated by calculating the energy integral of the specified time window point by point for the displacement change information.
- the time width of the integration window can be 10ms, 50ms, 100ms and other suitable widths, and the energy integration can be the absolute value, square, square root and other calculation methods after taking the average value.
- the vibration information acquired by the acceleration sensor essentially corresponds to hemodynamic acceleration change information, that is, the second high-frequency component information.
- the acceleration change information can be processed by first-order integration to generate the first high-frequency component information. Integrating acceleration vibration information can generate vibration energy information.
- the first high-frequency component information and the second high-frequency component information are expressed by performing first-order differential processing and second-order differential processing on the displacement vibration information. It should be understood that other methods such as polynomial fitting smoothing filter Obtaining signals equivalent to the first high-frequency component information and the second high-frequency component information after the first-order differential processing and the second-order differential processing are also within the protection scope of the present invention.
- curve 41 is a time-domain waveform curve of the first high-frequency component information
- curve 42 is a time-domain waveform curve of the second high-frequency component information
- curve 43 is a vibration energy information curve.
- the horizontal axis represents time, and the vertical axis is dimensionless.
- the curve 41 and the curve 42 are the waveform curves of the hemodynamic related information shown in FIG. 3, that is, the curve 31 after the first-order differential processing and the second-order differential processing.
- Curve 43 is a waveform curve obtained by energy integration of the hemodynamic related information shown in FIG. 3.
- the curve 31, the curve 41, the curve 42, and the curve 43 are placed on the same time axis for synchronous display.
- the hemodynamic related information, the first high-frequency component information, the second high-frequency component information, and the vibration energy information generated based on the vibration information processing are also continuous data.
- the above information is divided into heart beats.
- the center beat can be divided according to the characteristics of hemodynamic related information, first high-frequency component information, or second high-frequency component information waveform signal.
- the heart activity has obvious periodicity, there are some obvious features that are highly repetitive. For example, the heartbeat cycle of a normal person is between 0.6s and 1 second. You can set the search interval accordingly, search for the highest peak, and set the highest peak. As a feature of heartbeat division. Similarly, the lowest valley can also be used as a heartbeat division feature.
- the ECG information of the object can be obtained through the ECG sensor. Because the ECG signal has low noise and clean signal, it is used to divide the heartbeat with high accuracy. Therefore, it can be based on the ECG signal obtained synchronously with the vibration information.
- the hemodynamic related information, the first high-frequency component information, or the second high-frequency component information is divided into heart beats.
- the subsequent process can be to process the hemodynamic related information, the first high-frequency component information, and the second high-frequency component information in each heartbeat, or it can be a preset period of time.
- hemodynamic related information, the first high-frequency component information, and the second high-frequency component information are superimposed and averaged according to the heartbeat to generate the corresponding average information, and then perform follow-up on each average information deal with. Therefore, the hemodynamic related information, the first high-frequency component information, and the second high-frequency component information described below can refer to the data of a heartbeat, or the data after a preset period of time that is superimposed and averaged according to the heartbeat. .
- S1033. Perform wave group division on the hemodynamic related information, the first high frequency component information, and the second high frequency component information, and determine the first wave group, the second wave group, and the third wave group.
- the wave group division method can divide the first wave group, the second wave group and the third wave group based on the information related to hemodynamics and the vibration energy information, and based on the vibration energy information.
- Fig. 5 it is a schematic diagram of an enlarged waveform of a cardiac cycle in Fig. 4 selected. It can be seen that there are two energy envelope bands in the vibration energy information 43, one of which has a relatively high energy peak and its duration window includes the time corresponding to the highest peak of hemodynamics, which is determined as the systolic energy Zone, the other prominent energy peak is the diastolic energy zone.
- the duration of the systolic energy band envelope range is used as the first time window, and the duration of the diastolic energy band envelope range is used as the second time window.
- the wave clusters corresponding to the first time window on the hemodynamic information, the first high frequency component information, and the second high frequency component information synchronized with the vibration energy information are the respective first wave groups and correspond to the second time window.
- the wave clusters are the respective second wave groups, and the "W"-shaped wave group before the respective first wave group is determined as the third wave group. Due to the synchronization in time, for the convenience of comparison, the first wave group on curve 31, curve 41, and curve 42 are uniformly represented as 501, the second wave group is uniformly represented as 502, and the third wave group is uniformly represented Is 503. It should be understood that each of the curve 31, the curve 41 and the curve 42 can be divided into the first wave group, the second wave group and the third wave group.
- the wave group division can also be: while obtaining the object's vibration information, the object's ECG information can be obtained through the ECG sensor.
- the ECG information can help distinguish between the systolic energy zone and the diastolic energy zone, and the ECG information
- the QRS complex is closest to the systolic energy band of the vibration energy information, so the first wave group, the second wave group and the third wave group can be divided by the ECG information.
- the synchronously acquired ECG information is synchronized with the curves in Figure 5 on the same time axis.
- Curve 61 is a schematic diagram of the ECG information. Since the ECG information represents the electrophysiological activity of the heart, Electrophysiological activity has a strong correlation with the mechanical vibration of the heart, so it can be used for verification with vibration information.
- S1034 Determine the first parameter and the second parameter based on the second wave group and the third wave group on the hemodynamic related information, the first high frequency component information, or the second high frequency component information.
- S1034 can be implemented in two ways.
- the distance L11 is the first parameter.
- the amplitude between the second trough in "W” and the first peak after it can also be used as the first parameter.
- the distance L12 is the first parameter. Among them, the curves shown in FIGS.
- curves 7A and 7B are generated based on the thoracic cavity vibration information of subject B, curve 72 is hemodynamic related information, and curve 71 is vibration energy information, which is generated after energy integration of curve 72 Curve, curve 73 is the time-domain waveform curve of the first high-frequency component information, curve 74 is the time-domain waveform curve of the second high-frequency component information, curve 73 and curve 74 are curves 721 for first-order differential processing and second-order differential processing After the wave curve.
- each curve is generated based on the vibration information of the thoracic body surface of the subject C.
- the curve 75 is the ECG information obtained synchronously
- the curve 76 is the vibration energy information
- the curve 77 is the first high-frequency component information.
- the distance L13 is used as the first parameter.
- the distance L21 is the second parameter.
- the amplitude between the second wave trough in "W” and the first wave peak after it can also be used as the second parameter.
- the distance L22 is the first parameter.
- the ECG information obtained in synchronization with the vibration information can be combined with the first wave group.
- the high-frequency component information is placed on the same time axis as a reference after synchronization.
- "W” is usually in the PR interval of ECG information. If the "W" waveform exceeds the range of the third wave group, then the complete “W” waveform is taken as The target "W", the amplitude between the second trough in "W” and the first peak after it is the second parameter. As shown in Figure 7C, the distance L23 is the second parameter.
- the second wave group and the third wave group can also be used to determine the first feature point and the second feature point on the second high-frequency component information; and then based on the first feature point
- the first parameter and the second parameter of the hemodynamic information, the first high-frequency component information or the second high-frequency component information are determined with the second feature point.
- the first step is to determine the first feature point and the second feature point based on the second wave group and the third wave group on the second high frequency component information.
- the first trough after the highest peak of the second wave group of the second high-frequency component information is the first feature point.
- the point 811 is the first feature point.
- a trough search is performed on the third wave group of the second high-frequency component information to determine the second trough as the second feature point.
- the point 812 is the second feature point.
- the curves shown in FIGS. 8A and 8B are generated based on the thoracic cavity vibration information of the subject D.
- the curve 85 is hemodynamic related information
- the curve 82 is the vibration energy information, which is a curve generated after energy integration of the curve 85.
- Curve 83 is the time-domain waveform curve of the first high-frequency component information
- curve 84 is the time-domain waveform curve of the second high-frequency component information
- curve 83 and curve 84 are the first-order differential processing and second-order differential processing of curve 85
- the waveform curve, curve 81 is the ECG information of the object acquired synchronously.
- the first parameter and the second parameter of the hemodynamic information, the first high frequency component information or the second high frequency component information are determined based on the first feature point and the second feature point.
- the amplitude between the trough where the first feature point is located and the first peak before it is determined as the first parameter of the second high frequency component.
- the distance L34 is the first parameter of the second high frequency component.
- the horizontal axis represents time, and the vertical axis is dimensionless.
- the distance L34 refers to the amplitude between the trough where the first feature point is located and the first peak before it.
- the amplitude between the trough where the first feature point is located and the first wave crest after it can also be used as the first parameter of the second high frequency component.
- the distance L35 is the first parameter of the second high frequency component.
- the amplitude between the trough corresponding to the second characteristic point and the first peak after it is determined as the second parameter of the second high-frequency component.
- the distance L44 is the second parameter.
- the amplitude between the trough where the second feature point is located and the first peak before it can also be used as the second parameter of the second high frequency component.
- the distance L45 is the second parameter of the second high frequency component.
- the first parameter and the second parameter can also be taken from the first high-frequency component information or the hemodynamic related information in a similar manner.
- the first parameter and the second parameter can also be taken from the first high-frequency component information or the hemodynamic related information in a similar manner.
- the amplitude between the first trough after the corresponding time point of the first feature point and the first peak before it is determined as the first parameter of the first high-frequency component.
- the distance L14 is the first parameter of the first high frequency component.
- the amplitude between the first wave trough after the corresponding time point of the first feature point and the first wave peak thereafter may also be used as the first parameter of the first high frequency component.
- the distance L15 is the first parameter of the first high frequency component.
- the amplitude between the first trough and the subsequent first peak after the time point corresponding to the second feature point is determined as the second parameter of the first high frequency component.
- the distance L24 is the second parameter of the first high frequency component.
- the amplitude between the first wave trough after the corresponding time point of the second feature point and the first wave peak before it can also be used as the second parameter of the first high frequency component.
- the distance L25 is the second parameter of the first high frequency component.
- the above methods are also applicable to hemodynamic related information.
- the amplitude between the first wave trough after the corresponding time point of the first feature point and the first wave crest thereafter is determined as the first parameter on the hemodynamic related information.
- the distance L55 is the first parameter of the first high frequency component.
- the amplitude between the first trough after the corresponding time point of the second feature point and the first peak before it is determined as the first in hemodynamic related information parameter.
- the distance L65 is the second parameter of the first high frequency component.
- Transvalvular blood flow mainly refers to the blood flow from the left atrium across the mitral valve into the left ventricle.
- the ventricular filling event in the early diastole and the atrial contraction event in the end diastole can obtain information of different dimensions through different sensors.
- the electrophysiological sensor can obtain the electrical signal of the event
- the vibration sensor can obtain the vibration signal of the event.
- the thoracic body surface motion of the subject can be acquired through the vibration sensor, and then the ventricular filling event in the early diastole of the subject and the atrial contraction event in the end diastole of the subject can be extracted therefrom.
- the ventricular filling events in the early diastole include the vibrations formed on the body surface of the subject by muscle movement and blood flow movement caused by ventricular filling
- the atrial contractions in the end diastole include the vibrations formed by the muscle and blood flow movement on the body surface caused by atrial contractions.
- we select the first parameter to characterize the vibration amplitude caused by ventricular filling in the early diastole of the heart and blood flow motion on the body surface of the subject and select the second parameter to characterize the end-diastolic atrial contraction.
- the vibration amplitude formed by the movement of muscles and blood flow on the body surface. It is understandable that in addition to the vibration amplitude, we can also select parameters that characterize vibration energy, vibration frequency, or vibration time to characterize early diastolic ventricular filling events and end diastolic atrial contractions.
- the first parameter when the first parameter is taken as the second trough in W of the second wave group in the first high-frequency component information, or the falling edge amplitude formed by the first feature point and the first peak before it, It is used to characterize the vibration amplitude of muscle and blood flow on the body surface caused by the acceleration event of transvalvular blood flow in the early diastole, such as L11, L14, L34; when the first parameter is the second wave group in the first high frequency component information
- the second trough in W or the rising edge amplitude formed by the first feature point and the first peak after it is used to characterize the vibration formed on the body surface caused by the transvalvular blood flow deceleration event in the early diastole Amplitude, such as L12, L55, L15, L35.
- the two values of the second parameter are both used to characterize the vibrations formed on the body surface caused by atrial contraction, such as L24, L25, L44, and L45.
- S104 Generate an indicator parameter based on the first parameter and the second parameter, and evaluate the cardiac filling pressure state of the subject based on the indicator parameter.
- the ratio of the first parameter to the second parameter can be used as the indicator parameter
- the indicator parameter obtained on the first high frequency component information can be used as the indicator parameter I1
- the indicator parameter obtained on the second high frequency component information can be used as the indicator parameter.
- I2 the indicator parameter obtained on the hemodynamic information is used as the indicator parameter I3.
- indicating parameter I1 L12/L22
- indicating parameter I2 L35/L45
- indicating parameter I3 L55/L65.
- the state of high filling pressure of the heart is considered to be the state of ultrasound parameters E/e'>14, Vtr>2.8m/s, E/A>1.
- the heart is in a restrictive filling state, the active relaxation ability is impaired and the ventricles Wall compliance is reduced, and high filling pressure will cause heart function to enter a rapid vicious circle, requiring timely intervention to prevent further deterioration of the patient.
- FIG. 9A is a schematic diagram of the first parameter and the second parameter calculated according to the vibration information of the thoracic body surface of the subject E.
- the subject E is a patient with heart failure in a state of high filling pressure.
- the curve 91 is the ECG information obtained synchronously with the vibration information
- the curve 93 is the time-domain waveform diagram of hemodynamic related information
- the curve 92 is the time-domain waveform diagram of the vibration energy information, which is after the energy integration of the curve 93 Generated
- curve 94 is the time-domain waveform curve of the first high-frequency component information
- curve 95 is the time-domain waveform curve of the second high-frequency component information
- curve 94 and curve 95 are curves 93 for first-order differentiation processing and second-order differentiation The processed wave curve.
- the first parameter can be L955, L915, L935, and the second parameter can be L965, L925, L915.
- the ratio of the first parameter and the second parameter is selected to characterize the change.
- a person of ordinary skill in the art can obtain a method for evaluating the diastolic function when the ratio of the second parameter to the first parameter is used as the indicator parameter, which is also included in the protection scope of the present invention.
- the second parameter and the first parameter can be subjected to other operations to generate the indicator parameter, including but not limited to: addition, subtraction, multiplication, division, exponent and other operations are also protected by the present invention. Within range.
- the 25 patients with heart failure included 12 patients with high filling pressure (marked as positive) and 13 patients with non-high filling pressure (marked as negative).
- the indicator parameters of 25 test subjects were calculated, and the sensitivity and specificity of the indicator parameters of 25 test subjects were analyzed, and the ROC curve was constructed as shown in Figures 9B, 9C and 9D, respectively.
- the indicating parameter I1, indicating parameter I2, and indicating parameter I3 ROC curve According to the index parameter I1 to discriminate the state of cardiac filling pressure: the AUC area is 0.833, and the best cut-off value is 0.801.
- the threshold is a threshold determined based on people with heart failure.
- the threshold may also be an absolute threshold, which is used to distinguish between normal people and people with diastolic dysfunction.
- the threshold value may also be a threshold value based on the subject itself. For example, a relative threshold value when the diastolic function deteriorates can be obtained based on the analysis of personal history data of the monitored subject.
- the diastolic function of the heart is characterized by the state of ventricular filling pressure, for example, the state of high filling pressure is indicative of severe diastolic dysfunction.
- the diastolic function of the heart can also be characterized by atrial pressure.
- the heart structure causes the left ventricular filling pressure to be correlated with left atrial pressure and pulmonary artery pressure. Therefore, in some embodiments, the indicator parameters can be used to evaluate the filling pressure state, It can be used to indirectly evaluate the left atrial pressure state, the pulmonary artery pressure state and the degree of heart failure after a series of transformations, and it is also within the protection scope of the present invention.
- the second embodiment of the present invention provides a computer-readable storage medium that stores a computer program that, when executed by a processor, implements the diastolic function assessment method provided in the first embodiment of the present invention A step of.
- the third embodiment of the present invention provides a diastolic function evaluation device.
- FIG. 10 shows a structural block diagram of the diastolic function evaluation device 200.
- the diastolic function evaluation device 200 may be a dedicated computer device specially designed to process the vibration information of the optical fiber sensor.
- the diastolic function evaluation device 200 may include a communication port 201 connected to a network connected to it to facilitate data communication.
- the diastolic function assessment device 200 may further include a processor 203, in the form of one or more processors, for executing computer instructions.
- the computer instructions may include, for example, routines, programs, objects, components, data structures, procedures, modules, and functions that perform the cardiac filling pressure assessment method described herein.
- the processor 203 can obtain the vibration information of the optical fiber sensor, and preprocess the vibration information to generate hemodynamic related information.
- the processor 203 may include one or more hardware processors, such as a microcontroller, a microprocessor, a reduced instruction set computer (RISC), an application specific integrated circuit (ASIC), a graphics processing unit (GPU), and a central Processing unit (CPU), digital signal processor (DSP), field programmable gate array (FPGA), advanced RISC machine (ARM), programmable logic device (PLD), etc. Any circuit or processing capable of performing one or more functions ⁇ , etc., or any combination thereof.
- RISC reduced instruction set computer
- ASIC application specific integrated circuit
- GPU graphics processing unit
- CPU central Processing unit
- DSP digital signal processor
- FPGA field programmable gate array
- ARM advanced RISC machine
- PLD programmable logic device
- the diastolic function assessment device 200 may include an internal communication bus 205, a memory 207 for processing and/or sending various data files by the computer, and other types of non-transitory storage media stored in the memory 207 and executed by the processor 203 Program instructions in. The method and/or process of this application can be implemented as program instructions.
- the diastolic function evaluation device 200 also includes an input/output component 209, which supports input/output between the computer and other components (for example, user interface elements).
- the diastolic function assessment device 200 in this application may also include multiple processors. Therefore, the operations and/or method steps disclosed in the present application may be executed by one processor as described in the present application. Can be executed jointly by multiple processors. For example, if the processor 203 of the diastolic function assessment device 200 in the present application performs step A and step B, it should be understood that step A and step B can also be performed jointly or separately by two different processors in information processing ( For example, the first processor performs step A, the second processor performs step B, or the first and second processors jointly perform steps A and B).
- the fourth embodiment of the present invention provides a system for monitoring the filling pressure state of the heart, including:
- One or more vibration sensors are One or more vibration sensors.
- a device for evaluating the filling pressure state of the heart provided in the third embodiment of the present invention.
- a cardiac hypertension state monitoring system 300 may include one or more vibration sensors 301, one or more diastolic function assessment devices 303, and one or more storage devices 305.
- the vibration sensor 301 may be an acceleration sensor, a speed sensor, a displacement sensor, a pressure sensor, a strain sensor, a stress sensor, and it may also be a sensor that converts physical quantities equivalently based on acceleration, speed, displacement, or pressure (for example, Static charge sensitive sensors, gas-filled micro-motion sensors, radar sensors, etc.).
- the strain sensor can be an optical fiber sensor.
- the vibration sensor 301 is an optical fiber sensor, it can be placed under the subject's body.
- the subject can be in a posture such as supine, prone, side-lying, etc.
- the optical fiber sensor can be placed on the bed, and the subject is supine (prone or side) on it.
- the preferred measurement position is that the fiber optic sensor is configured to be placed under the subject's back
- the preferred measurement state is that the fiber optic sensor is configured to be placed in the area between the subject's left and right shoulder blades.
- the body surface area corresponding to the left and right shoulder blades of the subject is defined as the middle shoulder.
- the vibration sensor can also be placed on the contact surface behind the supine human body at a certain tilt angle, the contact surface behind the reclining human body on a wheelchair or other objects that can lean on, and so on to collect vibration information.
- the diastolic function evaluation device 303 is as described in the third embodiment of the present invention.
- the diastolic function evaluation device 303 may be connected to the vibration sensor 301 through the network 320.
- the network 320 may be a single network, such as a wired network or a wireless network, or a combination of multiple networks.
- the network 320 may include, but is not limited to, a local area network, a wide area network, a shared network, a dedicated network, and the like.
- the network 320 may include a variety of network access points, such as wireless or wired access points, base stations or network access points, through which other components of the cardiac filling pressure monitoring system 300 can connect to the network 103 and pass through the network Send information.
- the storage device 305 may be configured to store data and instructions.
- the storage device 305 may include, but is not limited to, random access memory, read only memory, programmable read only memory, and the like.
- the storage device 305 may be a device that uses electrical energy, magnetic energy, and optical methods to store information, such as hard disks, floppy disks, magnetic core memories, CDs, DVDs, and the like.
- the storage devices mentioned above are just some examples, and the storage devices used by the storage device 305 are not limited to these.
- the cardiac filling pressure monitoring system 300 may further include an output device 307 configured to output the result of diastolic function evaluation, and the output method includes but is not limited to graphics, text, data, voice, etc., for example One or more of graphic display, digital display, voice broadcast, braille display, etc.
- the output device 307 may be one or more of a display, a mobile phone, a tablet computer, a projector, a wearable device (watch, earphone, glasses, etc.), a braille display, and the like.
- the output device 307 may display the assessment result of the cardiac filling pressure of the subject 102 in real time.
- the output device 307 may display a report in a non-real-time manner, which is the measurement result of the subject in a preset time period.
- the user For example, the user’s cardiac filling pressure monitoring results during the sleeping time period.
- the monitoring object is a patient with heart failure
- the diastolic function assessment device evaluates its diastolic function as a high filling pressure state, the patient with heart failure will face a worsening heart failure at this time and require hospitalization.
- the output of the monitoring system The device can send reminders to the heart failure patient, such as sending text messages, emails, phone calls, WeChat and other instant chat messages, and can also send messages to the family doctor of the heart failure patient, prompting that the patient may be facing worsening heart failure to help The doctor makes decisions.
- the system may further include a doctor-patient communication platform, and when the doctor receives the system push, the patient may be facing worsening heart failure, and communicate with the patient in time.
- the output device 307 can also implement an early warning function, such as a voice warning.
- an early warning function such as a voice warning.
- the diastolic function assessment device assesses the diastolic function of a heart failure patient as a high filling pressure state, the heart failure patient will face a worsening heart failure at this time. Remind patients to see a doctor in time through sound.
- the invention monitors the filling pressure of the heart by collecting the vibration information of the user, without intruding the human body, passively measuring, and can realize continuous monitoring.
- the user only needs to lie on the measuring device to perform the measurement without the assistance of professionals, and It has the advantages of high measurement accuracy and simple operation, can improve the comfort of the tester, and can be applied to scenes such as hospitals and homes.
- the cardiac filling pressure state monitoring system provided by the present invention can evaluate the user's cardiac filling pressure state, and then warn the user in advance when signs of deterioration appear, helping the user to avoid the consequences of deterioration.
- the program can be stored in a computer-readable storage medium, and the storage medium can include: Read Only Memory (ROM, Read Only Memory), Random Access Memory (RAM, Random Access Memory), magnetic disks or CDs, etc.
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Abstract
Description
Claims (23)
- 一种心脏舒张功能评估方法,其特征在于,所述方法包括:非侵入式获取对象胸腔体表的振动信息;对所述振动信息进行预处理生成血流动力学相关信息;基于所述血流动力学相关信息确定第一参数和第二参数,其中,第一参数用于表征心脏舒张早期心室充盈事件,第二参数用于表征心脏舒张末期心房收缩事件;基于所述第一参数和第二参数生成指示参数,并基于所述指示参数评估所述对象的心脏舒张功能。
- 如权利要求1所述的方法,其特征在于,所述非侵入式获取对象胸腔体表的振动信息包括通过一个或多个振动传感器获取对象胸腔体表的振动信息。
- 如权利要求2所述的方法,其特征在于,所述振动传感器是加速度传感器、速度传感器、位移传感器、压力传感器、应变传感器、应力传感器、或者是以加速度、速度、压力、或位移为基础将物理量等效性转换的传感器中的一种或多种。
- 如权利要求3所述的方法,其特征在于,所述应变传感器包括光纤传感器,所述光纤传感器被配置为置于所述对象的身体下方。
- 如权利要求2所述的方法,其特征在于,所述振动传感器的配置位置之一为所述对象的左肩胛骨和右肩胛骨之间区域的下方。
- 如权利要求2所述的方法,其特征在于,所述振动传感器的感应区域的面积至少是二十平方厘米。
- 如权利要求5所述的方法,其特征在于,所述振动传感器的感应区域的面积覆盖所述对象的左肩胛骨和右肩胛骨之间的体表区域。
- 如权利要求1所述的方法,其特征在于,所述对象的身体姿势之一是仰卧。
- 如权利要求1所述的方法,其特征在于,所述预处理包括滤波、去噪、信号缩放中的至少一种。
- 如权利要求1所述的方法,其特征在于,所述心脏舒张早期心室充盈事件是心脏舒张早期心室充盈造成的肌肉和血流运动在体表形成的振动;所述心脏舒张末期心房收缩事件是心脏舒张末期心房收缩造成的肌肉和血流运动在体表形成的振动。
- 如权利要求10所述的方法,其特征在于,所述第一参数包括心脏舒张早期心室充盈造成的肌肉和血流运动在体表形成的振动幅度,所述第二参数包括心脏舒张末期心房收缩造成的肌肉和血流运动在体表形成的振动幅度。
- 12 如权利要求11所述的方法,其特征在于,所述基于所述血流动力学相关信息确定第一参数和第二参数包括:直接在所述血流动力学相关信息上确定第一参数和第二参数;或者对所述血流动力学相关信息进行高频分量提取,生成第一高频分量信息或第二高频分量信息,在所述第一高频分量信息或第二高频分量信息上确定第一参数和第二参数,其中第一高频分量信息用于表征速度,第二高频分量信息用于表征加速度。
- 如权利要求12所述的方法,其特征在于,所述直接在所述血流动力学相关信息上确定第一参数和第二参数,或者在所述第一高频分量信息或第二高频分量信息上确定第一参数和第二参数,包括:对所述血流动力学相关信息进行能量积分生成振动能量信息,所述振动能量信息在一个心动周期内包含两个能量包络带;将所述血流动力学相关信息、第一高频分量信息、或第二高频分量信息与所述振动能量信息置于同一时间轴同步,确定所述血流动力学相关信息、第一高频分量信息、或第二高频分量信息在同一个心动周期内的最高峰;将所述振动能量信息两个能量包络带中包括所述血流动力学相关信息、第一高频分量信息、或第二高频分量信息的最高峰的能量包络带的持续时间确定为第一时间窗,另一个能量包络带的持续时间确定为第二时间窗;在所述血流动力学相关信息、第一高频分量信息、或第二高频分量信息上将处于第一时间窗之内的波丛确定为第一波群,在第二时间窗之内的波丛确定为第二波群,第一波群之前的W形状的波丛确定为第三波群;基于所述第二波群和第三波群确定第一参数和第二参数。
- 如权利要求 13所述的方法,其特征在于,基于所述第二波群和第三波群确定第一参数和第二参数,包括:对第二波群进行“W”波形搜索,确定 “W”中第二个波谷与其前第一个波峰间的幅度作为第一参数,或者是确定 “W”中第二个波谷与其后第一个波峰间的幅度作为第一参数;对第三波群进行“W” 波形搜索,确定“W”中第二个波谷与其后第一个波峰间的幅度作为第二参数,或者是确定 “W”中第二个波谷与其前第一个波峰间的幅度作为第二参数。
- 如权利要求12所述的方法,其特征在于,所述方法包括:对所述血流动力学相关信息进行能量积分生成振动能量信息,所述振动能量信息在一个心动周期内包含两个能量包络带;将所述第二高频分量信息与所述振动能量信息置于同一时间轴同步,确定所述第二高频分量信息在同一个心动周期内的最高峰;将所述振动能量信息两个能量包络带中包括所述第二高频分量信息的最高峰的能量包络带的持续时间确定为第一时间窗,另一个能量包络带的持续时间确定为第二时间窗;在所述第二高频分量信息上将处于第一时间窗之内的波丛确定为第一波群,在第二时间窗之内的波丛确定为第二波群,第一波群之前的W形状的波丛确定为第三波群;确定所述第二波群的最高峰之后的第一个波谷为第一特征点,确定所述第三波群的第二个波谷为第二特征点;在所述第二高频分量信息上,确定第一特征点与其前第一个波峰间的幅度作为第二高频分量的第一参数;或者是将第一特征点与其后第一个波峰间的幅度作为第二高频分量的第一参数;在同一个心动周期内,在第二高频分量信息上,确定第二特征点与其后第一个波峰间的幅度作为第二高频分量的第二参数;或者是将第二特征点与其前第一个波峰间的幅度作为第二高频分量的第二参数;在所述第一高频分量信息和血流动力学相关信息上,确定第一特征点对应时间点之后的第一个波谷与其前第一个波峰间的幅度作为第一高频分量和血流动力学相关信息上的第一参数;或者是将第一特征点对应时间点之后的第一个波谷与其后第一个波峰间的幅度作为第一高频分量和血流动力学相关信息上的第一参数;在同一个心动周期内,在第一高频分量信息和血流动力学相关信息上,确定第二特征点对应时间点之后的第一个波谷与其后第一个波峰间的幅度作为第一高频分量和血流动力学相关信息的第二参数;或者是将第二特征点对应时间点之后的第一个波谷与其前第一个波峰间的幅度作为第一高频分量和血流动力学相关信息的第二参数。
- 16 如权利要求1所述的方法,其特征在于,所述基于所述指示参数评估所述对象的心脏舒张功能包括评估所述对象的心脏充盈压状态。
- 如权利要求16所述的方法,其特征在于,所述基于所述指示参数评估所述对象的心脏充盈压的状态,具体是:确定第一参数与第二参数的比值作为指示参数;当所述指示参数大于阈值时,判定所述对象心脏为高充盈压状态。
- 如权利要求17所述的方法,其特征在于,所述阈值是基于人群的阈值。
- 如权利要求1所述的方法,其特征在于,所述血流动力学相关信息是:一个心动周期内的数据;或预设时间段内的以心动周期为单位进行叠加和平均后的数据。
- 一种计算机可读存储介质,所述计算机可读存储介质存储有计算机程序,其特征在于,所述计算机程序被处理器执行时实现如权利要求1至19任一项所述的心脏舒张功能评估方法的步骤。
- 一种用于心脏舒张功能评估的设备,包括:一个或多个处理器;存储器;以及一个或多个计算机程序,其中所述一个或多个计算机程序被存储在所述存储器中,并且被配置成由所述一个或多个处理器执行,其特征在于,所述处理器执行所述计算机程序时实现如权利要求1至19任一项所述的心脏舒张功能评估方法的步骤。
- 一种用于心脏充盈压状态监测的系统,其特征在于,所述系统包括:一个或多个振动传感器,用来获取所述对象的胸腔体表振动信息;和与振动传感器连接的,如权利要求21所述的用于心脏舒张功能评估的设备。
- 一种基于机器学习的心脏充盈压评估系统,其特征在于,所述系统包括:一个或多个处理器,所述处理器被集中或各自编程为实现:接收对象的胸腔体表振动信息作为训练输入信息;通过机器学习对训练输入信息进行分析建立评估模型;接收待评价对象的胸腔体表振动信息,所述评估模型对所述待评价对象的心脏充盈压状态做出评估;其中,评估模型执行以下操作:对所述振动信息进行预处理生成血流动力学相关信息;基于所述血流动力学相关信息确定第一参数和第二参数,其中,第一参数用于表征心脏舒张早期心室充盈事件,第二参数用于表征心脏舒张末期心房收缩事件;基于所述第一参数和第二参数生成指示参数,并基于所述指示参数评估所述对象的心脏舒张功能。
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Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5178151A (en) * | 1988-04-20 | 1993-01-12 | Sackner Marvin A | System for non-invasive detection of changes of cardiac volumes and aortic pulses |
US20070055170A1 (en) * | 2005-09-08 | 2007-03-08 | Michael Lippert | Device for determining cardiac function parameters |
US20140275976A1 (en) * | 2013-03-15 | 2014-09-18 | Adventist Health System/Sunbelt, Inc. | Global Ventricular Cardiac Diastolic Function Evaluation System and Associated Methods |
US20150038856A1 (en) * | 2011-05-03 | 2015-02-05 | Heart Force Medical Inc | Method and apparatus for estimating myocardial contractility using precordial vibration |
CN107427260A (zh) * | 2015-08-27 | 2017-12-01 | 深圳市大耳马科技有限公司 | 光纤传感器以及监测微运动的方法 |
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WO2012090208A2 (en) * | 2010-12-29 | 2012-07-05 | Diacardio Ltd. | Automatic left ventricular function evaluation |
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Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5178151A (en) * | 1988-04-20 | 1993-01-12 | Sackner Marvin A | System for non-invasive detection of changes of cardiac volumes and aortic pulses |
US20070055170A1 (en) * | 2005-09-08 | 2007-03-08 | Michael Lippert | Device for determining cardiac function parameters |
US20150038856A1 (en) * | 2011-05-03 | 2015-02-05 | Heart Force Medical Inc | Method and apparatus for estimating myocardial contractility using precordial vibration |
US20140275976A1 (en) * | 2013-03-15 | 2014-09-18 | Adventist Health System/Sunbelt, Inc. | Global Ventricular Cardiac Diastolic Function Evaluation System and Associated Methods |
CN107427260A (zh) * | 2015-08-27 | 2017-12-01 | 深圳市大耳马科技有限公司 | 光纤传感器以及监测微运动的方法 |
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