WO2020232604A1 - 一种心脏舒张功能评估方法、设备和*** - Google Patents

一种心脏舒张功能评估方法、设备和*** Download PDF

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Publication number
WO2020232604A1
WO2020232604A1 PCT/CN2019/087632 CN2019087632W WO2020232604A1 WO 2020232604 A1 WO2020232604 A1 WO 2020232604A1 CN 2019087632 W CN2019087632 W CN 2019087632W WO 2020232604 A1 WO2020232604 A1 WO 2020232604A1
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parameter
information
frequency component
vibration
subject
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PCT/CN2019/087632
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English (en)
French (fr)
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褚正佩
赵东东
曾令均
刘蓬勃
庄少春
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深圳市大耳马科技有限公司
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Priority to PCT/CN2019/087632 priority Critical patent/WO2020232604A1/zh
Priority to US17/613,033 priority patent/US20220248962A1/en
Priority to CN201980074503.4A priority patent/CN113226170B/zh
Publication of WO2020232604A1 publication Critical patent/WO2020232604A1/zh

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • 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
    • A61B5/021—Measuring pressure in heart or blood vessels
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1102—Ballistocardiography
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • 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
    • A61B5/021—Measuring pressure in heart or blood vessels
    • A61B5/02108—Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • 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
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • 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
    • A61B5/6813—Specially adapted to be attached to a specific body part
    • A61B5/6823—Trunk, e.g., chest, back, abdomen, hip
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • A61B5/7267—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271—Specific aspects of physiological measurement analysis
    • A61B5/7285—Specific aspects of physiological measurement analysis for synchronising or triggering a physiological measurement or image acquisition with a physiological event or waveform, e.g. an ECG signal
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2562/00—Details of sensors; Constructional details of sensor housings or probes; Accessories for sensors
    • A61B2562/02—Details of sensors specially adapted for in-vivo measurements
    • A61B2562/0219—Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2562/00—Details of sensors; Constructional details of sensor housings or probes; Accessories for sensors
    • A61B2562/02—Details of sensors specially adapted for in-vivo measurements
    • 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

一种心脏舒张功能评估方法（100），用于心脏监测领域，方法（100）包括：非侵入式获取对象胸腔体表的振动信息（101）；对振动信息进行预处理生成血流动力学相关信息（102）；基于血流动力学相关信息确定第一参数和第二参数（103）；基于第一参数和第二参数生成指示参数，并基于指示参数评估对象的心脏舒张功能（104）。

Description

一种心脏舒张功能评估方法、设备和*** 技术领域
本发明属于心脏监测领域，尤其涉及一种非侵入式心脏舒张功能评估方法、设备和***。
 背景技术
心力衰竭（简称心衰）是一个包含多种病因和发病机制的临床综合征。随着人口老龄化以及急性心肌梗死患者存活率的升高，慢性心衰患者的数量快速增长。心衰患者从慢性状态过度到急性的恶化状态中，伴随着心脏充盈压的升高。其中高充盈会使心脏功能进入快速的恶性循环，但是患者本身要在充盈压持续升高约20天左右，才感觉到症状从而需要紧急入院，这时心脏的损伤已经发生，且不可逆转。当识别到患者处于高充盈压状态时，需要及时干预，从而可以避免患者进一步恶化，这一点已经成为临床医生的共识。
目前有植入性产品用于评估心脏舒张功能，但价格较高，而且若只为监测所需，患者接受度较差。因此需要一种对人体更友好、使用方便的产品来监测心脏舒张功能。
 技术问题
本发明的目的在于提供一种能评估测量对象的心脏舒张功能的评估方法、设备、***和计算机可读存储介质, 旨在实现非侵入式评估心脏舒张功能。
 技术解决方案
第一方面，本发明提供了一种心脏舒张功能评估方法，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。
第二方面，本发明提供了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，所述计算机程序被处理器执行时实现如上述的心脏舒张功能评估方法的步骤。
第三方面，本发明提供了一种心脏舒张功能评估设备，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，所述处理器执行所述计算机程序时实现如上述的心脏舒张功能评估方法的步骤。
第四方面，本发明提供了一种心脏舒张功能评估***，所述***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，如上述的心脏舒张功能评估设备。
 有益效果
本发明是通过采集使用者的振动信息来监测心脏的舒张功能，无需侵入人体，被动测量，而且可以实现连续监测，使用者只需要躺在测量设备上即可进行测量，无需专业人员辅助，并且具有测量精度高、操作简单的优点，能提高测试者的舒适性，可以适用于医院和家庭等场景。本发明提供的心脏舒张功能评估***，可以评估使用者的心脏舒张功能，进而在出现恶化迹象时提前预警，帮助使用者避免恶化后果。
 附图说明
图1是依据本发明实施例一提供的心脏舒张功能评估方法的流程图；
图2是光纤传感器采集得到的对象A的振动信息的波形示意图；
图3是血流动力学相关信息的时域波形示意图；
图4是血流动力学相关信息、第一高频分量信息和第二高频分量信息位于同一时间轴的时域波形示意图；
图5是一个心动周期内血流动力学相关信息、振动能量信息、第一高频分量信息和第二高频分量信息的第一波群、第二波群和第三波群的示意图；
图6是一个心动周期内心电信息、血流动力学相关信息、振动能量信息、第一高频分量信息和第二高频分量信息置于同一时间轴的时域波形示意图；
图7A和图7B是基于对象B的振动信息的第一参数和第二参数的取值示意图；
图7C是基于对象C的振动信息的第一参数和第二参数的取值示意图；
图8A和图8B是基于对象D的振动信息的第一参数和第二参数的取值示意图；
图9A是基于对象E的振动信息的第一参数和第二参数的取值示意图；
图9B、图9C和图9D是指示参数的ROC曲线图；
图10是依据本发明实施例三提供的心脏舒张功能评估设备的结构框图；
图11是依据本发明实施例四提供的心脏充盈压状态监测***的结构框图。
 本发明的实施方式
为了使本发明的目的、技术方案及有益效果更加清楚明白，以下结合附图及实施例，对本发明进行进一步详细说明。应当理解，此处所描述的具体实施例仅仅用以解释本发明，并不用于限定本发明。
如本发明和权利要求书中所示，除非上下文明确提示例外情形，“一”、“一个”、“一种”和/或“该”等词并非特指单数，也可包括复数。一般说来，术语“包括”与“包含”仅提示包括已明确标识的步骤和元素，而这些步骤和元素不构成一个排它性的罗列，方法或者设备也可能包含其它的步骤或元素。
为了说明本发明所述的技术方案，下面通过具体实施例来进行说明。
实施例一：
请参阅图1，本发明实施例一提供的一种心脏舒张功能评估方法100包括以下步骤：需注意的是，若有实质上相同的结果，本发明的心脏舒张功能评估方法并不以图1所示的流程顺序为限。
S101、非侵入式获取对象胸腔体表的振动信息。
在本发明实施例一中，非侵入式获取对象胸腔体表振动信息可以是通过一个或多个振动传感器获取的。振动传感器可以是加速度传感器、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，此外还可以是以加速度、速度、位移、或压力为基础将物理量等效性转换的传感器（例如静电荷敏感传感器、充气式微动传感器、雷达传感器等）。其中应变传感器可以是光纤传感器。在本发明实施例一中，非侵入式获取对象胸腔体表振动信息还可以是通过其他方式获取的，例如光电传感器。
在实施例一中，通过光纤传感器采集对象的胸腔体表振动信息，光纤传感器可被放置于对象身体下方。例如对象可以呈仰卧、俯卧、侧卧等姿势，光纤传感器可放置于床上，对象仰卧（俯卧或侧卧）于其上。以对象呈仰卧姿势为例，光纤传感器可以被配置为置于对象的背部下方，较佳的测量状态是光纤传感器被配置为置于对象的左肩胛骨和右肩胛骨之间的区域下方，也就中肩下方，一般地，为描述方便，将对象左肩胛骨和右肩胛骨之间所对应的体表区域定义为中肩。本领域普通人员可以理解的是，当对象呈俯卧姿势时，测量位置是与呈仰卧姿势时的测量位置对应的，例如与背部对应的测量位置是对象的胸部。光纤传感器还可以放置于一定倾斜角仰卧人体背后的接触面、轮椅或其它可倚靠物体的倚卧人体背后的接触面等进行振动信息的采集。此外，振动传感器还可以置于呈仰卧姿势的对象的身体上方，例如加速度传感器可以置于对象的心尖对应的胸部体表区域之上。
振动传感器应至少一个，当振动传感器有多个时，各传感器独立且同步工作，每个传感器的大小可以相同，也可以被设计成不同的尺寸，比如20cm*30cm的传感器或者5cm*4cm的传感器，任意尺寸的传感器可以以任意方式排列组合。例如在一些实施例中，体型较瘦小的对象可以配置一块大传感器，也可以配置两块小传感器，而体型较宽的对象可以配置两块大传感器或两块小传感器和一块大传感器组合的形式。当振动传感器采用光纤传感器时，至少一个光纤传感器被置于对象右肩部分，光纤传感器可以直接置于对象身体下方，也可以放置于床垫下方与对象非直接接触。在一些例子中，光纤传感器的感应区域至少是20平方厘米，此处的感应区域是指振动传感器实际用来感应振动的区域（例如，光纤传感器的感应区域是指光纤传感器中光纤分布的区域）。
图2所示为光纤传感器采集得到的一个对象的振动信息的波形示意图。其中，曲线21的横轴表示时间，纵轴表示归一化处理后的振动信息，无量纲。振动传感器采集的振动信息包含被测对象呼吸信号成分、血流动力学信号成分、以及环境微震动、被测对象体动引起的干扰和电路自身的噪声信号。此时的信号大轮廓即为人体呼吸产生的信号包络，而血流动力学信号与其它干扰噪声则叠加在呼吸包络曲线上。
S102、对振动信息进行预处理生成血流动力学相关信息。
不同的传感器获得的振动信息包含的信息量不同，有的包含的信息量比较丰富，因此需要对其进行预处理来捕获相关信号。例如，振动传感器采用光纤传感器时获得的振动信息中还包含被测对象的呼吸信号、体动信号、血流动力学信号、传感器固有的一些噪声等信号。
在本发明实施例一中，S102具体可以包括：
对振动信息进行滤波、去噪、信号缩放中的至少一种，得到血流动力学相关信息；具体可以为：根据对滤波后信号特征的需求采用IIR滤波器、FIR滤波器、小波滤波器、零相位双向滤波器、多项式拟合平滑滤波器、积分变换、微分变换中的一种或多种组合，对振动信息进行滤波去噪。例如对所述振动信息滤除2Hz以下的信息可以滤除呼吸信号和体动信号。预处理还可以包括：判断振动信息是否携带工频干扰信号，如果有，则通过工频陷波器滤除工频噪声。还可以对一些高频噪声（例如45Hz以上）进行去噪处理，处理后的信息可以根据情况进行信号缩放后可得到血流动力学相关信息。也可以直接设置滤波区间，例如滤波区间可以是1Hz-50Hz之间的任意区间。
如图3所示为对图2所示的光纤传感器获取的振动信息进行预处理后的血流动力学相关信息的时域波形示意图，曲线31滤波区间选择的是9Hz-45Hz。曲线31每个波形特征明显且一致性良好、周期规律、轮廓清晰、基线平稳，也即信号质量较佳。
S103、基于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。
在实施例一中，S103具体可以包括：
S1031、对血流动力学相关信息进行处理生成第一高频分量信息、第二高频分量和振动能量信息。其中，第一高频分量信息用于表征速度信号；第二高频分量信息用于表征加速度信号；振动能量信息用于表征能量信号。
心脏的周期性搏动会导致各种变化的周期现象，例如心内压和心血管压、心房与心室的容积、心内瓣膜（包括二尖瓣、三尖瓣、主动脉瓣、肺动脉瓣）的启闭、血流速度等的周期变化。这些变化驱使血液在血管中沿着一定的方向流动。血流动力学(hemodynamics)研究的是血液在心血管***中流动的力学，是以血液与血管的变形和流动为研究对象。本发明描述的“血流动力学相关信息”指任何与血流动力学相关的信息，可以包括但不限于，与血流产生相关的信息（例如心脏的收缩舒张导致射血）、与血流流动相关的信息（例如心排量CO（cardiac output）、左心室射血冲击主动脉弓）、与血流压力相关的信息（例如动脉收缩压、舒张压、平均动脉压）、与血管相关的信息（例如血管弹性）中的一种或几种。心脏的周期性搏动可以维持血液循环，因此与心脏搏动相关的各种参数，例如心内瓣膜的启闭、心房与心室容积的变化、心房与心室压力的变化、心房与心室中血流的流速和方向等，都是与血流动力学相关的信息。
通过光纤传感器获取的振动信息本质上对应的是位移变化信息，位移变化信息较为平滑，一些加速度或速度的变化细节在位移变化信息上较难识别。例如速度从零逐渐增加到某一峰值，再从该峰值逐渐递减到零，速度变化曲线形成先上升后下降的波形，但是位移变化曲线为单调波形。因此相较于与位移对应的信号分量而言，与速度、加速度对应的信号分量对应的峰谷时间宽度更窄，称之为高频分量信息。高频分量提取方法可以是多项式拟合平滑滤波的方式，还可以对血流动力学相关信息进行微分处理生成高频分量信息，例如，S1031具体可以是对血流动力学相关信息进行一阶微分处理生成第一高频分量信息和进行二阶微分处理生成第二高频分量信息。振动能量信息可以通过对位移变化信息逐点计算指定时间窗口的能量积分生成。积分窗口的时间宽度可以是10ms，50ms，100ms等合适宽度，能量积分可以是取均值后的绝对值、平方、平方根等计算方式。
此外，通过加速度传感器获取的振动信息本质上对应的是血流动力学加速度变化信息，即第二高频分量信息，这时可以对加速度变化信息进行一阶积分处理生成第一高频分量信息，对加速度振动信息进行积分可以生成振动能量信息。
其它种类的传感器，例如雷达波，如果本质上感受的也是对象的身***移振动变化，因此本领域普通人员可以理解的是，其信号处理可以采用上述的光纤传感器的信号处理过程，也在本发明的保护范围之内。
本发明中对第一高频分量信息和第二高频分量信息是以对位移振动信息进行一阶微分处理和二阶微分处理表述的，应当理解的是，通过其他方法例如多项式拟合平滑滤波方式等获得与一阶微分处理和二阶微分处理后的第一高频分量信息和第二高频分量信息等效的信号，也在本发明的保护范围之内。
如图4所示，曲线41是第一高频分量信息的时域波形曲线，曲线42是第二高频分量信息的时域波形曲线，曲线43是振动能量信息曲线。横轴表示时间，纵轴无量纲。曲线41和曲线42是图3所示的血流动力学相关信息即曲线31进行一阶微分处理和二阶微分处理后的波形曲线。曲线43是对图3所示的血流动力学相关信息进行能量积分后的波形曲线。为方便对照，将曲线31、曲线41、曲线42和曲线43置于同一时间轴进行同步显示。
S1032、将血流动力学相关信息、第一高频分量信息、第二高频分量信息和振动能量信息置于同一时间轴上进行同步，并划分心拍。
在一些例子中，振动信息是连续获取时，基于振动信息处理生成的血流动力学相关信息、第一高频分量信息、第二高频分量信息、振动能量信息同样也是连续数据，此时需要对上述信息进行心拍划分。其中心拍划分可以依据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波形信号中重复出现的特征来进行划分。由于心脏活动具有明显的周期性，有一些明显的特征重复性高，例如，正常人的心动周期大约是0.6s至1秒之间，可以据此设定搜索区间，搜索最高峰，将最高峰作为心拍划分特征。类似的，最低谷也同样可以作为心拍划分特征。
在获取对象振动信息的同时，可以通过心电传感器获取对象的心电信息，由于ECG信号噪声小，信号干净，用来划分心拍准确度高，因此可以基于与振动信息同步获取的ECG信号来对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进行心拍划分。
在另一些例子中，振动信息是以心动周期为单位离散获取时，并不需要进行心拍划分，S1032可以被省略。在本发明实施例一中，后续流程可以是对逐个心拍内的血流动力学相关信息、第一高频分量信息、第二高频分量信息进行处理，还可以是将预设的一段时间内（例如5分钟、30分钟）的血流动力学相关信息、第一高频分量信息、第二高频分量信息按照心拍进行数据叠加平均处理后生成对应的平均信息，再对各个平均信息进行后续处理。因此下文描述的血流动力学相关信息、第一高频分量信息、第二高频分量信息可以是指一个心拍的数据，也可以是预设一段时间内的按心拍进行叠加平均处理后的数据。
S1033、对所述血流动力学相关信息、第一高频分量信息、第二高频分量信息进行波群划分，确定第一波群、第二波群和第三波群。
波群划分方法可以依据血流动力学相关信息和所述振动能量信息，并基于振动能量信息划分第一波群、第二波群和第三波群。如图5所示，是选取图4中的一个心动周期的波形放大示意图。可见振动能量信息43存在两个能量包络带，其中一个能量包络带的能量峰相对高而且其持续时间窗将血流动力学的最高峰所对应的时间包含在内，确定为收缩期能量带，则另一个突出的能量峰为舒张期能量带。收缩期能量带包络范围的持续时间作为第一时间窗，舒张期能量带包络范围的持续时间作为第二时间窗。与振动能量信息同步的血流动力学信息、第一高频分量信息、第二高频分量信息上与第一时间窗对应的波丛是各自的第一波群，与第二时间窗对应的波丛是各自的第二波群，另外将各自的第一波群之前的“W”形状波群确定为第三波群。因具有时间上的同步性，为方便比较，图5中将曲线31、曲线41和曲线42上的第一波群统一表示为501，第二波群统一表示为502，第三波群统一表示为503。应当理解的是，曲线31、曲线41和曲线42各自都可以划分出第一波群、第二波群和第三波群。
在一些例子中，波群划分还可以是：在获取对象振动信息的同时，通过心电传感器获取对象的心电信息，心电信息可以帮助区分收缩期能量带和舒张期能量带，心电信息的QRS波群与振动能量信息的收缩期能量带最接近，因而可以借助心电信息划分第一波群、第二波群和第三波群。如图6所示，将同步获取的心电信息与图5中的各条曲线置置于同一时间轴同步，曲线61是心电信息示意图，由于心电信息表征了心脏的电生理活动，心脏的电生理活动与心脏的机械振动具有强相关性，因此可以用来和振动信息进行验证。
S1034、在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基于第二波群和第三波群确定第一参数和第二参数。
在实施例一中，S1034有两种方法可以实现。
方法一：
以在第一高频分量信息曲线上，基于第二波群和第三波群进行波形搜索确定第一参数和第二参数为例，具体包括：
首先，对所述第一高频分量信息的第二波群进行“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。如图7A所示，距离L11即为第一参数。也可以将“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。如图7B所示，距离L12即为第一参数。其中，图7A 和图7B所示的曲线是基于对象B的胸腔振动信息生成的，曲线72是血流动力学相关信息，曲线71是振动能量信息，是对曲线72进行能量积分后的生成的曲线，曲线73是第一高频分量信息的时域波形曲线，曲线74是第二高频分量信息的时域波形曲线，曲线73和曲线74是曲线721进行一阶微分处理和二阶微分处理后的波形曲线。
此外，在一些实施例中，对所述第一高频分量信息的第二波群进行“W” 波形搜索时，若“W”波形并未全部包含在第二波群内，即超出了第二波群的范围，则从第二波群起始往后搜索，第一个“W”即为目标“W”；若“W”的第二个谷不平整，比如有拐点或者凸起，则取至最深的谷作为“W”第二个谷。如图7C所示各条曲线是依据对象C的胸腔体表振动信息生成的，其中，曲线75是同步获取的心电信息，曲线76是振动能量信息，曲线77是第一高频分量信息，此处，将距离L13作为第一参数。
其次，在同一个心动周期内，对所述第一高频分量信息的第三波群进行“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二参数。如图7A所示，距离L21即为第二参数。也可以将“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。如图7B所示，距离L22即为第一参数。
在一些实施例中，对所述第一高频分量信息的第三波群进行“W” 波形搜索时，若“W”位置不确定，可将与振动信息同步获取的心电信息和第一高频分量信息置于同一时间轴同步后作为参考，“W”通常处于心电信息的PR间期，若“W”波形超出了第三波群的范围，则取完整的“W”波形作为目标“W”，“W”中第二个波谷与其后第一个波峰间的幅度即为第二参数。如图7C，距离L23即为第二参数。
应当理解的是，上述是以在第一高频分量信息上基于第二波群和第三波群确定第一参数和第二参数为例进行说明的。在血流动力学相关信息或第二高频分量信息上上述方法同样适用。
方法二：
在一些例子中，若 “W”位置不好确定，还可以在第二高频分量信息上第二波群和第三波群确定第一特征点和第二特征点；进而基于第一特征点和第二特征点确定血流动力学信息、第一高频分量信息或第二高频分量信息的第一参数和第二参数。具体包括：
第一步，在第二高频分量信息上，基于第二波群和第三波群，确定第一特征点和第二特征点。
首先，确定所述第二高频分量信息的第二波群的最高峰之后的第一个波谷为第一特征点。如图8A所示，点811即为第一特征点。
其次，对第二高频分量信息的第三波群进行波谷搜索确定第二个波谷为第二特征点。如图8A所示，点812即为第二特征点。
图8A和图8B所示的曲线是基于对象D的胸腔振动信息生成的，曲线85是血流动力学相关信息，曲线82是振动能量信息，是对曲线85进行能量积分后的生成的曲线，曲线83是第一高频分量信息的时域波形曲线，曲线84是第二高频分量信息的时域波形曲线，曲线83和曲线84是曲线85进行一阶微分处理和二阶微分处理后的波形曲线，曲线81是同步获取的对象的心电信息。
第二步，基于第一特征点和第二特征点确定血流动力学信息、第一高频分量信息或第二高频分量信息的第一参数和第二参数。
在第二高频分量信息上，确定第一特征点所在的波谷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。如图8A所示，距离L34即为第二高频分量的第一参数。图8A中，横轴表示时间，纵轴是无量纲的。距离L34指的是第一特征点所在的波谷与其前第一个波峰间的幅度。也可以将第一特征点所在的波谷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。如图8B所示，距离L35即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，确定第二特征点所对应的波谷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。如图8A所示，距离L44即为第二参数。也可以将第二特征点所在的波谷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。如图8B所示，距离L45即为第二高频分量的第二参数。
基于第一特征点和第二特征点，也可以类似方法在第一高频分量信息上或血流动力学相关信息上取第一参数和第二参数。例如：
在第一高频分量信息上，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的第一参数。如图8A所示，距离L14即为第一高频分量的第一参数。也可以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的第一参数。如图8B所示，距离L15即为第一高频分量的第一参数。
在同一个心动周期内，在第一高频分量信息上，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的第二参数。如图8A所示，距离L24即为第一高频分量的第二参数。也可以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的第二参数。如图8B所示，距离L25即为第一高频分量的第二参数。
在血流动力学相关信息上上述方法同样适用。在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后第一个波峰间的幅度作为血流动力学相关信息上的第一参数。如图8B所示，距离L55即为第一高频分量的第一参数。在同一个心动周期内，在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前第一个波峰间的幅度作为血流动力学相关信息上的第一参数。如图8B所示，距离L65即为第一高频分量的第二参数。
心脏舒张早期心室充盈事件包括舒张早期跨瓣血流加速事件和跨瓣血流减速事件，跨瓣血流主要指从左心房跨越二尖瓣流入左心室的血流。
心脏舒张早期的心室充盈事件和心脏舒张末期的心房收缩事件可以通过不同的传感器来获取不同维度的信息，例如电生理传感器可以获取该事件的电信号，振动传感器可以获取该事件的振动信号。具体地，可以通过振动传感器获取对象的胸腔体表运动，进而从中提取出该对象的心脏舒张早期的心室充盈事件和心脏舒张末期的心房收缩事件。心脏舒张早期的心室充盈事件包括心室充盈造成的肌肉运动和血流运动在对象体表形成的振动，心脏舒张末期心房收缩事件包括心房收缩造成的肌肉和血流运动在体表形成的振动。本发明实施例一中，我们选取第一参数用来表征心脏舒张早期心室充盈造成的肌肉运动和血流运动在对象体表形成的振动幅度，选取第二参数用来表征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。可以理解的是，除了振动幅度我们还可以选取表征振动能量、振动频率、或振动时间等参数，用于表征心脏舒张早期心室充盈事件和心脏舒张末期心房收缩事件。
参考图7和图8所示，第一参数当取第一高频分量信息中第二波群的W中第二个波谷或者是第一特征点与其前第一个波峰形成的下降沿幅度，用来表征心脏舒张早期跨瓣血流加速事件造成的肌肉和血流运动在体表形成的振动幅度，如L11，L14，L34；当第一参数取第一高频分量信息中第二波群的W中第二个波谷或者是第一特征点与其后第一个波峰形成的上升沿幅度，用来表征心脏舒张早期跨瓣血流减速事件造成的肌肉和血流运动在体表形成的振动幅度，如L12，L55，L15，L35。第二参数的两种取值取法都用于表征心房收缩造成的肌肉和血流运动在体表形成的振动，如L24、L25、L44和L45。
S104、基于第一参数和第二参数生成指示参数，并基于指示参数评估所述对象的心脏充盈压状态。例如，可以将第一参数与第二参数的比值作为指示参数，将在第一高频分量信息上取得的指示参数作为指示参数I1，在第二高频分量信息上取得的指示参数作为指示参数I2，在血流动力学信息上取得的指示参数作为指示参数I3。如指示参数I1= L12/L22，指示参数I2= L35/L45，指示参数I3=L55/L65。当指示参数大于阈值时，判定对象心脏舒张功能等级为高充盈压状态。其中，心脏高充盈压状态被认为是超声参数E/e’>14，Vtr>2.8m/s，E/A>1的状态，此时心脏处于限制性充盈状态，主动松弛能力受损和心室壁顺应性降低，高充盈压会使心脏功能进入快速的恶性循环，需要及时干预，从而可以避免患者进一步恶化。
图9A所示是依据对象E的胸腔体表振动信息计算得到的第一参数和第二参数的示意图，对象E是一位处于高充盈压状态的心衰患者。其中，曲线91是与振动信息同步获取的心电信息，曲线93是血流动力学相关信息的时域波形图，曲线92是振动能量信息的时域波形图，是对曲线93进行能量积分后生成的，曲线94是第一高频分量信息的时域波形曲线，曲线95是第二高频分量信息的时域波形曲线，曲线94和曲线95是曲线93进行一阶微分处理和二阶微分处理后的波形曲线。第一参数可以取L955、L915、L935，第二参数可以取L965、L925、L915。同图7和图8相比，可见该心衰患者的第一参数变化较大，这里选取第一参数和第二参数的比值来表征变化。
本领域普通技术人员可以据此得到将第二参数与第一参数的比值作为指示参数时心脏舒张功能评估的方法，也包含在本发明的保护范围内。另外，本领域普通技术人员容易想到可以将第二参数与第一参数进行其他运算后生成指示参数，包括但不限于：加、减、乘、除、指数等操作，也均在本发明的保护范围之内。
选取25名心衰患者作为测试对象入组进行临床试验，25名心衰患者中包括12名高充盈压状态的患者（标记为阳性），13名非高充盈压状态患者（标记为阴性）。按照上述的心脏舒张功能评估方法100计算25位测试对象的指示参数，并对25位测试对象的指示参数进行敏感性、特异性分析，构建ROC曲线如图9B、9C和9D所示，分别是依据上述指示参数I1、指示参数I2和指示参数I3的ROC曲线。依据指数参数I1对心脏充盈压状态的判别结果：AUC面积为0.833，最佳cut-off值为0.801，此时，敏感性：92.3%，特异性：75%。依据指数参数I2对心脏充盈压状态的判别结果为：AUC面积为0.865，最佳cut-off值为0.824，此时，敏感性：100%，特异性：83.3%。依据指数参数I3对心脏充盈压状态的判别结果：AUC面积为0.782，最佳cut-off值为1.055，此时，敏感性：69.2%，特异性：83.3%。其中，阈值是基于心衰人群确定的阈值。在本发明一些实施例中，阈值还可以是绝对阈值，用来区分正常人和患有心脏舒张功能障碍的人。阈值还可以是基于对象自身的阈值，例如，基于对监测对象的个人历史数据分析可以得到其心脏舒张功能恶化时的相对阈值。
在本发明实施例一中，心脏舒张功能是用心室充盈压状态来表征的，例如高充盈压状态表征了重度舒张功能障碍。此外，心脏舒张功能还可以用心房压来表征，心脏结构导致左心室充盈压与左房压、肺动脉压具有相关性，因此在一些实施例中，指示参数除了可以用来评价充盈压状态，还可以经过一系列变换后用作间接评估左心房压力状态、肺动脉压力状态以及心衰程度等，同样在本发明的保护范围之内。
实施例二：
本发明实施例二提供了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，所述计算机程序被处理器执行时实现如本发明实施例一提供的心脏舒张功能评估方法的步骤。
实施例三：
本发明实施例三提供了一种心脏舒张功能评估设备，图10所示是一种心脏舒张功能评估设备200的结构框图。该心脏舒张功能评估设备200可以是专门设计用于处理光纤传感器的振动信息的专用计算机设备。
例如，心脏舒张功能评估设备200可以包括连接到与其连接的网络的通信端口201，以便于数据通信。心脏舒张功能评估设备200还可以包括处理器203，处理器203以一个或多个处理器的形式，用于执行计算机指令。计算机指令可以包括例如执行本文描述的心脏充盈压评估方法的例程、程序、对象、组件、数据结构、过程、模块和功能。例如，所述处理器203可以获得光纤传感器的振动信息，并对振动信息进行预处理生成血流动力学相关信息等。
在一些例子中，处理器203可以包括一个或多个硬件处理器，例如微控制器、微处理器、精简指令集计算机（RISC）、专用集成电路（ASIC）、图形处理单元（GPU）、中央处理单元（CPU）、数字信号处理器（DSP）、现场可编程门阵列（FPGA）、高级RISC机器（ARM）、可编程逻辑器件（PLD）等能够执行一个或多个功能的任何电路或处理器等，或其任何组合。
心脏舒张功能评估设备200可以包括内部通信总线205、存储器207用于由计算机处理和/或发送的各种数据文件，以及存储在存储器207中由处理器203执行的其他类型的非暂时性存储介质中的程序指令。本申请的方法和/或过程可以作为程序指令实现。心脏舒张功能评估设备200还包括输入/输出组件209，支持计算机和其他组件（例如，用户界面元件）之间的输入/输出。
应当理解的是，为了描述方便在本申请中心脏舒张功能评估设备200中仅描述了一个处理器。然而，应当注意，本申请中的心脏舒张功能评估设备200还可以包括多个处理器，因此，本申请中披露的操作和/或方法步骤可以如本申请所述的由一个处理器执行，也可以由多个处理器联合执行。例如，如果在本申请中心脏舒张功能评估设备200的处理器203执行步骤A和步骤B，则应该理解，步骤A和步骤B也可以由信息处理中的两个不同处理器联合或分开执行（例如，第一处理器执行步骤A，第二处理器执行步骤B，或者第一和第二处理器共同执行步骤A和B）。
实施例四：
本发明实施例四提供了一种心脏充盈压状态的监测***，包括：
一个或多个振动传感器；和
本发明实施例三提供的心脏充盈压状态的评估设备。
如图11所示是一种心脏充盈压状态监测***300的结构框图。一种心脏高压状态监测***300可以包括一个或多个振动传感器301，一个或多个心脏舒张功能评估设备303，一个或多个存储装置305。
其中，振动传感器301可以是加速度传感器、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，此外还可以是以加速度、速度、位移、或压力为基础将物理量等效性转换的传感器（例如静电荷敏感传感器、充气式微动传感器、雷达传感器等）。其中应变传感器可以是光纤传感器。振动传感器301是光纤传感器时，可被放置于对象身体下方。例如对象可以呈仰卧、俯卧、侧卧等姿势，光纤传感器可放置于床上，对象仰卧（俯卧或侧卧）于其上。以对象呈仰卧姿势为例，较佳的测量位置是光纤传感器被配置为置于对象的背部下方，较佳的测量状态是光纤传感器被配置为置于对象的左肩胛骨和右肩胛骨之间的区域。一般地，为描述方便，将对象左肩胛骨和右肩胛骨之间所对应的体表区域定义为中肩。本领域普通人员可以理解的是，当对象呈俯卧姿势时，与仰卧姿势时的背部对应的测量位置对应的是对象的胸部。此外，还可以振动传感器放置于一定倾斜角仰卧人体背后的接触面、轮椅或其它可倚靠物体的倚卧人体背后的接触面等进行振动信息的采集。
心脏舒张功能评估设备303如本发明实施例三所述。心脏舒张功能评估设备303可以通过网络320与振动传感器301相连接。网络320可以是单一网络，例如有线网络或无线网络，还可以是多种网络的组合。网络320可以包括但不限于局域网、广域网、共用网络、专用网络等。网络320可以包括多种网络接入点，例如无线或有线接入点、基站或网络接入点，通过以上接入点使心脏充盈压状态监测***300的其他组成部分可以连接网络103并通过网络传送信息。
存储装置305可以被配置为存储数据和指令。存储装置305可以包括但不限于随机存储器、只读存储器、可编程只读存储器等。存储装置305可以是利用电能方式、磁能方式、光学方式等存储信息的设备，例如硬盘、软盘、磁芯存储器、CD、DVD等。以上提及的存储设备只是列举了一些例子，存储装置305使用的存储设备并不局限于此。
在一些例子中，该心脏充盈压状态监测***300还可以包括输出装置307，输出装置307被配置为将心脏舒张功能评估结果输出，输出方式包括但不限于图形、文字、数据、语音等，例如图形显示、数字显示、语音播报、盲文显示等中的一种或多种。输出装置307可以是显示器、手机、平板电脑、投影仪、可穿戴设备（手表、耳机、眼镜等）、盲文显示器等中的一种或多种。在一些例子中，输出装置307可以实时显示对象102的心脏充盈压评估结果，在另一些例子中，输出装置307可以非实时显示一份报告，该报告是对象在预设时间段内的测量结果，例如用户在入睡时间段内的心脏充盈压监测结果。当监测对象是心衰患者时，如果心脏舒张功能评估设备将其心脏舒张功能评估为高充盈压状态，那心衰患者此时会面临心衰状况恶化，需要接受住院治疗，该监测***的输出装置可以给该心衰患者发送提示信息，例如发送短信、电子邮件、电话、微信等即时聊天信息，还可以给该心衰患者的家庭医生发送信息，提示该患者有可能面临心衰恶化以帮助医生做决策。该***还可以进一步包括医患交流平台，当医生接收到***推送的患者可能面临心衰恶化时，及时与患者沟通。
再如，输出装置307还可以实现预警功能，例如通过语音预警，当心脏舒张功能评估设备将心衰患者心脏舒张功能评估为高充盈压状态，那心衰患者此时会面临心衰状况恶化，通过声音来提醒患者及时就诊。
本发明是通过采集使用者的振动信息来监测心脏的充盈压，无需侵入人体，被动测量，而且可以实现连续监测，使用者只需要躺在测量设备上即可进行测量，无需专业人员辅助，并且具有测量精度高、操作简单的优点，能提高测试者的舒适性，可以适用于医院和家庭等场景。本发明提供的心脏充盈压状态监测***，可以评估使用者的心脏充盈压状态，进而在出现恶化迹象时提前预警，帮助使用者避免恶化后果。
本领域普通技术人员可以理解上述实施例的各种方法中的全部或部分步骤是可以通过程序来指令相关的硬件来完成，该程序可以存储于一计算机可读存储介质中，存储介质可以包括：只读存储器（ROM，Read Only Memory）、随机存取记忆体（RAM，Random Access Memory）、磁盘或光盘等。
以上所述仅为本发明的较佳实施例而已，并不用以限制本发明，凡在本发明的精神和原则之内所作的任何修改、等同替换和改进等，均应包含在本发明的保护范围之内。

Claims (23)

  1. 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。
  2. 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。
  3. 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。
  4. 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。
  5. 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。
  6. 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。
  7. 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。
  8. 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。
  9. 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。
  10. 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。
  11. 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. 　　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。
  13. 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。
  14. 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。
  15. 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. 　　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。
  17. 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。
  18. 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。
  19. 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。
  20. 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。
  21. 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。
  22. 一种用于心脏充盈压状态监测的***，其特征在于，所述***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。
  23. 一种基于机器学习的心脏充盈压评估***，其特征在于，所述***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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