WO2020224600A1 - 一种心动图的非接触测量方法 - Google Patents

一种心动图的非接触测量方法 Download PDF

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WO2020224600A1
WO2020224600A1 PCT/CN2020/088812 CN2020088812W WO2020224600A1 WO 2020224600 A1 WO2020224600 A1 WO 2020224600A1 CN 2020088812 W CN2020088812 W CN 2020088812W WO 2020224600 A1 WO2020224600 A1 WO 2020224600A1
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radar
center
signal
circle
sampling points
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董淑琴
冉立新
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浙江大学
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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
    • A61B5/103—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
    • A61B5/103—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
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes

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  • the present invention relates to a method for non-contact measuring cardiogram, in particular to a radar system based on high linearity and sensitivity and a method for human body non-contact measuring cardiogram based on the above system.
  • ECG electrocardiogram
  • Cardiogram refers to the curve of the change of the heart's activity with time measured by the sensor device in the basic activity of the heart.
  • the present invention proposes a non-contact measurement method of cardiogram, which can extract relevant feature points from the motion curve of the human thoracic cavity surface, and obtain the key motion information of the atria and ventricles.
  • the internal connection between the bioelectric signals of the diastole and contraction of the heart and the changes in the volume of the atria and ventricles that occur on the skin surface is achieved.
  • the present invention measures the weak displacement conducted to the skin surface of the chest and the back by the volume change of the ventricle and the atrium through the non-contact method, and obtains a new type of cardiogram used to describe the movement of the central atrium and the ventricle in the cardiac cycle.
  • the method is specifically: using Doppler radar or pulse radar based on electromagnetic waves, light waves and sound waves to measure the distance change between the radar and the skin surface to obtain a displacement curve containing the volume change information of the human heart, and use the displacement curve processing to obtain a cardiogram
  • the speed and acceleration curves obtained by first-order and second-order derivation (or other equivalent methods) of the displacement curve. Take the zero and pole points of the above curve as the speed and acceleration information, respectively, as the atrium and The characteristic points of different stages of ventricular systole and diastole, together with the displacement curve, can obtain the time, volume change, velocity and acceleration information of the central atrium and ventricle systole and diastole of the aforementioned cardiac cycle.
  • the measurement is performed from behind the subject, and the radar sensor is placed directly opposite to the skin of the subject's back.
  • a radar sensor is used to measure the displacement of the skin surface, and the following methods are used for DC offset compensation during the measurement process to improve the measurement accuracy, specifically: Find the location based on the baseband signal obtained by the quadrature downconversion of the radar receiver in the radar sensor To the center of the baseband signal constellation diagram, the DC offset component is determined by the coordinates of the center of the circle, and the baseband signal is corrected and compensated by the DC offset component.
  • the radar sensor includes a radar transmitter and a radar receiver.
  • the radar receiver is a quadrature down-conversion structure, which is connected to an excitation signal source after a filter, a mixer, and a digital-to-analog converter.
  • the amplifier is connected with the radar transmitter; the radar transmitter emits electromagnetic waves to the moving object, which is reflected on the surface of the moving organism to be measured and then received by the radar receiver.
  • the radar transmitter and the radar receiver are integrated in the same radio frequency front-end module.
  • the DC offset compensation is specifically:
  • I and Q respectively represent two orthogonal signals
  • DC I (t) and DC Q (t) represent the DC offset components of signal I and signal Q respectively.
  • three sampling points are randomly selected from all sampling points of the baseband signal output by the radar receiver to determine a circle and its center, and the distance between all sampling points and the center of the circle is calculated. Then make a judgment: if the proportion of sampling points whose distance is less than the set distance threshold to all sampling points is greater than the proportion threshold, the specific implementation sets the proportion threshold to 90%, then the circle and its center are output; if the distance is less than the set distance threshold If the proportion of sampling points to all sampling points is not greater than the proportion threshold, three sampling points are randomly selected again and a circle and its center are determined until a circle center that satisfies the condition is found or the number of random selections exceeds the set value; After the number of random selections exceeds the set value, the center of the circle that satisfies the condition that the ratio of sampling points whose distance is less than the set distance threshold to the ratio of all sampling points is greater than the ratio threshold is not found, then the circle with the highest ratio before and its center are selected
  • the above compensation method can use the simple but very effective method to find the DC offset and eliminate the DC offset component in the presence of a large number of various interference signals.
  • the movement of the human heart will cause a displacement of the skin surface of the chest.
  • the displacement caused by breathing is between 10mm and 20mm, and the displacement caused by the heartbeat is between 0.2mm and 0.5mm.
  • the amplitude of the fretting caused by the heartbeat is very weak, and the present invention can detect this weak motion through the Doppler radar sensor with high linearity and high sensitivity.
  • the present invention can obtain a new type of electrocardiogram of the human body by linearly extracting displacement information from the signal scattered by the skin, which is called "Doppler cardiogram" (DCG).
  • DCG Doppler cardiogram
  • DCG not only the correspondence between it and conventional ECG can be observed, but DCG also contains real-time volume, velocity, and acceleration information when the atria and ventricles contract and relax that cannot be observed in conventional ECG. These characteristics are very necessary for hospitalization and personal daily health care.
  • the method of the present invention Compared with traditional computed tomography and nuclear magnetic resonance technology, the method of the present invention has the advantages of low cost and low radiation hazard; compared with other contact cardiogram measurements, the method does not require direct contact with the human body and is special Daily cardiac diagnostic measurements for patients and special occasions provide a convenient and easy way.
  • Figure 1 shows the changes in the atrial and ventricular volume of healthy people (left) and people with congenital heart disease (right) obtained by MRI and the weak displacement curves of the skin surface caused by them, as well as the extracted feature points.
  • Figure 2 is a specific radar sensor system used in the present invention.
  • Fig. 3 is the cardiogram proposed in the present invention and the displacement velocity acceleration curve contained therein and the ECG measured at the same time.
  • the specific implementation adopts the following radar sensor system, including a radar transmitter and a radar receiver.
  • the radar receiver is connected to the excitation signal source through a filter and a multiplier, a digital-to-analog converter, and the multiplier is connected to a crystal oscillator.
  • the amplifier is connected with the radar transmitter; the radar transmitter emits electromagnetic waves to the skin surface of the human chest/back, and is received by the radar receiver after reflecting on the skin surface of the human chest/back.
  • the radar transmitter and radar receiver are integrated in the same RF front-end module.
  • the radar sensor is used for measurement.
  • the radar transmitter emits electromagnetic waves to the back surface of the stationary human body to be measured.
  • the radar receiver receives the reflected waves that are superimposed and modulated by the simultaneous movement of the atria and ventricles, and then performs signal processing for down-conversion and baseband demodulation. , To obtain the baseband signal with heart motion information;
  • the baseband signal B(t) of the reflected wave after down-conversion processing is:
  • A(t) is the amplitude of the signal
  • ⁇ 0 is a fixed phase shift, which is related to the initial distance of the RF front-end module from the object to be measured
  • x(t) is the displacement curve with heart motion information
  • ⁇ is the carrier wavelength
  • It is phase residual noise, which can be ignored.
  • the radar sensor emits electromagnetic wave signals against the human back skin surface, and is reflected by the human back skin surface.
  • the RF front-end module receives the reflected electromagnetic wave signal, and digitally orthogonal down-converts the reflected electromagnetic wave signal to generate signal Q and signal I, respectively Satisfy:
  • the DC offset compensation algorithm is used to compensate and eliminate the signal Q and signal I;
  • Figure 3 is an electrocardiogram measured using the system.
  • the chest displacement curve caused by the recovered heartbeat there is also velocity acceleration information obtained by deriving the displacement curve.
  • the gray-marked heartbeat cycle you can observe the corresponding relationship between the heartbeat curve and the ECG, that is, the key points determined according to the inflection point, concave point, zero point and extreme point on the displacement, velocity and acceleration curve and the simultaneous use of the electrocardiograph Correspondence between corresponding key points in the measured electrocardiogram.
  • point B corresponds to P wave
  • point C corresponds to QRS wave
  • point E corresponds to the end of T wave.
  • Figure 1 shows the change curve of the heart volume of healthy people and people with congenital heart disease measured by MRI in medical research, and the displacement curve caused by the heartbeat is calculated based on this.
  • the characteristic points A-E corresponding to the different stages of contraction and diastole of the atria and ventricles can be determined, which are marked with black dots in Figure 1.

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Abstract

一种心动图的非接触测量方法，用基于电磁波、光波和声波的多普勒雷达或脉冲雷达测量雷达与皮肤表面间的距离变化得到包含人体心脏体积变化信息的位移曲线，对位移曲线进行一阶和二阶求导得到的速度和加速度曲线，取曲线的零点和极点分别作为速度和加速度信息，作为心房和心室收缩和舒张不同阶段的特征点，从而共同获得心动周期中心房和心室收缩和舒张的时间、体积变化、速度和加速度信息。测量方法具有低成本，低辐射危害的优点，不需要直接接触人体，为特殊病人的日常心脏诊断测量提供了方便易行的方式。

Description

一种心动图的非接触测量方法 技术领域
本发明涉及了一种非接触式测量心动图的方法，尤其是涉及了一种基于高线性度和灵敏度的雷达系统以及基于以上系统的的人体非接触测量心动图的方法。
背景技术
在现代社会中，心血管病死亡率一直高居疾病死亡构成的首位。在心血管疾病的诊断和预防中，人体心动图的测量和长期监测是必不可少的。基于不同的原理和技术，当今社会已经存在了用于测量不同心电图的各种医疗器械。迄今为止，商用心动图仪器已能够测量心电图(ECG)，超声心动图(UCG)，心音图(PCG)，阻抗心电图(ICG)，球形心电图(BCG)，基于磁共振成像(MRI)的实时心动图。人体心动图的测量对于心血管疾病的诊断和日常保健至关重要。
到目前为止，专门用于测量人体心动图的医疗仪器，例如最常用的心电图(ECG)仪器，必须使用接触式传感器。除了昂贵且不适合日常保健的辐射MRI心电图外，其他所有心动图都必须使用接触传感器测量，如ECG电极和UCG探头。这种接触式心动图测量不仅麻烦，而且对于诸如早产儿和烧伤患者也是不切实际的。
心动图是指在心脏基本活动中，通过传感器设备测量到心脏的活动随时间变化的曲线。心脏的这种基本活动形式有两种：电活动和机械活动。这两种活动相互联系相互作用，从而实现推动血液通过心房和心室泵入肺部或血液循环系统，向器官、组织提供充足的血流量，以供应氧和各种营养物质，并带走代谢的终产物。
发明内容
为了解决背景技术中存在的问题，本发明提出了一种心动图的非接触式测量方法，可以从人体胸腔表面的运动曲线中提取相关特征点，从中得到心房心室的关键运动信息，基于控制人类心脏舒张和收缩的生物电信号与皮肤表面发生的心房和心室体积变化之间的内在联系来实现。
本发明采用的具体技术方案是：
本发明通过非接触方法测量心室和心房联合运动时的体积变化传导到胸部和背部皮肤表面的微弱位移，得到一种新类型、用于描述心动周期中心房和心室运动的心动图。
所述的方法具体为：用基于电磁波、光波和声波的多普勒雷达或脉冲雷达测量雷达与皮肤表面间的距离变化得到包含人体心脏体积变化信息的位移曲线，用位移曲线处理获得心动图中的时间、速度和加速度信息，对位移曲线进行一阶和二阶求导(或其它等效方法)得到的速度和加速度曲线，取上述曲线的零点和极点分别作为速度和加速度信息，作为心房和心室收缩和舒张不同阶段的特征点，与位移曲线一起，从而共同获得上述心动周期中心房和心室收缩和舒张的时间、体积变化、速度和加速度信息。
所述测量从被测者的背后进行测量，将雷达传感器朝向被测者的背部皮肤正对放置。
用雷达传感器对皮肤表面的位移进行测量，且测量过程中采用以下方式进行直流偏移补偿，来提高测量准确性，具体为：根据雷达传感器中雷达接收机正交下变频所得的基带信号寻找定位到基带信号星座图的圆心，通过圆心的坐标确定直流偏移分量，用直流偏移分量对基带信号进行修正补偿处理。
所述的雷达传感器包括雷达发射器和雷达接收机，雷达接收机为正交下变频构架，经滤波器和混频器、数模转换器后和激励信号源连接，混频器依次经本振、放大器和雷达发射器连接；雷达发射器向运动物体发射电磁波，到待测运动生物体表面反射后被雷达接收机接收。
所述的雷达发射器和雷达接收机集成于同一射频前端模块中。
所述直流偏移补偿具体为：
实际在有干扰信号存在的运动物体的测量过程中，雷达接收机基带输出的信号I和信号Q的两个正交信号的星座图绘制成一个以直流偏移(DC I(t)，DC Q(t))为圆心、幅度A R(t)为半径的圆或圆弧曲线：
[I(t)-DC I(t)] 2+[Q(t)-DC Q(t)] 2＝A R 2(t)
其中，I和Q分别表示两个正交信号，DC I(t)、DC Q(t)分别表示信号I和信号Q的直流偏移分量。
在有干扰信号存在的运动物体的测量过程中，将雷达接收机输出的基带信号的全部采样点中随机选取三个采样点确定一个圆及其圆心，计算全部采样点分别到该圆心的距离，然后进行判断：如果距离小于设定距离阈值的采样点占所有采样点的比例大于比例阈值，具体实施将比例阈值设置为90％，则输出该 圆及其圆心；如果距离小于设定距离阈值的采样点占所有采样点的比例不大于比例阈值，则重新随机选取三个采样点再确定一个圆及其圆心，直到找到满足条件的圆心或进行重新随机选取的次数超过设定值；若进行重新随机选取的次数超过设定值后还未找到满足距离小于设定距离阈值的采样点占所有采样点的比例大于比例阈值的条件的圆心，则选取之前比例最高对应的圆及其圆心，以圆心的横纵坐标作为两个正交信号的直流偏移分量；最后在基带输出的信号I和信号Q的两个正交信号基础上减去圆心坐标，即信号I和信号Q分别减去各自对应的直流偏移分量，从而实现对信号I和信号Q的消除补偿。
上述补偿方式能在有大量各种干扰信号的存在下，使用上述简单却非常有效的方式找到直流偏移，并消除直流偏移分量。
人类心脏的运动会引起胸部皮肤表面的位移，由呼吸引起的位移幅度在10mm至20mm之间，由心跳引起的位移幅度在0.2mm至0.5mm之间。由心跳引起的微动幅度十分微弱，本发明通过高线性度和高灵敏度的多普勒雷达传感器能检测这种微弱的运动。
本发明通过从皮肤散射的信号中线性提取的位移信息，可以得到一种新型的人体心电图，称为“多普勒心动图”(DCG)。在DCG中，不仅可以观察到其与常规ECG之间的对应关系，而且DCG还包含常规ECG中不能观察到的心房和心室收缩和放松时的实时体积，速度和加速度信息。这些特征对于住院治疗和个人日常保健非常需要。
本发明的有益效果是：
相比于传统的计算机断层扫描以及核磁共振技术，本发明方法具有低成本，低辐射危害的优点；相比于其他接触式心动图的测量等，所述的方法不需要直接接触人体，为特殊病人和特殊场合下的日常心脏诊断测量提供了方便易行的方式。
附图说明
图1是分别显示了通过核磁共振成像得到的健康人(左)和先天性心脏病人(右)的心房心室体积变化以及其引起的皮肤表面的微弱位移曲线，以及提取的特征点。
图2是本发明中应用的一种具体的雷达传感器系统。
图3是本发明中提出的心动图以及其包含的位移速度加速度曲线和同时测量到的ECG。
具体实施方式
下面结合本发明实施例中的附图，详细描述本发明的一种实施过程。
如图2所示，具体实施采用以下雷达传感器系统，包括雷达发射器和雷达接收机，雷达接收机依次经滤波器和乘法器、数模转换器后和激励信号源连接，乘法器依次经晶振、放大器和雷达发射器连接；雷达发射器向人胸部/背部皮肤表面发射电磁波，到人胸部/背部皮肤表面反射后被雷达接收机接收。雷达发射器和雷达接收机集成于同一射频前端模块中。
具体实施中采用雷达传感器进行测量，雷达发射机向待测静止人体的背部表面发射电磁波，雷达接收机接收到受到心房心室同时运动叠加调制的反射波，然后进行下变频和基带解调的信号处理，获得带有心脏运动信息的基带信号；
所述进行下变频和基带解调的信号处理，具体过程如下：
首先，反射波经过下变频处理后基带信号B(t)为：
Figure PCTCN2020088812-appb-000001
其中，A(t)为信号的幅度；θ 0为固定相移，与射频前端模块距离待测物体的初始距离有关；x(t)为带有心脏运动信息的位移曲线；λ为载波波长；
Figure PCTCN2020088812-appb-000002
为相位残余噪声，可忽略不计。
然后利用下变频、AD转换、基带解调等环节得到带有心脏运动信息的基带信号x(t)。
如附图2所示，本发明具体工作过程和工作原理如下：
雷达传感器对着人背部皮肤表面发射电磁波信号，经过人背部皮肤表面被反射，射频前端模块接收到反射电磁波信号，并将反射电磁波信号数字正交下变频，生成信号Q和信号I两路，分别满足：
Figure PCTCN2020088812-appb-000003
Figure PCTCN2020088812-appb-000004
其中，A I(t),A Q(t)分别为信号I和信号Q的幅度；由于数字域的正交解调，忽略幅度不平衡，即A I(t)＝A Q(t)＝A R(t)；θ为一固定相移，与射频前端模块距离待测物体的初始距离有关；x(t)为运动物体的位移信息；λ为载波波长；DC I(t)和DC Q(t)分别为信号I和信号Q的直流偏移。
(2)在心跳引起的微弱运动测量情况下，信号Q和信号I中的直流偏移变化很小，幅度变化也很小，此时认为不变；因此信号I和信号Q组成了一段以直流偏移(DC I(t)，DC Q(t))为圆心、幅度A R(t)为半径的圆弧曲线：
[I(t)-DC I(t)] 2+[Q(t)-DC Q(t)] 2＝A R 2(t)
为了消除变化的直流偏移信号对最终成像结果的影响，使用直流偏移补偿算法在信号Q和信号I中对其进行补偿消除；
(3)随后使用反正切算法对信号Q和信号I进行处理，得到其相位信息：
Figure PCTCN2020088812-appb-000005
(4)附图3为使用所述系统测量到的心动图。其中除了恢复出的心跳引起的胸部的位移曲线，还有通过对位移曲线求导得到的速度加速度信息。并且以灰色标注的心动周期为例，可以观察到心动曲线跟ECG的对应关系，即根据位移、速度和加速度曲线上的拐点、凹点、零点和极值点确定的关键点与同时用心电图仪测量得到的心电图中相应的关键点之间的对应关系。具体地，B点对应P波，C点对应QRS波，E点对应T波的结束。
图1为医学研究中通过核磁共振测量到的健康人与先天性心脏病人的心脏容积在两个周期内的变化曲线，并且以此计算得到了心跳引起的位移曲线。通过该位移曲线，可以确定对应心房和心室收缩和舒张不同阶段的特征点A-E，在图1中用黑点标出。
通过对比发现，使用本发明所述的一种非接触心动图测量方法所测量到的心动图，符合图1中医学测量的实际运动趋势，证明了所述系统的有效性。
以上所述，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明披露的技术范围内，可轻易想到的变化或者替换，都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应该以权力要求书的保护范围为准。

Claims (3)

  1. 一种心动图的非接触测量方法，其特征在于：通过非接触方法测量心室和心房联合运动时的体积变化传导到背部皮肤表面的微弱位移，得到一种新类型、用于描述心动周期中心房和心室运动的心动图；
    所述测量从被测者的背后进行测量，将雷达传感器朝向被测者的背部皮肤正对放置；
    所述的方法具体为：用基于电磁波、光波和声波的多普勒雷达或脉冲雷达测量雷达与皮肤表面间的距离变化得到包含人体心脏体积变化信息的位移曲线，对位移曲线进行一阶和二阶求导得到的速度和加速度曲线，取上述曲线的零点和极点分别作为速度和加速度信息，作为心房和心室收缩和舒张不同阶段的特征点，从而共同获得上述心动周期中心房和心室收缩和舒张的时间、体积变化、速度和加速度信息；
    用雷达传感器对皮肤表面的位移进行测量，且测量过程中采用以下方式进行直流偏移补偿，具体为：根据雷达传感器中雷达接收机正交下变频所得的基带信号寻找定位到基带信号星座图的圆心，通过圆心的坐标确定直流偏移分量，用直流偏移分量对基带信号进行修正补偿处理。
  2. 根据权利要求1所述的一种人体心动图的非接触式测量方法，其特征在于：所述的雷达传感器包括雷达发射器和雷达接收机，雷达接收机为正交下变频构架，经滤波器和混频器、数模转换器后和激励信号源连接，混频器依次经本振、放大器和雷达发射器连接；雷达发射器向运动物体发射电磁波，到待测运动生物体表面反射后被雷达接收机接收。
  3. 根据权利要求1所述的一种人体心动图的非接触式测量方法，其特征在于：在有干扰信号存在的运动物体的测量过程中，将雷达接收机输出的基带信号的全部采样点中随机选取三个采样点确定一个圆及其圆心，计算全部采样点分别到该圆心的距离，然后进行判断：如果距离小于设定距离阈值的采样点占所有采样点的比例大于比例阈值，则输出该圆及其圆心；如果距离小于设定距离阈值的采样点占所有采样点的比例不大于比例阈值，则重新随机选取三个采样点再确定一个圆及其圆心，直到找到满足条件的圆心或进行重新随机选取的次数超过设定值；若进行重新随机选取的次数超过设定值后还未找到满足距离小于设定距离阈值的采样点占所有采样点的比例大于比例阈值的条件的圆心，则选取之前比例最高对应的圆及其圆心，以圆心的横纵坐标作为两个正交信号 的直流偏移分量；最后在基带输出的信号I和信号Q的两个正交信号基础上减去圆心坐标，即信号I和信号Q分别减去各自对应的直流偏移分量，从而实现对信号I和信号Q的修正补偿。
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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101511268A (zh) * 2006-08-30 2009-08-19 皇家飞利浦电子股份有限公司 监测体内脉动对象的装置
CN103948381A (zh) * 2014-04-09 2014-07-30 浙江大学 一种用于大动态范围多普勒生物信号成像方法
US20180263502A1 (en) * 2014-10-08 2018-09-20 The University Of Florida Research Foundation, Inc. Method and apparatus for non-contact fast vital sign acquisition based on radar signal
CN108577815A (zh) * 2018-04-03 2018-09-28 电子科技大学 一种基于超宽带雷达的人体呼吸速率和心率的测定方法
CN108852327A (zh) * 2018-04-16 2018-11-23 浙江大学 一种从运动干扰中非接触检测微弱生命信号的方法
CN110115585A (zh) * 2019-05-06 2019-08-13 浙江大学 一种心动图的非接触测量方法

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103070728A (zh) * 2013-02-06 2013-05-01 南京理工大学 一种非接触式生命体征监护设备
CN109414179A (zh) * 2016-06-24 2019-03-01 杜克大学 使用超声波估计心脏应变和位移的系统和方法

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101511268A (zh) * 2006-08-30 2009-08-19 皇家飞利浦电子股份有限公司 监测体内脉动对象的装置
CN103948381A (zh) * 2014-04-09 2014-07-30 浙江大学 一种用于大动态范围多普勒生物信号成像方法
US20180263502A1 (en) * 2014-10-08 2018-09-20 The University Of Florida Research Foundation, Inc. Method and apparatus for non-contact fast vital sign acquisition based on radar signal
CN108577815A (zh) * 2018-04-03 2018-09-28 电子科技大学 一种基于超宽带雷达的人体呼吸速率和心率的测定方法
CN108852327A (zh) * 2018-04-16 2018-11-23 浙江大学 一种从运动干扰中非接触检测微弱生命信号的方法
CN110115585A (zh) * 2019-05-06 2019-08-13 浙江大学 一种心动图的非接触测量方法

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