CN109602395B - Noninvasive multichannel arterial system detection method and device - Google Patents
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Abstract
The application relates to a noninvasive multichannel arterial system detection method. Another technical solution of the present application is to provide a non-invasive multi-channel arterial system detection device, which is characterized by comprising: two pressure pulse wave sensors; at least two photoelectric sensors; a signal processing module; and the computer is used for executing the detection method. The method based on the photoelectric volume pulse wave by using the photoelectric reflection sensor solves the problem of great implementation difficulty in actual detection operation and achieves the effect of better actual operability.
Description
Technical Field
The application relates to a noninvasive multichannel arterial system detection method and device, and belongs to the technical field of biomedical treatment.
Background
With the development of social economy, the national lifestyle has changed deeply. Especially, the population aging and the urbanization process are accelerated, the epidemic trend of the risk factors of the cardiovascular diseases in China is in a obviously rising situation, and the incidence number of the cardiovascular diseases is continuously increased. The number of cardiovascular diseases will increase rapidly in the next decade. Arterial lesions are one of the leading causes of morbidity and mortality in cardiovascular and cerebrovascular diseases. In clinical medicine, the pulse wave data obtained by analysis can be used as the basis of clinical diagnosis and treatment, in particular for assessing arterial cardiovascular function conditions.
Clinical attention to pulse waves is mainly focused on the measurement of two-point blood pressure, namely Diastolic Pressure (DP) and Systolic Pressure (SP), and different physiological and pathological phenomena cause different changes in pulse shape. The magnitude of the Pulse Wave Velocity (PWV) reflects the degree of elasticity of the blood vessel, i.e., the higher the degree of arteriosclerosis, the greater the pulse wave velocity, compared to the Diastolic (DP) and Systolic (SP) pressures, and the Pulse Wave Velocity (PWV) has become an important indicator for measuring arteriosclerosis. Therefore, the parameters representing the functions of the arterial cardiovascular system can be obtained by detecting and acquiring more pulse wave information in a deeper level, and the state of arterial cardiovascular is estimated, so that early discovery and early treatment of cardiovascular diseases are realized.
At present, the noninvasive pulse wave detection analysis mainly adopts a pressure sensor direct measurement method, and is represented by the golden standard carotid pulse wave conduction velocity cfPWV of the most authoritative arteriosclerosis detection in the world, and although the carotid artery conduction velocity measurement based on the pressure pulse wave is clinically accepted, the clinical operation is very difficult, and the operation can be performed after professional training in the measurement process.
Secondly, the current pulse wave detection analysis mainly focuses on one or two paths of pulse wave detection, but only one pulse wave signal at two detection points is detected, so that the information of cardiovascular states of all local arteries of the body is difficult to obtain, and therefore, the multipoint synchronous measurement is required to be carried out on different arterial segments of the human body.
Disclosure of Invention
The purpose of the application is that: the system can comprehensively analyze the signals of the photoelectric volume pulse wave signals and the pressure pulse waves of multiple parts of the body, which are obtained by synchronous measurement, so as to obtain parameters of an arterial system, and provide a more comprehensive means for evaluating the cardiovascular conditions of clinical arteries.
In order to achieve the above object, a technical solution of the present application is to provide a method for detecting a non-invasive multi-channel arterial system, which is characterized by comprising the following steps:
step 1, synchronously measuring a pressure pulse wave signal at the radial artery of the left wrist and a pressure pulse wave signal at the radial artery of the right wrist of a detected person through a pressure pulse wave sensor;
step 2, determining symmetrically arranged multipath measuring points on the left and right sides of the body of the detected person, arranging a photoelectric sensor on each measuring point, and synchronously measuring photoelectric volume pulse wave signals of the multipath specific measuring points which are symmetrical on the left and right sides of the body of the detected person by adopting a method based on photoelectric volume pulse waves through the photoelectric sensor;
step 3, acquiring pulse wave velocity of each artery segment part of the body part in bilateral symmetry according to the synchronously measured pressure pulse wave signals and the photoelectric volume pulse wave signals of each specific measuring point of the plurality of paths, wherein the pulse wave velocity of the artery segment part of the ith segment is defined as PWV i Then there is PWV i ＝ΔS i /ΔT i ，ΔS i For the length of the i-th segment of the artery, deltaT i The time difference between the starting point and the starting point of the photoelectric volume pulse wave signals obtained between the photoelectric sensors on the ith arterial segment part or the time difference between the starting point and the starting point of the photoelectric volume pulse wave signals obtained between the photoelectric sensors on the ith arterial segment part and the pressure pulse wave sensors;
step 4, comparing the pulse wave velocity of the artery segment part of the left half body of the detected person with the pulse wave velocity of the symmetrical artery segment part of the right half body of the detected person, so as to evaluate the vascular state of each artery segment part of the body part;
step 5, calculating waveform characteristic parameters of the photoelectric volume pulse wave signals of the specific measuring points, and evaluating microcirculation distribution conditions of the arterial system according to the waveform characteristic parameters;
calculating waveform characteristic parameters of the pressure pulse wave signals, and evaluating the overall congestion condition of the arterial system according to the waveform characteristic parameters;
and 6, calculating a Poincare heart rate scatter diagram according to any pressure pulse wave signal or any photoelectric volume pulse wave signal, and evaluating the change of the heart rate through the Poincare heart rate scatter diagram.
Preferably, in step 5, a waveform characteristic parameter K of the photoplethysmography signal is calculated PPG ：
K PPG ＝(PPG M -PPG _DC )/(PPG -PEAK -PPG _DC ) In the formula, PPG M Is the average value of the waveform of the photoplethysmogram signal, PPG -PEAK PPG, which is the maximum value of the waveform of the photoplethysmography signal _DC Is a photoplethysmography pulseAmplitude of the DC portion of the waveform of the wave signal.
Preferably, in step 5, a waveform characteristic parameter K of the pressure pulse wave signal is calculated:
k= (MP-DP)/(SP-DP), where MP is the mean pressure, DP is the diastolic pressure, and SP is the systolic pressure.
Preferably, in step 3, the length of each arterial segment portion is measured from human anatomy, statistically in combination with a plurality of external body surface data of the individual.
Preferably, the method further comprises:
and 7, calculating the time length of each cardiac cycle according to any pressure pulse wave signal or any photoelectric volume pulse wave signal.
Another technical solution of the present application is to provide a non-invasive multi-channel arterial system detection device, which is characterized by comprising:
the two pressure pulse wave sensors are used for synchronously measuring the pressure pulse wave signals of the radial artery of the left wrist and the radial artery of the right wrist of the detected person;
at least two paths of photoelectric sensors are symmetrically arranged on the left side and the right side of the body of the detected person and are used for synchronously measuring photoelectric volume pulse wave signals of multiple paths of specific measuring points which are symmetrical on the left side and the right side of the body of the detected person;
the signal processing module is used for receiving the pressure pulse wave signals acquired by the two pressure pulse wave sensors and the photoelectric volume pulse wave signals acquired by all the photoelectric sensors and then forwarding the pressure pulse wave signals and the photoelectric volume pulse wave signals to the computer;
and the computer is used for executing the detection method.
Preferably, the pressure sensor is a piezoelectric film type pressure sensor; the photoelectric sensor is a photoelectric reflection type sensor.
Preferably, the signal processing module comprises a signal conditioning circuit, a digital-to-analog conversion circuit, a data processing circuit, a data transmission circuit, a power supply and management circuit, wherein:
the signal conditioning circuit comprises a pre-amplifier, a band-pass filter, a trap and a post-amplifier, wherein the pre-amplifier amplifies a received pulse wave signal and then sends the pulse wave signal into the band-pass filter, the band-pass filter filters out edge impurities of the signal, the trap eliminates interference, and the post-amplifier secondarily amplifies the pulse wave signal and then sends the pulse wave signal into the digital-to-analog conversion circuit;
the digital-analog conversion circuit is used for converting the received pulse wave signals into digital pulse wave signals which can be processed by the computer;
the data processing circuit selects an NRF51822 model MCU chip of NORDIC company, processes the digital pulse wave signals output by the digital-to-analog converter circuit by adopting digital filtering, period identification and baseline adjustment in sequence, and meanwhile, the NRF51822 model MCU chip performs data interaction and transmission with a mobile phone through Bluetooth;
the data transmission circuit is used for carrying out instruction and data interaction with the computer;
and the power supply and management circuit is connected with the signal conditioning circuit, the digital-to-analog conversion circuit, the data processing circuit and the data transmission circuit and provides power for each circuit.
Compared with the prior art, the application has the beneficial effects that:
the application collects the pulse wave data of multiple paths at multiple parts of the human body, can obtain the local pulse wave velocity PWV of each arterial segment of the human body, and provides more specific and comprehensive state information for arterial vessel detection.
The application can process the pulse wave signal of the photo-capacitance product, and can obtain the pulse wave waveform characteristic quantity K of each specific measuring point of the body through the signal comprehensive analysis of the photoelectric blood flow PPG And the value provides support for analysis of the microcirculation distribution condition of the arterial system.
The application can process the pulse wave signals of the pressure sensor, can comprehensively analyze the signals of the pressure pulse waves, and can obtain the characteristic quantity K value of the radial pulse wave waveforms at the left side and the right side of the body, thereby providing support for analyzing the whole congestion condition of the arterial system.
The application can process the photo-capacitance product pulse wave signal and the pressure sensor pulse wave signal, and can calculate a Poincare (Poincare) heart rate scatter diagram by utilizing any path of signals, and is used for evaluating the change HRV of heart rate.
The method for synchronously measuring the left and right symmetrical multiple points can provide the comparison of the wave velocities PWV of the same local pulse waves on the left and right sides of the body, and provide primary support for the analysis of the arteriosclerosis state of a certain local blood vessel of the body.
The method based on the photoelectric volume pulse wave by using the photoelectric reflection sensor solves the problem of great implementation difficulty in actual detection operation and achieves the effect of better actual operability.
Drawings
FIG. 1 is a flow chart of a method for non-invasive multi-channel arterial system detection in accordance with the present application;
FIG. 2 is a schematic diagram of eight measurement points of a method for detecting a non-invasive multi-channel arterial system according to the present application;
FIG. 3 is an explanatory diagram of multiple measuring points of a method for detecting a noninvasive multichannel arterial system according to the present application;
FIG. 4 is a block diagram of a non-invasive multi-channel arterial system detection apparatus according to the present application;
FIG. 5 is a schematic diagram of a signal processing module of a non-invasive multi-channel arterial system detection device according to the present application;
fig. 6 is a circuit diagram of a signal conditioning circuit of a non-invasive multi-channel arterial system detection device according to the present application.
Detailed Description
The application will be further illustrated with reference to specific examples. It is to be understood that these examples are illustrative of the present application and are not intended to limit the scope of the present application. Furthermore, it should be understood that various changes and modifications can be made by one skilled in the art after reading the teachings of the present application, and such equivalents are intended to fall within the scope of the application as defined in the appended claims.
The embodiment of the application provides a non-invasive multichannel arterial system detection method, referring to fig. 1,2 and 3, comprising the following steps:
step 1, synchronously measuring a pressure pulse wave signal at the radial artery of the left wrist and a pressure pulse wave signal at the radial artery of the right wrist of a detected person through a pressure pulse wave sensor;
step 2, determining symmetrically arranged multipath measuring points on the left and right sides of the body of the detected person, arranging a photoelectric sensor on each measuring point, and synchronously measuring photoelectric volume pulse wave signals of the multipath specific measuring points which are symmetrical on the left and right sides of the body of the detected person by adopting a method based on photoelectric volume pulse waves through the photoelectric sensor;
step 3, according to the synchronously measured pressure pulse wave signals and the photoelectric volume pulse wave signals of the specific measuring points of the plurality of paths, obtaining pulse wave velocities of the artery segment parts of the body part which are bilaterally symmetrical, wherein two ways for calculating the pulse wave velocity PWM exist:
the first calculation mode is as follows: referring to fig. 2, when the number of sensors is small, as in fig. 2, the number of sensors is eight, four pulse wave sensors are respectively arranged on the left and right sides of the body, and a pulse wave segment can be calculated between any two points of four measuring points on each single side of the left and right sides of the body, so that the left and right sides of the body are respectively provided withCalculated values of pulse wave velocity PWV for different segments.
Further, according to the waveform start time of each sensor synchronous signal on the left side of the body, respectively calculating the start time difference between synchronous pulse wave signals of each group of measuring points on the left side of the body, wherein the start time difference is respectively calculated as follows:
synchronous pulse wave signal waveform initiation time difference delta T (er) between earlobe e and distal end of radial artery r
The pulse wave signal waveform start time difference delta T (et) is synchronized between the earlobe e and the tip of the thumb T
The waveform start time difference delta T (ef) of the synchronous pulse wave signals between the earlobe e and the index finger f
Synchronous pulse wave signal waveform initiation time difference delta T (rf) between radial artery r and index finger f end
Synchronous pulse wave signal waveform start time difference delta T (rt) between radial artery r and tip of thumb T
Synchronous pulse wave signal waveform initiation time difference DeltaT (ft) between index finger f end and thumb T top end
Further, the height of the subject (H is the height of the subject in cm) is input according to the following formula, and the distances of the pulse wave measuring points corresponding to the groups are calculated respectively, wherein the lengths of the sections of the blood vessel only depend on the height and the gender of the subject is not distinguished from the left side and the right side of the body, and the formula is as follows:
the distance from the heart h to the earlobe e is Lhe (cm) =0.3499×h (cm) -23.4568
The distance from heart h to distal end of radial artery r is Lhr (cm) =0.4205×h (cm) -1.3362
The distance from the distal end of the radial artery r to the end of the index finger f is Lrf (cm) =0.0785×h (cm) +4.3913
The distance from heart h to index finger f was Lhf (cm) =0.499×h (cm) +3.0551
The distance from the heart h to the tip of the big toe t is Lht (cm) =0.9331×h (cm) +9.9674
The distances between the pulse wave measurement points are respectively:
distance Δs (er) =lhr (cm) -Lhe (cm) from earlobe e to distal end of radial artery r
Distance Δs (ef) =lhf (cm) -Lhe (cm) from earlobe e to index finger f
Distance Δs (et) =lht (cm) -Lhe (cm) from earlobe e to tip of thumb t
Distance Δs (rf) =lrf (cm) from radial artery r to index finger f end
Distance Δs (rt) =lht (cm) -Lhr (cm) from radial artery r to tip of big toe t
Distance Δs (ft) =lht (cm) -Lhf (cm) from the end of index finger f to the tip of thumb t
Further, the pulse wave velocity between the pulse wave signals of the arterial segments on the left side of the body is calculated according to the formula pwv=Δs/Δt, and is erbwv_ L, efPWV _ L, etPWV _ L, rfPWV _ L, rtPWV _ L, ftPWV _l, respectively.
Further, the pulse wave velocity erpwv_ R, efPWV _ R, etPWV _ R, rfPWV _ R, rtPWV _ R, ftPWV _r between the pulse wave signals of the arterial segments on the right side of the body can be calculated according to the formula.
Further, the pulse wave velocity PWV measured by the synchronous pulse wave sensors at the left side and the right side of the body can be compared to preliminarily judge the difference between the pulse wave velocities PWV of the arterial blood vessels at the same local segment at the left side and the right side of the body.
And a second calculation mode: referring to fig. 3, when a large number of sensors are used, as in the special case shown in fig. 3, each pulse wave measurement point is provided with a pulse wave sensor, the number of pulse wave sensors is twenty, ten pulse wave sensors are respectively arranged on the left and right sides of the body, and one calculated pulse wave segment can be adopted between two adjacent points in the ten measurement points on each single side of the left and right sides of the body, so that the left and right sides of the body respectively have calculated values of pulse wave velocity PWV of 10-1=9 different segments.
Further, the positions of the measurement points according to fig. 3 are described as follows:
l1 is the location where the telecentric (or downstream) sensor of the left carotid artery of the body is placed, along the carotid trend, at the upper extremity of the neck and in the lower part of the mandible.
L2 is the location where the proximal (or upstream) sensor of the left carotid artery of the body is placed, and can be placed along the carotid trend at the lower extremity of the neck, where it corresponds to the intersection of the left carotid artery with the left subclavian artery.
L3 is the position of the left side of the body along the left subclavian artery and under the armpit, i.e. the position of the left side of the armpit artery.
L4 is the position of the medial left arm of the body at the elbow midline, and is the junction of the upper arm (humerus) and lower arm (radius/ulna).
L5 is the position of the distal end of the radial artery on the left side of the body, i.e. the position of the pulse feeling in traditional Chinese medicine.
L6 is the position of the finger belly of the left index finger end of the body.
L7 is the groin of the left lower limb of the body and is the starting point of the left common femoral artery.
L8 is the external third of the midline of the left popliteal fossa (posterior to the left knee) of the body, the popliteal artery can be measured.
L9 is the right lower part of the left medial malleolus of the body, and the posterior tibial artery can be measured.
L10 is the position of the toe of the thumb on the left side of the body.
R1-R10: is the measurement point of the right side of the body corresponding to the left sides L1-L10.
Further, according to the waveform start time of each sensor synchronous signal on the left side of the body, respectively calculating the start time difference between synchronous pulse wave signals of each group of measuring points on the left side of the body, wherein the start time difference is respectively calculated as follows:
synchronous pulse wave signal waveform initiation time difference DeltaT (12) between test point 1 and test point 2
Synchronous pulse wave signal waveform initiation time difference DeltaT (23) between test point 2 and test point 3
Synchronous pulse wave signal waveform initiation time difference DeltaT (34) between test point 3 and test point 4
Synchronous pulse wave signal waveform initiation time difference DeltaT (45) between test point 4 and test point 5
Synchronous pulse wave signal waveform initiation time difference DeltaT (56) between test point 5 and test point 6
Synchronous pulse wave signal waveform initiation time difference DeltaT (27) between test point 2 and test point 7
Synchronous pulse wave signal waveform initiation time difference DeltaT between test point 7 and test point 8 (78)
Synchronous pulse wave signal waveform initiation time difference DeltaT (89) between test point 8 and test point 9
Synchronous pulse wave signal waveform start time difference delta T between test point 9 and test point 10 (910)
Further, the distance between the synchronous pulse wave signals of each group of measurement points on the left side of the body obtained by combining the formula in the first calculation mode with the actual measurement of the external body surface data of the individual is as follows: Δs (12), Δs (23), Δs (34), Δs (45), Δs (56), Δs (27), Δs (78), Δs (89), Δs (910);
further, pulse wave velocities between pulse wave signals of the arterial segments on the left side of the body are calculated according to the formula pwv=Δs/Δt, and are 12pwv_l, 23pwv_l, 34pwv_l, 45pwv_l, 56pwv_l, 27pwv_l, 78pwv_l, 89pwv_l, 910pwv_l, respectively.
Further, pulse wave velocities 12pwv_r, 23pwv_r, 34pwv_r, 45pwv_r, 56pwv_r, 27pwv_r, 78pwv_r, 89pwv_r, and 910pwv_r between pulse wave signals of the right-side artery segments of the body can be calculated according to the formula.
Further, the pulse wave velocity PWV measured by the synchronous pulse wave sensors at the left side and the right side of the body can be compared to preliminarily judge the difference between the pulse wave velocities PWV of the arterial blood vessels at the same local segment at the left side and the right side of the body.
Step 4, calculating characteristic parameters K of each waveform by using the photoplethysmogram signals of each specific measurement point measured by the photoelectric sensor PPG Value:
K PPG ＝(PPG M -PPG _DC )/(PPG -PEAK -PPG _DC ) In the formula, PPG M Is the average value of the waveform of the photoplethysmogram signal, PPG -PEAK PPG, which is the maximum value of the waveform of the photoplethysmography signal _DC Is the amplitude of the direct current part of the waveform of the photoelectric volume pulse wave signal.
Calculating the characteristic parameter K value of each waveform by the pressure pulse wave signals of the left radial artery and the right radial artery measured by the pressure pulse wave sensor:
k= (MP-DP)/(SP-DP), where MP is the mean pressure, DP is the diastolic pressure, and SP is the systolic pressure.
And 5, calculating a Poincare (Poincare) heart rate scatter diagram for evaluating the change HRV of the heart rate according to any pulse wave signal measured by the photoelectric sensor and the pressure pulse wave sensor.
Further, for any pulse wave signal measured by any one of the photoelectric sensor and the pressure pulse wave sensor, a time length T (n), n=1, 2,3 …, and a sequence of each cardiac cycle may be calculated.
In addition, according to the formula heart rate hr=heart rate/min=60/T (unit ppm=pulse Per Minute), the above-mentioned cardiac cycle scatter plot T (n) vs T (n-1) can be converted into a heart rate scatter plot HR (n) vs HR (n-1).
An embodiment of the present application provides a non-invasive multi-channel arterial system detection device for home personal use, please refer to fig. 4, the device includes:
the pressure pulse wave sensors are piezoelectric film type pulse wave sensors, the input ends of the pressure pulse wave sensors 1.2 and 1.3 are contacted with the skin surfaces at radial arteries of the left wrist and the right wrist of a detected person, and radial artery pulse wave signals of the left wrist and the right wrist are collected.
The input ends of three photoelectric sensors 1.21, 1.22 and 1.23 in the six photoelectric sensors are respectively contacted with the skin surfaces of a left earlobe, a left index finger and a left big toe on the left side of the body of a detected person, and the photo-capacitance pulse wave signals of each specific point on the left side of the body are collected; the input ends of the other three photoelectric sensors 1.31, 1.32 and 1.33 of the six photoelectric sensors are respectively contacted with the skin surfaces of the right earlobe, the right index finger and the right big toe on the right side of the body of the detected person, and the photo-capacitance pulse wave signals of each specific point on the right side of the body are collected.
The input end of the signal processing module 1.1 is respectively connected with the output ends of the two pressure pulse wave sensors and the six photoelectric sensors and used for receiving radial artery pulse wave signals of the left wrist and the right wrist and photo-capacitance accumulated pulse wave signals of specific points on the left side and the right side of the body;
radial artery pulse wave signals of the left wrist and the right wrist measured by the two pressure pulse wave sensors 1.2 and 1.3 are input into the signal processing module 1.1; the three-way photoelectric sensors 1.21, 1.22 and 1.23 of the six-way photoelectric sensors measure photo-capacitance pulse wave signals of specific points on the left side of the body, the photo-capacitance pulse wave signals of specific points on the right side of the body, which are measured by the three-way photoelectric sensors 1.31, 1.32 and 1.33, are input into the signal processing module 1.1 together, the signal processing module 1.1 is connected with the computer 1.4 through USB serial communication, the computer 1.4 synthesizes information of each way, processes and calculates pulse wave velocity PWV of each section part of the body part, pulse wave waveform characteristic quantity K value of each specific measurement point, and displays pulse wave waveforms of each pressure, pulse wave waveforms of each photo-capacitance and Poincare heart rate scatter diagram.
Further, referring to fig. 5, the signal processing module 1.1 specifically includes: the device comprises a signal conditioning circuit, a digital-to-analog conversion circuit, a data processing circuit, a data transmission circuit and a power supply circuit.
The signal conditioning circuit, please refer to fig. 6, is composed of a pre-amplifier, a band-pass filter, a trap, and a post-amplifier.
A preamplifier: the volume pulse wave is a low-frequency and weak physiological signal, and has a strong noise background, so that in order to detect an effective signal without distortion, the signal acquisition system is often required to have performances such as high accuracy, high stability, high input impedance, high common mode rejection ratio, low noise, and strong anti-interference capability. The pre-amplifying circuit is a key link of the acquisition circuit, and the noise is amplified at the same time when the signal is amplified at the forefront end of the signal, so that the amplification factor of the pre-stage is designed to be 5 times.
Band-pass filter: after the signal is amplified by the pre-amplifier, the signal is weak and can be effectively collected by the analog-digital conversion circuit after further amplification, and meanwhile, the signal also contains a plurality of noise interferences. In order to prevent saturation from occurring when amplifying an ac small signal, unwanted signals and dc signals of lower frequencies contained in the signal are filtered out first, and thus a high pass filter and a low pass filter are required.
High pass filter: the DC component in the pulse wave signal is mainly filtered, and the low-pass filter filters out high-frequency noise.
A wave trap: the interference of the power frequency noise to the pulse wave signals with low frequency and small amplitude is serious, and the interference to the signal measurement is obvious although the band-pass filter has a certain inhibition effect on the 50Hz interference signals, and a trap special for filtering the 50Hz power frequency interference is also needed. And the method is used for eliminating the interference of the power frequency signal of 50hz to the generation.
Post-amplifier: most of noise in the pulse wave signals processed by the wave trap is filtered, but the pulse wave signals are conditioned to meet the signal input requirement of the analog-to-digital converter, so that the pulse wave signals are further amplified and DC level lifted to be converted into the range of 0-3.3V.
The digital-analog conversion circuit is used for carrying out subsequent digital processing on the acquired signals, the heart rate range of a person is about 40-200 times per minute, and in order to ensure that sampled data is not distorted, the sampling rate of the CPU is 333 Hz, namely the sampling interval is 3ms according to the Nyquist sampling principle. The data acquisition quantity of the signal acquisition unit is reduced as much as possible on the basis of ensuring the acquisition of the required signal frequency band, thereby being beneficial to reducing the measurement noise and reducing the hardware cost of the device; the delta S is smaller in multipath measurement, and the corresponding delta T is also short, so that the sampling rate can be increased to 1000 Hz, and the sampling time interval is 1ms.
The data processing circuit selects an NRF51822 model MCU chip of NORDIC company, and sequentially processes the acquired pulse wave signals by adopting digital filtering, period identification, baseline adjustment and other methods; and when the single period is identified, the waveform data of the original signal is intercepted, the complete period part is intercepted, and the data of which the initial part and the end part are not complete periods in the original recorded data are removed.
The data transmission circuit is used for carrying out instruction and data interaction with a computer through a USB interface, meanwhile, an NRF51822 model MCU chip also has a Bluetooth function, data interaction and transmission can be carried out with a mobile phone through Bluetooth, and meanwhile, the USB interface is also a power supply interface of the signal processing module.
The power supply and management circuit is connected with the signal conditioning circuit, the digital-to-analog conversion circuit, the data processing circuit and the data transmission circuit and is used for providing power for the circuits; in addition, the signal processing module can be powered by a rechargeable lithium battery and detects the voltage of the battery in real time, when the voltage of the battery is low and can not meet the working requirement of the device, a low-voltage alarm is sent out to inform a user to charge the battery through a USB interface, a charging management unit circuit monitors the charging process, and after the electric quantity of the battery is full, the charging is finished through LED display.
Specifically, the two paths of pressure pulse wave sensors and the six paths of photoelectric sensors are used for connecting signals and transmitting the signals to the signal conditioning circuit, the signal conditioning circuit is connected with the digital-to-analog conversion circuit, the digital-to-analog conversion circuit is used for connecting and transmitting converted data to the MCU in the data processing circuit for processing, the MCU is in data communication with the upper computer through a serial port protocol of the USB, the computer is used for calculating Pulse Wave Velocity (PWV) of each segment part of the body part, pulse wave waveform characteristic quantity K value or KPPG value of each specific measuring point, and finally, each pressure pulse wave waveform, each photoelectric volume pulse wave waveform and Poincare (Poincare) heart rate scatter diagram are displayed.
Claims (8)
1. A method for detecting a noninvasive multichannel arterial system, comprising the following steps:
step 1, synchronously measuring a pressure pulse wave signal at the radial artery of the left wrist and a pressure pulse wave signal at the radial artery of the right wrist of a detected person through a pressure pulse wave sensor;
step 2, determining symmetrically arranged multipath measuring points on the left and right sides of the body of the detected person, arranging a photoelectric sensor on each measuring point, and synchronously measuring photoelectric volume pulse wave signals of the multipath specific measuring points which are symmetrical on the left and right sides of the body of the detected person by adopting a method based on photoelectric volume pulse waves through the photoelectric sensor;
step 3, acquiring pulse wave velocity of each artery segment part of the body part in bilateral symmetry according to the synchronously measured pressure pulse wave signals and the photoelectric volume pulse wave signals of each specific measuring point of the plurality of paths, wherein the pulse wave velocity of the artery segment part of the ith segment is defined as PWV i Then there is PWV i ＝ΔS i /ΔT i ，ΔS i For the length of the i-th segment of the artery, deltaT i For the time difference between the start and the start of the photoplethysmographic pulse wave signal obtained between photosensors on the i-th segment of an artery segment, or DeltaT i A photoelectric volume pulse wave signal obtained between a photoelectric sensor and a pressure pulse wave sensor on the section of the ith artery segment and a time difference between a starting point and a starting point of the pressure pulse wave signal;
step 4, comparing the pulse wave velocity of the artery segment part of the left half body of the detected person with the pulse wave velocity of the symmetrical artery segment part of the right half body of the detected person, so as to evaluate the vascular state of each artery segment part of the body part;
step 5, calculating waveform characteristic parameters of the photoelectric volume pulse wave signals of the specific measuring points, and evaluating microcirculation distribution conditions of the arterial system according to the waveform characteristic parameters;
calculating waveform characteristic parameters of the pressure pulse wave signals, and evaluating the overall congestion condition of the arterial system according to the waveform characteristic parameters;
and 6, calculating a Poincare heart rate scatter diagram according to any pressure pulse wave signal or any photoelectric volume pulse wave signal, and evaluating the change of the heart rate through the Poincare heart rate scatter diagram.
2. The method for detecting a non-invasive multi-channel arterial system according to claim 1, wherein in step 5, a waveform characteristic parameter K of the photoplethysmography signal is calculated PPG ：
K PPG ＝(PPG M -PPG _DC )/(PPG -PEAK -PPG _DC ) In the formula, PPG M Is the average value of the waveform of the photoplethysmogram signal, PPG -PEAK PPG, which is the maximum value of the waveform of the photoplethysmography signal _DC Is the amplitude of the direct current part of the waveform of the photoelectric volume pulse wave signal.
3. The method for detecting a non-invasive multi-channel arterial system according to claim 1, wherein in step 5, a waveform characteristic parameter K of the pressure pulse wave signal is calculated:
k= (MP-DP)/(SP-DP), where MP is the mean pressure, DP is the diastolic pressure, and SP is the systolic pressure.
4. A method of non-invasive multi-channel arterial system testing according to claim 1, wherein in step 3, the length of each arterial segment portion is measured from human anatomy, statistics, in combination with a plurality of external body surface data of the individual.
5. A method of non-invasive multi-channel arterial system detection as claimed in claim 1, further comprising:
and 7, calculating the time length of each cardiac cycle according to any pressure pulse wave signal or any photoelectric volume pulse wave signal.
6. A non-invasive multi-channel arterial system detection device, comprising:
the two pressure pulse wave sensors are used for synchronously measuring the pressure pulse wave signals of the radial artery of the left wrist and the radial artery of the right wrist of the detected person;
at least two paths of photoelectric sensors are symmetrically arranged on the left side and the right side of the body of the detected person and are used for synchronously measuring photoelectric volume pulse wave signals of multiple paths of specific measuring points which are symmetrical on the left side and the right side of the body of the detected person;
the signal processing module is used for receiving the pressure pulse wave signals acquired by the two pressure pulse wave sensors and the photoelectric volume pulse wave signals acquired by all the photoelectric sensors and then forwarding the pressure pulse wave signals and the photoelectric volume pulse wave signals to the computer;
a computer for performing the detection method of claim 1.
7. The non-invasive multi-channel arterial system detection device according to claim 6, wherein said pressure pulse wave sensor is a piezoelectric thin film pressure sensor; the photoelectric sensor is a photoelectric reflection type sensor.
8. The non-invasive multi-channel arterial system detection device according to claim 6, wherein the signal processing module comprises a signal conditioning circuit, a digital-to-analog conversion circuit, a data processing circuit, a data transmission circuit, a power supply and management circuit, wherein:
the signal conditioning circuit comprises a pre-amplifier, a band-pass filter, a trap and a post-amplifier, wherein the pre-amplifier amplifies a received pulse wave signal and then sends the pulse wave signal into the band-pass filter, the band-pass filter filters out edge impurities of the signal, the trap eliminates interference, and the post-amplifier secondarily amplifies the pulse wave signal and then sends the pulse wave signal into the digital-to-analog conversion circuit;
the digital-analog conversion circuit is used for converting the received pulse wave signals into digital pulse wave signals which can be processed by the computer;
the data processing circuit selects an NRF51822 model MCU chip of NORDIC company, processes the digital pulse wave signals output by the digital-to-analog converter circuit by adopting digital filtering, period identification and baseline adjustment in sequence, and meanwhile, the NRF51822 model MCU chip performs data interaction and transmission with a mobile phone through Bluetooth;
the data transmission circuit is used for carrying out instruction and data interaction with the computer;
and the power supply and management circuit is connected with the signal conditioning circuit, the digital-to-analog conversion circuit, the data processing circuit and the data transmission circuit and provides power for each circuit.
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| CN112869725B (en) * | 2021-02-23 | 2022-05-27 | 佛山科学技术学院 | Multichannel pulse acquisition system and method |
| CN115644838A (en) * | 2022-10-12 | 2023-01-31 | 诺丁汉大学卓越灯塔计划(宁波)创新研究院 | Method for non-invasive synchronous detection of pulse wave velocity and local pulse wave velocity of multiple regions |
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