CN110115583A - The method and apparatus of monitoring of respiration - Google Patents

Abstract

Embodiments of the present invention provide a method and device for respiratory monitoring. The method includes receiving the original signal sent by the pressure sensor belt, the original signal including the pressure value of the bedding; performing analog conversion and digital AD sampling processing on the original signal to obtain a respiration signal; and calculating the respiration signal according to the respiration signal. frequency. The method receives the original signal carrying the pressure value of the bedding sent by the pressure sensing belt, and obtains the respiratory frequency according to the original signal, and can collect the original signal without contacting the human body, so that it is economical and convenient. Respiratory monitoring.

Description

Method and device for respiratory monitoring

technical field

Embodiments of the present invention relate to the field of medical technology, in particular to a method and device for respiratory monitoring.

Background technique

my country has entered a stage of rapid aging development. Statistics show that in 2015, the number of aging population in my country was 210 million, of which the proportion of the population over 60 years old was 15.7%. The proportion of the population is 17.0%. By 2050, it will enter the stage of severe aging. At that time, the number of aging population in my country will reach 437 million, and the proportion of the population over 60 years old will be 30.0%, which means that there will be one elderly person in every four people. Faster than ever before.

With the development of population aging, there are more and more empty nesters and elderly people living alone. The health and safety of these elderly people have received more and more social attention.

For middle-aged and elderly people, various diseases are prone to sudden outbreaks during nighttime rest. Therefore, monitoring vital signs during the sleep of the elderly can largely prevent the occurrence of accidents for the empty-nest elderly, and can improve the health and well-being of the elderly. Happiness index.

Breathing, body temperature, pulse, and blood pressure are the four vital signs of a person, among which breathing, as the first of the vital signs, is an important indicator of human survival.

The method of monitoring respiration in the prior art is mainly to monitor respiration frequency, which represents the number of respirations per minute, that is, one inhalation and one exhalation.

In the existing technology, professional respiratory monitoring instruments are used for monitoring. Most of the professional respiratory monitoring instruments are desktop computers, which are costly, complicated to operate, and inconvenient to use. They can only be used in fixed places such as medical institutions, physical examination institutions, communities, and nursing homes. The application scenarios are greatly limited.

If the elderly live at home and do not have professional respiratory monitoring equipment at home, health tracking cannot be performed.

It can be seen that the cost of monitoring breathing in the current prior art is high and the use is inconvenient.

Contents of the invention

Aiming at the defects of the prior art, embodiments of the present invention provide a method and device for monitoring respiration.

On the one hand, an embodiment of the present invention provides a method for respiratory monitoring, the method comprising:

Receive the original signal sent by the pressure sensor belt, the original signal includes the pressure value of the bedding;

Carrying out analog conversion and digital AD sampling processing on the original signal to obtain a respiratory signal;

From the respiration signal, a respiration rate is calculated.

On the other hand, an embodiment of the present invention provides a respiratory monitoring device, the device comprising:

The receiving module is used to receive the original signal sent by the pressure sensing belt, and the original signal includes the pressure value borne by the bedding;

A processing module, configured to perform analog conversion and digital AD sampling processing on the original signal to obtain a respiratory signal;

A calculation module, configured to calculate the respiratory rate according to the respiratory signal.

On the other hand, an embodiment of the present invention also provides an electronic device, including a memory, a processor, a bus, and a computer program stored in the memory and operable on the processor. When the processor executes the program, the above method is implemented. A step of.

On the other hand, an embodiment of the present invention also provides a storage medium on which a computer program is stored, and when the program is executed by a processor, the steps of the above method are implemented.

It can be known from the above technical solutions that the breathing monitoring method and device provided by the embodiments of the present invention, the method receives the original signal sent by the pressure sensor belt and carries the pressure value of the bedding, and obtains the breathing frequency according to the original signal. The original signal is collected without touching the human body, so that respiratory monitoring is economical and convenient.

Description of drawings

FIG. 1 is a schematic flow chart of a method for respiratory monitoring provided by an embodiment of the present invention;

FIG. 2 is a schematic diagram of a breathing signal provided by an embodiment of the present invention;

FIG. 3 is a schematic diagram of an original signal provided by another embodiment of the present invention;

Fig. 4 is a schematic structural diagram of a breathing monitoring device provided in another embodiment of the present invention;

Fig. 5 is a schematic diagram of a respiratory signal peak value provided by another embodiment of the present invention;

Fig. 6 is a schematic diagram of peak values initially determined for respiratory signals provided by yet another embodiment of the present invention;

Fig. 7 is a schematic flow chart of a breathing monitoring method proposed in another embodiment of the present invention;

Fig. 8 is a schematic structural diagram of a breathing monitoring device provided by another embodiment of the present invention;

FIG. 9 is a schematic structural diagram of an electronic device provided by another embodiment of the present invention.

Detailed ways

In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are the Embodiments of the invention are some embodiments, but not all embodiments.

Fig. 1 shows a schematic flow chart of a method for monitoring respiration provided by an embodiment of the present invention.

As shown in Figure 1, the method provided by the embodiment of the present invention specifically includes the following steps:

Step 11, receiving the original signal sent by the pressure sensor belt, the original signal includes the pressure value of the bedding;

The method provided by the embodiment of the present invention is implemented on a device for monitoring the respiration, and the device for monitoring the respiration is a processor with a signal processing function.

Optionally, the pressure sensing belt is arranged under the bedding, which is a device for a human body to lie on, such as a mattress.

Optionally, the pressure sensing belt may not be in direct contact with the human body, and may also measure the respiratory rate. In the embodiment of the present invention, the pressure sensing belt is set under the mattress as an example for illustration.

Optionally, the pressure sensing belt includes at least one pressure transducer (Pressure Transducer), which is used to sense the change of pressure and convert the change of pressure into an original signal. The original signal describes the change of voltage value with time.

Optionally, the pressure sensor can be realized by a piezoelectric ceramic sensor.

Optionally, when a person breathes, the abdominal cavity will rise and fall, which will cause different pressure values on the mattress, and the piezoelectric ceramic sensor will obtain the original signal according to the change value of the pressure.

The pressure sensing belt sends the original signal detected by the piezoelectric ceramic sensor to the processor, and the processor executes step 12 after receiving the original signal.

Step 12, performing analog conversion and digital AD sampling processing on the original signal to obtain a respiratory signal;

Optionally, the processor can implement the analysis and processing function of the original signal, and provide a reference voltage of +1.5V for the pressure sensor.

Optionally, the processor includes an operational amplifier and an AD (analog to digital, analog to digital) module.

Optionally, since the original signal collected by the pressure sensor may be very weak, it needs to be amplified to clarify the waveform of the original signal and determine the positions of the peaks and troughs.

Optionally, an operational amplifier is used to amplify the signal. Considering overflow will occur if the amplification factor is too high, the amplification factor can be set to 10 times.

Optionally, the AD module performs AD sampling on the amplified original signal.

Optionally, the original signal is an analog signal, and the AD sampling is to convert the analog signal into a digital signal, and then set the sampling frequency.

Optionally, the sampling frequency refers to how many sampling points are collected per second.

Optionally, several sampling points are selected from the digital signal (original signal), and the selected sampling points form a sampling signal.

Optionally, under the condition that the sampling theorem is satisfied, and considering the data storage space and computational complexity, the embodiment of the present invention sets the sampling frequency to 100 Hz (collecting 100 sampling points in 1 second).

Optionally, the sampling theorem describes the relationship between the sampling frequency and the digital signal, which is the basic basis for the discretization of the continuous signal. The sampling theorem is that when the sampling frequency is greater than twice the highest frequency in the digital signal, the sampling signal completely retains the information in the digital signal.

Optionally, the original signal collected by the pressure sensor may contain noise, and the sampling signal may be denoised to obtain a respiration signal reflecting respiration.

Fig. 2 is a schematic diagram of a breathing signal provided by an embodiment of the present invention.

As shown in Figure 2, the breathing signal describes the voltage variation of each sampling point over time. The abscissa is the number of sampling points, and the ordinate is the voltage (v). The unit directly detected by the pressure sensor is mv, and after being amplified by the operational amplifier, the unit is v.

Step 13. Calculate the respiratory frequency according to the respiratory signal.

Optionally, take the sampling points (60*100) collected in 1 minute as a unit, and check how many peaks there are in each unit. One peak is recorded as a breath, and the respiratory rate per minute is the number of peaks in a unit. number.

With the pressure sensing belt of the embodiment of the present invention, the pressure value of the bedding is detected by the pressure sensing belt instead of directly contacting the human body, so the detection is performed without restraining the human body, and the original signal is obtained, the cost is low, and the use is convenient , It can also reduce the psychological pressure of the user, and the processor will perform further signal processing to finally obtain the respiratory rate, so as to realize the long-term monitoring of human health in the natural sleep state.

The respiratory monitoring method provided in this embodiment can collect the original signal without touching the human body by receiving the original signal carrying the pressure value of the bedding sent by the pressure sensor belt, and obtaining the respiratory frequency according to the original signal , so as to carry out respiratory monitoring economically and conveniently.

On the basis of the above-mentioned embodiments, another embodiment of the present invention provides a respiratory monitoring method, the original signal includes a respiratory signal and a heartbeat signal, and correspondingly, analog conversion and digital AD sampling processing is performed on the original signal to obtain a respiratory The specific steps of the signal are:

performing band-pass filtering on the original signal to eliminate the heartbeat signal to obtain the respiration signal.

Fig. 3 is a schematic diagram of an original signal provided by another embodiment of the present invention.

As shown in Figure 3, each person's sleeping posture is different, and the lying position is also different. When the heartbeat also produces vibrations of different frequencies, the pressure sensor also detects the pressure value caused by the heartbeat, and the pressure value caused by the heartbeat The change is called the heartbeat signal.

That is to say, the actually detected original signal includes a respiration signal and a heartbeat signal, the respiration signal is superimposed with the heartbeat signal, and the heartbeat signal interferes with the respiration signal.

Optionally, after AD sampling is performed, the obtained sampling signal is band-pass filtered to obtain the respiratory signal as shown in FIG. 2 .

Because the breathing rate is generally between 6 times/min and 42 times/min, the band-pass filter is designed as an 80-order FIR (Finite Impulse Response, finite impulse response) band-pass filter, and the specific parameter is Fstop1=0.08; Fpass1=0.1; Fpass2=0.5; Fstop2=0.7; eliminate the influence of other signals on the respiratory waveform. After the original signal is filtered, a respiration waveform is obtained.

Other steps in this embodiment are similar to those in the foregoing embodiments, and will not be repeated in this embodiment.

The respiration monitoring method provided in this embodiment can eliminate the influence of the heartbeat signal on the respiration signal by performing band-pass filtering on the original signal, thereby obtaining the respiration signal in the original signal.

Fig. 4 is a schematic structural diagram of a breathing monitoring device provided by another embodiment of the present invention.

As shown in Figure 4, on the basis of the above-mentioned embodiments, another embodiment of the present invention provides a breathing monitoring method, the pressure sensing belt includes a plurality of pressure sensors, and each pressure sensor detects the pressure of a region of the bedding. The pressure value corresponds to an original signal; correspondingly, the original signal is subjected to analog conversion and digital AD sampling processing, and the steps of obtaining the respiratory signal are specifically as follows:

The processor calculates the energy of each original signal according to the plurality of original signals;

According to the original signal with the largest energy among the original signals, AD sampling processing is performed to obtain the breathing signal.

Optionally, the device for respiratory monitoring includes a pressure sensing belt 2, a signal line 3 and a processor 4, the pressure sensing belt 2 includes a plurality of piezoelectric ceramic sensors 1, and the processor 4 and the pressure sensing belt 2 pass through the signal line 3 The signal line 3 transmits the original signal of the piezoelectric ceramic sensor 1 to the processor 4 .

Optionally, each person's sleeping posture is different, and the lying position is also different. The pressure sensing belt 2 is provided with a plurality of piezoelectric ceramic sensors, and each piezoelectric ceramic sensor corresponds to detecting a region of the bedding. The ceramic sensor obtains one original signal, and the pressure sensing belt 2 as a whole can obtain multiple original signals, and each original signal can reflect the breathing condition of a person.

When the processor performs signal processing, it can only analyze the original signal of one piezoelectric ceramic sensor 1 to obtain the respiration signal, thereby obtaining the respiration frequency of the human body, without analyzing all the obtained multiple original signals.

The energy of the original signal of the piezoelectric ceramic sensor directly under the human body is often greater than the energy of the original signal of other piezoelectric ceramic sensors. The pressure value detected by the piezoelectric ceramic sensor directly under the human body can best reflect the vibration of the abdominal cavity. By calculating The energy of each original signal is selected, and then the original signal with the largest energy is selected for calculating the respiratory rate.

Optionally, after performing AD sampling, start to calculate the energy of each original signal.

Optionally, there are multiple ways to calculate the energy of the original signal, and this embodiment of the present invention uses one of them as an example for description.

The steps for the processor to calculate the energy of each original signal according to multiple original signals are as follows:

According to the square sum of the voltage values of all sampling points of each original signal, the energy of the original signal is obtained.

Optionally, the energy of one original signal is equal to the sum of the squares of the voltage values of all sampling points of the original signal, the energy of the original signals of each piezoelectric ceramic sensor is compared, and the original signal corresponding to the maximum energy is taken.

Optionally, after the original signal with the maximum energy is obtained, AD sampling processing and band-pass filtering processing are performed on the original signal with the maximum energy, so that the breathing signal can be accurately obtained.

Optionally, multiple pressure sensors (piezoelectric ceramic sensors) are provided. When the lying position of the human body changes, there may still be pressure sensors corresponding to the position of the abdominal cavity, so that accurate original signals can be obtained.

Other steps in this embodiment are similar to those in the foregoing embodiments, and will not be repeated in this embodiment.

In the breathing monitoring method provided in this embodiment, multiple original signals are obtained by multiple pressure sensors, and the original signal with the highest energy is selected from the multiple original signals for analysis and processing, so that accurate original signals can be obtained.

Fig. 5 is a schematic diagram of a respiratory signal peak value provided by another embodiment of the present invention.

As shown in Fig. 5, on the basis of the above-mentioned embodiments, in the breathing monitoring method provided by another embodiment of the present invention, the steps for the processor to calculate the breathing frequency according to the breathing signal are specifically:

Calculate the interval between adjacent peaks according to the positions of adjacent peaks of the respiratory signal:

According to multiple intervals, the average breathing interval is obtained;

According to the average breathing interval and the preset sampling frequency, the breathing frequency is obtained.

Optionally, obtain the position of each peak of the respiratory signal, mark the position of the peak as shown in Figure 5, and use the number of sampling points to describe the position of the peak, such as the 100th sampling point is the position of the first peak .

Optionally, calculate the interval between adjacent peaks based on their positions:

Y _i =X _i+1 -X _{i, i} =1, 2, . . .

In the formula, Y _i is the interval between adjacent peaks, Xi is a peak position, Xi ₊₁ is the next peak position adjacent to Xi _, and _i is a positive integer.

Thus, several intervals Y _i in each unit are obtained, and each interval is an interval between two breaths.

Optionally, the interval can be represented by the number of sampling points, that is, how many sampling points are separated from one peak to obtain the next peak.

For example, the peak of the first breath is the 100th sampling point, and the peak of the second breath is the 480th sampling point, then the first interval is 380 sampling points.

Optionally, for each unit (60*100 sampling points collected in 1 minute), the number of intervals is counted, and the intervals are averaged using the following formula to obtain the average breathing interval.

in, is the average breathing interval, Y _i is the ith interval, n is the total number of intervals, and n is a positive integer.

Optionally, the respiratory rate per unit (minute) is obtained according to the following formula:

Wherein, P is the breathing frequency, the unit is times/minute, and f is the sampling frequency, for example, 100HZ/second.

Other steps in this embodiment are similar to those in the foregoing embodiments, and will not be repeated in this embodiment.

The breathing monitoring method provided in this embodiment analyzes the peak of the breathing signal, and can obtain the breathing frequency more accurately.

Fig. 6 is a schematic diagram of peak values initially determined for respiratory signals provided by yet another embodiment of the present invention.

As shown in Figure 6, on the basis of the above-mentioned embodiments, another embodiment of the present invention provides a breathing monitoring method, before the step of calculating the interval between adjacent peaks according to the position of the adjacent peaks of the respiratory signal, the method Also includes:

Note that the voltage value of the current sampling point is curData, the voltage value of the previous sampling point of the current sampling point is preData, and the voltage value of the next sampling point of the current sampling point is nextData;

If curData-preData>0 and curData-nextData>0, the current sampling point is preliminarily determined as the peak position.

Optionally, before the step of calculating the interval between adjacent peaks according to the positions of adjacent peaks of the respiratory signal, the position of each peak needs to be determined first.

When curData-preData>0 and curData-nextData>0 are satisfied, the current sampling point is preliminarily determined as the peak position.

Optionally, the positions of the obtained peaks are marked as shown in FIG. 6 .

Other steps in this embodiment are similar to those in the foregoing embodiments, and will not be repeated in this embodiment.

The breathing monitoring method provided in this embodiment can quickly determine the position of the peak according to the voltage value of the sampling point for analyzing the breathing signal.

As shown in Fig. 6, on the basis of the above-mentioned embodiment, in the method of breathing monitoring provided by another embodiment of the present invention, two adjacent peaks include a sampling point with a smaller voltage value and a sampling point with a larger voltage value, corresponding Specifically, after the step of initially determining the current sampling point as the position of the peak, the method also includes:

If the interval between adjacent peaks is smaller than the first threshold, the sampling point with a larger voltage value is used as the peak.

Optionally, the initially obtained peak may not be the position of the sampling point of the actual waveform peak, for example, the peak near the 100th sampling point, because there are two sampling points satisfying curData-preData>0 and curData-nextData>0 , the positions of the two peaks are marked, but it can be clearly seen from Figure 6 that there is only one peak near the 100th sampling point.

In the embodiment of the present invention, the initially determined peaks may be screened from the perspective of the abscissa of the waveform of the respiratory signal: time, so as to exclude abnormal sampling points.

If the interval between two peaks is smaller than the first threshold, the sampling point with a large voltage value is used as a peak, and the sampling point with a relatively small voltage value is no longer used as a peak.

Optionally, the interval between two peaks represents the interval between two breaths, and the first threshold can be set according to actual conditions, for example, 1.5 seconds. The human body is unlikely to take two breaths within 1.5 seconds, and one of the peaks is a misjudgment, and it should not be regarded as a peak.

Taking the sampling frequency as 100Hz as an example, compare two peaks. If the number of sampling points between the two peaks is less than 150, select the sampling point with a large voltage value as the peak, and use the sampling point with a relatively small voltage value as the peak. crest.

If the number of sampling points between two peaks is not less than 150, both peaks are regarded as peaks.

Optionally, after screening, the wave peaks as shown in Figure 5 can be obtained. For the filtered peaks, the interval between adjacent peaks is calculated, and then the average breathing interval is obtained according to the multiple intervals, so that the breathing frequency can be accurately obtained.

Other steps in this embodiment are similar to those in the foregoing embodiments, and will not be repeated in this embodiment.

The respiratory monitoring method provided in this embodiment screens the peaks initially determined from the perspective of time, and can accurately calculate the respiratory rate according to the screened peaks.

As shown in Fig. 6, on the basis of the above-mentioned embodiment, in the method of breathing monitoring provided by another embodiment of the present invention, two adjacent peaks include a sampling point with a smaller voltage value and a sampling point with a larger voltage value, corresponding Specifically, after the step of initially determining the current sampling point as the position of the peak, the method also includes:

If the peak parameter is less than the second threshold, then use the sampling point with a larger voltage value as the peak;

The peak parameter λ is calculated according to the following formula:

λ=(smallPeak-Valley)/(largePeak-Valley)

In the formula, smallPeak is the voltage value of the sampling point with a smaller voltage value among two adjacent peaks, largePeak is the voltage value of the sampling point with a larger voltage value, and Valley is the minimum sampling point between two adjacent peaks. Voltage value.

Optionally, the preliminarily obtained peak may not be the position of the sampling point of the actual waveform peak, for example, the 300th sampling point close to the trough is also preliminarily determined as curData-preData>0 and curData-nextData>0. The peak, but it can be clearly seen from Figure 6 that the 300th sampling point is obviously not a peak, but close to the trough. The sampling points initially determined as peaks can be screened from the angle of the ordinate of the waveform: the peak to exclude abnormal sampling points.

Define the peak parameter λ, compare λ with the second threshold, if it is smaller than the second threshold, the sampling point with a larger voltage value will be regarded as a peak, and the sampling point with a smaller voltage value will no longer be regarded as a peak.

If λ is not less than a second threshold, two adjacent peaks are indeed peaks,

Optionally, the second threshold can be set according to actual conditions, for example, 0.35.

λ=(smallPeak-Valley)/(largePeak-Valley), the numerator of λ is the voltage difference between smallPeak and the voltage value of the valley, and the denominator is the voltage difference between largePeak and the voltage value of the valley.

If λ is less than 0.35, it means that the numerator is relatively small relative to the denominator, and the voltage difference between smallPeak and the valley voltage is very small, so the sampling point corresponding to smallPeak should not be used as a peak.

If λ is greater than or equal to 0.35, both peaks are preserved.

Optionally, after screening, the wave peaks shown in Figure 5 are obtained. For the filtered peaks, the interval between adjacent peaks is calculated, and then the average breathing interval is obtained based on the multiple intervals, so that the breathing frequency can be accurately calculated.

Other steps in this embodiment are similar to those in the foregoing embodiments, and will not be repeated in this embodiment.

The respiratory monitoring method provided in this embodiment screens the initially determined peaks from the perspective of peaks, and can accurately calculate the respiratory rate according to the screened peaks.

On the basis of the above-mentioned embodiments, another embodiment of the present invention provides a breathing monitoring method. After the processor calculates the breathing frequency according to the breathing signal, the method further includes:

When the respiratory rate is lower than the lower limit or exceeds the upper limit, an alarm message is sent to the remote device.

Optionally, the processor compares the respiratory rate with preset upper and lower thresholds, and when the respiratory rate is abnormal, an alarm is automatically triggered and an alarm message is sent to the remote device through the network.

There are two cases of abnormal respiratory rate, one is that the respiratory rate is lower than the lower limit, and the other is that the respiratory rate exceeds the upper limit, either of which is an abnormal respiratory rate and triggers an alarm.

The lower limit and upper limit can be set according to the health condition of the user.

The remote device is the remote device corresponding to the respiratory monitoring device. The remote device can be the terminal of the user's family members or the monitoring platform of the health institution, so as to monitor the health and safety of the elderly at home.

Other steps in this embodiment are similar to those in the foregoing embodiments, and will not be repeated in this embodiment.

In the respiratory monitoring method provided in this embodiment, when the respiratory rate is lower than the lower limit or exceeds the upper limit, an alarm message is sent to the remote device to realize remote health monitoring.

In order to fully understand the technical content of the present invention, on the basis of the above-mentioned embodiments, the breathing monitoring method provided in this embodiment will be described in detail.

Aiming at the defects of the prior art, the embodiment of the present invention provides a non-contact and non-disturbance breathing monitoring method suitable for remote monitoring, which realizes real-time monitoring of the breathing of the human body during bed rest, and provides an automatic alarm function for abnormalities, which can realize Elderly health and safety monitoring.

Utilize new technologies such as the Internet of Things and information communication to realize remote home health monitoring and improve the level of health services for the elderly in my country.

Basic principles of respiratory monitoring:

An embodiment of the present invention provides a breathing monitoring device as shown in FIG. 4 . The piezoelectric ceramic sensor 1 senses the pressure change signal of the human body, obtains breathing information through signal processing technology, and realizes long-term monitoring of breathing in a bedridden state.

Optionally, the piezoelectric ceramic sensor 1 senses the change of pressure, and the pressure sensing belt 2 can play the role of fixing the piezoelectric ceramic sensor 1, and the signal line 3 transmits the original signal of the piezoelectric ceramic sensor 1 to the processor 4 for processing The device 4 processes the original signal and provides a reference voltage of +1.5V for the piezoelectric ceramic sensor 1 .

The respiration measurement method is as follows:

Fig. 7 is a schematic flow chart of a breathing monitoring method according to another embodiment of the present invention.

As shown in Figure 7, the piezoelectric ceramic sensor collects multiple original signals, and after the steps of signal amplification, AD (analog-to-digital) sampling, selection of the best signal channel, and signal processing, the respiratory frequency is finally obtained.

Step 1: Signal Acquisition

When a person breathes, the abdominal cavity will rise and fall, resulting in different pressure values on the piezoelectric ceramic sensor, and these pressure values are the original breathing signals. At the same time, the human heartbeat will also have a similar effect. In fact, the heartbeat signal is superimposed on the original breathing signal, which interferes with the breathing signal, as shown in Figure 3.

Step 2: Signal Amplification

Since the signal collected by the piezoelectric ceramic sensor is very weak, in order to extract the useful signal, it needs to be amplified. The signal amplification is completed by the operational amplifier. Considering that the amplification factor is too high and overflow will occur, the amplification factor here is 10 times.

Step 3: AD sampling

AD sampling is performed on multiple amplified original respiratory signals. Under the condition of satisfying the sampling theorem, considering the data storage space and computational complexity, the sampling frequency is set to 100Hz.

Step 4: Choose the Best Signal Channel

Everyone's sleeping posture is different, and the sleeping position is also different. Using multiple piezoelectric ceramic sensors can increase the scope of respiratory monitoring. Multiple sensors can reflect the human breathing situation. When performing signal processing, it is only necessary to analyze the original signal of one sensor. Actual observations have found that the energy of the sensor signal directly under the human body is often greater than that of other sensors. By calculating the energy of all sensor signals, the signal with the highest energy is selected to calculate the respiratory rate.

Step 5: Signal Processing

Signal processing is to obtain the respiratory rate, the process is as follows:

(1) Bandpass filtering

Because the breathing rate is generally between 6 times/min and 42 times/min, the band-pass filter is designed as an 80-order FIR band-pass filter, and the specific parameters are Fstop1=0.08; Fpass1=0.1; Fpass2=0.5; Fstop2= 0.7; Eliminate the influence of other signals on the respiratory waveform. After the original signal is filtered, the waveform diagram of the respiratory signal is obtained, as shown in Figure 2.

(2) Obtain the peak interval of respiratory waveform

The time interval between peaks is the key to calculating the respiration rate. The calculation process is as follows: record the current data point as curData, the previous data point as preData, and the next data point as nextData. When curData-preData>0 and curData-nextData>0 are satisfied, it means that the current data is the peak value. Peak markers are shown in Figure 6.

(3) Exclusion of outliers

The elimination of outliers is mainly completed in two steps:

Step 1: If the time interval between two peaks is less than 1.5 seconds, select the maximum value between the two peaks and delete the smaller one.

Step 2: Define the parameter λ. The smaller of any two adjacent peaks is recorded as smallPeak, the larger one is largePeak, and the minimum value between the two peaks is Valley. The formula is as follows.

λ=(smallPeak-Valley)/(largePeak-Valley)

If λ is greater than 0.35, both peaks are retained, otherwise, the smaller peak is deleted.

After completing the above two steps, it can ensure that the calculation of the breathing rate has a relatively high accuracy, as shown in Figure 5.

(4) Calculation of respiratory rate

From Figure 5, several respiratory peak intervals are obtained, and these respiratory intervals are averaged Y _i is the breathing interval (represented by sampling points), and n is the total number of breathing intervals. Assuming the sampling frequency is f, the respiration rate is: times/min.

Piezoelectric ceramic sensor collects multi-channel original respiratory signals, after signal amplification, AD (analog-to-digital) sampling, selection of the best signal channel, waveform processing of respiratory signals (including filtering, signal smoothing, respiratory peak-to-peak interval and respiratory value calculation), etc. After the steps, the respiration rate is finally obtained, realizing long-term monitoring of respiration in a bedridden state.

The embodiment of the present invention provides a non-contact and non-disturbance breathing monitoring method and device suitable for remote monitoring, which realizes real-time monitoring of human breathing during bed rest, and provides an automatic alarm function for abnormalities, which can realize the health and safety of the elderly at home guardianship.

Fig. 8 is a schematic structural diagram of a breathing monitoring device according to another embodiment of the present invention.

Referring to FIG. 8, on the basis of the above-mentioned embodiments, the device for allocating physical cell identities provided by this embodiment includes a receiving module 81, a processing module 82, and a computing module 83, wherein:

The receiving module 81 is used to receive the original signal sent by the pressure sensor belt, and the original signal includes the pressure value of the bedding; the processing module 82 is used to perform analog conversion and digital AD sampling processing on the original signal to obtain a breathing signal; the calculation module 83 is used for calculating the respiratory frequency according to the respiratory signal.

Optionally, the pressure sensing belt is arranged under the bedding, which is a device for a human body to lie on, such as a mattress.

Optionally, the pressure sensing belt may not be in direct contact with the human body, but may also measure the respiratory frequency. In the embodiment of the present invention, it is described by setting it under the mattress as an example.

Optionally, the pressure sensing belt includes at least one pressure transducer (Pressure Transducer), which is used to sense pressure changes and convert pressure changes into original signals.

Optionally, the pressure sensor can be realized by a piezoelectric ceramic sensor.

Optionally, when a person breathes, the abdominal cavity will rise and fall, resulting in different pressure values on the mattress, and the pressure sensor can obtain the original signal according to the pressure change value.

The pressure sensing belt sends the original signal detected by the piezoelectric ceramic sensor to the processor. After the processor receives the original signal, it can realize the analysis and processing function of the original signal and provide +1.5V for the pressure sensor. The reference voltage.

Optionally, the processing module 82 includes an operational amplifier and an AD (analog to digital, analog to digital) module.

Optionally, since the original signal collected by the pressure sensor may be very weak, it needs to be amplified to clarify the waveform of the original signal and determine the positions of the peaks and troughs.

Optionally, an operational amplifier is used to amplify the signal. Considering overflow will occur if the amplification factor is too high, the amplification factor can be set to 10 times.

Optionally, the AD module performs AD sampling on the amplified original signal.

Optionally, the original signal is an analog signal, and the AD sampling is to convert the analog signal into a digital signal, and then set the sampling frequency.

Optionally, the sampling frequency refers to how many sampling points are collected per second.

Optionally, several sampling points are selected from the digital signal (original signal), and the selected sampling points form a sampling signal.

Optionally, under the condition that the sampling theorem is satisfied, and considering the data storage space and computational complexity, the embodiment of the present invention sets the sampling frequency to 100 Hz (collecting 100 sampling points in 1 second).

Optionally, the sampling theorem describes the relationship between the sampling frequency and the digital signal, which is the basic basis for the discretization of the continuous signal. The sampling theorem is that when the sampling frequency is greater than twice the highest frequency in the digital signal, the sampling signal completely retains the information in the digital signal.

Optionally, the original signal collected by the pressure sensor may contain noise, and the sampled signal may be denoised to obtain a breathing signal reflecting the heartbeat.

As shown in Figure 2, the respiratory signal describes the voltage variation of each sampling point over time. The abscissa is the number of sampling points, and the ordinate is the voltage (v). The unit directly detected by the pressure sensor is mv, and after being amplified by the operational amplifier, the unit is v.

Optionally, 100 sampling points are collected in 1 second, and the calculation module 83 uses the sampling points (60*100) collected in 1 minute as a unit to check how many peaks there are in each unit, and a peak is recorded as a breath, and each Minute respiratory rate is the number of peaks in one unit.

Using the pressure sensing belt of the embodiment of the present invention, the pressure sensor belt detects the pressure value of the bedding, rather than directly contacting the human body, so the detection is performed without restraining the human body, and the original signal is obtained, which is further processed by the processing module 82 signal processing, the calculation module 83 finally obtains the respiratory rate, and realizes long-term monitoring of human health in a natural sleep state.

The original signal can be obtained by detecting the pressure value of the bedding with the respiration monitoring device. The respiration monitoring device has low cost and is easy to use.

The breathing monitoring device provided in this embodiment can be used to implement the methods in the above method embodiments, and details will not be repeated in this embodiment.

The respiratory monitoring device provided in this embodiment can collect the original signal without contacting the human body by receiving the original signal sent by the pressure sensor belt and carrying the pressure value of the bedding, and the calculation module calculates the respiratory rate according to the original signal. Frequency, so that respiratory monitoring is economical and convenient.

Fig. 9 shows a schematic structural diagram of an electronic device provided by another embodiment of the present invention.

Referring to FIG. 9 , an electronic device provided by an embodiment of the present invention includes a memory (memory) 91, a processor (processor) 92, a bus 93, and a computer program stored in the memory 91 and operable on the processor. Wherein, the memory 91 and the processor 92 communicate with each other through the bus 93 .

The processor 92 is configured to call the program instructions in the memory 91 to implement the method as shown in FIG. 1 when executing the program.

In another implementation manner, the processor implements the following method when executing the program:

The original signal includes a respiration signal and a heartbeat signal. Correspondingly, the original signal is subjected to analog conversion and digital AD sampling processing, and the steps for obtaining the respiration signal are specifically:

performing band-pass filtering on the original signal to eliminate the heartbeat signal to obtain the respiration signal.

In another embodiment, when the processor executes the program, the following method is implemented: the pressure sensing belt includes a plurality of pressure sensors, and each pressure sensor detects the pressure value of a region of the bedding, and obtains a corresponding Original signal; Correspondingly, the analog conversion digital AD sampling process is carried out to described original signal, and the step of obtaining respiratory signal is specifically as follows:

The processor calculates the energy of each original signal according to the plurality of original signals;

According to the original signal with the largest energy among the original signals, AD sampling processing is performed to obtain the breathing signal.

In another embodiment, when the processor executes the program, the following method is realized: the step of calculating the respiratory frequency by the processor according to the respiratory signal is specifically:

Calculate the interval between adjacent peaks according to the positions of adjacent peaks of the respiratory signal:

According to multiple intervals, the average breathing interval is obtained;

According to the average breathing interval and the preset sampling frequency, the breathing frequency is obtained.

In another embodiment, when the processor executes the program, the following method is implemented: before the step of calculating the interval between adjacent peaks according to the positions of the adjacent peaks of the respiratory signal, the method further includes:

Note that the voltage value of the current sampling point is curData, the voltage value of the previous sampling point of the current sampling point is preData, and the voltage value of the next sampling point of the current sampling point is nextData;

If curData-preData>0 and curData-nextData>0, the current sampling point is preliminarily determined as the peak position.

In another embodiment, when the processor executes the program, the following method is implemented: two adjacent peaks include a sampling point with a smaller voltage value and a sampling point with a larger voltage value, and correspondingly, the current sampling point After the step of initially determining the location of the peak, the method further includes:

If the interval between adjacent peaks is smaller than the first threshold, the sampling point with a larger voltage value is used as the peak;

and / or,

If the peak parameter is less than the second threshold, then use the sampling point with a larger voltage value as the peak;

The peak parameter λ is calculated according to the following formula:

λ=(smallPeak-Valley)/(largePeak-Valley)

In the formula, smallPeak is the voltage value of the sampling point with a smaller voltage value among two adjacent peaks, largePeak is the voltage value of the sampling point with a larger voltage value, and Valley is the minimum sampling point between two adjacent peaks. Voltage value.

In another embodiment, when the processor executes the program, the following method is implemented: after the step of calculating the respiratory frequency by the processor according to the respiratory signal, the method further includes:

When the respiratory rate is lower than the lower limit or exceeds the upper limit, an alarm message is sent to the remote device.

The electronic device provided in this embodiment can be used to execute the program corresponding to the method in the above method embodiment, and details will not be described in this embodiment.

The electronic device provided in this embodiment, when the processor executes the program, receives the original signal sent by the pressure sensor belt and carries the pressure value of the bedding, and obtains the respiratory rate according to the original signal, which can be achieved without touching the human body. In the case of the original signal acquisition, it is economical and convenient to carry out respiratory monitoring.

Another embodiment of the present invention provides a storage medium, where a computer program is stored on the storage medium, and when the program is executed by a processor, the steps shown in FIG. 1 are implemented.

In another implementation manner, when the program is executed by the processor, the following methods are implemented:

The original signal includes a respiration signal and a heartbeat signal. Correspondingly, the original signal is subjected to analog conversion and digital AD sampling processing, and the steps for obtaining the respiration signal are specifically:

performing band-pass filtering on the original signal to eliminate the heartbeat signal to obtain the respiration signal.

In another implementation manner, when the program is executed by the processor, the following methods are implemented:

The pressure sensing belt includes a plurality of pressure sensors, and each pressure sensor detects the pressure value borne by a region of the bedding, correspondingly obtaining an original signal; correspondingly, performing analog conversion and digital AD sampling processing on the original signal to obtain a breathing The specific steps of the signal are:

The processor calculates the energy of each original signal according to the plurality of original signals;

According to the original signal with the largest energy among the original signals, AD sampling processing is performed to obtain the breathing signal.

In another implementation manner, when the program is executed by the processor, the following methods are implemented:

The steps for the processor to calculate the respiratory frequency according to the respiratory signal are as follows:

Calculate the interval between adjacent peaks according to the positions of adjacent peaks of the respiratory signal:

According to multiple intervals, the average breathing interval is obtained;

According to the average breathing interval and the preset sampling frequency, the breathing frequency is obtained.

In another implementation manner, when the program is executed by the processor, the following methods are implemented:

Before the step of calculating the interval between adjacent peaks according to the positions of adjacent peaks of the respiratory signal, the method further includes:

Note that the voltage value of the current sampling point is curData, the voltage value of the previous sampling point of the current sampling point is preData, and the voltage value of the next sampling point of the current sampling point is nextData;

If curData-preData>0 and curData-nextData>0, the current sampling point is preliminarily determined as the peak position.

In another implementation manner, when the program is executed by the processor, the following methods are implemented:

Two adjacent peaks include a sampling point with a smaller voltage value and a sampling point with a larger voltage value. Correspondingly, after the step of initially determining the current sampling point as the position of the peak, the method further includes:

If the interval between adjacent peaks is smaller than the first threshold, the sampling point with a larger voltage value is used as the peak;

and / or,

If the peak parameter is less than the second threshold, then use the sampling point with a larger voltage value as the peak;

The peak parameter λ is calculated according to the following formula:

λ=(smallPeak-Valley)/(largePeak-Valley)

In the formula, smallPeak is the voltage value of the sampling point with a smaller voltage value among two adjacent peaks, largePeak is the voltage value of the sampling point with a larger voltage value, and Valley is the minimum sampling point between two adjacent peaks. Voltage value.

In another implementation manner, when the program is executed by the processor, the following methods are implemented:

After the step of calculating the respiratory rate by the processor according to the respiratory signal, the method further includes:

When the respiratory rate is lower than the lower limit or exceeds the upper limit, an alarm message is sent to the remote device.

The storage medium provided in this embodiment implements the method in the foregoing method embodiment when the program is executed by a processor, which will not be repeated in this embodiment.

The storage medium provided in this embodiment can collect the original signal without contacting the human body by receiving the original signal carrying the pressure value of the bedding sent by the pressure sensor belt, and obtaining the respiratory rate according to the original signal. Economical and convenient respiratory monitoring.

Yet another embodiment of the present invention discloses a computer program product, the computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program includes program instructions, and when the program instructions are executed by a computer When, the computer can execute the method provided by the above method embodiments, for example including:

Receive the original signal sent by the pressure sensor belt, the original signal includes the pressure value of the bedding;

Carrying out analog conversion and digital AD sampling processing on the original signal to obtain a respiratory signal;

From the respiration signal, a respiration rate is calculated.

Those skilled in the art will understand that although some embodiments described herein include some features included in other embodiments but not others, combinations of features from different embodiments are meant to be within the scope of the invention And form different embodiments.

Those skilled in the art can understand that each step in the embodiment can be realized by hardware, or by a software module running on one or more processors, or by a combination thereof. Those skilled in the art should understand that a microprocessor or a digital signal processor (DSP) may be used in practice to implement some or all functions of some or all components according to the embodiments of the present invention. The present invention can also be implemented as an apparatus or an apparatus program (for example, a computer program and a computer program product) for performing a part or all of the methods described herein.

Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention. within the bounds of the requirements.

Claims (10)

1. A method of respiratory monitoring, the method comprising:

receiving an original signal sent by a pressure sensing belt, wherein the original signal comprises a pressure value born by bedding;

carrying out analog conversion digital AD sampling processing on the original signal to obtain a respiratory signal;

and calculating the respiratory frequency according to the respiratory signal.

2. The method of claim 1, wherein: the original signal comprises a respiration signal and a heartbeat signal, correspondingly, analog-to-digital AD sampling processing is carried out on the original signal, and the steps of obtaining the respiration signal are specifically as follows:

and performing band-pass filtering on the original signal, and eliminating heartbeat signals to obtain the respiration signals.

3. The method of claim 1, wherein: the pressure sensing belt comprises a plurality of pressure sensors, and each pressure sensor detects a pressure value borne by one area of the bedding to correspondingly obtain an original signal; correspondingly, the step of performing analog-to-digital (AD) sampling processing on the original signal to obtain the respiratory signal specifically comprises the following steps:

the processor calculates the energy of each original signal according to a plurality of original signals;

and carrying out AD sampling processing according to the original signal with the maximum energy in the original signals to obtain the respiratory signal.

4. The method of claim 1, wherein the step of calculating the breathing rate from the breathing signal by the processor is specifically:

calculating the interval of adjacent peaks according to the positions of the adjacent peaks of the respiratory signal:

obtaining an average breathing interval according to a plurality of intervals;

and obtaining the respiratory frequency according to the average respiratory interval and the preset sampling frequency.

5. The method of claim 4, wherein the step of calculating the spacing of adjacent peaks of the respiration signal is preceded by the step of:

recording the voltage value of the current sampling point as curData, the voltage value of the previous sampling point of the current sampling point as preData, and the voltage value of the next sampling point of the current sampling point as nextData;

if curData-preData >0 and curData-nextData >0, then the current sample point is initially determined to be the location of the peak.

6. The method according to claim 5, wherein two adjacent peaks include a sampling point having a smaller voltage value and a sampling point having a larger voltage value, and accordingly, after the step of preliminarily determining the current sampling point as the position of the peak, the method further comprises:

if the interval between adjacent wave crests is smaller than a first threshold value, taking a sampling point with a larger voltage value as a wave crest;

and/or the presence of a gas in the gas,

if the peak value parameter is smaller than the second threshold value, taking the sampling point with the larger voltage value as a peak;

the peak parameter λ is calculated according to the following formula:

λ＝(smallPeak-Valley)/(largePeak-Valley)

in the formula, smallPeak is a voltage value of a sampling point with a smaller voltage value in two adjacent wave crests, largePeak is a voltage value of a sampling point with a larger voltage value, and Valley is a voltage value of a minimum sampling point between the two adjacent wave crests.

7. The method of claim 1, wherein: after the step of calculating the breathing frequency by the processor from the breathing signal, the method further comprises:

and when the respiratory frequency is lower than the lower limit or exceeds the upper limit, sending an alarm message to the remote equipment.

8. A respiratory monitoring device, the device comprising:

the receiving module is used for receiving an original signal sent by the pressure sensing belt, and the original signal comprises a pressure value born by bedding;

the processing module is used for carrying out analog-to-digital AD sampling processing on the original signal to obtain a respiratory signal;

and the calculation module is used for calculating the respiratory frequency according to the respiratory signal.

9. An electronic device comprising a memory, a processor, a bus and a computer program stored on the memory and executable on the processor, the processor implementing the steps of any of claims 1-7 when executing the program.

10. A storage medium having a computer program stored thereon, characterized in that: the program when executed by a processor implementing the steps of any of claims 1 to 7.