Impedance respiration detection device and respiration detection equipment

Abstract

The invention discloses an impedance respiration detection device and respiration detection equipment, and relates to the field of respiration detection.The impedance respiration detection device comprises the steps that a data acquisition module obtains a thoracic cavity impedance signal; the first filtering module controls a high-pass filter to filter the thoracic impedance signal by adopting a first cut-off frequency to obtain first target data; wherein the first cut-off frequency is smaller than the lower limit of the breathing effective frequency band, and the high-pass filter is of a recursive structure; the first judgment module judges whether the first target data is greater than a preset threshold; if not, determining a current impedance respiration curve through a curve generation module based on the first target data; if yes, controlling a high-pass filter to adopt a second cut-off frequency through a second filtering module to obtain second target data; wherein the second cut-off frequency is greater than the upper limit of the breathing effective frequency band; a second judgment module judges whether the second target data meets a preset threshold value requirement or not; if yes, triggering a first filtering module; and if not, continuously judging. Therefore, the impedance respiration curve can be quickly displayed or recovered.

Description

Technical Field

[0001] The present invention relates to the field of breathing detection, and in particular to an impedance breathing detection device and breathing detection equipment. Background Art

[0002] In clinical medicine, respiratory monitoring is one of the important means to assess the health status of patients. Since the volume changes of the chest and abdomen during breathing will cause corresponding changes in electrical impedance, respiratory monitoring can be achieved by measuring the changes in human bioimpedance. However, since the patient's chest itself has base impedance, the impedance changes caused by breathing fluctuate up and down with the base impedance as the baseline, and are very small compared to the base impedance. Therefore, the baseline voltage generated by the base impedance needs to be filtered through a high-pass filter to clearly reflect the impedance breathing curve.

[0003] In the prior art, a high-pass filter with a fixed cutoff frequency is used for baseline filtering. However, due to the great differences in base impedance among different patients, and factors such as the fit between the electrode and the skin and body movement will affect the base impedance, the impedance breathing curve cannot be displayed or restored quickly.

[0004] Therefore, how to quickly display or restore the impedance respiration curve is a problem that needs to be solved urgently. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide an impedance respiration detection device for quickly displaying or restoring an impedance respiration curve. The specific scheme is as follows:

[0006] In order to solve the above technical problems, the present application provides an impedance breathing detection device, comprising:

[0007] A data acquisition module, used for acquiring chest impedance signals;

[0008] A first filtering module, used for controlling a high-pass filter to filter the chest impedance signal with a first cutoff frequency to obtain first target data; wherein the first cutoff frequency is less than a lower limit of a breathing effective frequency band, and the high-pass filter has a recursive structure;

[0009] A first judging module, used to judge whether the first target data is greater than a preset threshold;

[0010] A curve generating module, used for determining a current impedance breathing curve based on the first target data when the result of the first judging module is no;

[0011] A second filtering module, configured to control the high-pass filter to adopt a second cutoff frequency to obtain second target data when the result of the first judging module is yes; wherein the second cutoff frequency is greater than an upper limit of the effective frequency band of the breathing;

[0012] The second judgment module is used to judge whether the second target data is less than the preset threshold; if so, trigger the first filtering module; if not, continue to judge.

[0013] As an optional solution, the impedance respiration detection device further includes a gain adjustment module, which is used to determine the gain of the impedance respiration curve based on the amplitude of the impedance respiration curve and the amplitude of an ideal curve.

[0014] As an optional solution, in the above-mentioned impedance respiration detection device, it is specifically used to calculate the ratio K of the amplitude of the impedance respiration curve to the amplitude of the ideal curve when the amplitude of the impedance respiration curve exceeds the preset range of the ideal curve amplitude, and determine the gain to be 1 / K.

[0015] As an optional solution, the above impedance breathing detection device also includes a driving module for outputting a high-frequency current of a preset frequency to generate a high-frequency carrier signal.

[0016] As an optional solution, in the above impedance breathing detection device, the data acquisition module is specifically used to obtain the high-frequency carrier signal, and based on the high-frequency carrier signal, obtain the chest impedance signal.

[0017] As an optional solution, the above impedance respiration detection device also includes a display module to display the impedance respiration curve.

[0018] As an optional solution, the above impedance respiration detection device also includes a heart rate acquisition module for collecting electrocardiogram signals to obtain the current heart rate.

[0019] As an optional solution, the above-mentioned impedance respiration detection device also includes a validity judgment module, which is used to determine the minimum valid threshold based on the current heart rate; judge whether the amplitude of the impedance respiration curve is greater than the minimum valid threshold; if so, determine that the impedance respiration curve is a valid respiration curve.

[0020] As an optional scheme, in the above-mentioned impedance breathing detection device, the effectiveness judgment module is specifically used to determine that the minimum effective threshold is the first minimum effective threshold when the current heart rate is less than or equal to 90 times / minute; when the current heart rate is greater than 90 times / minute and less than or equal to 120, determine the minimum effective threshold as the second minimum effective threshold; when the current heart rate is greater than 120 times / minute, determine the minimum effective threshold as the third minimum effective threshold.

[0021] In order to solve the above technical problems, the present application also provides a breathing detection device, including the above impedance breathing detection device.

[0022] As can be seen from the above, after the chest impedance signal is obtained by the data acquisition module, the high-pass filter is first controlled by the first filtering module to filter the chest impedance signal with the first cut-off frequency to obtain the first target data, and the corresponding impedance breathing curve diagram is generated in the curve generation module according to the above first target data. At the same time, in the first judgment module, it is monitored in real time whether the generated first target data has a part exceeding the preset threshold value. When the first target data exceeding the preset threshold value is detected, the cut-off frequency of the high-pass filter needs to be set to the second cut-off frequency by the second filtering module, and the second target data is filtered and generated. Since the second cut-off frequency is higher than the upper limit of the effective frequency band of breathing, the base impedance voltage generated by the larger base impedance can be quickly filtered. Therefore, whether the base impedance itself is too large, or the base impedance increases due to the influence factors such as the electrode falling off and moving or the accidental disturbance of the electrode by the outside world, the second cut-off frequency can be selected to quickly filter the excessive base impedance, and when the second target data is detected to be not greater than the preset threshold value, the cut-off frequency is adjusted back to the first cut-off frequency again, and the chest impedance signal is filtered by the first filtering module. That is, the size of the high-pass filter cut-off frequency can be flexibly adjusted based on the actual generated target data, so that the impedance breathing curve can be quickly generated or restored under different circumstances. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0024] Figure 1 A schematic diagram of an impedance breathing detection device disclosed in the present application;

[0025] Figure 2 The adaptive filtering and gain adjustment flow chart disclosed in this application;

[0026] Figure 3 An original impedance respiration curve provided for this application;

[0027] Figure 4 An impedance respiration curve with a filtered baseline provided for this application;

[0028] Figure 5 A comparison chart of filtering speed using a fixed cutoff frequency and an adaptive filtering frequency baseline filtering provided in the present application;

[0029] Figure 6 An impedance breathing curve with too small gain provided for this application;

[0030] Figure 7 An impedance breathing curve with excessive gain is provided for this application. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] In clinical medicine, respiratory monitoring is one of the important means to assess the health status of patients. Since the volume changes of the chest and abdomen during breathing will cause corresponding changes in electrical impedance, respiratory monitoring can be achieved by measuring the changes in human bioimpedance. However, since the patient's chest itself has base impedance, the impedance changes caused by breathing fluctuate up and down with the base impedance as the baseline, and are very small compared to the base impedance. Therefore, the baseline voltage generated by the base impedance needs to be filtered through a high-pass filter to clearly reflect the impedance breathing curve.

[0033] In the prior art, a high-pass filter with a fixed cutoff frequency is used for baseline filtering. However, due to the great differences in base impedance among different patients, and factors such as the fit between the electrode and the skin and body movement will affect the base impedance, the impedance breathing curve cannot be displayed or restored quickly.

[0034] To this end, the present application provides an impedance respiration detection device to quickly display or restore an impedance respiration curve.

[0035] See also Figure 1 , Figure 2 As shown, an embodiment of the present invention discloses an impedance breathing detection device, comprising:

[0036] A data acquisition module, used for acquiring chest impedance signals;

[0037] A first filtering module is used to control a high-pass filter to filter the chest impedance signal using a first cutoff frequency to obtain first target data; wherein the first cutoff frequency is less than a lower limit of a breathing effective frequency band, and the high-pass filter has a recursive structure;

[0038] A first judging module, used to judge whether the first target data is greater than a preset threshold;

[0039] A curve generating module, used for determining a current impedance breathing curve based on the first target data when the result of the first judging module is no;

[0040] A second filtering module, for controlling the high-pass filter to adopt a second cutoff frequency to obtain second target data when the result of the first judging module is yes; wherein the second cutoff frequency is greater than the upper limit of the effective frequency band of breathing;

[0041] The second judgment module is used to judge whether the second target data is less than a preset threshold; if so, the first filtering module is triggered; if not, the judgment is continued.

[0042] In this embodiment, the data acquisition module is used to collect the chest impedance signal of the object to be detected. Figure 1 As shown, the data acquisition module can collect the voltage difference generated by the high-frequency current by separately setting a pair of patch electrodes, and further process the voltage difference as the above-mentioned chest impedance signal. It can be understood that, if Figure 2 As shown, after the system is initialized, it can be determined whether to trigger the first filtering module by detecting whether the electrode is in a detached state.

[0043] In addition, in addition to collecting chest impedance signals through the above-mentioned patch electrodes, chest impedance signals can also be obtained through wearable devices made of flexible electrode materials. Due to the soft characteristics of the flexible electrode material, it can fit better during use and reduce noise caused by poor contact.

[0044] It is understandable that the respiratory activity of the lungs will affect the impedance of the chest cavity. When inhaling, the lungs are filled and the air content increases, at which time the chest cavity impedance increases; when exhaling, the lungs contract and the air content decreases, at which time the chest cavity impedance decreases. The change in impedance will further lead to a change in the voltage difference, so the processed voltage difference can be used as a chest cavity impedance signal to reflect the respiratory condition.

[0045] Furthermore, due to the existence of the base impedance, the impedance change reflecting the respiratory condition fluctuates up and down based on the base impedance, and the impedance change is very small compared with the base impedance, such as Figure 3 The original impedance respiration curve and Figure 4 If the baseline voltage generated by the base impedance is not filtered, the impedance respiration curve obtained will have a small change range and cannot directly reflect the respiratory status. Therefore, the chest impedance signal obtained above needs to be filtered through a high-pass filter module.

[0046] In this embodiment, Figure 5 As shown, the upper figure uses a fixed cutoff frequency for fundamental wave filtering, and the fundamental wave filtering speed is slow, while the lower figure uses an adaptive cutoff frequency for fundamental wave voltage filtering. When the impedance target curve is above the threshold line, a higher cutoff frequency is used, and when it is below the threshold line, a lower cutoff frequency is used, which can speed up the fundamental wave filtering speed.

[0047] Therefore, in order to achieve rapid filtering of the base impedance in various impedance breathing curves, the high-pass filter module may include a first filter module, a second filter module, a first judgment module and a second judgment module. The first filter module filters the chest impedance signal at a first cutoff frequency, and the second filter module filters the chest impedance signal at a second cutoff frequency. The first cutoff frequency can be used as the default cutoff frequency of the high-pass filter in the high-pass filter module. After receiving the chest impedance signal acquired by the data acquisition module, the first filter module is first triggered and filtered using the first cutoff frequency to obtain the first target data.

[0048] It should be noted that the high-pass filter in the above-mentioned high-pass filter module needs to have a recursive structure, which can "memorize" and accumulate the signal during the filtering process, so that the output of the high-pass filter is not only related to the current input, but also to the past input and output. Therefore, when the high-pass filter quickly filters the reference voltage generated by the base impedance through the second cutoff frequency that is much larger than the upper limit of the breathing effective frequency band, the state inside the high-pass filter has changed. After the cutoff frequency is adjusted, the high-pass filter will continue to process the reference voltage based on the previous state and the current input. This cumulative effect will cause the reference voltage to be gradually weakened after multiple filtering until it is completely filtered. In a specific embodiment, an existing IIR digital filter can be selected. The differential equation of the IIR digital filter is:

[0049]

[0050] Among them, y(n) represents the output signal, x(n) represents the input signal, is the forward coefficient, is the feedback coefficient.

[0051] , ,……, and , ,……, They are all filter coefficients, which together determine whether the type of the IIR filter is a high-pass filter, a low-pass filter, or a high-pass filter, etc., and also determine the cutoff frequency of the filter. In this embodiment, two sets of filter coefficients are included, corresponding to the first cutoff frequency of the high-pass filter and the second cutoff frequency of the high-pass filter, respectively. The chest impedance signal is filtered by the first filter module or the second filter module, which is actually the adjustment of the filter coefficient in the high-pass filter to achieve the change of the cutoff frequency.

[0052] In another specific implementation, a digital filtering model with a recursive structure can also be constructed based on a deep learning model to implement the above filtering process.

[0053] Furthermore, since there are individual differences in base impedance, and the base impedance may increase when the electrode is disturbed by external factors, after obtaining the first target data, the first judgment module will be triggered to determine whether the current cutoff frequency can filter the fundamental voltage. If the result output by the first judgment module is no, it means that the current base impedance is too large and the cutoff frequency needs to be increased, that is, the second filter module is triggered to filter the chest impedance signal at the second cutoff frequency and obtain the second target data. It is understandable that since external interference to the electrode will also cause changes in the base impedance, the first judgment module will continue to analyze the first target data to determine whether the second filter module needs to be triggered.

[0054] It should be noted that since the first cutoff frequency is slightly lower than the lower limit of the effective breathing frequency band, and the second cutoff frequency is much larger than the upper limit of the effective breathing frequency band, from the frequency response characteristics of the high-pass filter, the higher the cutoff frequency, the steeper the attenuation slope of the low-frequency signal, that is, the signal below the cutoff frequency will be attenuated faster, including the fundamental voltage, so by filtering the chest impedance signal through the second cutoff frequency, the fundamental voltage generated by the fundamental impedance can be quickly filtered.

[0055] Furthermore, since the signal reflecting the respiratory status contains some lower-frequency detail information or slowly changing components, the use of the second cutoff frequency may mistakenly filter these components as interference signals, resulting in distortion of the final second target data, affecting the accurate analysis of the respiratory status. Therefore, after triggering the second filtering module, the second target data needs to be analyzed by the second judgment module. When it is detected that the second target data is less than the preset threshold, it means that most of the fundamental voltage has been filtered, so the first filtering module can be triggered to restore the cutoff frequency to the first cutoff frequency to ensure that the low-frequency part of the signal reflecting the respiratory status can be retained to accurately reflect the current respiratory status.

[0056] like Figure 2 As shown, when the first target data generated by the high-pass filter through the first cutoff frequency filtering cannot meet the threshold requirement, it is necessary to switch the cutoff frequency to the second cutoff frequency, that is, trigger the second filter module, filter the chest impedance signal, until the second target data generated by the filtration meets the threshold requirement, and then switch to the first cutoff frequency, that is, trigger the first filter module. It can be understood that the second target data generated by the second filter module that does not meet the threshold requirement is not returned to the high-pass filter module for secondary filtering after judgment, but is directly discarded. The chest impedance signal input to the high-pass filter module is a new chest impedance signal directly collected from the electrode. Figure 2 The target data in can be the first target data or the second target data.

[0057] As can be seen from the above, after the chest impedance signal is obtained by the data acquisition module, the high-pass filter is first controlled by the first filtering module to filter the chest impedance signal with the first cut-off frequency to obtain the first target data, and the corresponding impedance breathing curve diagram is generated in the curve generation module according to the above first target data. At the same time, in the first judgment module, it is monitored in real time whether the generated first target data has a part exceeding the preset threshold value. When the first target data exceeding the preset threshold value is detected, the cut-off frequency of the high-pass filter needs to be set to the second cut-off frequency by the second filtering module, and the second target data is filtered and generated. Since the second cut-off frequency is higher than the upper limit of the effective frequency band of breathing, the base impedance voltage generated by the larger base impedance can be quickly filtered. Therefore, whether the base impedance itself is too large, or the base impedance increases due to the influence factors such as the electrode falling off and moving or the accidental disturbance of the electrode by the outside world, the second cut-off frequency can be selected to quickly filter the excessive base impedance, and when the second target data is detected to be not greater than the preset threshold value, the cut-off frequency is adjusted back to the first cut-off frequency again, and the chest impedance signal is filtered by the first filtering module. That is, the size of the high-pass filter cut-off frequency can be flexibly adjusted based on the actual generated target data, so that the impedance breathing curve can be quickly generated or restored under different circumstances.

[0058] In order to make the obtained impedance respiration curve amplitude meet actual needs, according to the above embodiment, this embodiment provides a specific impedance respiration detection device, which also includes: a gain adjustment module, which is used to determine the gain of the impedance respiration curve based on the amplitude of the impedance respiration curve and the ideal curve amplitude.

[0059] In the present embodiment, the gain of the above-mentioned impedance breathing curve is actually the amplification multiple of the first target data. Properly increasing the gain can restore the attenuated first target data to a suitable intensity, so that the first target data can be accurately identified and processed in subsequent processing links. If the gain is not adjusted, the signal may be overwhelmed by noise because it is too weak, resulting in the inability to effectively extract useful information. It is understandable that the first target data obtained by the electrode is usually relatively weak, and after the processes of wire transmission, voltage division of circuit elements, etc., its signal strength may be further reduced, so that the first target data finally obtained cannot meet the actual needs. Therefore, the gain of the impedance breathing curve can be adjusted to achieve the above-mentioned attenuation compensation.

[0060] It is understandable that the gain is not the bigger the better, and it is also necessary to consider the actual display conditions and make reasonable adjustments, such as Figure 6 and Figure 7As shown in the figure, when the gain is too small, the amplitude of the impedance respiration curve displayed will not change significantly, and when the gain is too large, the impedance respiration curve will not be fully displayed. Therefore, the gain adjustment module can reasonably adjust the gain according to the actual amplitude of the impedance respiration curve to avoid the above situation.

[0061] It can be concluded from the above that by continuously monitoring the difference between the amplitude of the actual impedance respiration curve and the amplitude of the ideal curve and adjusting the gain of the impedance respiration curve in real time through the gain adjustment module, the obtained impedance respiration curve can meet the actual needs.

[0062] In order to make the amplitude of the obtained impedance respiration curve closer to the ideal curve amplitude, according to the above embodiment, this embodiment provides a specific impedance respiration detection device, a gain adjustment module, which is used to determine the gain of the impedance respiration curve based on the amplitude of the impedance respiration curve and the ideal curve amplitude.

[0063] In this embodiment, the gain adjustment module can monitor the amplitude of the impedance respiration curve in real time, and change the gain of the impedance respiration curve based on the amplitude of the impedance respiration curve and the amplitude of the ideal curve. Figure 2 As shown, after the impedance breathing curve is determined, when the amplitude of the impedance breathing curve is not within the range of ±10% of the ideal curve amplitude, it means that the current gain needs to be adjusted.

[0064] In a specific embodiment, the ratio K of the amplitude of the current impedance respiration curve to the amplitude of the ideal curve is calculated, and 1 / K is used as the adjustment gain to adjust the gain of the current impedance respiration curve to make it closer to the ideal curve amplitude.

[0065] From the above, it can be concluded that by comparing the difference between the amplitude of the current impedance respiration curve and the amplitude of the ideal curve, the adjustment gain is determined, and the gain of the current impedance respiration curve is adjusted based on this, so that the amplitude of the obtained impedance respiration curve can be closer to the amplitude of the ideal curve.

[0066] In order to obtain a signal that can reflect the breathing condition, according to the above embodiment, this embodiment provides a specific impedance breathing detection device, which also includes a driving module for outputting a high-frequency current of a preset frequency to generate a high-frequency carrier signal.

[0067] It can be understood that by outputting high-frequency current, a corresponding high-frequency carrier signal can be generated. Because high-frequency signals can more sensitively capture subtle physiological changes and are insensitive to external environmental noise, they can improve detection accuracy while reflecting the respiratory state.

[0068] From the above, it can be concluded that the base impedance and the impedance changes caused by breathing will modulate the high-frequency current to generate a high-frequency carrier signal that can carry changes in the breathing state as a signal reflecting the breathing state.

[0069] In order to obtain a signal that can reflect the breathing condition, according to the above embodiment, this embodiment provides a specific impedance breathing detection device, a data acquisition module, which is specifically used to obtain a high-frequency carrier signal, and based on the high-frequency carrier signal, obtain a chest impedance signal.

[0070] In this embodiment, after acquiring the high-frequency carrier signal, the data acquisition module can extract the chest impedance signal from the high-frequency carrier signal by demodulation. Since the frequency of the chest impedance change caused by breathing is relatively low, usually around 0.2-0.5Hz, and the frequency of the high-frequency carrier signal is relatively high, the demodulation process is to remove the high-frequency components in the high-frequency carrier signal and restore the low-frequency original signal related to breathing, that is, the chest impedance signal.

[0071] Furthermore, demodulation includes synchronous demodulation, envelope detection and other methods. Taking envelope detection as an example, the change law of the envelope is similar to the change law of chest impedance during breathing. By extracting the envelope of the high-frequency carrier signal and filtering the envelope, the original signal that can reflect the breathing condition, such as breathing frequency, breathing depth and other related information, can be obtained.

[0072] From the above, it can be seen that since the frequency of the signal reflecting the respiratory condition is small, the acquired high-frequency carrier signal is demodulated by the data acquisition module to filter the high-frequency components in the high-frequency carrier signal, so as to obtain the original signal that can reflect the respiratory condition, that is, the chest impedance signal.

[0073] In order to intuitively display the impedance respiration curve, according to the above embodiment, this embodiment provides a specific impedance respiration detection device, which also includes a display module to display the impedance respiration curve.

[0074] It is understandable that the display module can intuitively present the abstract impedance respiration curve. And by observing the shape, amplitude, frequency and other characteristics of the displayed impedance respiration curve, the real-time respiration status can be quickly understood. For example, the frequency of the curve directly reflects the respiration frequency, and the change in amplitude reflects the change in the depth of respiration. This intuitive presentation method helps medical staff to promptly detect respiratory abnormalities, such as rapid breathing, i.e., faster frequency of the curve, or weakened respiration, i.e., smaller amplitude of the curve.

[0075] In addition, for long-term monitoring scenarios, such as sleep breathing monitoring, the display module can be used to view the impedance breathing curve for the entire night, so that medical staff can determine whether there are problems such as apnea and shallow breathing during sleep based on the impedance breathing curve, and then diagnose diseases such as sleep breathing disorders. At the same time, observing the impedance breathing curve can also understand the changes in breathing status in different sleep stages, so as to achieve a comprehensive assessment of sleep quality.

[0076] As can be seen from the above, after receiving the impedance breathing curve, the display module can display it, so that the impedance breathing curve can be displayed more intuitively and reflect the current breathing condition.

[0077] In order to determine whether the currently determined impedance respiration curve is valid, according to the above embodiment, this embodiment provides a specific impedance respiration detection device, which also includes a heart rate acquisition module for collecting electrocardiogram signals to obtain the current heart rate.

[0078] It is understandable that, since the cardiopulmonary system is closely connected, the change of heart rate is also closely related to the respiratory state. The introduction of the current heart rate can determine whether the impedance respiratory curve obtained is valid. Therefore, it is also necessary to directly collect the ECG signal caused by cardiac activity through the above-mentioned electrodes, and further analyze the ECG signal to determine the current heart rate. In a specific embodiment, the R wave detection method can be used to determine the heart rate, and a suitable amplitude threshold is set. When the ECG signal exceeds the threshold, it is considered that an R wave is detected. By counting the number of R waves detected within a period of time, the current heart rate can be calculated. For example, if 60 R waves are detected within 1 minute, the current heart rate is 60 times / minute. In another specific embodiment, the acquisition of the current heart rate can also be achieved by spectrum analysis, and the collected ECG signal is Fourier transformed to convert the ECG signal from the time domain to the frequency domain. Since the frequency component corresponding to the heart rate has a specific position in the frequency domain, the heart rate can be estimated by finding the frequency corresponding to the peak in the spectrum. For example, the frequency corresponding to the normal heart rate range is usually between 0.8-2.5Hz. The spectrum peak within this frequency range is obtained and the heart rate is calculated based on its corresponding frequency. Assuming the peak frequency is 1.2Hz, the current heart rate is 1.2×60=72 beats / minute.

[0079] From the above, it can be concluded that the heart rate acquisition module can directly collect the ECG signal through the electrodes that collect the chest impedance signal, and process and analyze the acquired ECG signal to determine the current heart rate value for judging the effectiveness of the subsequent impedance breathing curve.

[0080] In order to determine whether the obtained impedance respiration curve is valid, according to the above embodiment, this embodiment provides a specific impedance respiration detection device, which also includes a validity judgment module for determining the minimum valid threshold based on the current heart rate; judging whether the amplitude of the impedance respiration curve is greater than the minimum valid threshold; if so, determining that the impedance respiration curve is a valid respiration curve.

[0081] Under normal physiological conditions, the rhythm of heart rate and breathing should be relatively stable and coordinated with each other. For example, in a calm state, the breathing rate is relatively stable and the heart rate is also relatively stable. If the breathing rate reflected by the impedance respiration curve is too different from the expected value of the breathing rate calculated by the heart rate, it is likely that there is a problem with the currently determined impedance respiration curve.

[0082] Furthermore, the increase in heart rate is accompanied by an increase in breathing rate, and the amplitude of the current impedance respiration curve will also increase accordingly. Therefore, the minimum effective threshold under different heart rate ranges is set. When the amplitude of the impedance respiration curve is less than the minimum effective threshold corresponding to the current heart rate, it means that the impedance respiration curve is invalid.

[0083] In addition, by observing whether the impedance respiration curve has periodic changes consistent with the heart rate, or reflects the interactive relationship between heart rate and respiration, it is also possible to determine whether the current impedance respiration curve is a valid respiration curve.

[0084] From the above, it can be concluded that by judging whether the respiratory frequency reflected by the obtained impedance respiration curve is consistent with the respiratory frequency reflected by the heart rate, it can be determined whether the current impedance respiration curve is valid, and the breathing amplitude will increase with the increase of the breathing frequency. Therefore, by determining whether the amplitude of the impedance respiration curve meets the requirements of the current heart rate, it can be determined whether the impedance respiration curve is a valid respiration curve.

[0085] In order to determine whether the obtained impedance respiration curve is valid, according to the above embodiment, this embodiment provides a specific impedance respiration detection device, and an effectiveness judgment module, which is specifically used to determine that when the current heart rate is less than or equal to 90 times / minute, the minimum effective threshold is the first minimum effective threshold; when the current heart rate is greater than 90 times / minute and less than or equal to 120 times / minute, the minimum effective threshold is determined to be the second minimum effective threshold; when the current heart rate is greater than 120 times / minute, the minimum effective threshold is determined to be the third minimum effective threshold.

[0086] In this embodiment, the minimum effective threshold is determined based on the heart rate range, so that after determining the impedance breathing curve and the current heart rate, Figure 1The validity judgment module shown in the figure determines whether the amplitude of the impedance breathing curve is greater than the minimum effective threshold, and then determines whether the impedance breathing curve is a valid breathing curve. The size of the minimum effective threshold is related to the current heart rate. For example, when the current heart rate is less than 90 beats / minute, 0.5 As the minimum effective threshold, when the current heart rate is greater than 90 beats / minute but less than 120 beats / minute, 0.7 is selected. As the minimum effective threshold, when the current heart rate is greater than 120 beats / minute, select 1 As the minimum effective threshold, it is understandable that the magnitudes of the first minimum effective threshold, the second minimum effective threshold, and the third minimum effective threshold, as well as their relationship with the current heart rate, can be reasonably planned based on actual conditions to ensure the rationality of the judgment.

[0087] From the above, it can be concluded that based on the relationship between the current heart rate and the amplitude of the impedance respiration curve, the minimum effective threshold in each heart rate range is determined, and then the effective judgment module can be used to determine whether the current impedance respiration curve is a valid respiration curve.

[0088] Finally, this embodiment provides a breathing detection device, including the above-mentioned impedance breathing detection device.

[0089] The impedance breathing detection device and breathing detection equipment provided by the present application are introduced in detail above. The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same and similar parts between the embodiments can be referenced to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description. It should be pointed out that for ordinary technicians in this technical field, without departing from the principles of the present application, several improvements and modifications can be made to the present application, and these improvements and modifications also fall within the scope of protection of the claims of the present application.

[0090] It should also be noted that, in this specification, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

Claims

1. An impedance breathing detection device, characterized in that: include: A data acquisition module, used for acquiring chest impedance signals; A first filtering module, used for controlling a high-pass filter to filter the chest impedance signal with a first cutoff frequency to obtain first target data; wherein the first cutoff frequency is less than a lower limit of a breathing effective frequency band, and the high-pass filter has a recursive structure; A first judging module, used to judge whether the first target data is greater than a preset threshold; A curve generating module, used for determining a current impedance breathing curve based on the first target data when the result of the first judging module is no; A second filtering module, for controlling the high-pass filter to filter the chest impedance signal with a second cutoff frequency to obtain second target data when the result of the first judgment module is yes; wherein the second cutoff frequency is greater than the upper limit of the effective breathing frequency band; The second judgment module is used to judge whether the second target data is less than the preset threshold; if so, trigger the first filtering module; if not, continue to judge.

2. The impedance breathing detection device according to claim 1, characterized in that: The method further comprises a gain adjustment module for determining the gain of the impedance respiration curve based on the amplitude of the impedance respiration curve and the amplitude of an ideal curve.

3. The impedance breathing detection device according to claim 2, characterized in that: The gain adjustment module is specifically used to calculate the ratio K of the amplitude of the impedance respiration curve to the amplitude of the ideal curve when the amplitude of the impedance respiration curve exceeds the preset range of the amplitude of the ideal curve, and determine the gain to be 1 / K.

4. The impedance breathing detection device according to claim 1, characterized in that: It also includes a driving module for outputting a high-frequency current of a preset frequency to generate a high-frequency carrier signal.

5. The impedance breathing detection device according to claim 4, characterized in that: The data acquisition module is specifically used to acquire the high-frequency carrier signal, and based on the high-frequency carrier signal, acquire the chest cavity impedance signal.

6. The impedance breathing detection device according to claim 1, characterized in that: A display module is also included to display the impedance respiration curve.

7. The impedance breathing detection device according to claim 1, characterized in that: It also includes a heart rate acquisition module for collecting electrocardiogram signals to obtain the current heart rate.

8. The impedance breathing detection device according to claim 7, characterized in that: It also includes a validity judgment module, which is used to determine the minimum valid threshold based on the current heart rate; judge whether the amplitude of the impedance respiration curve is greater than the minimum valid threshold; if so, determine that the impedance respiration curve is a valid respiration curve.

9. The impedance breathing detection device according to claim 8, characterized in that: The validity judgment module is specifically used to determine that the minimum valid threshold is the first minimum valid threshold when the current heart rate is less than or equal to 90 beats / minute; when the current heart rate is greater than 90 beats / minute and less than or equal to 120, determine that the minimum valid threshold is the second minimum valid threshold; when the current heart rate is greater than 120 beats / minute, determine that the minimum valid threshold is the third minimum valid threshold.

10. A breathing detection device, characterized in that: It comprises the impedance breathing detection device as described in any one of claims 1 to 9.

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