A method of detecting respiratory rate

Abstract

This application discloses a low-cost method for detecting respiratory rate, comprising: Step 1, a component data acquisition unit sequentially acquires raw data from a triaxial accelerometer; Step 2, sequentially traversing the acquired component data content, and a component data extremum extractor obtains the local extrema of the data; Step 3, sequentially traversing the acquired component data content, and a component data period extractor obtains the local period values ​​of the data; Step 4, a data extremum filter obtains the local extrema and obtains gating values ​​for the three components; Step 5, a respiratory rate converter obtains the local period values ​​and gating values ​​to obtain the respiratory rate value; Step 6, a respiratory rate buffer obtains a new respiratory rate value, the number of effective data elements in the respiratory rate buffer is increased by 1, and the process returns to Step 1. The detection method provided by this invention is characterized by its portability, lack of physical sensation, and high reliability.

Description

Technical Field

[0001] This application relates to the field of respiratory rate detection technology, and in particular to a method for detecting respiratory rate. Background Technology

[0002] Vital signs mainly include parameters such as heart rate, blood pressure, blood oxygen saturation, and respiratory rate. Among these, methods for measuring respiratory rate currently include the flow rate method and the thoracic and abdominal volume method.

[0003] The flow rate method is one of the most reliable detection methods. Its principle is to collect the flow rate of gas passing through the respiratory tract during respiration using a gas flow sensor, thereby obtaining time-gas flow data for the human body. Finally, respiratory rate is determined through data analysis. However, the flow rate method also has significant drawbacks. Primarily, the gas flow sensor must be installed in close contact with the human body, greatly reducing user comfort, especially in comfort-critical situations such as sleep, where this method is highly likely to impair sleep quality.

[0004] The thoracic-abdominal volumetric method is one of the most direct detection methods. One of its principles is to use a length-measuring sensor to collect the change in circumference of the human chest and abdomen caused by volume changes, thus obtaining time-circumference data. Because circumference is indirectly obtained through volume, the "time-circumference" data is to some extent equivalent to the "time-volume" data. Finally, respiratory rate is obtained through data analysis. The disadvantages of the thoracic-abdominal volumetric method are similar to those of the flow rate method; the length-measuring sensor must be installed in close contact with the human body, significantly reducing user comfort. Summary of the Invention

[0005] This application provides a method for detecting respiratory rate to solve the problem of low user comfort in the prior art for respiratory rate detection.

[0006] To solve the above-mentioned technical problems, this application is implemented as follows:

[0007] A low-cost method for detecting respiratory rate, comprising:

[0008] Step 1: The component data acquisition unit collects raw data from each of the triaxial accelerometers.

[0009] Step 2: Iterate through the collected component data one by one, and the component data extremum extractor obtains the local extrema of the data.

[0010] Step 3: Iterate through the collected component data content one by one, and the component data period extractor obtains the local period value of the data.

[0011] Step 4: The data extremum filter obtains local extrema and gets the gating values ​​of the three components;

[0012] Step 5: The respiratory rate converter obtains the local period value and gating value to get the respiratory rate value;

[0013] Step 6: The respiratory rate buffer acquires a new respiratory rate value, the number of valid data elements in the respiratory rate buffer is increased by 1, and the process returns to step 1.

[0014] Furthermore, before the component data acquisition unit acquires the raw data from the triaxial accelerometers one by one in step 1, it includes: performing an initialization operation on the relevant environment.

[0015] Specifically, the formulas used by the data extremum filter include:

[0016]

[0017] Where i is the sampling sequence number, and x takes the value 1, 2, or 3; Tp x Tp1 represents the peak-to-peak value of the X component, Tp2 represents the peak-to-peak value of the Y component, and Tp3 represents the peak-to-peak value of the Z component; Tp x-max and Tp x-min These represent the maximum and minimum values ​​of the three axes, respectively; k is the average of the peak-to-peak values ​​of the three components; a x For the gating values ​​of the three components, when Tp x The value is 0 when it is less than or equal to k, and 1 otherwise; sign is the sign function, which outputs 1 when it is greater than 0, 0 when it is equal to 0, and -1 when it is less than zero.

[0018] Specifically, the formulas used in the respiratory rate converter include:

[0019]

[0020] Among them, c x is the periodic value of the three components; f is the respiratory rate value.

[0021] The beneficial effects of this application are as follows:

[0022] This application proposes a method for detecting respiratory rate based on the component changes of a triaxial accelerometer, placed in the chest and abdomen position. It features lightweight, imperceptible operation, and high reliability. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the respiratory rate data structure in this application;

[0024] Figure 2 This is a flowchart illustrating the respiratory rate detection method in this application. Detailed Implementation

[0025] To make the technical problems to be solved, the technical solutions, and the beneficial effects of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present invention and are not intended to limit the present invention.

[0026] This application proposes a method for detecting respiratory rate, such as... Figure 1 As shown, the respiratory rate detection data structure includes: a triaxial accelerometer, a component data acquisition unit, a component data extremum extractor, a component data period extractor, a data extremum filter, a respiratory rate converter, and a respiratory rate buffer. Specifically, the triaxial accelerometer measures the components of gravitational acceleration in three-dimensional space; the component data acquisition unit acquires the raw data from the triaxial accelerometer; the component data extremum extractor calculates the extrema of each component; the component data period extractor calculates the period of each component; the data extremum filter selects the optimal component; the respiratory rate converter converts the optimal component period into respiratory rate data; and the respiratory rate buffer buffers the respiratory rate values. This respiratory rate data structure is used to manage its data content at the software level.

[0027] Furthermore, the formulas used by the data extremum filter include:

[0028]

[0029] Where i is the sampling sequence number, and x takes the values ​​1, 2, and 3; Tp x Tp1 represents the peak-to-peak value of the X component, Tp2 represents the peak-to-peak value of the Y component, and Tp3 represents the peak-to-peak value of the Z component; Tp x-max and Tp x-min These represent the maximum and minimum values ​​of the three axes, respectively; k is the average of the peak-to-peak values ​​of the three components; a x For the gating values ​​of the three components, when Tp x The value is 0 when it is less than or equal to k, and 1 otherwise; sign is the sign function, which outputs 1 when it is greater than 0, 0 when it is equal to 0, and -1 when it is less than zero.

[0030] The formulas used in the respiratory rate converter include:

[0031]

[0032] Among them, c x is the period value of the three components (unit: seconds); f is the final respiratory rate value (unit: breaths / minute).

[0033] like Figure 2 As shown, the flow steps of the respiratory rate detection method in this application are as follows:

[0034] Step 1. On first run, initialize the relevant environment;

[0035] Step 2. The component data acquisition unit acquires the raw data from each of the three-axis accelerometers one by one;

[0036] Step 3. Iterate through the collected component data one by one, and obtain the local extrema of the data through the component data extremum extractor;

[0037] Step 4. Iterate through the collected component data content one by one, and obtain the local periodic value of the data through the component data period extractor;

[0038] Step 5. Feed the local extrema into the data extrema filter to obtain the gating values ​​of the three components;

[0039] Step 6. Input the local period value and gating value into the respiratory rate converter to obtain the final respiratory rate value;

[0040] Step 7. Add a new breathing frequency to the breathing frequency buffer. At this time, the number of valid data elements in the breathing frequency buffer increases by 1, and then return to step 2.

[0041] The respiratory rate detection method described in this application can be applied to various monitoring devices, such as medical monitoring equipment—respiratory monitors. It converts acceleration data detected by the respiratory monitor into respiratory rate data; then, it uses the respiratory rate data to determine the current user's respiratory state, such as apnea or tachypnea; further, it calculates the local periodic value of the respiratory rate data to assess whether an alarm should be generated based on the user's respiratory state. The data can also be reported to the cloud via various data link methods. When an alarm is generated, the cloud can push an alarm signal to a pre-set handheld device belonging to a close relative or a server in a medical institution, enhancing applicability and effectiveness.

[0042] The beneficial effects of this application are as follows:

[0043] This application proposes a method for detecting respiratory rate based on the component changes of a triaxial accelerometer, placed in the chest and abdomen position. It features lightweight, imperceptible operation, and high reliability.

[0044] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A low cost method of detecting respiratory rate, characterized by, Comprise: Step 1, the component data collector collects the original data of the three-axis acceleration sensor one by one; Step 2, the component data maximum extractor obtains the local maximum value of the data by traversing the collected component data content one by one; Step 3, the component data cycle extractor obtains the local cycle value of the data by traversing the collected component data content one by one; Step 4, the data maximum filter obtains the local maximum value to obtain the gating value of the three components; the formula used by the data maximum filter comprises: where i is the sampling number, x takes values 1, 2, 3; Tp x is the peak-to-peak value of three components, Tp1 is the peak-to-peak value of X component, Tp2 is the peak-to-peak value of Y component, Tp3 is the peak-to-peak value of Z component; Tp x-max and Tp x-min are the maximum and minimum values of three axes respectively; k is the average value of the peak-to-peak value of three components; a x is the gating value of three components, which is 0 when Tp x is less than or equal to k, and 1 otherwise; sign is a sign function, which outputs 1 when greater than 0, 0 when equal to 0, and -1 when less than zero; Step 5, the respiration frequency converter obtains the local cycle value and the gating value to obtain the respiration frequency value; Step 6, the respiration frequency buffer obtains the new respiration frequency value, the number of valid data elements of the respiration frequency buffer increases by 1, and returns to step 1.

2. The low cost respiration rate detection method of claim 1, wherein, Before the component data collector collects the original data of the three-axis acceleration sensor one by one in the step 1, comprising: initializing the related environment.

3. The low cost respiration rate detection method of claim 1, wherein, The formula used by the respiration frequency converter comprises: where c x is the period value of the three components; f is the respiratory frequency value.

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