A low-power pulse acquisition and wireless transmission method

Abstract

This invention discloses a low-power pulse acquisition and wireless transmission method, comprising the following steps: connecting a bio-information acquisition sensor to a pulse capture and forwarding module; activating the device to wait for formal pulse acquisition; the processor captures, counts pulses, and calculates the pulse frequency; using the calculated pulse frequency each time, and dynamically correcting it using an inertial correction model, calculating and storing the flow value based on the corrected gain parameter; after data acquisition is completed, forwarding it to a mobile terminal for visualization, clearing cached data, and starting a timer; if no new pulse is captured for more than 200 seconds, entering sleep mode to wait for the next test; otherwise, turning off the timer and starting a new round of acquisition and detection. This invention's low-power pulse acquisition and wireless transmission method introduces a pulse activation design to reduce pulse acquisition power consumption and extend device usage time; it employs an inertial correction design to modify the gain parameter in real time, ensuring the accuracy of the detection results.

Description

Technical Field

[0001] This invention relates to the field of pulse acquisition and transmission, and in particular to a low-power pulse acquisition and wireless transmission method. Background Technology

[0002] Bioinformatics acquisition refers to the technology of collecting and processing biological information using high-tech means such as computers and biosensors. It is widely used in fields such as brain-computer interfaces and biomedicine. In bioinformatics detection, pulse acquisition is an important data acquisition technique. It converts biological information into digital signals through biosensitive elements and signal converters, and then collects and analyzes the data to extract relevant information.

[0003] Power consumption is a critical factor in signal acquisition. This is especially true when the device needs to operate for extended periods or in environments with limited power. To address these issues, researchers have proposed several low-power design methods. These include using gated clocking to disable part of the clock, employing multi-threshold voltage techniques to use standard cells with different speeds, and using multi-voltage domain designs to reduce power consumption by using different voltages in different modules. However, these techniques all introduce complex control strategies, increasing device complexity and timing issues. Furthermore, multiple clocks and power mode switching can lead to inconsistent device behavior under different operating conditions, impacting device performance.

[0004] Furthermore, in bioinformatics detection processes, deviations in detection results can occur due to the nature of the measured signal, conditions (such as temperature, pressure, composition, and flow range), and systematic errors in the detection device. The calibrated relationship between the detection device's output and the measured signal can only be determined based on a specific process condition. If the actual detection coefficient of the device changes, calculating the measurement value according to the original calibrated relationship will inevitably introduce errors. Such inaccurate results provide incorrect information, further affecting data analysis and use. To address this issue, additional sensors are typically introduced to detect changes in relevant conditions. However, in scenarios with limited budgets, the introduction of additional sensors can significantly increase equipment costs and product expenses. Summary of the Invention

[0005] In view of the aforementioned shortcomings of the prior art, the technical problem to be solved by the present invention is that existing bioinformatics acquisition devices suffer from high power consumption, easy deviation in results, and high cost. The present invention provides a low-power pulse acquisition and wireless transmission method, which introduces a pulse activation design to save pulse acquisition power consumption during the time from device initialization to the start of detection, thus extending device usage time; it employs an inertial correction design to modify gain parameters in real time, dynamically capture the influence of inertia on flow testing, and provide control supplementation to ensure the accuracy of detection results.

[0006] To achieve the above objectives, the present invention provides a low-power pulse acquisition and wireless transmission method, comprising the following steps:

[0007] Connect the bio-information acquisition sensor with the pulse capture and forwarding module to form a complete device;

[0008] After connection, the subject blows a breath into the sensor to activate it with a pulse. Once activated, the device can wait for formal pulse capture.

[0009] The subject continuously blows air, and the pulse capture and forwarding module captures and counts the pulses. Every 0.5 seconds, the pulse count value is checked and the pulse frequency is calculated. Using the pulse frequency calculated each time, the gain parameter of the bio-information acquisition sensor is dynamically corrected using an inertial correction model. The flow rate value is calculated and stored based on the corrected gain parameter.

[0010] After the data collection is completed, the data is forwarded to the mobile device for visualization via wireless Bluetooth, the cached data is cleared, and the timer is started.

[0011] If no new pulse is captured for more than 200 seconds, the device enters sleep mode and waits for the next test; otherwise, the timer is turned off and a new round of acquisition and detection begins.

[0012] Furthermore, the bio-information acquisition sensor includes a turbine, a Hall flow sensor, and an air blower that conforms to the size of the oral cavity. When the fluid being measured impacts the rotating blades, it drives the turbine to rotate. The turbine speed is proportional to the gas flow rate. The electromagnetic conversion device of the Hall flow sensor converts the turbine speed into electrical pulses of the corresponding frequency. The electrical pulses are sent to the processor for accumulation calculation, and the pulse frequency and instantaneous gas flow rate are calculated at intervals of Δt.

[0013] Furthermore, the pulse count is checked and the pulse frequency is calculated every 0.5 seconds. Specifically, the number of pulses N collected within the time interval Δt is converted into the pulse frequency f.

[0014]

[0015] Where N is the number of pulses, Δt is the sample acquisition time, and f is the signal frequency, in seconds.

[0016] Furthermore, the instantaneous gas flow rate is typically inversely proportional to the gain parameter of the bioinformation acquisition sensor. The instantaneous gas flow rate refers to the volume of gas flowing per unit time, calculated using the following formula:

[0017]

[0018] Where K is the gain parameter of the flow sensor, in units of flow rate / m³.3 , representing the number of pulses emitted when a unit volume of flow passes through the sensor. f is the signal frequency, measured in pulses per second, and Q is the instantaneous flow rate, measured in cubic meters per second (m³). 3 / s.

[0019] Furthermore, the gain parameter K is not a constant value, but a function of the output signal f, that is:

[0020] K = Ψ(f) = Ψ(QK′) = p(Q)

[0021] Where K′ is the gain value calculated in the previous Δt time interval.

[0022] Furthermore, it also includes dynamically correcting the gain parameter value during measurement, thereby ensuring that the instrument accurately measures the signal frequency while obtaining an accurate flow rate value.

[0023] Furthermore, dynamically correcting the gain parameter value during measurement includes the following steps:

[0024] (3) Use a standard flow source to measure the pulse frequency obtained under different gas flow rates and calculate the corresponding gain coefficients respectively. Based on the actual calibration results of the sensor, a set of data is obtained, with gain coefficients K0, K1, K2...Km and corresponding pulse frequencies f0, f1, f2...fm;

[0025] (4) Construct a set of polynomial functions {Kj(f)(j=0,1,...n)} of degree no more than n that are orthogonal at a given point. Then, we can first use {Kj(f)(j=0,1,...n)} as basis functions and perform curve fitting using the least squares method, that is:

[0026]

[0027] Where θ is a parameter. The value can be the recommended gain value for this sensor;

[0028] For ease of representation using matrices, we let f 0 =1, therefore the above equation can be represented by a matrix as:

[0029] K θ =Fθ

[0030] Where F = (1, f 1 ,...,f n-1 To minimize the difference between the predicted value and the error, the error function can be defined as follows:

[0031]

[0032] Where R is the actual calibration result of the sensor, and the optimization objective is to minimize the error function E. Since the extreme point of the function is the point where the derivative is 0, we only need to take the derivative of the loss function and set it equal to 0 to solve for θ.

[0033] First, simplify the objective function:

[0034] E(θ)=θ T F T Fθ-θ T F T RR T Fθ+R T R

[0035] Differentiate and set it to 0:

[0036]

[0037] Solving for θ, we get θ = (F T F) -1 F T R, after derivation, yields an analytical solution for θ, which can be directly calculated by substituting the data.

[0038] Furthermore, inertial correction is performed during the measurement, including the following steps:

[0039] 5) Set the initial sensor coefficient K, let This refers to the recommended value for the sensor's factory-set gain parameter;

[0040] 6) By Convert the number of captured pulses to the current frequency;

[0041] 7) By Calculate and store the instantaneous flow rate;

[0042] 8) By K θ =Fθ calculates the new gain value K;

[0043] 5) Proceed to step 2) and continue with the next set of cycles.

[0044] 9. The low-power pulse acquisition and wireless transmission method as described in claim 1, characterized in that, before the device is activated, only the Bluetooth module is in a standby state, without any other additional power consumption.

[0045] Furthermore, the subject performs a continuous blowing operation, and when more than 5 pulse data are detected consecutively, it is determined that this is a continuous blowing operation.

[0046] Technical effect

[0047] This invention provides a low-power pulse acquisition and wireless transmission method, which introduces a pulse activation design: by detecting an additional pulse, the device is activated, effectively saving pulse acquisition power consumption from device initialization to the start of detection, thus extending device usage time; it also features an automatic sleep design: by introducing an automatic sleep module that links user behavior with system power management, the system directly enters a sleep state after a certain period of time to reach the device's minimum power consumption, waiting for the next power-on startup, which not only meets the testing needs of the user but also avoids introducing complex clock and power modes, enabling the device to effectively store power while ensuring reliability; and it employs an inertia correction design: without introducing additional sensor costs, the pulse frequency-gain parameter is modeled, and the influence of inertia on flow testing is dynamically captured and controlled and compensated by modifying the gain parameter in real time.

[0048] The following will further explain the concept, specific structure, and technical effects of the present invention in conjunction with the accompanying drawings, so as to fully understand the purpose, features, and effects of the present invention. Attached Figure Description

[0049] Figure 1 This is a flowchart illustrating a preferred embodiment of a low-power pulse acquisition and wireless transmission method of the present invention. Detailed Implementation

[0050] To make the technical problems, solutions, and beneficial effects of this invention clearer, the 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 and not intended to limit the invention.

[0051] In the following description, specific details, such as particular internal procedures and techniques, are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of the invention. However, those skilled in the art will appreciate that the invention may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of the invention with unnecessary detail.

[0052] This invention provides a low-power pulse acquisition and wireless transmission method. The entire device includes two modules: a bio-information acquisition sensor and a pulse capture and forwarding module. The bio-information acquisition sensor and the pulse capture and forwarding module are connected to form a complete device.

[0053] The bio-information acquisition sensor includes a turbine, a Hall effect flow sensor, and an air blower sized to fit the mouth. When the fluid being measured impacts the rotating blades of the turbine, it drives the turbine to rotate. The turbine speed is proportional to the gas flow rate. The Hall effect flow sensor's electromagnetic conversion device converts the turbine speed into electrical pulses of a corresponding frequency. These electrical pulses are then sent to a processor for accumulation and calculation, and the pulse frequency and instantaneous gas flow rate are calculated at intervals of Δt. The bio-information acquisition sensor is used to capture and collect gas flow information and convert it into pulse signals.

[0054] The pulse capture and forwarding module is a program running on the CC2640R2-LAUNCHXL development board platform. Its main function is to receive data from the bioinformatics acquisition sensor, then perform further processing and analysis on this data, and forward it via the onboard Bluetooth. The two modules are typically connected using three wires: a power wire, a ground wire, and a pulse signal wire. Together, these two parts constitute the hardware device module of this system, which will be referred to as the device below.

[0055] like Figure 1 As shown in the figure, this embodiment of the invention also provides a low-power pulse acquisition and wireless transmission method, including the following steps:

[0056] Step 100: Connect the bio-information acquisition sensor to the pulse capture and forwarding module to form a complete device. After connection, first turn on the power switch to power on the device. The device automatically enables Bluetooth broadcasting and waits to connect to the mobile device. Bluetooth uses the onboard Bluetooth module of the CC2640R2-LAUNCHXL. Once the connection is successfully established, Bluetooth communication is ready.

[0057] Step 200: After connection, the subject blows a breath onto the sensor to activate it with a pulse. Once activated, the device waits for formal pulse capture. When pulse data is detected, the device will be activated and start a new task specifically for pulse data acquisition and processing. Before device activation, only the Bluetooth module is in a standby state, with no additional power consumption.

[0058] Step 300: The subject continuously blows air, and the pulse capture and forwarding module captures and counts the pulses. Every 0.5 seconds, the pulse count value is checked and the pulse frequency is calculated. Using the calculated pulse frequency each time, the gain parameter of the bio-information acquisition sensor is dynamically corrected using an inertial correction model. Based on the corrected gain parameter, the flow rate value is calculated and stored. Specifically,

[0059] Step 301: The subject performs a continuous blowing operation. After five or more consecutive pulse data points are detected, the operation is considered a continuous blowing operation. The device starts counting and records the detected pulse data. Specifically, a timer is started, and the number of captured pulse data points is checked every 0.5 seconds. If data lasting more than 3 seconds is correctly captured, the data is considered valid; otherwise, the data is cleared, and the system waits for the next pulse. After valid data acquisition, the number of pulses is converted into pulse frequency based on mathematical relationships, and the instantaneous gas flow rate is further calculated. The specific mathematical relationships are as follows:

[0060] (1) Pulse frequency refers to the number of pulses per unit time. The number of pulses N collected in the time interval Δt is converted into pulse frequency f as follows:

[0061]

[0062] Where N is the number of pulses, Δt is the sample acquisition time, and f is the signal frequency, in seconds.

[0063] (2) Instantaneous gas flow rate refers to the volume of gas flowing through per unit time. When the pulse frequency is constant, the instantaneous gas flow rate is usually inversely proportional to the gain parameter of the bio-information acquisition sensor. The calculation formula is as follows:

[0064]

[0065] Where K is the gain parameter of the flow sensor, in units of flow rate / m³. 3 , representing the number of pulses emitted when a unit volume of flow passes through the sensor. f is the signal frequency, measured in pulses per second, and Q is the instantaneous flow rate, measured in cubic meters per second (m³). 3 / s.

[0066] Step 302: Using the pulse frequency obtained from each calculation, the gain parameters of the bio-information acquisition sensor are dynamically corrected using an inertial correction model. The flow rate value is calculated and stored based on the corrected gain parameters.

[0067] Typically, the gain parameter K is not a constant value, but rather a function of the output signal f, as the flow rate changes.

[0068] K = Ψ(f) = Ψ(QK′) = p(Q)

[0069] Where K′ is the gain value calculated in the previous Δt time interval.

[0070] Because the fluid drag torque differs significantly between laminar and turbulent flow regimes, the characteristic curve exhibits an extreme value at the boundary between laminar and turbulent flow. The higher the fluid viscosity, the more this peak value shifts towards higher flow rates.

[0071] Therefore, the relationship between the gain coefficient K and the pulse frequency f can be pre-constructed, and the gain parameter value can be dynamically corrected during measurement, thereby ensuring that the instrument accurately measures the signal frequency while obtaining an accurate flow rate value.

[0072] The specific process is as follows:

[0073] (5) Measure the pulse frequencies obtained under different gas flow rates using a standard flow source and calculate the corresponding gain coefficients. A set of data is obtained based on the actual calibration results of the sensor, with gain coefficients K0, K1, K2...Km and corresponding pulse frequencies f0, f1, f2...fm.

[0074] (6) Construct a set of polynomial functions {Kj(f)(j=0,1,...n)} of degree no more than n that are orthogonal at a given point. Then, we can first use {Kj(f)(j=0,1,...n)} as basis functions and perform curve fitting using the least squares method, that is:

[0075]

[0076] Where θ is a parameter. The recommended gain value for this sensor can be selected.

[0077] For ease of representation using matrices, we let f 0 =1, therefore the above equation can be represented by a matrix as:

[0078] K θ =Fθ

[0079] Where F = (1, f 1 ,...,f n-1 To minimize the difference between the predicted value and the error, the error function can be defined as follows:

[0080]

[0081] Where R is the actual calibration result of the sensor. The optimization objective is to minimize the error function E. Since the extreme points of the function are the points where the derivative is 0, we only need to take the derivative of the loss function and set it equal to 0 to solve for θ.

[0082] First, simplify the objective function:

[0083] E(θ)=θ T F T Fθ-θ T F T RR T Fθ+R T R

[0084] Differentiate and set it to 0:

[0085]

[0086] Solving for θ, we get θ = (F T F) -1 F T R, after derivation, yields an analytical solution for θ, which can be directly calculated by substituting the data.

[0087] A mathematical relationship model between frequency f and sensor gain K was obtained using the least squares method. Based on this model, the sensor parameter K can be dynamically corrected during sensor testing to reduce the influence of inertia on the measurement results.

[0088] Based on the above model, inertial correction can be performed in actual measurements through the following steps:

[0089] 9) Set the initial sensor coefficient K, let This refers to the recommended value for the sensor's factory-set gain parameter;

[0090] 10) By Convert the number of captured pulses to the current frequency;

[0091] 11) By Calculate and store the instantaneous flow rate;

[0092] 12) By K θ =Fθ calculates the new gain value K;

[0093] Proceed to step 2) to continue the next set of loops. Since the gain value K changes continuously with the flow rate, the dynamic update of the gain value continues throughout the entire test process until the test ends.

[0094] Step 400: After the data collection is completed, the data is forwarded to the mobile terminal for visualization via wireless Bluetooth, the cached data is cleared, and the timer is started.

[0095] In step 500, if no new pulse is captured within 200 seconds, the system enters sleep mode and waits for the next test; otherwise, the timer is turned off, and a new round of acquisition and detection begins.

[0096] Because biometric data acquisition is a continuous process, a timer is started after acquisition is complete. If no new pulse data is captured within 200 seconds, the detection is considered complete, and the device enters sleep mode to further conserve power. Otherwise, the timer is turned off, and the process proceeds to step 300 to begin a new round of acquisition and detection.

[0097] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A low power consumption pulse acquisition and wireless transmission method, characterized in that, Includes the following steps: Connect the bio-information acquisition sensor with the pulse capture and forwarding module to form a complete device; After connection, the subject blows a breath into the sensor to activate it with a pulse. Once activated, the device can wait for formal pulse capture. The subject continuously blows air, and the pulse capture and forwarding module captures and counts the pulses, checking the pulse count value and calculating the pulse frequency every 0.5 seconds. The pulse frequency obtained from each calculation is used, and the gain parameters of the bioinformation acquisition sensor are dynamically corrected using an inertial correction model. The flow rate value is calculated and stored based on the corrected gain parameters. The instantaneous gas flow rate is typically inversely proportional to the gain parameter of the bioinformatics sensor. The instantaneous gas flow rate refers to the volume of gas flowing per unit time, calculated using the following formula: ， Where K is the gain parameter of the flow sensor, in units of flow rate / m³. 3 This represents the number of pulses emitted when a unit volume of flow passes through the sensor; The signal frequency is expressed in cycles per second (Q), and the instantaneous flow rate is expressed in cubic meters per second (m³). 3 / s After the data collection is completed, the data is forwarded to the mobile terminal for visualization via wireless Bluetooth, the cached data is cleared, and the timer is started. If no new pulse is captured for more than 200 seconds, the system enters sleep mode and waits for the next test; otherwise, the timer is turned off and a new round of acquisition and detection begins. The gain parameter K is not a constant value, but rather a value related to the signal frequency. The function, that is: ， in For the previous one The gain value calculated over a time period; Dynamically correcting the gain parameter value during measurement includes the following steps: (1) Use a standard flow source to measure the pulse frequency obtained under different gas flow rates and calculate the corresponding gain coefficients respectively. Based on the actual calibration results of the sensor, a set of data is obtained, with gain coefficients K0, K1, K2...Km and corresponding pulse frequencies f0, f1, f2...fm; (2) Construct a set of polynomial functions of degree no more than n that are orthogonal at a given point, {Kj(f)(j=0,1,...n)}. Then, we can first use {Kj(f)(j=0,1,...n)} as basis functions and perform curve fitting using the least squares method, that is: ， Where θ is a parameter. The value can be the recommended gain value for this sensor; For ease of representation using matrices, we let Therefore, the above equation can be represented by a matrix as follows: ， in =(1, , ..., To minimize the difference between the predicted value and the error, the error function can be defined as follows: ， Where R is the actual calibration result of the sensor, and the optimization objective is to minimize the error function E. Since the extreme points of the function are the points where the derivative is 0, we only need to take the derivative of the loss function and set it equal to 0 to obtain the solution. ; First, simplify the objective function: T F T F - T F T R-R T F +R T R, Differentiate and set it to 0: ， Solving = (F T F) -1 F T R, obtained through derivation The analytical solution can be obtained by substituting the data directly. ; Inertial correction during measurement includes the following steps: 1) Set the initial sensor coefficient K, let K = This refers to the recommended value for the sensor's factory-set gain parameter; 2) By Convert the number of captured pulses to the current frequency; 3) By Calculate and store the instantaneous flow rate; 4) By Calculate the new gain value K; 5) Proceed to step 2) and continue to the next set of cycles.

2. The low-power pulse acquisition and wireless transmission method as described in claim 1, characterized in that, The bio-information acquisition sensor includes a turbine, a Hall effect flow sensor, and an air blower sized to fit the mouth. When the fluid being measured impacts the rotating blades, it drives the turbine to rotate. The turbine speed is proportional to the gas flow rate. The Hall effect flow sensor's electromagnetic conversion device converts the turbine speed into electrical pulses of a corresponding frequency. These electrical pulses are then sent to a processor for accumulation and calculation, and are processed at intervals. The time is used to calculate the pulse frequency and instantaneous gas flow rate.

3. The low-power pulse acquisition and wireless transmission method as described in claim 1, characterized in that, Every To check the pulse count and calculate the pulse frequency, specifically, convert the number of pulses N collected within the time interval Δt into the pulse frequency. , ， Where N is the number of pulses, measured in pulses. The duration of sample collection. The signal frequency is expressed in cycles per second.

4. The low-power pulse acquisition and wireless transmission method as described in claim 1, characterized in that, It also includes dynamically correcting the gain parameter value during measurement, thereby ensuring that the instrument accurately measures the signal frequency while obtaining an accurate flow rate value.

5. The low-power pulse acquisition and wireless transmission method as described in claim 1, characterized in that, Before the device is activated, only the Bluetooth module is in a standby state, with no other additional power consumption.

6. The low-power pulse acquisition and wireless transmission method as described in claim 1, characterized in that, The subject performs a continuous blowing operation. When more than 5 pulse data are detected consecutively, it is determined that this is a continuous blowing operation.

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