Blood pressure volume tracking system and method based on PPG signals
By integrating multi-wavelength PPG signals and dynamically adjusting pressure, the problems of high signal noise, poor adaptability to individual differences, and insufficient robustness of existing PPG blood pressure monitoring technologies have been solved, achieving high-precision, stable, and continuous blood pressure tracking, which is suitable for wearable devices and clinical applications.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHANXI YIKANG XINYUE MEDICAL INSTR CO LTD
- Filing Date
- 2025-12-30
- Publication Date
- 2026-04-24
AI Technical Summary
Existing PPG-based blood pressure monitoring technologies suffer from high signal noise at the hardware level, difficulty in adapting to individual differences and physiological changes at the algorithm level, and insufficient robustness, resulting in large estimation errors and making it difficult to achieve high-resolution and stable continuous blood pressure monitoring.
Multi-wavelength reflective PPG signals are acquired using green and infrared light sensors. Signal fusion and denoising are performed using a Butterworth filter and a least mean square algorithm. External pressure is applied through a controllable pressure module, and the pressure is adjusted in real time using a PID controller and physiological calibration method. Data fusion is performed using Kalman filtering to achieve continuous blood pressure tracking.
It achieves high-precision and robust continuous blood pressure monitoring, and can stably compensate for physiological and environmental interference in noisy environments, making it suitable for wearable health monitoring devices and clinical support fields.
Smart Images
Figure CN121910345A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of blood pressure monitoring technology, and specifically to a blood pressure volume tracking system and method based on PPG signals. Background Technology
[0002] Photoplethysmography (PPG) is a non-invasive optical technique that measures changes in light absorption on the skin surface to reflect fluctuations in blood volume within the microvascular bed. It is widely used in heart rate, blood oxygen saturation, and blood pressure monitoring. Traditional blood pressure measurement primarily relies on cuff-type blood pressure monitors, which measure systolic and diastolic blood pressure through inflation. While accurate, this method carries risks such as measurement interruptions, user discomfort, and potential vascular damage. With the rise of wearable devices, recent studies have shown that PPG signals contain rich hemodynamic information that can be used for continuous blood pressure estimation, for example, by modeling the correlation between pulse wave transit time (PTT) or waveform characteristics and blood pressure.
[0003] Existing PPG-based blood pressure monitoring technologies, such as cuffless methods based on machine learning models, primarily predict blood pressure by extracting PPG waveform features and combining them with neural networks or regression algorithms. While these methods achieve non-invasive and continuous monitoring to some extent, they still have the following limitations: Hardware limitations: Existing PPG sensors typically use a single wavelength, which is susceptible to skin type, ambient light, and motion artifacts, resulting in high signal noise and an inability to effectively capture deep blood flow information; Algorithm-level shortcomings: Traditional methods rely heavily on fixed feature extraction or static models, which are difficult to adapt to individual physiological differences such as age and gender, as well as dynamic changes caused by posture or activity state, resulting in large estimation errors; Robustness issues: PPG signal amplitude is weak and easily affected by breathing, temperature and light scattering. Although existing learning methods can compensate for some noise, the response is slow and frequent user calibration is required, which limits the application of long-term monitoring.
[0004] Therefore, there is an urgent need for a PPG blood pressure tracking system that simultaneously possesses multi-wavelength signal fusion, low-noise acquisition capabilities, and adaptive dynamic adjustment capabilities, in order to achieve high-resolution and highly stable continuous blood pressure monitoring. Summary of the Invention
[0005] To address the aforementioned shortcomings in the prior art, this invention provides a blood pressure volume tracking system and method based on PPG signals.
[0006] To achieve the above-mentioned objectives, the technical solution adopted by this invention is as follows: In a first aspect, the present invention proposes a blood pressure volume tracking system based on PPG signals, comprising: The PPG signal acquisition module is configured to use a green light sensor and an infrared light sensor to acquire multi-wavelength reflective PPG signals, and to perform signal fusion and noise reduction processing to output AC and DC components. The pressure application module is configured to apply external pressure to the finger in a controllable manner and adjust the magnitude of the external pressure based on the servo system. The signal processing unit, connected to the PPG signal acquisition module and the pressure application module, is configured to estimate the average pressure using the volume oscillation method, adjust the external pressure in real time based on the DC component error using a PID controller, and slowly adjust the DC component set point using a physiological calibration method to achieve continuous blood pressure tracking.
[0007] Optionally, the PPG signal acquisition module includes a Butterworth filter for separating the AC and DC components.
[0008] Optionally, the PPG signal acquisition module is further configured to perform adaptive filtering using the least mean square algorithm, and its weight update formula is: ;
[0009] in, Let n be the filter weights at time point n. Step size factor For error signals, This is the input signal.
[0010] Optionally, the signal processing unit is configured to gradually increase the external pressure in increments of 5-10 mmHg when estimating the average pressure using the volumetric oscillation method, and monitor the point of maximum AC component amplitude, wherein the AC component amplitude is calculated as the peak-to-valley difference. ;
[0011] in, For the amplitude of the communication component, Let be the PPG signal at time t. To find the maximum value function, This is a function that takes the minimum value.
[0012] Optionally, the signal processing unit is configured to approximately lock the external pressure through equivalent compliance when an initial external pressure is applied: ;
[0013] in, For vascular compliance, This represents the change in blood vessel volume. This represents the change in transmural pressure within the blood vessel. For the amplitude of the communication component, External pressure.
[0014] Optionally, the PID controller of the signal processing unit is configured to adjust the pressure based on the error between the setpoint and the measured value of the DC component, specifically: ;
[0015] in, This is the adjustment amount for external pressure. The DC component error at time t is... , , These are the tuning parameters.
[0016] Optionally, the signal processing unit is configured to slowly adjust the DC setpoint using a physiological calibration method, including unloading pressure every 70 heartbeat cycles, and to identify waveform characteristics using an automatic multi-scale peak detection algorithm. The peak position is calculated as follows: ;
[0017] in, Let k be the candidate position for the k-th peak. To maximize the value of a function, the operator corresponding to the argument variable, For the elements of the scale matrix, This represents the total number of scales.
[0018] Optionally, the signal processing unit further integrates Kalman filtering for data fusion, and the state update formula is: ;
[0019] in, For the posterior state estimation at time k, For the prior state estimation at time k, Let Kalman gain be the value at time k. Let k be the measurement value at time k. Let be the observation matrix at time k.
[0020] Optionally, it also includes a data output module connected to the signal processing unit and configured to output the blood pressure tracking results through a communication interface.
[0021] Secondly, this invention proposes a blood pressure volume tracking method based on PPG signals, applied to the aforementioned blood pressure volume tracking system based on PPG signals, comprising the following steps: A green light sensor and an infrared light sensor are used to collect multi-wavelength reflective PPG signals, and the signals are fused and denoised to output AC and DC components. External pressure is applied to the fingers in a controlled manner, and the magnitude of the external pressure is adjusted based on a servo system; The mean pressure is estimated using the volume oscillation method. The external pressure is adjusted in real time based on the DC component error by a PID controller, and the DC component set point is slowly adjusted using a physiological calibration method to achieve continuous blood pressure tracking.
[0022] The present invention has the following beneficial effects: This invention estimates the current mean blood pressure (PPG) of a finger using green and infrared light signals, and combines this with real-time and slow adjustments based on the DC signal and waveform characteristics of the PPG (Pulse Pressure Gauge), achieving continuous, non-invasive blood pressure tracking. The method includes a PPG signal acquisition module, a pressure application module, a signal processing unit, and a data output module. The PPG signal acquisition module uses green light (wavelength 495-570 nm) and infrared light (wavelength 750-1700 nm) sensors to acquire multi-wavelength reflective PPG signals. An adaptive filtering algorithm using the least mean square (LMS) is employed to remove noise and motion artifacts, improving signal quality. The signal processing unit estimates the initial mean pressure based on the volumetric oscillation method, adjusts the applied pressure in real-time using a PID controller, and uses a physiological calibration method combined with an automatic multi-scale peak detection algorithm to slowly adjust the DC setpoint, achieving millisecond-level response and long-term stability compensation. This invention features high precision, high robustness, and good anti-interference performance, and can be applied to wearable health monitoring devices, mobile blood pressure tracking, and clinical support in the future. Attached Figure Description
[0023] Figure 1 This is a schematic diagram of a blood pressure volume tracking system based on PPG signals according to the present invention. Figure 2 This is a schematic diagram illustrating the real-time pressure adjustment principle based on PID control in this invention. Figure 3 This is a schematic diagram illustrating the principle of slow adjustment in physiological calibration in this invention; Figure 4 This is a schematic diagram of a blood pressure volume tracking method based on PPG signals according to the present invention. Detailed Implementation
[0024] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.
[0025] like Figure 1 As shown in the figure, an embodiment of the present invention provides a blood pressure volume tracking system based on PPG signals, comprising: The PPG signal acquisition module is configured to acquire multi-wavelength reflective PPG signals using a green light sensor and an infrared light sensor, and to fuse and denoise the signals, outputting AC and DC components. The pressure application module is configured to apply external pressure to the finger in a controllable manner and adjust the magnitude of the external pressure based on the servo system. The signal processing unit, connected to the PPG signal acquisition module and the pressure application module, is configured to estimate the average pressure using the volume oscillation method, adjust the external pressure in real time based on the DC component error using a PID controller, and slowly adjust the DC component set point using a physiological calibration method to achieve continuous blood pressure tracking.
[0026] In an optional embodiment of the present invention, the PPG signal acquisition module uses a green LED (wavelength 525 nm) and an infrared LED (wavelength 940 nm) as light sources to alternately irradiate the finger (irradiation time 0.4 ms each, with an interval of 0.1 ms). The change in reflected light intensity is measured by a silicon photodetector (such as PD3000) to generate a multi-wavelength PPG signal containing an alternating current (AC) component (pulsatile blood volume change) and a direct current (DC) component (mean blood volume and tissue absorption).
[0027] Signal separation employs a fourth-order Butterworth filter to separate the AC and DC components. The AC component is filtered at frequencies of 0.5–8 Hz, and its transfer function is: ;
[0028] in, This is the cutoff angular frequency. The DC component is extracted using a low-pass filter with a cutoff frequency of 0.1 Hz.
[0029] By fusing green light and infrared signals, noise and motion artifacts are removed through adaptive filtering using the Least Mean Square (LMS) algorithm, thus improving signal quality. The weight update formula is as follows: ;
[0030] in, Let n be the filter weights at time point n. Step size factor For error signals, The input signal is used. This fusion utilizes the shallow sensitivity of green light and the deep penetration of infrared light to ensure a signal-to-noise ratio greater than 25 dB.
[0031] In an optional embodiment of the invention, the pressure application module employs a controllable pressure device, such as a finger-clamp inflatable bladder or a mechanical clamping mechanism, to apply external pressure to the finger, simulating the volume clamp principle. The initial pressure is locked by a servo system to ensure the finger's blood vessels are in an unloaded state (zero transmural pressure), thus stabilizing blood volume. The equivalent compliance is approximately: ;
[0032] in, For vascular compliance, This represents the change in blood vessel volume. This represents the change in transmural pressure within the blood vessel. For the amplitude of the communication component, Using external pressure, the maximum compliance point is selected as the reference to achieve precise control of the pressure range of 0-200 mmHg.
[0033] In an optional embodiment of the present invention, the signal processing unit includes a MAP estimation submodule, a real-time pressure adjustment submodule, a slow DC adjustment submodule, and a data fusion submodule. The core function of this unit is to dynamically analyze and control the pressure of the acquired PPG signal to achieve continuous blood pressure tracking.
[0034] In the MAP estimation submodule, the volume-oscillometric method is used to estimate the current mean systolic pressure (MAP) of the finger. External pressure is gradually increased (starting from 0 mmHg, increasing in steps of 5-10 mmHg), while simultaneously monitoring the amplitude of the AC component of the fused PPG signal; the AC amplitude is calculated as the peak-to-trough difference. ;
[0035] in, For the amplitude of the communication component, Let be the PPG signal at time t. To find the maximum value function, This is a function for minimizing the value. When the AC amplitude reaches its maximum value, this pressure value is the initial MAP estimate. It is calculated within each heartbeat cycle, and the maximum oscillation point (corresponding to the zero transwall pressure state) is determined through envelope analysis. The estimation accuracy is improved by utilizing the shallow sensitivity of green light and the deep penetration of infrared light.
[0036] The real-time pressure adjustment submodule monitors the DC component of the PPG and adjusts the external pressure via a fast servo control loop to maintain the DC signal at the setpoint. A proportional-integral-derivative (PID) controller is used to calculate the error. The pressure is adjusted to: ;
[0037] in, This is the adjustment amount for external pressure. The DC component error at time t is... , , These are tuning parameters. The adjustment is performed in 10 ms cycles, achieving millisecond-level response to compensate for immediate changes in blood flow, respiratory effects, or slight movements.
[0038] The slow DC adjustment submodule uses PPG waveform characteristics (such as AC amplitude, rise time, or bipeak spacing) for periodic calibration. Employing a physiological calibration method, the external pressure is slowly unloaded every 70 heartbeats or per minute (gradually reduced to 0 mmHg, then incrementally increased again) to re-identify the point of maximum AC amplitude and update the DC setpoint. Waveform characteristics are identified using an Automatic Multi-Scale Peak Detection (AMPD) algorithm, and the peak positions are calculated as follows: ;
[0039] in, Let k be the candidate position for the k-th peak. To maximize the value of a function, the operator corresponding to the argument variable, For the elements of the scale matrix, This represents the total number of scales. The adjustment finds the point of maximum AC amplitude, updates the DC setpoint, and applies a smoothing effect through a low-pass filter with a cutoff frequency of 0.1 Hz to compensate for long-term drift, environmental interference, or physiological variations.
[0040] The data fusion submodule further integrates Kalman filtering to fuse multi-wavelength data, and the state update formula is as follows: ;
[0041] in, For the posterior state estimation at time k, For the prior state estimation at time k, Let Kalman gain be the value at time k. Let k be the measurement value at time k. This represents the observation matrix at time k. It improves robustness across different users and supports continuous blood pressure waveform reconstruction.
[0042] In an optional embodiment of the present invention, the system further includes a data output module connected to the signal processing unit and configured to output the blood pressure tracking results through a communication interface.
[0043] The data output module is used to output blood pressure tracking results and waveform data to mobile devices or the cloud. The system can transmit data via Bluetooth, Wi-Fi, or USB interface, and supports real-time visualization and long-term storage.
[0044] This invention also provides a blood pressure volume tracking method based on PPG signals, applied to a blood pressure volume tracking system based on PPG signals described in the above embodiments, comprising the following steps: A green light sensor and an infrared light sensor are used to collect multi-wavelength reflective PPG signals, and the signals are fused and denoised to output AC and DC components. External pressure is applied to the fingers in a controlled manner, and the magnitude of the external pressure is adjusted based on a servo system; The mean pressure is estimated using the volume oscillation method. The external pressure is adjusted in real time based on the DC component error by a PID controller. The DC component set point is adjusted slowly using a physiological calibration method to achieve continuous blood pressure tracking.
[0045] The system and method of this invention can be used in smart bracelets or finger-clip wearable devices, supporting Bluetooth transmission to a mobile app for real-time blood pressure monitoring. Its compact structure and low power consumption make it suitable for daily health monitoring, clinical blood pressure tracking, or scientific research scenarios. Test results show that the mean blood pressure estimation error is less than 5 mmHg, meeting the AAMI standard.
[0046] In summary, this invention, through multi-wavelength PPG signal fusion and dynamic pressure adjustment, not only enables continuous, non-invasive blood pressure tracking, but also provides stable compensation for physiological and environmental interference in noisy environments, offering a new technical approach for mobile health monitoring.
[0047] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0048] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0049] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0050] Specific embodiments have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.
[0051] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of this invention.
Claims
1. A blood pressure volume tracking system based on PPG signals, characterized in that, include: The PPG signal acquisition module is configured to acquire multi-wavelength reflective PPG signals using a green light sensor and an infrared light sensor, and to fuse and denoise the signals, outputting AC and DC components. The pressure application module is configured to apply external pressure to the finger in a controllable manner and adjust the magnitude of the external pressure based on the servo system. The signal processing unit, connected to the PPG signal acquisition module and the pressure application module, is configured to estimate the average pressure using the volume oscillation method, adjust the external pressure in real time based on the DC component error using a PID controller, and slowly adjust the DC component set point using a physiological calibration method to achieve continuous blood pressure tracking.
2. The blood pressure volume tracking system based on PPG signals according to claim 1, characterized in that, The PPG signal acquisition module includes a Butterworth filter for separating the AC and DC components.
3. A blood pressure volume tracking system based on PPG signals according to claim 1 or 2, characterized in that, The PPG signal acquisition module is further configured to use the least mean square algorithm for adaptive filtering, and its weight update formula is as follows: ； in, Let n be the filter weights at time point n. Step size factor For error signals, This is the input signal.
4. The blood pressure volume tracking system based on PPG signals according to claim 1, characterized in that, The signal processing unit is configured to gradually increase the external pressure in increments of 5-10 mmHg when estimating the average pressure using the volumetric oscillation method, and monitor the point of maximum AC component amplitude, where the AC component amplitude is calculated as the peak-to-valley difference. ； in, For the amplitude of the communication component, Let be the PPG signal at time t. To find the maximum value function, This is a function that takes the minimum value.
5. A blood pressure volume tracking system based on PPG signals according to claim 1, characterized in that, The signal processing unit is configured to approximately lock the external pressure upon application of an initial external pressure using equivalent compliance: ； in, For vascular compliance, This represents the change in blood vessel volume. This represents the change in transmural pressure within the blood vessel. For the amplitude of the communication component, External pressure.
6. A blood pressure volume tracking system based on PPG signals according to claim 1, characterized in that, The PID controller of the signal processing unit is configured to adjust the pressure based on the error between the setpoint and the measured value of the DC component, specifically: ； in, This is the adjustment amount for external pressure. The DC component error at time t is... , , These are the tuning parameters.
7. A blood pressure volume tracking system based on PPG signals according to claim 1, characterized in that, The signal processing unit is configured to slowly adjust the DC setpoint using a physiological calibration method, including unloading pressure every 70 heartbeat cycles, and to identify waveform characteristics using an automatic multi-scale peak detection algorithm. The peak position is calculated as follows: ； in, Let k be the candidate position for the k-th peak. To maximize the value of a function, the operator corresponding to the argument variable, For the elements of the scale matrix, This represents the total number of scales.
8. A blood pressure volume tracking system based on PPG signals according to claim 1, characterized in that, The signal processing unit further integrates Kalman filtering for data fusion, and the state update formula is: ； in, For the posterior state estimation at time k, For the prior state estimation at time k, Let Kalman gain be the value at time k. Let k be the measurement value at time k. Let be the observation matrix at time k.
9. A blood pressure volume tracking system based on PPG signals according to claim 1, characterized in that, It also includes a data output module, which is connected to the signal processing unit and configured to output the blood pressure tracking results through a communication interface.
10. A method for blood pressure volume tracking based on PPG signals, applied to a blood pressure volume tracking system based on PPG signals as described in any one of claims 1 to 9, characterized in that, Includes the following steps: A green light sensor and an infrared light sensor are used to collect multi-wavelength reflective PPG signals, and the signals are fused and denoised to output AC and DC components. External pressure is applied to the fingers in a controlled manner, and the magnitude of the external pressure is adjusted based on a servo system; The mean pressure is estimated using the volume oscillation method. The external pressure is adjusted in real time based on the DC component error by a PID controller, and the DC component set point is slowly adjusted using a physiological calibration method to achieve continuous blood pressure tracking.