Blood oxygen real-time monitoring system based on photoelectric volume pulse wave

Abstract

The invention relates to the technical field of medical diagnosis, and discloses a real-time blood oxygen monitoring system based on photoelectric volume pulse waves, which is characterized in that vasomotor response is induced through periodic thermal excitation, and physiological pulse waves are demodulated from thermal modulation signals by utilizing a synchronous lock-in amplification technology. A background signal which is regarded as invalid noise in traditional monitoring is converted into an analyzable vital sign carrier, non-invasive evaluation of microcirculation functions is realized through a thermal response index, an early screening means is provided for peripheral vasculopathy, the system maintains medical-level precision, and meanwhile, the accuracy of the system is improved. And the engineering feasibility of consumption-level equipment is realized by a very simple hardware architecture.

Description

Technical Field

[0001] The invention relates to a real-time blood oxygen monitoring system based on photoplethysmography, belonging to the technical field of medical diagnosis. Background Art

[0002] In the field of medical monitoring, photoplethysmography (PPG) blood oximetry (O2) monitoring technology faces a long-standing challenge. Its effectiveness relies on the presence of a recognizable pulse wave signal in the measured tissue. When a patient is in a state of silent hypoperfusion, such as shock, hypothermia, or severe peripheral circulatory dysfunction, the physiological signal strength falls below the detection threshold. Traditional systems face a dilemma: they can either misinterpret noise as valid signal and output false values, or simply abandon monitoring, resulting in the loss of critical vital signs. Current mainstream solutions typically rely on multi-wavelength optical filtering, inertial sensor fusion, and complex signal processing algorithms to improve the signal-to-noise ratio in low-perfusion states. However, these methods primarily rely on passively extracting pulse signals from background noise. In critical care settings, such as those with peripheral circulatory dysfunction caused by diabetes, pulse signals can easily be drowned out by noise. To improve the ability to identify weak signals, existing systems often require the integration of highly sensitive sensors and high-performance processing modules. This increases the complexity and cost of system design, making it difficult to balance the hardware resource and energy efficiency constraints of consumer-grade products.

[0003] Although some studies have attempted to use methods such as deep learning to improve robustness to noise, such methods often face problems such as large computing resource consumption and high inference latency in actual deployment, making it difficult to achieve real-time processing on resource-constrained edge devices. Further analysis shows that the existing technical system has three deep bottlenecks: 1. Physiological signals and noise are regarded as opposing entities, and the convergence of their energy levels under extreme working conditions is ignored, resulting in a lack of signal regeneration ability; 2. Focusing on blood oxygen value extraction, it fails to explore the dynamic response characteristics of vascular networks to physical stimuli, resulting in the loss of high-value clinical data such as microcirculation function assessment; 3. In order to improve the accuracy of weak signal detection, it falls into a vicious cycle of hardware stacking-soaring computing power-out-of-control costs, which deviates from the principle of universal medical care.

[0004] Of particular note, in dynamic scenarios such as vascular elasticity degradation (such as hypertension) or pathological response variations (such as Raynaud's syndrome), existing solutions lack an adaptive mechanism for shifting physiological response characteristics, further deteriorating their measurement robustness. This technical bottleneck not only restricts critical care capabilities but also hinders the feasibility of implementing home health management scenarios. Therefore, the technical challenge addressed by this invention is to develop a blood oxygen monitoring mechanism that transcends signal presence dependence, simultaneously achieves physiological parameter acquisition and vascular function assessment, and meets the constraints of consumer-grade engineering. Summary of the Invention

[0005] The present invention provides a real-time blood oxygen monitoring system based on photoplethysmography, the main purpose of which is to solve the problems of failure to capture vital sign signals in silent hypoperfusion state, lack of vascular function assessment and insufficient implementation of medical equipment engineering.

[0006] To achieve the above objectives, the present invention provides a real-time blood oxygen monitoring system based on photoplethysmography, the system comprising: a photoplethysmography signal acquisition unit configured to transmit a light signal to a measured tissue region and receive a reflected or transmitted light signal from the measured tissue region to obtain an original photoplethysmography mixed signal; a thermal excitation unit, disposed adjacent to the photoplethysmography signal acquisition unit, and configured to periodically apply safe microthermal excitation to the measured tissue region according to a preset square wave drive frequency, wherein the safe microthermal excitation induces periodic dilation and contraction of blood vessels in the measured tissue region, thereby amplitude-modulating the physiological pulse wave signal contained in the original photoplethysmography mixed signal; A signal processing unit is electrically connected to the photoplethysmography signal acquisition unit and is configured to: receive a raw photoplethysmography mixed signal; input the raw photoplethysmography mixed signal into a phase-locked amplifier module, the phase-locked amplifier module being configured to perform phase-locked processing on the raw photoplethysmography mixed signal and a reference reference signal having a square wave drive frequency and being phase-synchronized with the drive signal of the thermal excitation unit, so as to demodulate a physiological pulse wave signal from the raw photoplethysmography mixed signal and amplify its amplitude; calculate the blood oxygen saturation of the measured tissue area based on the demodulated and amplified physiological pulse wave signal; and quantitatively determine the microcirculatory perfusion state of the measured tissue area based on the relationship between the real-time drive energy of the thermal excitation unit and the envelope amplitude of the demodulated and amplified physiological pulse wave signal.

[0007] Preferably, the thermal excitation unit includes a chip resistor, which is configured to receive a periodic electric pulse current from a pulse current driving module to generate safe trace thermal excitation.

[0008] Preferably, the thermal stimulation unit is configured to generate safe micro-thermal stimulation by periodically overdriving the light emitting diodes themselves in the photoplethysmography signal acquisition unit at a square wave driving frequency.

[0009] Preferably, the phase-locked amplification module is configured to implement phase-locked processing by the following steps: performing point-by-point multiplication operation on the original photoplethysmography mixed signal and the reference base signal, and then performing digital low-pass filtering on the result of the multiplication operation.

[0010] Preferably, the signal processing unit is further configured to: continuously monitor the envelope amplitude of the demodulated and amplified physiological pulse wave signal to calculate in real time the vascular thermal response index reflecting the intensity of the response of the measured tissue area to thermal excitation; and, the signal processing unit is configured to adaptively adjust the driving energy of the thermal excitation unit based on the comparison result of the vascular thermal response index with a preset optimal interval to stably maintain the vascular thermal response index within the preset optimal interval.

[0011] Preferably, the vascular thermal response index is calculated as follows: ,in, represents the vascular thermal response index, It represents the average value of the envelope amplitude of the demodulated and amplified physiological pulse wave signal within the preset duration window. It represents the average thermal actuation energy applied to the thermal actuation unit within the same preset duration window.

[0012] Preferably, the signal processing unit is further configured to: obtain a residual noise signal by subtracting the demodulated and amplified physiological pulse wave signal from the original photoplethysmography mixed signal; calculate the complexity index of the residual noise signal within a continuous time window, and the complexity index is obtained by calculating the standard deviation of the first-order difference of the residual noise signal; and when the complexity index continuously and unidirectionally deviates from an established individual baseline fluctuation range, trigger an early warning signal, which indicates that the measured tissue area may be at risk of physiological instability.

[0013] Preferably, the square wave driving frequency ranges from 0.1 Hz to 0.5 Hz.

[0014] Preferably, the safe micro-thermal stimulation causes the local temperature fluctuation of the measured tissue area to range from 0.05 degrees Celsius to 0.5 degrees Celsius.

[0015] Preferably, the system also includes an energy management unit configured to dynamically adjust the power supply of the thermal excitation unit according to real-time instructions of the signal processing unit, so as to maintain the total power consumption of the system within a preset energy-saving threshold range while ensuring safe trace thermal excitation efficiency.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. By injecting a preset frequency of micro-thermal excitation into the measured tissue, the vascular network in an extremely low perfusion state produces a periodic dilation and contraction response. Synchronous phase-locked amplification technology is used to capture the physiological pulse wave modulated by the thermal excitation, and the background signal, which is regarded as invalid noise in traditional monitoring, is converted into a resolvable vital sign carrier. This active detection mechanism enables the system to stably obtain pulse waveforms even in extreme working conditions such as peripheral circulatory failure, avoiding the risk of false alarms or missed diagnoses caused by conventional equipment when the signal is overwhelmed.

[0017] 2. Based on the dynamic coupling relationship between thermal excitation energy and demodulated signal amplitude, the system generates a thermal response index that reflects vascular reactivity. This parameter quantitatively characterizes the state of peripheral vasomotor function by monitoring the intensity of the tissue's physiological response to a standard thermal perturbation. This mechanism, which combines detection energy with physiological feedback, enables simultaneous microcirculatory perfusion assessment during blood oxygen monitoring, providing an early screening method for vascular diseases such as diabetic foot and Raynaud's syndrome. When pathological fluctuations in vascular reactivity occur, the system tracks changes in the demodulated signal envelope amplitude in real time and dynamically adjusts the thermal excitation energy through closed-loop feedback. This self-calibration mechanism keeps the phase-locked amplification link within the linear operating range, avoiding the idealized reliance of traditional active detection technology on physiological response consistency and ensuring monitoring continuity even in dynamic pathological conditions such as vasospasm.

[0018] 3. The system extracts complexity indicators from the residual signal after phase-locked processing. By analyzing its persistent trend of deviation from the individualized baseline, it captures the nonlinear dynamic characteristics of the cardiopulmonary compensatory system before instability. This early warning mechanism based on signal entropy change can identify latent hypoxia risks before the blood oxygen value drops significantly, thus creating a critical intervention window for critical care. The thermal excitation unit reuses light source components or standard chip resistors to achieve energy injection, and the signal demodulation process is completed using basic multiplication and addition operations. The vascular response assessment and risk warning functions share the original signal processing pipeline. The minimalist design of this hardware architecture and the cross-functional reuse of computing resources enable the system to achieve the engineering feasibility of consumer-grade devices while maintaining medical-grade performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a flowchart of the real-time blood oxygen monitoring system based on photoplethysmography of the present invention; Figure 2 This is a curve diagram of the change of the vascular thermal response index (VTRI) of the present invention; Figure 3 This is a signal processing and evaluation framework diagram of the real-time blood oxygen monitoring system of the present invention; Figure 4 This is a workflow diagram of the real-time blood oxygen monitoring system based on photoplethysmography of the present invention.

[0020] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0021] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0022] The embodiment of the present application provides a real-time blood oxygen monitoring system based on photoplethysmography. In a clinical scenario requiring continuous blood oxygen saturation monitoring and microcirculatory function assessment for patients in a silent hypoperfusion state, the system can operate specifically as follows: by actively applying periodic thermal excitation to induce a vasomotor response in the measured tissue area, and using synchronous phase-locked amplification technology to accurately demodulate the physiological pulse wave from the thermally modulated signal, thereby solving the challenge of traditional monitoring methods in obtaining signals in a hypoperfusion state, and converting the background signal that was originally regarded as invalid noise into a resolvable vital sign carrier. At the same time, the system can also perform non-invasive assessment of microcirculatory function through the thermal response index, providing an early screening method for peripheral vascular disease; the system includes a photoplethysmography signal acquisition unit, a thermal excitation unit, and a signal processing unit. The photoplethysmography signal acquisition unit is configured to transmit an optical signal to the measured tissue area and receive a reflected or transmitted optical signal from the measured tissue area to obtain the original photoplethysmography. The pulse wave mixed signal unit typically consists of at least one light-emitting diode (LED) and at least one photodetector. The LED emits light of a specific wavelength. This light penetrates or reflects off the tissue being measured, is received by the photodetector, and converted into an electrical signal, forming a mixed signal containing physiological pulse wave information, environmental noise, and information about the vasomotor response induced by thermal stimulation. In engineering implementations, the photoplethysmography (PP) signal acquisition unit is typically designed as a wearable sensor, such as a finger clip or wristband, to ensure a stable optical path and comfortable wear. The thermal stimulation unit is positioned adjacent to the PPG signal acquisition unit and is configured to periodically apply safe microthermal stimulation to the measured tissue region at a preset square wave drive frequency. This safe microthermal stimulation induces periodic dilation and contraction of blood vessels within the measured tissue region, thereby amplitude-modulating the physiological pulse wave signal contained in the original PPG mixed signal. Furthermore, the square wave drive frequency of the periodic thermal stimulation primarily affects the effectiveness of the vasomotor response and the real-time nature of monitoring. If the frequency is too high, the blood vessels may not fully respond due to physiological delays, resulting in a weakened modulation effect. If the frequency is too low, the real-time monitoring will be reduced and may cause discomfort to the user. Taking all factors into consideration, setting the frequency within the range of 0.1 Hz to 0.5 Hz can ensure effective modulation while meeting the requirements of real-time and comfort. One specific implementation of the thermal excitation unit is to include a chip resistor, which is configured to receive a periodic electric pulse current from a pulse current drive module to generate safe micro-thermal excitation; another implementation is that the thermal excitation unit is configured to generate safe micro-thermal excitation by periodically overdriving the light-emitting diodes in the photoelectric volumetric pulse wave signal acquisition unit at a square wave drive frequency; this method of multiplexing light-emitting diodes can further simplify the hardware architecture and reduce costs.

[0023] The signal processing unit is electrically connected to the photoplethysmography signal acquisition unit, which is configured to receive the original photoplethysmography mixed signal. The received mixed signal is then input into a phase-locked amplifier module. The phase-locked amplifier module is configured to perform phase-locked processing on the original photoplethysmography mixed signal and a reference reference signal having a square wave driving frequency and phase-synchronized with the thermal excitation unit driving signal, so as to demodulate the physiological pulse wave signal from the original photoplethysmography mixed signal and amplify its amplitude. The phase-locked amplifier module is configured to achieve phase-locked processing through the following steps: performing point-by-point multiplication operation on the original photoplethysmography mixed signal and the reference reference signal, and then performing digital low-pass filtering on the result of the multiplication operation. This combination of multiplication and low-pass filtering is a classic phase-locked amplification technology, which can effectively extract the pulse wave signal in phase with the reference frequency from the noise background. Based on the demodulated and amplified physiological pulse wave signal, the signal processing unit calculates the blood oxygen saturation of the measured tissue area. The calculation of blood oxygen saturation usually adopts the light absorption rate ratio method of red light and infrared light, and converts it through a preset calibration curve or algorithm model. The stability and high signal-to-noise ratio of the demodulated physiological pulse wave signal are the basis for accurate calculation of blood oxygen saturation; the signal processing unit is further configured to quantitatively determine the microcirculation perfusion state of the measured tissue area based on the relationship between the real-time driving energy of the thermal excitation unit and the envelope amplitude of the demodulated and amplified physiological pulse wave signal. To achieve this function, the signal processing unit continuously monitors the envelope amplitude of the demodulated and amplified physiological pulse wave signal to calculate in real time the vascular thermal response index reflecting the response intensity of the measured tissue area to thermal excitation. The vascular thermal response index is calculated as follows: = ,in, represents the vascular thermal response index, Indicates the average value of the envelope amplitude of the demodulated and amplified physiological pulse wave signal within the preset duration window represents the average thermal excitation energy applied to the thermal excitation unit within the same preset duration window; the signal processing unit is configured to adaptively adjust the driving energy of the thermal excitation unit according to the comparison result of the vascular thermal response index with a preset optimal interval, so as to stably maintain the vascular thermal response index within the preset optimal interval. The fundamental technical consideration for setting the preset optimal interval is to achieve a technical optimization balance between ensuring that the vascular thermal response index can sensitively reflect the changes in the microcirculation perfusion state and avoiding excessive thermal stimulation or insufficient stimulation. If the upper limit of the preset optimal interval is set too high, it may cause the system to apply excessive thermal excitation energy in order to achieve the high value, thereby excessively sacrificing the patient's comfort. On the contrary, if the lower limit is set too low, the vascular response may be too weak in the low perfusion state, making the change of the vascular thermal response index unclear, thereby excessively sacrificing the sensitivity and diagnostic accuracy of microcirculation perfusion assessment. Therefore, in specific engineering practice, the determination of the optimal interval is not an isolated absolute value, but needs to be based on the physiological characteristics of the measured tissue, the system's detection sensitivity requirements for microcirculation changes, and combined with clinical experience to set it within a reasonable engineering range that can optimize the overall technical effect. This adaptive adjustment mechanism can ensure that the system can maintain optimal monitoring performance in different individuals and different physiological states.

[0024] The signal processing unit is further configured to obtain a residual noise signal by subtracting the demodulated and amplified physiological pulse wave signal from the original photoplethysmography mixed signal, and calculate the complexity index of the residual noise signal in a continuous time window. The complexity index is obtained by calculating the standard deviation of the first-order difference of the residual noise signal. The fundamental technical consideration for calculating the complexity index is to achieve a technical optimization balance between effectively characterizing the randomness or disorder of the signal and avoiding misjudgment of normal physiological fluctuations. If the calculation method or threshold setting of the complexity index is too sensitive, normal physiological noise or small non-pathological fluctuations may be misjudged as physiological state instability, thereby excessively sacrificing the specificity of the warning and leading to frequent false alarms; on the contrary, if its setting is too slow, it may occur when the physiological state has already appeared. Failure to identify signs of instability in a timely manner will excessively sacrifice the sensitivity and timeliness of the warning, and may miss the critical intervention window. Therefore, in specific engineering practice, the determination of the complexity index is not an isolated absolute value, but needs to be based on the statistical characteristics of the residual noise signal, the clinical definition of physiological instability, and the system's demand for early warning. It should be set within a reasonable engineering range that can optimize the overall warning efficiency. When the complexity index continuously and unidirectionally deviates from an established individual baseline fluctuation range, the system will trigger an early warning signal. The warning signal indicates that the measured tissue area may have a risk of physiological instability. This early warning mechanism based on the complexity of the residual noise signal can identify the risk of latent hypoxia before the blood oxygen saturation value drops significantly, thereby gaining a key intervention window for critical care.

[0025] The system also includes an energy management unit configured to dynamically adjust the power supply of the thermal excitation unit according to the real-time instructions of the signal processing unit, so as to maintain the total power consumption of the system within the preset energy-saving threshold range while ensuring the effectiveness of safe micro-thermal excitation. The fundamental technical consideration of the power supply adjustment of the energy management unit is to achieve a technical optimization balance between ensuring the effectiveness of safe micro-thermal excitation and maintaining the total power consumption of the system within the preset energy-saving threshold range. If the power supply is set too high, it may cause the total power consumption of the system to exceed the preset energy-saving threshold, thereby excessively sacrificing the portability and battery life of the device, which is not in line with the requirements of consumer-grade devices. Engineering constraints; on the contrary, if it is set too low, it may lead to insufficient thermal excitation, affecting the amplitude and stability of vasoconstrictor response, thereby excessively sacrificing the effective modulation of physiological pulse waves and the accuracy of microcirculatory perfusion assessment. Therefore, in specific engineering practice, the determination of the power supply is not an isolated absolute value, but needs to be set according to the characteristics of the thermal excitation unit, the system's power consumption restrictions, and the demand for thermal excitation effects. It is within a reasonable engineering range that can optimize the overall technical effect. This unit can ensure that while providing effective thermal excitation, it can maximize the optimization of system energy efficiency to meet the low power consumption requirements of consumer-grade devices.

[0026] At the same time, in the specific deployment and implementation of the present invention, the system workflow is strictly divided into a one-time offline calibration phase and a continuous online monitoring phase. In the offline calibration phase, its core goal is to provide a vascular thermal response index. Establishing a universal optimal working range, this process uses a tissue simulator that can accurately control the perfusion rate of internal blood simulant fluid through a precision pump. After the calibration process is started, the system is driven by a fixed, low level of thermal excitation energy, while the perfusion rate gradually decreases linearly from the level simulating normal circulation. The signal processing unit continuously records the demodulated physiological pulse wave signal noise ratio and the synchronously calculated When the signal-to-noise ratio drops to a preset critical point where the basic morphological features of the pulse wave can no longer be stably identified, the corresponding The value is defined and stored as the lower bound of the optimal interval , the upper limit of the interval It is set to 90% of the average index value measured in a healthy resting state. This setting is intended to retain sufficient dynamic response space and avoid unnecessary adjustments to small normal physiological fluctuations.

[0027] When the system is applied to a specific individual and online monitoring is started, it will first automatically enter a five-minute individualized baseline establishment phase. During this period, the system assumes that the individual being tested is in a physiologically stable state and continuously calculates the complexity index of the residual noise signal. The specific calculation process of the complexity index is: perform a first-order difference operation on the residual noise signal, and then calculate the standard deviation of the difference sequence within a two-second sliding time window. After the end of five minutes, the system will store the arithmetic mean of all complexity index values ​​during this period. and standard deviation Based on this, a quantitative individual baseline fluctuation range was formally established, with an upper limit of , the lower limit is .

[0028] After the baseline is established, the system seamlessly switches to real-time closed-loop monitoring and early warning mode. In this mode, the signal processing unit executes a fixed set of internal algorithm logic with a calculation cycle of every two seconds. First, it accurately calculates the vascular thermal response index of the previous cycle. The calculation formula is: , in this formula, It is clearly defined as the arithmetic mean of the amplitude of the demodulated and amplified physiological pulse wave signal envelope within the past two-second time window; It is defined as the total thermal excitation energy obtained by time-integrating the product of the driving current and voltage applied to the thermal excitation unit within the same time window. The optimal range established during the offline calibration phase For comparison, if Lower than , the energy management unit will instruct the thermal excitation unit to increase its driving energy by a preset minimum step size; if Higher than , it instructs the system to decrease the step size by the same amount; if it falls within this range, the current energy is maintained. This regulation logic ensures that detection sensitivity is always optimal. Simultaneously, the system synchronously calculates the latest residual noise complexity index and compares it with the established individual baseline fluctuation range. The warning triggering condition is strictly set: the system only triggers the warning signal when it continuously detects five or more complexity index values, all on the same side of the baseline fluctuation range (i.e., all above the upper limit or all below the lower limit). This series of operations is based on the systematic parameter setting of the digital low-pass filter in the phase-locked amplifier module. The filter's cutoff frequency is set to one-tenth of the thermal excitation drive frequency to thoroughly filter out high-order harmonic interference, and its equivalent time constant is set to 30 seconds. This is designed to ensure sensitive tracking of minute-level microcirculatory state changes while smoothing out meaningless transient noise, achieving an optimal trade-off between signal smoothness and physiological response tracking speed.

[0029] Example 1: In a specific implementation scenario, when a patient is in a silent hypoperfusion state, such as in the early stages of shock or in a hypothermic environment, their peripheral blood flow velocity slows significantly, making it difficult for traditional photoplethysmography detection equipment to capture effective physiological pulse wave signals. The system is often unable to monitor blood oxygen saturation because the signal strength is below the detection threshold, which in turn prevents the clinician from obtaining key vital sign data in a timely manner. To address this technical challenge, the present system can operate as follows: the thermal excitation unit in the system periodically applies safe micro-thermal excitation to the measured tissue area based on a preset square wave drive frequency. This thermal stimulation is not intended to directly change blood oxygen saturation, but rather to convert an otherwise difficult-to-detect silent physiological state into a dynamic response that can be actively sensed by the system. Specifically, this micro-thermal excitation can induce periodic relaxation and contraction in the vascular network in a hypoperfused state. Even under extremely low perfusion conditions, it can induce weak but periodic volume changes in the vascular wall. This periodic relaxation and contraction acts on the original photoplethysmography mixed signal, causing the physiological pulse wave signal contained in it to be The signal is amplitude modulated, a modulation effect that transforms background signals, traditionally considered ineffective noise, into interpretable vital sign signals. Subsequently, the phase-locked amplifier module in the signal processing unit receives this raw photoplethysmography mixed signal and phase-locks it with a reference signal whose frequency is the square wave drive frequency and is phase-synchronized with the thermal excitation unit's drive signal. The phase-locked amplifier module is configured to perform point-by-point multiplication of the raw photoplethysmography mixed signal and the reference signal, then digitally low-pass filter the multiplication result to demodulate the physiological pulse wave signal from the raw photoplethysmography mixed signal and amplify its amplitude. The active modulation of the thermal excitation unit provides the phase-locked amplifier module with a clear modulation frequency and phase reference, enabling it to specifically capture the physiological pulse wave information actively marked by thermal excitation. This combination of active modulation and synchronous demodulation allows the periodic characteristics generated by thermal modulation to be effectively extracted and amplified even when the physiological pulse wave's intensity is extremely low, avoiding the detection blind spots of traditional methods when signal strength is insufficient.

[0030] Based on the demodulated and amplified physiological pulse wave signal, the system can accurately calculate the blood oxygen saturation of the measured tissue area. At the same time, the system does not stop at a single blood oxygen monitoring. The signal processing unit further continuously monitors the envelope amplitude of the demodulated and amplified physiological pulse wave signal and calculates the vascular thermal response index based on the relationship between the real-time driving energy of the thermal excitation unit and the envelope amplitude of the demodulated and amplified physiological pulse wave signal. The vascular thermal response index is calculated as follows: ,in, represents the vascular thermal response index, It represents the average value of the envelope amplitude of the demodulated and amplified physiological pulse wave signal within the preset duration window. It represents the average thermal excitation energy applied to the thermal excitation unit within the same preset duration window. This index quantitatively characterizes the physiological response intensity of peripheral blood vessels to standard thermal disturbances, thereby simultaneously realizing the assessment of microcirculatory perfusion status during blood oxygen monitoring. Through thermal excitation, signal acquisition and microcirculatory function assessment are unified under the same physical excitation and signal processing architecture. The signal processing unit adaptively adjusts the driving energy of the thermal excitation unit based on the comparison result of the vascular thermal response index with a preset optimal interval to stably maintain the vascular thermal response index within the preset optimal interval. This closed-loop feedback mechanism ensures that the intensity of thermal excitation always matches the real-time responsiveness of the measured tissue, avoiding both discomfort caused by excessive excitation and failure of signal modulation due to insufficient excitation. It achieves adaptation to dynamic changes in vascular reactivity and ensures the continuity and robustness of monitoring. The system also has early warning capabilities. The signal processing unit subtracts the demodulated and amplified physiological pulse wave signal from the raw photoplethysmography mixed signal to obtain a residual noise signal. For this residual noise signal, the system calculates its complexity index within a continuous time window. The complexity index is obtained by calculating the standard deviation of the first-order difference of the residual noise signal. When the complexity index continuously and unidirectionally deviates from an established individual baseline fluctuation range, the system triggers a warning signal, indicating that the measured tissue area may be at risk of physiological instability. This warning, based on the nonlinear dynamic characteristics of the residual signal, can provide an earlier warning than traditional blood oxygen value declines, creating a critical intervention window for critical care. This architecture integrates active detection, synchronous demodulation, physiological assessment, and early warning functions, achieving medical-grade accuracy with a minimalist hardware configuration. It provides an implementation paradigm with inherent robustness and broad application prospects for consumer medical devices to accurately monitor and intervene early in complex physiological conditions.

[0031] Example 2: This example constructs a test platform consisting of a precision syringe pump, a tissue simulator with an adjustable blood perfusion rate, and a prototype of the monitoring system of the present invention. The tissue simulator integrates a microfluidic channel network with optical properties highly similar to those of human tissue. The precision syringe pump pumps a blood-simulating fluid into the simulator at a controllable rate, accurately reproducing the physiological and pathological processes from normal peripheral circulation to severe hypoperfusion. In this experiment, the setting of key parameters follows a rigorous engineering decision-making logic chain. For example, the square wave drive frequency of the thermal excitation unit must be set to strike an optimal balance between ensuring effective induction of vasomotor responses and avoiding excessively long monitoring periods. The fundamental technical consideration for this frequency selection is that if the frequency is too high, vascular smooth muscle may not be able to fully relax and contract due to its inherent physiological response delay, resulting in a weakened amplitude modulation effect on the physiological pulse wave, thereby reducing the signal-to-noise ratio of the subsequent phase-locked demodulation. Conversely, if the frequency is too low, the single measurement time is prolonged, sacrificing the ability to track rapid changes in vital signs in real time. Based on this technical trade-off, in order to achieve the best balance between the effectiveness of the induced response and the real-time monitoring, this experiment sets the driving frequency to 0.2 Hz. This value is not only within the above-mentioned preferred range of 0.1 Hz to 0.5 Hz, but also ensures that a complete modulation and demodulation cycle can be completed every five seconds. Similarly, the cut-off frequency setting of the digital low-pass filter in the phase-locked amplifier module is essentially a trade-off between the smoothness of the output signal and the response speed of the system to changes in physiological state. In order to effectively filter out noise components that are not related to the 0.2 Hz reference frequency and ensure that the minute-level microcirculation perfusion state changes can be tracked, the equivalent time constant of the filter is set to 50 seconds. This value is much larger than the excitation signal period, thereby ensuring the stable and accurate extraction of the demodulated signal envelope amplitude. After the test process is started, the flow rate of the precision injection pump is first set to 5.0 ml per minute to simulate normal peripheral perfusion in a healthy state. At this stage, the system The system ran steadily for five minutes to establish a physiological baseline. At this point, a clear pulse waveform was observed in the raw photoplethysmography mixed signal. Subsequently, the syringe pump flow rate was abruptly reduced to 0.5 ml / minute to simulate a state of silent hypoperfusion, and this state was maintained for continuous monitoring. During this transition, a crucial phenomenon was observed: as the perfusion volume dropped sharply, the traditional pulse wave AC component in the raw signal, driven by pulsation, rapidly decayed. Within two minutes, its amplitude was submerged in background noise and could not be effectively identified. This accurately replicated the signal loss dilemma that traditional photoplethysmography devices inevitably face under such operating conditions. However, the system of the present invention, through active thermal excitation and synchronous phase-locked demodulation, successfully extracted a physiological pulse wave signal clearly marked by a 0.2 Hz frequency from the noise. Although its amplitude decreased, its morphology remained stable and resolvable. The exemplary data in the following table quantitatively solidify this key evidence.

[0032] Table 1: Comparison of pulse wave signal characteristics and vascular thermal response indicators under different perfusion states.

[0033] The above data reveals the inherent technical mechanism of the present invention. In the low perfusion state, the failure of traditional signals is due to the excessively weak pulsating changes in blood volume. The present system actively induces responsive contraction and relaxation of blood vessels by applying periodic micro-thermal excitation, converting the passive and weak physiological pulsation into a signal modulated by a specific frequency amplitude that can be targeted and identified. The phase-locked amplifier module utilizes this active marker to accurately demodulate and amplify the signal from the noise background under conditions of extremely low signal-to-noise ratio. Furthermore, the vascular thermal response index drops sharply from 0.95 under normal perfusion to 0.20 under low perfusion. This change is not a simple attenuation of the signal amplitude, but a change in the physiological response amplitude by the demodulated signal. With constant excitation energy applied The quantitative index obtained by normalization calculation objectively reflects the significant decrease in the ability of blood vessels to respond to standard thermal disturbances, thereby realizing a direct and non-invasive assessment of the microcirculatory perfusion status.

[0034] Example 3: This example combines Figures 1 to 4 , a real-time blood oxygen monitoring system based on photoplethysmography is described. Figure 1 As shown in the figure, the system workflow starts from the thermal excitation unit, which generates a periodic thermal excitation signal to periodically apply micro-thermal excitation with an excitation frequency of 0.1-0.5Hz. Then, the PPG acquisition unit is responsible for collecting the photoplethysmography signal, including the original photoplethysmography mixed signal, which includes the physiological pulse wave signal, environmental noise and vasoconstriction response information induced by thermal excitation. After being compared with the synchronous reference standard signal, the signal enters the phase-locked amplifier module for signal demodulation and amplification. After demodulation, the physiological pulse wave signal is obtained. The signal processing unit further processes the demodulated signal and calculates the blood oxygen saturation and vascular thermal response index ( ) to evaluate the microcirculatory perfusion status; during this process, the system dynamically adjusts the energy of the thermal excitation unit according to real-time monitoring data to ensure the accuracy and stability of signal acquisition. Through this system, reliable blood oxygen monitoring data can be obtained under extremely low perfusion conditions, and microcirculatory function evaluation can be achieved.

[0035] like Figure 2 As shown in the figure, the horizontal axis represents time (minutes) and the vertical axis represents the vascular thermal response index ( ), the figure clearly shows the different vascular response states Changes; Under normal perfusion conditions, The value is 0.95, which is in the normal perfusion area. As the perfusion volume gradually decreases, The value drops rapidly and enters a silent hypoperfusion state. The value is about 0.20, which is lower than the lowest value range of 0.4. The curve also marks the optimal range (0.4-0.8). This range represents the ideal range of normal vascular response. Within this range, the vascular response is healthy and stable. The data in the figure reflects the dynamic changes of blood vessels under different perfusion states, which can provide an intuitive basis for the evaluation of vasoconstriction function and microcirculation status, especially in low perfusion state. Changes in vascular reactivity can effectively monitor vascular reactivity and provide data support for early intervention.

[0036] like Figure 3 As shown in the figure, in this system, the thermal excitation unit first generates a periodic thermal excitation signal, and the reflected or transmitted light signal is collected by the PPG acquisition unit. These signals include the original photoelectric volume pulse wave mixed signal, which contains the physiological pulse wave signal modulated by thermal excitation. Then, the system is supported by a synchronous reference signal to demodulate and phase-lock the signal, and input it into the phase-locked amplifier module. The phase-locked amplifier module extracts the effective physiological pulse wave signal by demodulating and amplifying the signal, and finally sends it to the signal processing unit. The signal processing unit further calculates the blood oxygen saturation and vascular thermal response index ( ), the signal processing unit also performs microcirculation function evaluation and early warning based on the characteristics of the residual noise signal and the signal processing results. One of the key technologies of signal processing is analysis based on the demodulated waveform, which further provides data support for the calculation of blood oxygen saturation and the evaluation of the vascular thermal response index. In addition, through complexity analysis based on the residual noise signal, the system can realize the early warning function of physiological instability and provide important auxiliary decision-making information for clinicians.

[0037] like Figure 4As shown in the figure, first, the photoplethysmography signal acquisition unit is responsible for emitting light signals to the measured tissue area and receiving reflected or transmitted light signals from the area, thereby obtaining the original photoplethysmography mixed signal, which contains physiological pulse wave signals, background noise and vasoconstriction response information induced by thermal excitation. In order to process the signal, a thermal excitation unit is set up in the system. The thermal excitation unit periodically applies safe trace thermal excitation to the measured tissue area at a square wave driving frequency (0.1~0.5Hz) through a chip resistor (or LED), thereby inducing periodic relaxation and contraction of blood vessels and modulating the original photoplethysmography signal. Then, the signal processing unit inputs the obtained original signal into the phase-locked amplifier module, which is synchronized with the reference reference signal and is obtained by point-by-point multiplication. The system extracts the physiological pulse wave signal from the noise through the demodulated and amplified signals and amplifies the amplitude. The signal processing unit calculates the blood oxygen saturation based on these demodulated and amplified signals, and also uses the vascular thermal response index to evaluate the microcirculation perfusion state. The signal processing unit also adjusts the driving energy of the thermal excitation unit in real time according to the comparison result of the vascular thermal response index with the preset optimal interval, so as to ensure that the vascular response index is stable within the optimal range. In addition, the system also includes an energy management unit, which dynamically adjusts the power supply of the thermal excitation unit according to the instructions of the signal processing unit to ensure the thermal excitation efficiency while keeping the total power consumption of the system within the energy-saving range. Through this structure, the system realizes real-time processing and efficient detection of blood oxygen monitoring and microcirculation function evaluation under low perfusion state.

[0038] Example 4: In this embodiment, first, the optimal range of the vascular thermal response index and its closed-loop feedback adjustment mechanism are determined. The specific implementation procedures can be decomposed into the following steps. Before the system is applied to a specific type of measured tissue or population, a one-time offline calibration process can be performed. This process uses a tissue simulator to precisely control the perfusion rate from a normal level. During this process, the system continues to operate with an initial, low constant thermal excitation energy and records the changes in the vascular thermal response index with the perfusion rate. When the technicians drop the signal-to-noise ratio of the demodulated physiological pulse wave signal to a preset engineering critical point where the key feature points of the waveform cannot be stably identified, the corresponding vascular thermal response index value is defined as the lower limit of the preset optimal range, and the upper limit of the range is set to the average index value measured in a healthy resting state. A predetermined percentage position, such as 90 percent, is set to retain redundancy for normal physiological fluctuations and avoid unnecessary adjustments. After the system enters real-time monitoring, the internal logic of the signal processing unit follows a clear, step-by-step adjustment rule: at fixed time intervals, such as every ten seconds, it calculates the average value of the vascular thermal response index over the past ten seconds and compares this average value with the set optimal range. If the average value is below the lower limit, the signal processing unit generates an instruction to increase the driving energy of the thermal excitation unit by a fixed minimum step size; if it is above the upper limit, it is instructed to decrease it by the same step size; if it is within the range, it is instructed to maintain the current energy unchanged. This series of operations concretizes the functional description of adaptive adjustment into a discrete, rule-based, and directly executable control process.

[0039] Secondly, for the physiological instability warning function based on residual noise complexity, its core individual baseline establishment and warning triggering logic can be concretized as follows: when the system starts to monitor a new individual, it will automatically enter an initialization baseline establishment phase, which lasts for a preset time that is sufficient to cover normal physiological fluctuations, such as five minutes. During this period, the system assumes that the subject is in a relatively stable physiological state and continuously calculates the complexity index of the residual noise signal. After the end of this phase, the system stores the arithmetic mean and standard deviation of all complexity index values ​​during this period. Based on these two statistics, a quantified individual baseline fluctuation range is established, and its upper limit is defined as The standard deviation of the mean value is added with a preset multiple (for example, three times), and the lower limit is the mean value minus the standard deviation of the same multiple. After the baseline is established, the system enters the continuous monitoring and early warning mode. The judgment logic of the early warning trigger is strictly defined as: when the system detects that the calculated values ​​of the complexity index for a specific number of consecutive times (for example, five times) or more are all on the same side of the baseline fluctuation range, that is, all above the upper limit, or all below the lower limit, the early warning signal is formally generated and triggered. The combination of this continuous counting and unidirectional deviation condition converts the description of continuous and unidirectional deviation into a judgment procedure that can be executed unambiguously by the microprocessor and achieves a technical balance between sensitivity and specificity.

[0040] Furthermore, regarding how the energy management unit cooperates with the signal processing unit to achieve an optimal balance between ensuring efficiency and maintaining low power consumption, its internal decision-making mechanism is as follows: the signal processing unit calculates the currently required target thermal excitation energy based on the closed-loop feedback algorithm of its vascular thermal response index, and transmits this target value to the energy management unit. The energy management unit internally solidifies an absolute energy-saving threshold representing the upper limit of the system power consumption. Its decision-making logic is a priority limitation mechanism: the energy management unit compares the received target thermal excitation energy with this absolute energy-saving threshold. If the target energy is lower than or equal to the threshold, the energy management unit will accurately regulate the power supply to the thermal excitation unit according to the target value. However, if the target energy exceeds the energy-saving threshold, the energy management unit will no longer follow the target, but will forcibly limit the power supply to a level equal to the energy-saving threshold. Through this peak-shaving processing mechanism, the system ensures that the total power consumption does not exceed the preset limit under any circumstances, and prioritizes meeting the energy-saving engineering constraints under extreme working conditions.

[0041] Finally, the parameter setting of the digital low-pass filter in the phase-locked amplifier module aims to strike a balance between filtering out noise and retaining valid physiological changes. The core parameter of the filter, namely its cutoff frequency, is selected primarily based on the principle that it must be significantly lower than the reference thermal excitation square wave drive frequency. Specifically, the cutoff frequency can be set to one-tenth of the drive frequency or lower to ensure thorough filtering of the modulated carrier frequency and its higher harmonics. At the same time, the cutoff frequency cannot be too low, otherwise it will oversmooth and obscure the true physiological information representing the slowly changing microcirculatory state. Therefore, the second selection principle is that the equivalent time constant corresponding to the cutoff frequency must be shorter than the shortest valid physiological change time of interest in the clinical application scenario. For example, it can be set to no longer than half of this shortest valid time. Combined with the specific excitation frequency and clinical monitoring requirements, the optimal filter parameters can be systematically determined without creative effort to ensure the smoothness of the demodulated signal and the speed of response to physiological changes.

[0042] Example 5: In this example, to ensure that the calculation of the vascular thermal response index has clear engineering feasibility, the envelope amplitude of the physiological pulse wave signal is defined as the average amplitude of the demodulated signal within a continuous ten-second time window, in millivolts, to reflect the instantaneous response intensity of the tissue to standard thermal stimulation. The thermal stimulation energy is obtained by time-integrating the product of the pulse current and voltage, in millijoules, representing the actual total energy applied to the thermal stimulation unit within the same time window. The sampling frequency is preferably set to one hundred times per second to ensure the dynamic resolution of amplitude changes. It can be flexibly configured at the software level according to different application scenarios. This definition method can achieve cross-individual comparison without introducing complex parameters and has good engineering universality.

[0043] To further clarify the setting principle of the filter parameters in the phase-locked amplifier module, it should be ensured that its cutoff frequency is much lower than the reference base frequency used for modulation, so as to effectively suppress the interference of high-order harmonics and background noise. The preferred setting method is less than one-tenth of the driving frequency to clearly define the passband range of the phase-locked demodulation. At the same time, in order to balance the response delay and data smoothness, its equivalent time constant needs to be controlled to be less than half of the shortest period of change of the measured physiological parameters. For example, if the system is for tracking microcirculatory changes at the sub-minute level, it is recommended to set the time constant between thirty seconds and sixty seconds. This setting path not only has a theoretical basis, but also is convenient for setting in a parameterized form during system initialization. It can be deployed in actual hardware without creative work. In addition, it should be noted that in order to truly simulate the photoelectric signal acquisition characteristics under low perfusion conditions, a microchannel structure with an inner diameter of 200 microns can be configured and injected with a simulation medium with tissue-equivalent optical properties, thereby establishing an experimental platform with optical conditions similar to those of human subcutaneous capillaries. Scattering particles of a specific particle size can be added to the simulation medium to reproduce the reflection behavior of red blood cells in the blood. A dual-band light source with a wavelength in the range of 660 nanometers and 940 nanometers is used for signal injection, and a linear-response photoelectric detection component is used for reception, which can effectively restore the change process of the influence of thermal modulation on the signal morphology.

[0044] Example 6: In another specific embodiment of the present invention, first, a clear engineering definition is given for the calculation of the vascular thermal response index VTRI, wherein the envelope amplitude EPPA of the physiological pulse wave signal has its input as the demodulated physiological pulse wave signal time series output by the phase-locked amplifier module, and is processed by performing an arithmetic average operation on the envelope peak value of the signal series within a continuous two-second sliding time window, and its output is a real number representing the current pulse intensity; the thermal excitation energy ETIE has its input as the synchronously recorded instantaneous driving current and voltage values ​​applied to both ends of the thermal excitation unit, and is processed by performing a time integration of the product of the driving current and voltage, i.e., the instantaneous power, within the same two-second time window as EPPA, and its output is a real number in joules representing the total energy injected within the window.

[0045] Secondly, the calibration process of the preset optimal interval is standardized. The lower limit of this interval, VTRImin, is determined with the engineering goal of finding the lowest physiological response boundary at which the system can stably identify the valid pulse wave morphology. The determination process is as follows: using a tissue simulator whose perfusion rate can be controlled by a precision injection pump, the system is started and a fixed initial thermal excitation energy is applied; the perfusion rate is linearly reduced from the level simulating normal circulation in steps of 0.1 ml per minute; at each step, the signal processing unit continuously executes a pulse wave peak detection algorithm and calculates the success rate of the algorithm in successfully identifying the main peak of the pulse wave in the past thirty seconds; when the success rate is continuously lower than 95% for the first time, the system records the corresponding vascular thermal response index value at this moment and defines it as VTRImin.

[0046] Furthermore, the fundamental technical consideration for setting the equivalent time constant of the digital low-pass filter in the phase-locked amplifier module lies in achieving a technically optimal balance between the smoothness of the demodulated signal and the system's response speed to changes in physiological state. If the time constant is set too short, excessive high-frequency noise will remain in the demodulated signal envelope, unduly compromising the stability of subsequent blood oxygen calculation and VTRI assessment. Conversely, if it is set too long, minute-level fluctuations in the actual microcirculatory state will be excessively smoothed, unduly compromising the timeliness of system monitoring. Therefore, in specific engineering practices, the determination of this time constant is not an isolated absolute value, but rather needs to be set based on the square wave drive frequency of the thermal excitation unit. Preferably, it is set to five to ten times the square wave drive period. For example, for a drive frequency of 0.2 Hz, or a period of five seconds, the equivalent time constant can be set between 25 and 50 seconds, ensuring stable demodulation of the modulated signal and effective tracking of physiological changes.

[0047] At the same time, the calculation process of blood oxygen saturation is deepened to eliminate the potential impact of thermal modulation. The input of this process is the two original photoplethysmography mixed signals of red light and infrared light output by the photoplethysmography signal acquisition unit. The processing process first inputs these two signals in parallel to the phase-locked amplifier module. Using the reference signal synchronized with the thermal excitation signal, the physiological pulse wave signals of red light and infrared light are demodulated respectively to obtain the envelope amplitude of their AC components. At the same time, the two original signals are processed by a digital low-pass filter with a cutoff frequency much lower than the heart rate frequency. The final output is obtained by calculating the ratio of the AC envelope amplitude to the DC component of the two signals, then comparing these two ratios to obtain a ratio value. This ratio value is then substituted into a pre-established empirical formula or lookup table based on the calibration of a standard oximeter to calculate the final blood oxygen saturation value. This process ensures that the impact of thermal modulation on the two signals is systematically offset in the final ratio calculation by performing consistent demodulation operations on the two optical signals at the same stage of signal processing, thereby ensuring the accuracy of the blood oxygen calculation results.

[0048] As well as the setting of the absolute energy-saving threshold of the energy management unit, its fundamental technical consideration is to achieve a technical optimization balance between ensuring monitoring performance and meeting the power consumption limits of specific application scenarios. Especially when applied to battery-powered portable or wearable devices, the threshold is directly derived from a comprehensive calculation of the device's battery capacity, target continuous working time and safe discharge specifications. For example, for a wristband device with a goal of working continuously for twenty-four hours, the absolute energy-saving threshold of its energy management unit will be set to ensure that the average value of its total power consumption does not exceed the value obtained by dividing the total battery energy by twenty-four hours. This ensures that the present invention achieves medical-grade monitoring accuracy while complying with the core design constraints of specific products.

[0049] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0050] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A real-time blood oxygen monitoring system based on photoplethysmography, characterized in that: The system comprises: a photoplethysmography signal acquisition unit configured to transmit a light signal to a measured tissue region and receive a reflected or transmitted light signal from the measured tissue region to obtain an original photoplethysmography mixed signal; a thermal excitation unit, disposed adjacent to the photoplethysmography signal acquisition unit, and configured to periodically apply safe microthermal excitation to the measured tissue region according to a preset square wave drive frequency, wherein the safe microthermal excitation induces periodic dilation and contraction of blood vessels in the measured tissue region, thereby amplitude-modulating the physiological pulse wave signal contained in the original photoplethysmography mixed signal; A signal processing unit is electrically connected to the photoplethysmography signal acquisition unit and is configured to: receive a raw photoplethysmography mixed signal; input the raw photoplethysmography mixed signal into a phase-locked amplifier module, the phase-locked amplifier module being configured to perform phase-locked processing on the raw photoplethysmography mixed signal and a reference reference signal having a square wave drive frequency and being phase-synchronized with the drive signal of the thermal excitation unit, so as to demodulate a physiological pulse wave signal from the raw photoplethysmography mixed signal and amplify its amplitude; calculate the blood oxygen saturation of the measured tissue area based on the demodulated and amplified physiological pulse wave signal; and quantitatively determine the microcirculatory perfusion state of the measured tissue area based on the relationship between the real-time drive energy of the thermal excitation unit and the envelope amplitude of the demodulated and amplified physiological pulse wave signal.

2. The real-time blood oxygen monitoring system based on photoplethysmography according to claim 1, characterized in that: The thermal excitation unit includes a chip resistor configured to receive a periodic electric pulse current from a pulse current driving module to generate safe trace thermal excitation.

3. The real-time blood oxygen monitoring system based on photoplethysmography according to claim 1, characterized in that: The thermal stimulation unit is configured to generate safe micro-thermal stimulation by periodically overdriving the light emitting diode itself in the photoplethysmography signal acquisition unit at a square wave driving frequency.

4. The real-time blood oxygen monitoring system based on photoplethysmography according to claim 1, characterized in that: The phase-locked amplifier module is configured to implement phase-locked processing by performing point-by-point multiplication of the original photoplethysmography mixed signal with the reference base signal, and then performing digital low-pass filtering on the result of the multiplication operation.

5. The real-time blood oxygen monitoring system based on photoplethysmography according to claim 1, characterized in that: The signal processing unit is further configured to: continuously monitor the envelope amplitude of the demodulated and amplified physiological pulse wave signal to calculate in real time a vascular thermal response index reflecting the intensity of the response of the measured tissue area to thermal excitation; and, the signal processing unit is configured to adaptively adjust the driving energy of the thermal excitation unit based on a comparison result of the vascular thermal response index with a preset optimal interval to stably maintain the vascular thermal response index within the preset optimal interval.

6. The real-time blood oxygen monitoring system based on photoplethysmography according to claim 5, characterized in that: The vascular thermal response index is calculated as follows: ,in, represents the vascular thermal response index, It represents the average value of the envelope amplitude of the demodulated and amplified physiological pulse wave signal within the preset duration window. It represents the average thermal actuation energy applied to the thermal actuation unit within the same preset duration window.

7. The real-time blood oxygen monitoring system based on photoplethysmography according to claim 1, characterized in that: The signal processing unit is further configured to: obtain a residual noise signal by subtracting the demodulated and amplified physiological pulse wave signal from the original photoplethysmography mixed signal; calculate the complexity index of the residual noise signal within a continuous time window, and the complexity index is obtained by calculating the standard deviation of the first-order difference of the residual noise signal; and when the complexity index continuously and unidirectionally deviates from an established individual baseline fluctuation range, trigger an early warning signal, which indicates that the measured tissue area may be at risk of physiological instability.

8. The real-time blood oxygen monitoring system based on photoplethysmography according to claim 1, characterized in that: The square wave drive frequency ranges from 0.1 Hz to 0.5 Hz.

9. The real-time blood oxygen monitoring system based on photoplethysmography according to claim 1, characterized in that: Safe microcaloric excitation results in local temperature fluctuations in the measured tissue area ranging from 0.05 degrees Celsius to 0.5 degrees Celsius.

10. The real-time blood oxygen monitoring system based on photoplethysmography according to claim 1, characterized in that: The system also includes an energy management unit configured to dynamically adjust the power supply of the thermal actuation unit according to real-time instructions from the signal processing unit.

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