539 results about "Pulsed wave" patented technology

The invention provides a sleep monitoring model training method, a sleep monitoring method and equipment. The method is applied to radar signal processing. The method comprises the following steps: acquiring a data set S1 and a data set S2; a pure radar feature extractor M3 is trained by using a pre-trained teacher network model M2 and the data set S1, the teacher network model M2 fuses the radar data and the pulse wave data in the data set S1 and outputs fused feature data, and the pure radar feature extractor M3 performs feature extraction on the radar data in the data set S1 and outputs radar feature data; training a bimodal sleep monitoring model M4 and a pure radar modal sleep monitoring model M5 by using the data set S2, and determining first sleep stage and / or respiratory event information by a first recognition layer according to fusion feature data output by the teacher network model M2, and the second identification layer determines second sleep stage and / or respiratory event information according to the radar feature data output by the pure radar feature extractor M3. According to the invention, the sleep monitoring task is efficiently completed at low cost.

The invention relates to the technical field of medical diagnosis, and discloses a blood oxygen monitoring system fused with sleep rhythm modeling, which comprises the following steps: identifying a sleep stage conversion moment through a photoelectric volume pulse wave signal, detecting a blood oxygen saturation valley value in a window after conversion, and calculating response lag duration; according to the method, the physiological rhythm is converted into a natural probe for the compensatory ability of the respiratory system, dual diagnosis of sleep staging and respiratory function is realized through a single-path signal, and meanwhile, body movement interference is converted into an observation window for the respiratory stress recovery ability. The diagnosis reliability in a home monitoring scene is remarkably improved, the system completes core analysis at an edge node, and a respiratory function evaluation report which can be directly used for clinical decision making is output.

The invention discloses a wearable cardiovascular pressure early warning system, which relates to the technical field of wearable medical health monitoring and comprises wearable equipment, and a signal acquisition module, a signal processing module, a posture self-adaptive module and a communication module which are integrated in the wearable equipment. The signal acquisition module comprises a photoelectric volume pulse wave sensor and an inertial measurement unit and is used for acquiring physiological signals and motion data of a user; the signal processing module is used for extracting pulse wave characteristics based on the signals and judging the motion state and the body position state of the user in combination with data of the inertial measurement unit so as to realize pulse-by-pulse blood pressure estimation and cardiovascular pressure trend analysis; the posture self-adaption module identifies user postures through deep learning and dynamically selects a compensation algorithm according to different postures, so that the signal accuracy is improved. According to the invention, continuous, non-invasive and dynamic monitoring of cardiovascular pressure is realized, and long-term and convenient health state monitoring and risk early warning service can be provided for users.

The invention is suitable for the technical field of intelligent wearable devices, and provides a blood pressure dynamic calibration method and device of an intelligent wearable device and the wearable device. According to the blood pressure dynamic calibration method of the intelligent wearable device, the dual-wavelength pulse wave signal collected by the dual-wavelength PPG sensor is obtained, differential processing is conducted on the dual-wavelength pulse wave signal, the purified pulse wave signal is obtained, the signal-to-noise ratio of the purified pulse wave signal is calculated, and when the signal-to-noise ratio is higher than the threshold value, the blood pressure dynamic calibration of the intelligent wearable device is completed. Extracting a pulse wave characteristic value from the purified pulse wave signal, iterating the vascular elasticity coefficient according to the pulse wave characteristic value to obtain an iterative vascular elasticity coefficient, and outputting a first calibrated blood pressure value according to the pulse wave characteristic value and the iterative vascular elasticity coefficient. According to the embodiment of the invention, motion artifacts are effectively suppressed through differential processing of the dual-wavelength PPG sensor, the signal-to-noise ratio of signals is increased, and the problem that the blood pressure measurement error is large due to noise interference and blood vessel elastic fixation when a traditional intelligent wearable device is in a motion state is solved.

The invention discloses an integrated pediatric vital sign intelligent monitoring and early warning method and system, and relates to the technical field of biomedical signal processing. The method is used for solving the problems of large monitoring interference and early warning lag in a dynamic environment. The method comprises the following steps: firstly, synchronously collecting a multi-modal signal to generate a motion intensity envelope signal and an R wave peak value interval sequence, carrying out orthogonal projection denoising on a photoelectric volume pulse wave signal by utilizing motion envelope based on a recursive least square algorithm, and outputting a reconstructed blood oxygen waveform; then, calculating a cross correlation coefficient of a heart rate trend and a motion envelope, quantifying a physiological coupling degree to generate an independent heart rate anomaly index, and accurately identifying a non-motion related risk; finally, the real-time blood oxygen value is analyzed, the index is used for dynamically increasing the low oxygen threshold value so as to tighten the alarm boundary, physiological parameter linkage grading early warning is achieved, and the recognition sensitivity of the compensation period risk is improved while interference resistance is guaranteed.

The invention relates to the technical field of intelligent medical instruments, and discloses a closed-loop electro-acupuncture therapeutic apparatus based on heart and brain coupling information feedback. The device comprises a forehead electroencephalogram signal acquisition module, a single-lead electrocardio acquisition module, a Bluetooth transmission module, a signal preprocessing module, an ECG and EEG feature extraction module, a dynamic coupling analysis module, an embedded XGBoost classifier and an electroacupuncture control module. According to the system, collected EEG and ECG signals are wirelessly transmitted through Bluetooth, HRV indexes and EEG frequency band power spectral density are extracted after preprocessing, and frequency domain coherence analysis is carried out to obtain heart and brain bidirectional coupling characteristics. The embedded XGBoost classifier outputs optimal electroacupuncture stimulation parameters based on the characteristics, and the electroacupuncture control module generates corresponding bidirectional pulse waves for stimulation. According to the therapeutic apparatus, closed-loop feedback control is achieved, therapeutic parameters can be dynamically optimized, the individuation and precision level is improved, and meanwhile safety is ensured through impedance monitoring and electrical isolation.

The invention discloses a non-invasive wearable vascular arteriosclerosis assessment system and method based on multi-mode pulse wave signal fusion, and belongs to the field of vascular function assessment. The system comprises a distributed acquisition front end, a butterfly-shaped flexible substrate, an integrated double-accelerometer, a four-wavelength LED (530nm / 660nm superficial blood vessel measurement), a 810nm / 940nm deep artery measurement device, a double-photodiode, a double-impedance electrode and a pressure sensor. The central integrated control end processes a multi-mode signal and realizes pressure-LED current closed-loop control; the upper computer terminal extracts the multi-modal pulse wave time difference of the limbs and the neck, the local and regional pulse wave conduction velocity and the blood oxygen hemoglobin change parameters induced by the standardized posture, the dimension is reduced to 30 through principal component analysis, then the parameters are input into the random forest regression model, and the vascular elasticity index is output. Signal stability is improved through flexible fitting, single-source limitation is solved through multi-modal fusion, signal quality is guaranteed through closed-loop control, sensitivity is enhanced through dynamic physiological excitation, and accuracy and universality of arteriosclerosis assessment are improved.

The invention discloses a pressure adjusting method and system for a pressure air gun for drying, and relates to the technical field of pressure air gun adjusting.The method comprises the steps that pressure distribution data and drying effect parameters of the surface of a dried object are collected in real time; the drying effect parameters are input into a reinforcement learning and quantum annealing collaborative decision model, a dynamic pressure adjusting strategy is generated, and the dynamic pressure adjusting strategy comprises control parameters of a pressure value, a waveform frequency and a nozzle direction; an air gun is controlled to output a target pressure waveform according to the dynamic pressure adjusting strategy, the target pressure waveform is generated based on the 3D geometrical characteristics of the drying object, and the impedance of an internal flow channel of the air gun is adjusted in real time through a magnetorheological fluid strategy; in the drying process, three-section mode switching is triggered according to the real-time water content and surface roughness data, chaos frequency modulation pulse waves are output in the initial stage to peel off water, fractal diffusion waves are switched in the middle stage to achieve uniform coverage, and nanometer resonance waves are adopted in the final stage to complete drying.

The invention relates to a device for performing electric field treatment on a digestive tract. The device comprises a catheter, a support body, an electrode array film and a pulse generator, the pulse generator comprises a current sensor for sensing current flowing through the electrode pair; in the initial time period, the voltage amplitude of the back pulse in the first sequence of pulse waves is larger than the voltage amplitude of the front pulse, and when the current sensor senses that the current is equal to or exceeds the lower limit value IS (MIN) of the set range, the absolute value US of the voltage amplitude of each pulse in the second sequence of pulse waves is equal in the next time period. The amplitude of the output voltage of the pulse generator is controlled through feedback of the current sensor, and the therapeutic instrument is safer for a human body during treatment.

Systems and methods are disclosed for blood pressure analysis. In some examples, a system receives sensor data from a sensor during a time period to monitor a blood pressure wave signal in the sensor data. The system inflates a cuff (worn by a patient) with a gas until a characteristic of the pulse wave signal crosses a characteristic threshold from a first side to a second side at a first time within the time period. The cuff is at a first pressure at the first time. The system deflates the cuff until the characteristic of the pulse wave signal crosses the characteristic threshold from the second side to the first side at a second time within the time period. The cuff is at a second pressure at the second time. The system identifies a blood pressure value corresponding to the patient as being between the first pressure and the second pressure.

The invention relates to the technical field of biomedical engineering. The invention discloses a triggering method and device of magnetic resonance imaging equipment based on multi-modal signal fusion, terminal equipment and a storage medium. The accuracy of triggering the magnetic resonance imaging equipment to collect images can be improved. The method comprises the following steps: acquiring a first morphological characteristic of a heart vibration signal of a target object, a second morphological characteristic of a jugular vein pulse signal and a third morphological characteristic of a photoelectric volume pulse wave signal; constructing a heterogeneous graph based on the first morphological feature, the second morphological feature and the third morphological feature; performing global graph feature vector extraction processing on the heterogeneous graph by adopting a heterogeneous graph attention network to obtain a target global graph feature vector; and performing time prediction processing on the target global map feature vector by adopting a trigger control model to obtain target time, and triggering magnetic resonance imaging equipment to collect images when the target object is in the middle and later period of cardiac diastole based on the target time.

The invention discloses a cerebral apoplexy recurrence risk monitoring method and device and a medium, and relates to the technical field of medical health monitoring, the cerebral apoplexy recurrence risk monitoring method comprises the following steps: according to a preparation result, collecting electroencephalogram, oxyhemoglobin saturation, electrocardio, pulse waves and acceleration signals, synchronously recording timestamps, and generating multi-modal physiological data; performing de-noising processing and feature extraction on the multi-modal physiological data to generate de-noised feature data; performing multi-modal feature fusion on the de-noised feature data by adopting a convolutional neural network to generate a multi-modal feature vector, identifying feature signal modes of epilepsy, brain structures and brain diseases according to the multi-modal feature vector, calculating a cerebral apoplexy recurrence risk score, and generating a risk score result and an anomaly identification report; and carrying out risk grade division on the risk scoring result and the abnormity identification report according to a recurrence risk threshold value and a personalized judgment rule, and generating risk early warning information and personalized intervention suggestions. According to the invention, real-time and explainable risk early warning information is provided for clinicians and patients.

The invention belongs to the technical field of biological signal processing and monitoring, and particularly relates to a multi-mode-based non-contact heart rate intelligent monitoring method which comprises the steps that a ballistocardiogram signal of a user is collected through a piezoelectric film sensor, meanwhile, a photoelectric volume pulse wave signal of the user is collected through a photoelectric sensor, and a multi-mode physiological signal is formed; performing space-time alignment processing on the multi-modal physiological signal, eliminating low-frequency breathing interference and motion noise by adopting an adaptive filtering algorithm, and outputting a pre-processed signal; inputting the preprocessed signal into a space-time coupling feature analysis engine, extracting time sequence features through a bidirectional long-short-term memory network, and extracting spatial features through a full convolutional network; adopting a multi-head self-attention mechanism to carry out dynamic weight fusion on the time sequence features and the spatial features to obtain fusion features; and calculating a real-time heart rate value based on the fused features, and judging a heart rate abnormal state. The problem that the heart rate monitoring difficulty is large is well solved.

The invention provides a flexible wearable multi-physiological-parameter monitoring device, and relates to the technical field of wearable medical instruments.The garment body comprises a flexible conductive fiber layer, a sensing center layer and an elastic protection layer which are attached to the human body; the sensor module in the sensor central layer is connected with the control module, and the power supply module is connected with the sensor module and the control module; the sensor module collects bioelectricity signals of a human body and transmits the bioelectricity signals to the control module, and the control module analyzes and processes the bioelectricity signals to obtain physiological parameters; a sensor in the sensor module is made of a flexible electronic material, the sensor module comprises a body temperature acquisition module, a blood pressure and blood oxygen acquisition module and an electrocardio acquisition module, and the blood pressure and blood oxygen acquisition module acquires a blood pressure signal and a blood oxygen signal by utilizing a photoelectric volume pulse wave tracing method. The equipment is high in integration level, comprehensive and dynamic monitoring of human health indexes is achieved, the accuracy of physiological parameter reading and monitoring result obtaining is improved, the wearing comfort is improved, and the equipment is suitable for the outdoor environment.

The invention discloses a video pulse wave extraction method based on progressive self-supervised learning, and the method comprises the steps: 1, preprocessing a face video clip, and obtaining an original signal; 2, processing the original signal by using a signal enhancement strategy to obtain an enhanced signal, and forming a positive sample pair with the original signal; 3, constructing a deep learning model capable of adaptively quantifying the contribution weight of the global domain of interest; 4, decomposing a video pulse wave extraction task into a signal extraction sub-task and a noise suppression sub-task, constructing a two-stage time-frequency domain joint loss function, and performing progressive self-supervised training; and 5, calling the pre-trained model to recover a high-quality pulse wave signal from the to-be-detected original signal to realize heart rate monitoring. According to the method, the deep learning model can be self-supervised and trained without a true value signal label, video pulse wave extraction is achieved, meanwhile, complex environment noise is restrained, the generalization performance of the model in a real scene is improved, and development of a non-contact health monitoring technology is promoted.

The invention discloses a device and system for conducting electric field treatment on the digestive tract, the device for conducting electric field treatment on the digestive tract comprises a slender catheter, a supporting body located at the far end of the catheter, an electrode array film and a pulse generator, the electrode array film and the pulse generator are arranged on the supporting body, and the output end of the pulse generator is coupled with an electrode pair on the electrode array film. A sequence pulse wave output by the pulse generator comprises a plurality of groups of nanosecond pulse strings, and the time interval between the adjacent nanosecond pulse strings is 1us-10000 us; the nanosecond pulse string is composed of a plurality of nanosecond pulse pairs, and the time interval between every two adjacent nanosecond pulse pairs ranges from 50 ns to 10000 ns; the nanosecond pulse pair comprises positive pulses and negative pulses which appear alternately, the pulse width of the positive pulses and the pulse width of the negative pulses are 10-1000 ns, and the time interval is 10-1000 ns. The cell membrane permeability and the cell death efficiency can be remarkably improved, and the limitation of the traditional IRE technology is broken through.

A wearable display device includes: a housing formed in a ring shape or a cylindrical shape, a display panel disposed in a ring shape or a cylindrical shape inside the housing, and for emitting light in a first direction from an inner side of the display panel and receiving light incident to the inner side to detect a first light-sensing signal and for emitting light in a second direction from an outer side of the display panel and receiving light incident to the outer side to detect a second light-sensing signal, a main driver circuit for detecting a pulse wave signal of a user and measuring biometric information of the user by using the first light-sensing signal, and sensing the movement of a touch by a part of the user's body by using the second light-sensing signal, and a wireless communication module for transmitting the biometric information of the user.

The application discloses an energy-saving control method of a CSR high-frequency PWM rectifier circuit. According to the value change of each line voltage of three-phase alternating current in a rectifier circuit and the characteristic that the rectifier circuit works at a high frequency, the two pulse wave edges of two phases of the three-phase alternating current are overlapped. The overlapping time of the overlapping of the two pulse wave edges is equal to the sum of the turn-on time and the turn-off time of a switching tube, so that the front edge or the rear edge of a pulse of a switching signal is in a soft switching state or in a cut-off low voltage state, thereby reducing the switching process loss of the switching tube. The application provides the energy-saving control method of the CSR high-frequency PWM rectifier circuit, which can reduce switching loss, reduce cost, save energy, prolong service life and is safe and reliable.

The invention relates to the technical field of physiological signal processing, and discloses a millimeter wave radar multi-dimensional physiological feature decoupling heart failure early warning system and method, and the method comprises the steps: configuring a millimeter wave radar to transmit a dual-beam frequency modulation continuous wave signal, collecting human body reflection echoes, and generating a multi-channel original digital signal matrix; generating a chest region and acra region phase signal, an overall reflection signal amplitude sequence and an overall phase drift signal after spatial isolation enhancement through distance-Doppler combined processing; decoupling to obtain a beat-by-beat heartbeat interval sequence, a pulse wave transmission time sequence and a daily net body fluid variation sequence; obtaining a rule engine risk level and a machine learning early warning sign, and determining a final risk assessment level through fusion decision; synchronous high-precision collection and decoupling of non-contact multi-dimensional physiological parameters are achieved, and accuracy and specificity of heart failure decompensation early warning are improved through double-layer model fusion.

The invention discloses a pressure monitoring method and device based on wearable equipment and electronic equipment. The method comprises the following steps: acquiring current photoelectric plethysmography (PPG) signals corresponding to a plurality of channels collected by wearable equipment; based on the current PPG signals corresponding to the multiple channels, candidate pulse wave sequences corresponding to the multiple channels are determined, and the candidate pulse wave sequences comprise multiple pulse waves of the corresponding channels; determining a target pulse wave sequence from the candidate pulse wave sequences corresponding to the multiple channels based on the pulse wave continuity evaluation results and the pulse wave quality evaluation results corresponding to the multiple channels; performing feature extraction on the target pulse wave sequence to obtain current heart rate variability features; and determining a current pressure monitoring result according to the current heart rate variability characteristic. According to the invention, the technical problem of low pressure monitoring accuracy and reliability of wearable equipment in a dynamic environment in the prior art is solved.

The invention discloses a non-invasive blood pressure monitoring system and method.The non-invasive blood pressure monitoring system comprises a pulse wave collecting module, an electrocardio collecting module and a control module.The pulse wave collecting module is used for collecting pulse wave signals; the electrocardio acquisition module is used for acquiring electrocardio signals; the control module is used for obtaining blood pressure according to the pulse wave signals and the electrocardiosignals and based on a built-in blood pressure prediction model. The non-invasive blood pressure monitoring system can collect pulse waves and electrocardiosignals to predict blood pressure, the defects that traditional blood pressure measuring equipment is inconvenient to wear and poor in real-time performance can be overcome, and meanwhile the problem that the error is large when the blood pressure is predicted through the pulse waves is solved. The invention further discloses a non-invasive blood pressure monitoring method based on the pulse waves.

The invention relates to a multi-sensor fused vital sign and motion posture monitoring system and method. The system comprises a photoelectric volume pulse wave acquisition module, an electrocardio acquisition module, an inertia measurement module, a synchronization module, an artifact suppression module, a contact state recognition module, a data quality evaluation module, a vital sign extraction module and an anomaly detection module. Synchronously acquiring a photoelectric volume pulse wave signal, an electrocardiosignal and motion information; suppressing motion artifacts in the photoplethysmography signal and / or the electrocardiosignal based on the motion information; identifying the contact state and generating a data quality indicator related to the measurement reliability in combination with the de-artifact physiological signal; when the data quality meets a preset condition, heart rate, oxyhemoglobin saturation and / or breathing information are extracted, and vital sign parameters are formed; and carrying out conjoint analysis on the artifact-removed physiological signal and the motion information, and marking heart rate rhythm abnormity and / or posture abnormity. According to the invention, the reliability and availability of vital sign monitoring can be improved.

The invention discloses a method for detecting a fatigue state based on a multi-modal data fusion technology, and the method comprises the following steps: S1, collecting multi-modal training data through a sleep deprivation experiment, and carrying out the training of a model. Comprising fNIRS, ECG, PPG, GSP and Resp, hemoglobin concentration data, obtained through a fNIRS headband, of the forehead lobe of the brain is obviously related to fatigue, data of electrocardio, pulse waves, skin electricity and respiratory waves are obtained through an electrocardio sensor (pectoral girdle), a PPG bracelet, a GSR ring and a respiratory wave (Resp) sensor (waistband), the data collected by different devices are objective, the defects of psychological experiment methods are effectively overcome, and the psychological experiment accuracy is improved. And different modalities can provide complementary information, and even capture the features of the target from multiple angles.

The invention discloses an inpatient alarm bracelet system and method based on multi-parameter vital sign monitoring, and relates to the technical field of inpatient alarm bracelets. Matching corresponding vital sign parameter initial weights from a preset disease-parameter sensitivity mapping library, wherein the vital sign parameters comprise heart rate, respiratory rate, oxyhemoglobin saturation, body temperature and heart rate variability; the method comprises the following steps: establishing an individualized physiological fluctuation baseline model based on vital sign data collected at the initial stage of wearing in combination with a resting state time period identified by an acceleration sensor, and generating a dynamic reference interval; collecting photoelectric volume pulse waves, electrocardiosignals, body temperature and acceleration data, judging whether motion artifacts exist or not by analyzing the spectrum correlation between physiological signals and motion signals, and generating a signal quality mark; and calling the initial weight and the dynamic reference interval under the condition that the signal quality mark indicates that the data is valid.

The invention relates to the field of facial paralysis rehabilitation stimulation, and provides a facial paralysis rehabilitation treatment mask integrating adjustable pulse electrical stimulation and a control system. A flexible electrode plate group and at least two groups of acupoint targeting electrode units are arranged on the inner side of the mask body corresponding to a facial paralysis treatment acupoint area; the first electrode group corresponds to Yangbai acupoint and temple areas; the second electrode group corresponds to the area of the Dizheng point and the area of the cheek-car point; the snap-fastener type electric connection interface is arranged at the edge of the outer side of the mask and is connected with each electrode group through a wire; the micro electrical stimulation therapeutic instrument outputs an adjustable pulse electric signal to the electrode group through the button interface; the micro electrical stimulation therapeutic apparatus comprises a pulse generation module, and pulse waves comprise dense waves, sparse waves and discontinuous waves.

An ultrasound imaging system (100) may automatically analyze a pulse wave Doppler spectrogram to determine high quality and low quality cardiac cycles. Based on the determination, the ultrasound imaging system (100) may exclude the low quality cardiac cycle from being used in calculations of parameter measurements such as peak systolic velocity, end diastolic velocity, and resistance index. In some examples, the ultrasound imaging system (100) may provide a visual indication on the display (138) which cardiac cycles were excluded from the measurements.

The invention discloses a smart watch arrhythmia early warning method and system based on deep learning. The method comprises the steps that firstly, PPG signals are collected through a photoelectric volume pulse wave sensor, and denoising and standardization processing are conducted through an adaptive filtering algorithm; then, the heart beat position is recognized through a wavelet transform peak value detection algorithm, and a heart rate variability feature sequence is obtained; converting the one-dimensional heart rate variability feature sequence into a two-dimensional heart rhythm image by using an improved Gramian angular field transformation algorithm; and training an arrhythmia classification model by adopting a ResNet-50 convolutional neural network to realize automatic identification of different types of arrhythmia. And finally, continuous monitoring and timely alarming are realized through a sliding window technology and an early warning mechanism. The key technical problems of low detection precision, poor real-time performance, high equipment cost, poor user experience and the like in the existing arrhythmia detection technology are effectively solved, and an innovative solution is provided for heart rhythm health monitoring of the intelligent wearable equipment.

The present application relates to the technical field of medical equipment, in particular to an automatic calibration method, a cardiac output monitoring method, a device and a monitoring device, the method comprising: acquiring a pulse wave signal of a target monitoring object; extracting at least one signal feature of the pulse wave signal; and determining a target correction factor based on the at least one signal feature. The signal feature is determined by using the pulse wave signal of the target monitoring object, and in the calibration process, the at least one signal feature is combined for processing, so that the target correction factor is automatically calibrated, thereby improving the reliability of the monitoring result.

The invention relates to the field of non-invasive monitoring, and particularly provides a method for evaluating vascular elasticity through radial artery pulse waves. The method comprises the following steps that 1, radial artery pulse waves are obtained; step 2, preprocessing the radial artery pulse wave to obtain an average pulse period; 3, calculating a dominant wave angle based on the average pulse period; step 4, calculating pulse duration based on the average pulse period; step 5, calculating rise time based on the average pulse cycle; step 6, calculating a main wave amplitude based on the average pulse period; step 7, calculating a waveform area based on the average pulse period; and 8, establishing an evaluation model, inputting the dominant wave angle, the pulse duration, the rise time, the dominant wave amplitude and the waveform area into the evaluation model, and outputting a vascular elasticity predicted value by the evaluation model. According to the method, the accuracy of predicting the vascular elasticity is high, and the cost is low.

The invention discloses a pulse wave signal detection-oriented transimpedance amplifier circuit with input voltage clamping and current offset functions, and relates to the technical field of integrated circuit design, the pulse wave signal detection-oriented transimpedance amplifier circuit comprises a pseudo-differential structure, a current offset module and a photosensitive diode, the pseudo-differential structure is composed of two independent operational amplifiers with double-end input and single-end output, the trans-impedance amplifier of a pseudo-differential structure composed of two independent operational amplifiers with double-end input and single-end output is used, the same voltage is connected to the same-direction input end of the trans-impedance amplifier, voltage clamping is carried out on double-end input, the differential mode precision and low-frequency stability of an input virtual site are improved, differential mode imbalance and flicker noise caused by operational amplifier mismatch are eliminated, and the stability of the trans-impedance amplifier is improved. The dynamic range of the pulse wave detection system is improved, and the pulse wave detection system has the advantages of high-precision and wide-range ambient light suppression effect, high circuit reliability, low circuit complexity, easy implementation, high loop stability, small area and low power consumption.