249 results about "Pulse wave" patented technology

The invention discloses a multi-mode-based flexible wearable heart function monitoring method, system and device, and relates to the technical field of health monitoring, and the method comprises the steps: outputting a multi-mode signal through a flexible patch sensing module when the flexible patch sensing module is arranged in a detection area; wherein the flexible patch sensing module comprises an electrocardio sensor, a pulse wave sensor, a heart sound sensor, a strain sensor and a microfluidic biosensor. According to the invention, high-precision synchronous signal acquisition is realized through flexible patch integrated multi-modal sensing, heart multi-source signal features are adaptively extracted in combination with a multi-scale convolutional neural model, and timing sequence relevance is captured by using a bidirectional long-short-term memory network, so that the accuracy and reliability of heart disease diagnosis are remarkably improved, and the accuracy and reliability of heart disease diagnosis are improved. Meanwhile, non-invasive and continuous monitoring and early pathological screening are supported.

The invention provides a method for collecting finger pulse health data based on a mobile phone camera of a mobile terminal, which comprises the following steps: S1, collecting a video, S2, preprocessing a photoelectric volume pulse wave PPG signal, S3, extracting an original photoelectric volume pulse wave PPG signal, S4, denoising the pulse wave signal, S5, averaging a single-cycle pulse wave, S6, calculating a pulse condition signal threshold-free recurrence plot, and S5, obtaining the finger pulse health data based on the pulse condition signal threshold-free recurrence plot. S7, establishing a pulse condition signal ensemble classification model; and S8, outputting a pulse condition classification analysis result. According to the method, the pulse oscillogram with high characteristic signals is obtained through deep algorithm research, in-depth systematic analysis is carried out on the pulse oscillogram in combination with medical theoretical knowledge, and effective and high-accuracy human health data analysis is established.

The invention provides a continuous identity authentication method based on multichannel PPG signals in an uncontrolled environment. Firstly, a smart watch is used for collecting wrist double-channel green light, red light and infrared light PPG signals and motion sensor data, and original information is obtained. Aiming at the problem that an uncontrolled environment signal is easily interfered, noise reduction and optimization are carried out on the signal through abnormal value processing, FIR high-pass, band-pass and multi-band-pass filtering and ICA independent component analysis, so that motion artifacts are effectively inhibited, and the signal quality is improved. Then, based on pulse wave valley positioning segmentation signals, a multi-channel standardized data set is constructed; and finally, by means of an Inception-LSTM neural network fusing multi-scale feature extraction and time sequence modeling, end-to-end learning of biological features is carried out, and a high-precision identity authentication decision in a dynamic environment is realized. According to the method, the robustness is verified in seven motion state simulation scenes, and the authentication accuracy and reliability in an uncontrolled environment are remarkably improved.

The invention provides a photoelectric volume pulse wave identity recognition method and system, and relates to the technical field of identity recognition, and the method comprises the steps: obtaining a to-be-recognized PPG signal; and inputting the PPG signals into a trained identification model, firstly extracting linear features and nonlinear features, then projecting the features fused by the two features into a feature space by using a learned discriminant projection matrix to obtain multi-view features, and finally classifying the PPG signals by using the multi-view features to obtain an identity identification result. According to the method, manifold regularization and inter-class-error double sparse constraints are combined, the problems of intra-class discretization and inter-class overlapping of a linear model are solved, a graph structure learning method for adaptive local density adjustment is provided, and the manifold modeling precision of non-stationary PPG signals is improved.

The invention relates to the technical field of medical instruments, and particularly provides a non-contact blood oxygen monitoring method and system based on mobile phone direct-current component calibration. The method comprises the following steps: acquiring a hand photoelectric volume pulse wave signal of a target user based on a constructed hand reflective light path of the target user, and extracting a hand direct current component and a hand pulsation component; first face video information of the target user is obtained, a face photoelectric volume pulse wave signal of the target user is collected, and a face direct current component is extracted; constructing a blood oxygen calibration model according to the hand direct current component, the hand pulsation component and the face pulsation component; second face video information of the target user is obtained, a direct current component in the second face video information is extracted and input into the blood oxygen calibration model, and current blood oxygen information of the target user is obtained. Through cooperative work of the front camera and the rear camera, the accuracy of continuous monitoring only depending on the front camera when the mobile phone camera is applied to daily blood oxygen monitoring is improved.

The invention relates to the technical field of vital sign monitoring, in particular to an information interaction control method and system of a vital sign monitor. The method comprises the following steps that physiological signals are synchronously collected through a sensor array, wherein the physiological signals comprise electrocardio waveform data, electric volume pulse wave data, motion acceleration data and body surface temperature data; time alignment is conducted on the electrocardiogram waveform data, the electric volume pulse wave data and the motion acceleration data based on a clock synchronization protocol, matrix construction is conducted, and a synchronous vital sign matrix is generated; carrying out risk change trajectory construction of a pathological trajectory on the filtering data and the historical case data, generating a vital sign risk trajectory, and carrying out super-boundary judgment on the vital sign risk trajectory; by means of the high-precision synchronization mechanism, it is ensured that the internal relevance of electrocardio, pulse waves, movement and temperature data is accurately captured.

The invention discloses a video pulse wave extraction method and system based on automatic noise recognition. The method comprises the steps that a face area is divided into a plurality of sub-areas; calculating the signal-to-noise ratio of each sub-region in the pulse frequency band, and performing weighted fusion on the original pulse signals of each sub-region according to the signal-to-noise ratio; performing ensemble empirical mode decomposition on the fusion signal; according to the peak-to-peak interval variation coefficient, the amplitude stability index and the spectrum purity, determining a noise component dominated by the motion artifact; performing adaptive filtering processing on the fused signal by using an adaptive filter and taking a reference noise signal as input; carrying out distortion detection on the filtered fusion signal, and carrying out signal restoration processing on a detected distortion region to obtain an extracted pulse signal; in order to solve the problem that in the prior art, when video pulse signals are extracted, motion artifacts and physiological signal frequency spectrums are overlapped, and consequently signal separation of a traditional frequency domain filtering method fails, effective signal separation and accurate pulse signal extraction are achieved.

The invention provides a method and a system for reading human body pulse health data based on a face video. The method comprises a method for reading the human body pulse health data and a pulse condition health intelligent detection system. The invention discloses a method for reading human pulse health data based on a face video. The method comprises the steps of S1, collecting the video, S2, positioning and tracking an area of interest, S3, extracting a photoelectric volume pulse wave PPG original signal, S4, carrying out pulse wave signal denoising processing, S5, carrying out pulse wave signal feature analysis, S6, carrying out a mixed feature selection algorithm, S7, carrying out optimal feature classification, and S8, outputting a pulse condition classification analysis result. The pulse condition health intelligent detection system comprises a physiological acquisition layer, a signal transmission layer, a cloud server layer and an application interaction layer. The method is convenient and fast to operate, can visualize the physiological indexes such as the pulse condition of the human body, helps a user of the health detection system to conveniently and timely know the own physiological health condition and timely see a doctor for treatment under the condition that the body has a health problem, and reduces the delay of an illness state.

The invention discloses an intelligent bracelet integrated with photoelectric volume pulse wave detection and a data processing method thereof, and belongs to the field of intelligent bracelets.The intelligent bracelet comprises a host, a display screen is arranged on the upper surface of the host, an acquisition sensor is arranged on the lower surface of the host, and a control knob is arranged in front of the outer surface of the host; through the detachable structure of the watchband, the mounting groove and the inner groove are formed in the left end and the right end of the host and matched with the clamping block, the pinch bar, the spring and the button of the watchband to form a quick dismounting mechanism, the pinch bar can be driven to be separated from the clamping groove of the clamping block by pressing the button, the watchband can be dismounted by hands without tools, and the operation time is shortened to be within 3 seconds; in order to solve the problem that a traditional watchband is tedious to replace and easy to damage, the method comprises the following steps: in a signal preprocessing stage, combining band-pass filtering and adaptive Kalman filtering, and synchronously introducing motion data of an acceleration sensor and a PPG signal signal-to-noise ratio evaluation mechanism, when SNRlt; and the acquisition time is automatically prolonged or a user is prompted to stabilize the hand at 10dB.

The invention provides a filling pipeline leakage monitoring and positioning method, device and equipment and a storage medium, and relates to the technical field of pipeline monitoring. The method comprises the following steps: acquiring time-varying data of pressure in a pipeline through a pressure sensing unit, and identifying leakage triggering characteristics; transmitting a pressure pulse wave at the starting end of the pipeline and receiving an echo signal, and calculating a pressure wave propagation speed under the current working condition according to the echo signal; and the arrival time of the pressure waves arriving at the sensors is extracted, and based on the pressure wave propagation speed and the pressure wave arrival time difference, leakage point coordinates are obtained through calculation. According to the method, the leakage characteristics are rapidly identified through real-time pressure collection, the real-time wave velocity under the current working condition is obtained through the active pulse echo technology, and the wave velocity calculation deviation caused by medium characteristic changes is effectively eliminated; and the actually measured wave velocity and the time difference of arrival are combined for calculation, so that error accumulation in long-distance transportation is overcome, and the precision and reliability of pipeline leakage positioning are remarkably improved.

The present invention relates to the field of intelligent medical technology, and in particular to an arrhythmia diagnosis system based on multi-sensor fusion, the system comprising: an electrocardiogram (ECG) signal module, comprising an ECG signal sensor for collecting ECG signals; a pulse wave signal module, comprising a pulse wave sensor for collecting pulse wave signals; a three-axis acceleration module, comprising an acceleration sensor for collecting acceleration signals; a main control chip module, serving as a data processing module, for receiving and analyzing data to obtain an arrhythmia diagnosis result; a Bluetooth module, serving as a communication module, for transmitting the ECG signal, the pulse wave signal, the acceleration signal, and the arrhythmia diagnosis result to a mobile terminal; and a power management module, comprising a charging, power supply, and switching circuit for providing power supply for the system. The system provided by the present invention is stable, portable, and has low power consumption, and is of great significance for the prevention of cardiovascular diseases and ECG monitoring via the Internet of Things.

The invention discloses a multi-sensor monitoring system and method based on time alignment, and belongs to the technical field of multi-sensor monitoring, and the system comprises a sensor collection module which is used for obtaining an electrocardiosignal, a photoelectric volume pulse wave signal, a heart sound signal and a respiratory impedance signal containing a main clock receiving timestamp; the time alignment module is used for performing acquisition time alignment on the electrocardiosignal, the pulse oximeter signal, the heart sound signal and the respiratory impedance signal containing the main clock receiving timestamp to form the electrocardiosignal, the pulse oximeter signal, the heart sound signal and the respiratory impedance signal which are in time alignment; the multi-modal fusion analysis module is used for extracting local morphological features in the electrocardiosignal, the pulse oximeter signal, the heart sound signal and the respiratory impedance signal after time alignment to form a feature map, and extracting dynamic weights between different signals and between different time points / features in the same signal; according to the invention, the interpretability and accuracy of judgment are improved.

The present application relates to the technical field of medical monitoring, and discloses a portable blood oxygen signal OSA intelligent detection system, which comprises the following steps: collecting a pulse wave signal through a blood oxygen sensor, generating an amplitude difference sequence and a period difference sequence in parallel, analyzing the rhythm synchronism of the two, and determining a respiratory effort event when a real-time relationship index deviates from a reference value. The present application captures the pulse wave timing-amplitude decoupling phenomenon, realizes direct sensing of the specific mode process of the invalid respiratory effort signal, avoids the traditional lag monitoring mode which relies on blood oxygen decline, has the inherent ability to distinguish physiological fluctuations from the specific mode struggle of the signal, and provides a new solution for early screening of mild and moderate OSA.

A processing method and a plasma processing apparatus that apply a pulsed wave of radio frequency power while maintaining plasma density are provided. The processing method uses a plasma processing apparatus having a first electrode and a second electrode, and includes a process of applying a pulsed wave of a first radio frequency power to either of the first electrode or the second electrode, and a process of applying a pulsed wave of a second radio frequency power having a frequency lower than the first radio frequency power to the first electrode with a given phase difference from the first radio frequency power, wherein different first and second on times of the second radio frequency power are controlled in such a manner that the on time of the second radio frequency power does not overlap with the on time of the first radio frequency power, and the first on time is controlled to be off immediately before the first radio frequency power is turned on.

The invention discloses a silicon controlled rectifier dimming device of an LED driving power supply. The silicon controlled rectifier dimming device comprises a voltage transformation unit, a rectification filtering unit, a first switch unit, a first filtering unit, a first voltage stabilization unit, a phase detection module and a control unit, the pre-stage circuit carries out voltage conversion and outputs steamed bun waves subjected to phase cutting control, reflected voltage of the voltage transformation unit is rectified into pulse waves through the rectification unit, the pulse waves are subjected to voltage division through the voltage distribution unit to drive the second switch unit, the pulse waves are converted into square waves with a duty ratio, and the square waves are converted into square waves with the duty ratio. The control unit outputs a corresponding driving waveform to the first switch unit according to the size of the square wave duty ratio, and the first switch unit is driven to carry out voltage chopping, so that the output current is changed in a range of 1-100% for dimming. The phase detection module is matched with the rectification filtering unit to filter clutters in the voltage signals so as to improve the detection precision, and the first filtering unit is matched with the first switch unit to fill up the energy lost by the waveform, so that the output current is smoother.

The application discloses an STO safety torque off circuit, comprising: the first shutdown circuit and the second shutdown circuit both comprise: the output end of an STO signal input circuit is connected with the input end of a delay shaping circuit, and the output end of the delay shaping circuit is connected with an or gate circuit; the output end of a DSP processor is connected with the input end of a high pulse wave generating circuit, and the high pulse wave generating circuit is connected with the STO signal input circuit; the input end of a diagnosis circuit is connected with the output end of the STO signal input circuit; the output end of the diagnosis circuit is connected with the or gate circuit; the or gate circuit is connected with a servo drive circuit; the output end of the DSP processor is also connected with the input end of the servo drive circuit; the output end of the STO signal input circuit, the output end of the delay shaping circuit and the output end of the diagnosis circuit in the first shutdown circuit and the second shutdown circuit are also connected with the input end of the DSP processor respectively. Through the application, the shutdown reliability and the fault positioning accuracy are improved.

The invention discloses a plateau driving emergency response method based on steering wheel biosensing, and relates to the technical field of intelligent safety vehicle control, and the plateau driving emergency response method comprises the following steps: arranging a dual-wavelength optical sensor and an annular capacitor array on a steering wheel to collect an original PPG pulse wave signal and a holding contact area of a driver, and calculating a final blood oxygen saturation value of the driver; performing altitude self-adaptive blood oxygen threshold value matching according to the real-time altitude during driving, and calculating an early warning threshold value and an emergency threshold value of the final blood oxygen saturation degree; according to the obtained final oxyhemoglobin saturation value, the early warning threshold value and the emergency threshold value, plateau driving emergency response is conducted, and the driving response state is triggered. Full-coverage safety guarantee can be provided under different oxygen deficit degrees, the monitoring precision and early warning pertinence are improved, and the active safety and reliability of plateau driving are remarkably improved.

This invention discloses a method for detecting link faults in a wearable vital signs simulator (WVSS) based on photoplethysmography (PPG), belonging to the field of intelligent fault diagnosis. The invention acquires the WVSS's set parameters and calculates the expected ideal AC / DC ratio based on pre-stored calibration coefficients. Within a continuous diagnostic time window, it acquires a PPG digital sequence, calculates the measured AC / DC ratio, and differs it from the expected value to obtain the parameter domain residual. Through adaptive pulse template reconstruction, it obtains a microstructure residual sequence and calculates its energy in the key frequency band as the microstructure distortion intensity. It calculates the absolute value of the correlation coefficient between the parameter domain residual sequence and the microstructure distortion intensity sequence within the continuous time window as a link integrity diagnostic indicator. After comparison with a preset threshold, it classifies and determines whether the link is intact, degraded, or faulty. This invention relies solely on the WVSS's own output signal, can distinguish between gain drift and waveform structural distortion, and possesses the ability to locate, classify, and interpret faults. It is suitable for production line calibration, on-site maintenance, and built-in self-test scenarios.

The invention discloses a continuous blood pressure estimation method based on pulse wave and electrocardiosignal time-frequency domain feature fusion, which comprises the following steps of: 1, acquiring a multi-modal signal of a subject and a corresponding blood pressure label, and preprocessing to obtain a time sequence; 2, performing short-time Fourier transform on each modal time sequence to obtain a frequency spectrum and extract frequency domain statistical characteristics, and constructing a frequency domain priori matrix; and 3, constructing a blood pressure prediction neural network which comprises a double-flow feature extraction module, a semantic alignment module, a modal fusion module, a time sequence modeling module and a regression module, guiding cross-modal feature alignment and fusion by utilizing frequency domain prior information, and outputting predicted systolic pressure and diastolic pressure. According to the method, light-weight and efficient multi-modal blood pressure prediction can be realized by utilizing frequency domain prior and a cross attention mechanism.

The application discloses a kind of based on face video's space-time field weighting photoelectric volume pulse wave recovery method, the model involved mainly includes signal extraction, signal quality score and signal enhancement three modules.First face video is detected and cut to face, obtain only containing face video as input;Signal extraction module calculates the frame difference graph of input, to extract spatial domain weight from input feature with weighting, from spatial domain attention face non-motion area, and further from the weighted signal, preliminary extraction is carried out to pulse wave signal;Signal quality score module is segmented to pulse wave signal score;Signal enhancement module assigns higher attention weight value to the signal section with low score, from time domain attention signal quality poor part, output recovered high-quality pulse wave signal.The application can alleviate the motion interference in imaging photoelectric volume pulse wave tracing method, extract effective signal from time domain and spatial domain, provide high-quality pulse wave signal for subsequent physiological parameter estimation.

This invention belongs to the field of nasal alar pulse wave signal processing technology, and provides a method, apparatus, medium, and wearable device for nasal alar pulse wave signal processing. The method includes: extracting the respiratory cycle based on the respiratory signal; determining the length of the mean sliding filter window to filter out the DC component of the original nasal alar pulse wave signal, obtaining a filtered nasal alar pulse wave signal; extracting the amplitude of the AC component of the filtered nasal alar pulse wave signal; adjusting the current of the light source element corresponding to the pulse wave signal sensing element to make the amplitude of the AC component of the filtered nasal alar pulse wave signal greater than or equal to a preset amplitude threshold; further filtering the nasal alar pulse wave signal using an adaptive weighted moving average filtering algorithm; and determining whether a nasal alar pulse wave signal meeting preset quality requirements is obtained based on a comparison between the noise figure of the further filtered nasal alar pulse wave signal and a preset noise figure threshold.

A mobility service providing method and apparatus are provided. The method includes: moving, by a vehicle, to a customer when the customer requests the vehicle to provide a mobility service and forming, by one or more anchors mounted on the vehicle, an Ultra-Wide Band (UWB) link with an information technology (IT) device carried by the customer when a determination is made that a distance between the vehicle and the customer is within a predetermined distance; performing a smart anchor positioning (SAP) algorithm to estimate a position of the IT device; performing position-based security authentication with the customer; and arriving, by the vehicle, at the customer, wherein the one or more anchors and the IT device transmit or receive UWB pulse waves.

The invention discloses a pulse wave matching method, device and equipment for non-invasive blood pressure measurement. The method comprises the steps that pulse wave data on each pressure step are collected to obtain a typical pulse wave waveform in a rising-first and falling-second form; performing characteristic value extraction on the pulse waveform by adopting double sliding windows, and judging whether the characteristic values of the current pulse wave and the previous pulse wave are matched or not; the characteristic values comprise a pulse wave amplitude value, a processing signal peak value, a processing signal valley value and a processing signal peak-valley interval; if not, continuing to collect the pulse wave data and continuing to perform characteristic value matching, and if yes, collecting the pulse wave data on the next pressure step. According to the method, the pulse wave features are enhanced through double-window processing, and the influence of interference factors is effectively reduced while the matching judgment precision is improved in combination with the original waveform features.

This invention discloses a method for detecting link faults in a wearable vital signs simulator (WVSS) based on photoplethysmography (PPG), belonging to the field of intelligent fault diagnosis. The invention acquires the WVSS's set parameters and calculates the expected ideal AC / DC ratio based on pre-stored calibration coefficients. Within a continuous diagnostic time window, it acquires a PPG digital sequence, calculates the measured AC / DC ratio, and differs it from the expected value to obtain the parameter domain residual. Through adaptive pulse template reconstruction, it obtains a microstructure residual sequence and calculates its energy in the key frequency band as the microstructure distortion intensity. It calculates the absolute value of the correlation coefficient between the parameter domain residual sequence and the microstructure distortion intensity sequence within the continuous time window as a link integrity diagnostic indicator. After comparison with a preset threshold, it classifies and determines whether the link is intact, degraded, or faulty. This invention relies solely on the WVSS's own output signal, can distinguish between gain drift and waveform structural distortion, and possesses the ability to locate, classify, and interpret faults. It is suitable for production line calibration, on-site maintenance, and built-in self-test scenarios.

The invention discloses near field communication electronic equipment, a card reader and an awakening method thereof. In the method, a card reader periodically emits detection waves with fixed amplitude; after receiving the detection wave, the simulation card modulates the detection wave by using the pulse wave with variable amplitude and transmits the pulse wave back to the card reader; the card reader detects the amplitude change of the signals received for multiple times and calculates the amplitude difference value between the adjacent signals; and if the amplitude difference values consecutively and repeatedly accord with the preset regular change, triggering wake-up interruption and establishing communication. According to the invention, by identifying the trend rule of the amplitude change, the detection sensitivity and anti-interference capability of the card reader to the simulation card are significantly improved, and the method is especially suitable for wearable equipment with limited antenna size.

The invention belongs to the technical field of non-contact physiological signal monitoring, and discloses a millimeter-wave radar-based personalized blood pressure measurement method, which comprises the following steps of: acquiring an echo signal of a millimeter-wave radar transmitting signal reflected by a wrist artery area, and constructing a three-dimensional data cube containing multiple pieces of virtual channel data; performing signal analysis on the three-dimensional data cube, and extracting a quasi-pulse wave signal; based on the quasi-pulse wave signal, a template evaluation mechanism is predefined, and a personalized pulse wave template is dynamically constructed and screened for the current user; based on the screened pulse wave template, performing waveform reconstruction on the pulse wave signal to obtain a reconstructed personalized pulse wave signal; the personalized pulse wave signals are input into a feature extraction network, and signal features of different scales are extracted through a multi-scale convolution structure; the problems that in the prior art, due to individual physiological differences, millimeter wave radar blood pressure measurement precision is insufficient, and the cross-user generalization ability is poor are effectively solved.

The invention discloses a health monitoring method, device and equipment and a storage medium, the method is applied to portable pulse condition collecting equipment, the portable pulse condition collecting equipment comprises a multi-point piezoelectric sensor array, and the method comprises the steps that pulse pressure signals of a user are collected through the multi-point piezoelectric sensor array distributed in the radial artery direction; preprocessing the pulse pressure signal to obtain a preprocessed pulse pressure signal, and converting the preprocessed pulse pressure signal into a pulse digital signal; obtaining pulse condition characteristic parameters by analyzing frequency domain characteristics of the pulse digital signals; inputting the pulse condition characteristic parameters into the traditional Chinese medicine diagnosis model to obtain health assessment information of the user. Three-dimensional acquisition of pulse waves is achieved through the multi-point piezoelectric sensor array, pulse pressure signals are converted into quantized pulse condition characteristic parameters, traditional empirical pulse conditions are converted into quantizable and reproducible digital characteristics and health assessment information, and objectivity and consistency of pulse condition analysis are improved.

To provide a biological meridian energy circulation device that realizes bioregulation of the human body's body fluid circulation. [Solution] The biological meridian energy circulation device adopts a wearable ring-shaped structure and includes components: a physiological signal collection layer that fits closely to the human body, a control layer integrating a core processing module, and a user interface layer. The physiological signal collection layer is used to acquire human pulse wave signals. The control layer incorporates a built-in pulse wave conduction simulation model and a traditional Chinese medicine meridian parameter mapping mechanism, and generates a pressure waveform control signal based on the pulse wave signal in accordance with the traditional Chinese medicine meridian regulation rules. The user interface layer is used to input regulation commands and display operating status. Pulse wave conduction characteristics are associated with qi and blood circulation parameters in traditional Chinese medicine meridian theory.

This detection system comprises: a detection device having a pulse wave sensor and an acceleration sensor; a data processing device capable of communicating with the detection device; and a management device that performs notification according to information received from the data processing device. The pulse wave sensor and the acceleration sensor alternately repeat a measurement state and a standby state. The data processing device has a pulse wave data processing unit that calculates an acceleration pulse wave from a pulse wave, a body movement data processing unit that performs frequency analysis of acceleration, and a determination unit that determines whether a person wearing the detection device is suspected of having developed sepsis. When at least one of a first condition and a second condition is satisfied, the determination unit transmits, to the management device, information indicating that there is a suspicion of sepsis. The first condition is that the spectral intensity in a specific frequency band among the frequency components of the acceleration obtained during one measurement state is equal to or greater than a predetermined threshold. The second condition is that the average value of acceleration pulse wave amplitudes of the acceleration pulse wave calculated from the pulse wave obtained during one measurement state is equal to or greater than a predetermined prescribed value.

A display device and an electronic device including the same are provided. The display device includes: a display panel; display pixels arranged in the display area of the display panel; a light sensing pixel in the display area together with the display pixel; an infrared emission pixel in the display area together with the display pixel; the display scanning driver is used for driving the display pixels and the infrared light-emitting pixels to emit light; the light sensing scanning driver is used for driving the light sensing pixels to detect light; and a main driving circuit for detecting a pulse wave signal of a user using a light sensing signal received through the light sensing pixels, and measuring biometric information, in which the main driving circuit is for separating and generating blood vessel image data from the image data, and receive a light sensing signal of the light-receiving area by distinguishing the light-receiving area according to blood vessel image data in the display area.