637results about "Respiratory organ evaluation" patented technology

An image processing apparatus is disclosed. The image processing apparatus of the present invention comprises: an image receiving unit for receiving a first image and a second image of the same object taken at different times; a processor for obtaining transformation information by registering the first image on the basis of the second image, obtaining a first segment image corresponding to an area of the object from the first image, and generating a second segment image corresponding to an area of the object of the second image by transforming the obtained first segment image according to the transformation information; and an output unit for outputting the second segment image.

The embodiment of the invention provides a breathing machine inspiration detection method and device and a computer readable storage medium, and the method comprises the steps: collecting first pressure data and first flow data in a current breathing period, and calculating a target flow baseline according to the first pressure data, the first flow data and a preset fitting formula; calculating a virtual traffic baseline according to the target traffic baseline and the first traffic data; if it is judged that the inspiration triggering state is not reached or the virtual inspiration flow change rate in the inspiration triggering state is smaller than a preset flow change threshold value, second pressure data and second flow data of the next respiratory cycle are continuously collected, and the virtual inspiration flow change rate is calculated; and judging that inspiration is detected until the detected virtual inspiration flow change rate is greater than or equal to the preset flow change threshold value. According to the invention, the phenomena of inspiration detection delay, group delay and the like can be avoided, the difference between detected inspiration and actual inspiration is reduced, and the sensitivity of inspiration detection is improved.

The present disclosure provides a system (100) and a method (300) for determining the physiological vital parameters of a user (104) in a vehicle (102). The system (100) determines the physiological vital parameters of the user (104) based on remote photoplethysmography (rPPG) signals generated by a semi-supervised machine learning (SSMLM) model. The SSMLM generates the rPPG signals based on spatial and temporal features extracted from facial video data acquired by a sensor array (110). The SSMLM includes separate layers for spatial and temporal feature extraction. Furthermore, the SSMLM is trained using semi-supervised learning, which reduces the dependence on large amounts of labeled training data and the challenges associated with synchronizing labels with video data.

The utility model is suitable for medical equipment technical field provides a kind of breathing apparatus for C13 detection;Including: blowing pipe, blow pipe inside is provided with flow passage, and the top of blowing pipe is provided with the opening that is communicated with flow passage;Connecting mounting seat, and the bottom of blowing pipe is rotatably installed in the installation groove on connecting mounting seat, and the side wall in the inside of blowing pipe that is provided with communicating hole is set in connecting mounting seat, and communicating hole is communicated with flow passage;First detection gas bag, and the gas delivery end of first detection gas bag is communicated with the first communicating flow passage on connecting mounting seat;Second detection gas bag, and the gas delivery end of second detection gas bag is communicated with the second communicating flow passage on connecting mounting seat, and first communicating flow passage and second communicating flow passage are all set on the track of communicating hole passing;And timer installed on connecting mounting seat, timer is installed with timing switch on the side wall close to blowing pipe, and setting touch protrusion on blowing pipe, and timing switch is set on the track of touch protrusion.

This invention discloses a non-invasive method, system, device, and storage medium for monitoring student attention based on gas sensing, belonging to the field of non-invasive sensing technology. The method includes: calculating a net physiological gas signal based on environmental baseline data and initial gas concentration data of the target student; calculating physiological characteristic indicators of the target student based on the net physiological gas signal, and determining the target student's metabolic rate level based on the physiological characteristic indicators; obtaining a state time-series signal based on the net physiological gas signal according to a preset discrimination criterion; inputting the net physiological gas signal and the state time-series signal into a pre-trained attention monitoring model to obtain the probability distribution of the target student's attention state; and determining the target student's attention state based on the target student's metabolic rate level and the probability distribution of the attention state. This invention assesses the cognitive state by capturing the gas released by the student, achieving non-invasive monitoring.

This invention relates to the field of physiological signal prediction technology, specifically a method for preoperative risk assessment in cardiology, comprising the following steps: calculating baseline offset by segmenting time-series data using a sliding window; generating anomaly markers by dynamically warping and aligning the fluctuation rates of parameters; triggering risk signals by comparing standard deviation with amplitude thresholds; mapping risk levels using K-means clustering of multidimensional data; detecting abnormal fluctuations using isolated forest and cross-validating with electrocardiogram and myocardial enzyme profiles; and outputting a preoperative risk assessment conclusion. In this invention, the sliding window algorithm eliminates individual differences and interference; dynamic time warping aligns the fluctuation rates of multiple parameters to address time variability; comparing standard deviation with amplitude thresholds establishes a quantitative assessment standard to avoid the limitations of a single threshold; K-means clustering combined with Euclidean distance achieves objective grading; and the isolated forest algorithm, combined with cross-validation of the ST segment of electrocardiogram and myocardial enzyme profiles, forms a multimodal assessment system, creating a complete closed loop that improves the sensitivity and specificity of risk assessment.

The present application relates to the technical field of vital sign monitoring, in particular to a patient vital sign real-time monitoring and intervention response system for smart tumor ward, which comprises a skin thermal state recognition module, a communication abnormal period screening module, a vital sign event screening module, an intervention task generation module and an intervention response execution state construction module.In the present application, through joint analysis of temperature trend and communication abnormal period, the timing correspondence relationship between vital sign fluctuation and channel interruption is established, the data section of closed loop interruption risk is screened, the continuous change trend of body temperature, heart rate and respiratory rate is combined, the abnormal section and task state are labeled, the nursing terminal activation condition and control equipment number are matched, the hierarchical generation, state identification and response matching of the task are completed, the vital sign recognition is changed from static index to trend linkage, the task scheduling is extended from artificial driving to closed loop control, and the continuity of vital sign perception, the identification ability of communication interference and the connection efficiency of intervention execution in the ward scene are enhanced.

The application provides a kind of individualized health intervention timing arrangement method and system based on stress-recovery-adaptation model and double digital twin, the method is realized by seven layers architecture: collect user multi-modal data;Build the system digital twin and cognitive digital twin that can simulate cross-scale physiological response;Determine the physiological phase of user using hybrid architecture classifier, and map to three-dimensional state space;Based on phase and state space position, use layered reinforcement learning algorithm, after simulating and deducing in twin, dynamically generate the coordinated timing instruction set of five dimensions of exercise, nutrition, environment, active ingredient and neural regulation;Output executable protocol through emotional interface;Finally, continuously optimize the system and model using feedback data.The application converts physiology theory into computable and optimizable intelligent decision system, realizes the leap of health intervention from static suggestion to dynamic, coordinated and individualized timing arrangement.

Device (10) for extracorporeal blood treatment, in particular a dialysis device (10) which includes a radar sensor (17) for monitoring a patient (P) located at a treatment station, at least one shut-off device (13, 30) for shutting off a line (23) connected venously to the patient (P) and / or for shutting off an arterial line (22) connected to the patient (P), in particular in the form of a hose clamp (30) clamping an elastic or flexible area of ​​the line (22, 23), a blood pump and has a control unit (14), wherein the control unit (14) is set up and configured to determine a patient's (P) respiratory rate and / or respiratory amplitude based on signals from the radar sensor (17) and to trigger an alarm signal if the respiratory rate and / or respiratory amplitude detected by the radar sensor (17) deviates from one or more preset limit values, the shut-off device (13, 30) can be automatically operated via the control unit (14) in the event of an alarm and The blood pump is stopped in case of an alarm.

A seat and seat system, belonging to the field of automotive seats, are disclosed. The seat includes a seat cushion and a backrest. The backrest has a detection area equipped with a piezoelectric sensor. The detection area covers the projection of the spine on the backrest corresponding to the apex height of the occupant when seated, allowing the piezoelectric sensor to collect cardiac impact signals transmitted through the occupant's spine. This seat effectively improves the measurement accuracy and sensitivity of cardiac impact signals and is suitable for various smart cockpits.

A method for planning and guiding an endoscopic procedure is disclosed. The method includes obtaining a first scan of a chest cavity at near total lung capacity, obtaining a second scan of the chest cavity at near functional residual capacity, generating a virtual chest cavity based at least in part on the first scan and the second scan, defining one or more regions of interest (ROI) in the virtual chest cavity, and determining a route to the one or more ROIs based on the virtual chest cavity. The method includes directing endoscope hardware through an airway to the one or more ROIs along the predetermined route, monitoring, by a processor, a real-time position of the endoscope hardware relative to an expected position along the predetermined route, and performing an examination of the one or more ROIs when the real-time position of the endoscope hardware corresponds to an expected ROI location.

The application discloses a Helicobacter pylori breath test signal denoising fitting method and system, and belongs to the technical field of medical detection and signal processing. The method processes the continuous monitoring signal of the 13CO2 / 12CO2 isotope ratio in exhalation: firstly, the original signal is subjected to band-pass digital filtering to suppress high-frequency noise; then, low-frequency drift is eliminated through adaptive baseline correction to generate a drift-removed signal; subsequently, a robust peak value recognition algorithm is used to extract physiological response characteristics; finally, the identified peak value is taken as the center, a nonlinear function with physiological constraints is used for local fitting, and the Delta Over Baseline value is calculated based on the generated fitting curve with high precision. The application effectively solves the signal distortion problem caused by breathing fluctuations, instrument noise and the like in in vivo detection, realizes high-fidelity restoration of the Helicobacter pylori metabolic response, and significantly improves the detection accuracy and reliability of the breath test.

The application discloses a kind of elderly hip fracture surgery perioperative adverse event real-time monitoring system and method, it is related to perioperative monitoring technical field.The method includes: real-time acquisition perioperative monitoring data, carries out data pre-processing, and extracts benchmark feature;Identify the decline segment of cerebral oxygen saturation below benchmark feature, jointly assess the decline amplitude and persistence, obtain the weak trend characterization of brain oxygen;Analysis of the relative change characteristics of serum inflammatory markers, form the weak trend characterization of inflammation;Assess the deviation degree of vital signs relative to benchmark, obtain the vital signs fluctuation characterization, and further judge the delirium precursor risk, output risk prompt;Visual display various weak trend characterizations and delirium precursor risk, link label risk trigger information and contribution source.The present application solves the technical problems that the prior art is difficult to extract and identify early weak abnormal trend in perioperative multi-source physiological signals.

The present application relates to a kind of mine personnel vital signs monitoring and early warning bracelet, relate to mine personnel vital signs monitoring and early warning technical field.The main body rear cover is externally fixedly arranged rubber ring, the inside of the rubber ring is opened gas storage cavity, located in body, is equipped with the gas supply mechanism for the gas storage cavity in rubber ring inflation;Second gas leakage passage leading to the space surrounded by rubber ring is opened on the gas storage cavity, the notch independent of gas storage cavity is opened in the bottom of rubber ring;Switching component for opening or closing second gas leakage passage is provided in the gas storage cavity.The present application is provided with the rubber ring that can inflate and deflate on bracelet, when wearing bracelet, utilize the rubber ring that inflates and expands and skin close adhesion, form closed loop sealing surface, to avoid external coal dust, rock dust into sensor sensing area, ensure the monitoring effect of sensor;Again, the inflation of rubber ring improves the comfort of wearing.

Examples of the disclosure include an implantable system comprising principal stimulation circuitry configured to provide electrical stimulation to a phrenic nerve via at least one phrenic nerve stimulation electrode, subordinate stimulation circuitry configured to provide electrical stimulation to an upper-airway nerve via at least one upper-airway-nerve stimulation electrode, at least one respiration sensor, and an implantable pulse generator (IPG) comprising the stimulation circuitries and at least one processor configured to cause the subordinate stimulation circuitry to deliver stimulation in an absence of delivery of the phrenic nerve stimulation, monitor a signal from the respiration sensor(s), identify a respiration reduction based on the signal during the stimulation delivery, and in response thereto, cause the stimulation circuitries to deliver the stimulations concurrently based in part on the respiration signal and control a timing of delivery of the upper- airway-nerve electrical stimulation relative to a timing of delivery of the phrenic nerve electrical stimulation.

Airflow changes in a subject's airway can be monitored and / or quantified using B-mode ultrasound, such as by computing respiratory parameter data from motion signals generated from B-mode signals. This monitoring may be performed before, during, or following a procedure, or may be used as a general patient monitoring tool. For example, signs of airway obstruction or respiratory compromise and / or failure during timeframes where patients have ongoing or residual sedation or anesthetics in their system can be monitored.

The application provides an emotion regulation ability detection method and device based on a brain-computer interface. The emotion regulation ability detection method can adjust emotion evoking materials presented in a detection process and detection models and detection features used according to the age of a subject, so that the detection process can accurately adapt to test populations of different age groups, and the accuracy of the prediction results output by the detection model is effectively improved.

The application provides a non-contact pain monitoring mattress and system based on multi-modal physiological signal fusion, the mattress body comprises, from bottom to top, a bottom support layer, a signal shielding layer, a sensing core layer and a breathable skin-friendly layer, the system comprises the non-contact pain monitoring mattress, a low-noise charge amplifier, a fiber demodulator, an edge computing gateway and a cloud analysis center, the data after signal conditioning is transmitted to the edge computing gateway and uploaded to the cloud analysis center, and the cloud analysis center performs quantitative scoring through a tumor-specific pain model.The application has the advantages that no electrode or wearable device needs to be pasted, the skin irritation and psychological burden of traditional monitoring are completely eliminated, the patient compliance is improved, the limitation of subjective evaluation is broken through, an objective pain evaluation method is provided for patients in the late stage / aphasia, multi-modal signal fusion monitoring is used to effectively distinguish pain from ordinary emotional fluctuations, the degree of pain is fed back in real time, the doctor is assisted in dynamically adjusting the dose of analgesic drugs, and the risk of drug overdose and deficiency is reduced.

The application relates to the technical field of medical treatment, in particular to a port-related complication early warning system and method, wherein the system comprises a collection device and a computer device; the collection device is used for collecting at least one of thermal imaging data, pressure data, ultrasonic image data and visible light image data of a region where a user's port is located, and obtaining clinical data of the user; the computer device communicates with the collection device, generates modality data according to the data collected by the collection device, calls a pre-trained prediction model, inputs the modality data into the prediction model, outputs a comprehensive risk level of the user existing in a complication through the prediction model, and executes a complication early warning action according to the risk level, so that the monitoring and early warning of the port-related complication are realized. Therefore, the problem that related technologies lack monitoring of early micro changes of the port and lead to delayed discovery of the port-related complication is solved.

The present application belongs to the field of sleep aid, and discloses a sleep aid regulation method, device, equipment and storage medium, comprising: acquiring user data, and constructing model input data containing 15-dimensional features, the model input data comprising static features representing user basic physiological attributes, statistical features representing historical sleep data, and dynamic time series features representing real-time physiological monitoring data; inputting the model input data into a sleep aid instruction generation model deployed on a local embedded hardware for inference, the sleep aid instruction generation model being a TabTransformer model; analyzing the sleep aid regulation instruction, generating and executing physical control instructions covering five dimensions of massage, support, body position, heating and vibration. The present application maps the 15-dimensional user portrait features containing static attributes, historical statistics and real-time dynamic signals into collaborative and executable physical regulation instructions by introducing the TabTransformer model, solves the drawbacks of "heavy monitoring and light regulation", and realizes the integration of intelligent decision-making and execution.

Provided is a medical device, comprising: at least one sensor for generating data related to a usage and / or operation of the medical device and / or data of one or more measured parameters of a user; a connectivity controller configured to: receive access data to a wireless access point from the communication device, and establish a wireless communication connection with the wireless access point using the received access data to wireless transmit the generated data.

This invention discloses an AI-based non-contact sleep analysis system and method. [Solution] The sleep analysis system is characterized by comprising a smartphone that receives a download of a sleep analysis app from a server, collects the user's sleep acoustic information in real time and transmits it to the server, and receives a sleep analysis result report learned by artificial intelligence from the server; and at least one smart home appliance that is located at a distance from the user, simultaneously collects sleep acoustic information and transmits it to the smartphone, and provides the user with a customized sleep environment in response to the control of the smartphone. It can accurately match the wake time, which is the foundation of all sleep treatments, and can conveniently and accurately analyze the sleep of various types of users at home, regardless of time or place. Furthermore, it can control electronic devices or home appliances that can create an environment based on the analyzed sleep state information.

The present application relates to the technical field of psychophysiological monitoring, and discloses a video psychophysiological index analysis method and system; the method comprises the following steps: positioning facial key points and partitioning from a video, extracting remote optoelectronic plethysmography pulse wave and action unit breathing characteristics, outputting heart rate and breathing signals through Kalman filtering; obtaining a heartbeat interval through peak value detection, calculating heart rate variability indicators and breathing frequency, and normalizing by establishing an individual baseline in an initial calm period; fusing emotional characteristics and normalized indicators to form an observation vector, inferring a stress state through an unsupervised model and a forward algorithm; detecting index mutation points to identify stimulus events, and adopting a gated recurrent unit network to predict excessive stress risk and grade early warning; storing multi-session data into a database, quantifying desensitization rate, tolerance and recovery capacity through linear regression, weighted scoring and model updating. The present application realizes contactless monitoring, real-time stress evaluation and early warning, and supports quantitative analysis of cross-training effects.

The application discloses an electrocardio monitor early warning method and system based on tensor modeling and chaos analysis, and relates to the field of intelligent medical monitoring. The early warning system comprises an electrocardio signal acquisition module, a tensor modeling module for constructing an electrocardio signal tensor model, a feature processing module for constructing a dominant feature vector, a chaos analysis module for calculating a first early warning index, a second early warning index and a real-time early warning index based on a chaos analysis method, a dynamic early warning threshold generation module for calculating a preset dynamic early warning threshold, an electrocardio signal feature classification module for identifying an abnormal feature possibility mark, and an early warning output module for outputting the first early warning index, the second early warning index, the real-time early warning index and the abnormal feature possibility mark and issuing an electrocardio signal abnormality early warning. The application combines tensor modeling, a chaos analysis method and a dynamic early warning threshold, thereby improving the early electrocardio abnormality capturing capability, the early warning accuracy and the adaptation to target objects.

The present application relates to the cross technical field of speech signal processing, respiratory physiological monitoring and artificial intelligence, and specifically discloses a respiratory-speech pause signal analysis system and method. The present application synchronously collects speech and respiratory signals, extracts language-adapted pause parameters and physiological indexes, performs time sequence alignment and correlation analysis, and then fuses a prediction model and a true-false recognition model for intelligent analysis, thereby solving the problems that traditional heart-lung function detection relies on professional equipment and cannot be remotely and non-contactly monitored, and that existing speech analysis lacks a physiological coupling mechanism, leading to the inability to identify synthetic speech and insufficient cross-language adaptation, and realizing the dual ability improvement of non-contact respiratory physiological state evaluation and speech fraud recognition.

Embodiments herein relate to compound detection systems. In an embodiment, a compound detection system includes an input opening to a flow path for receiving a fluid sample, a capture structure for receiving the fluid sample, a heating element configured to heat the capture structure to a temperature to vaporize first components of the fluid sample, and a detector assembly configured to receive the vaporized first components and to detect the presence of compounds among the first components, wherein the system includes a vaporization agent and can be configured so that the vaporization agent can be vaporized by the heating element.