902 results about "Saturation level" patented technology

The invention discloses a multi-parameter dynamic intelligent judgment method for the safety state of an operator, and belongs to the technical field of operation safety monitoring. According to the method, by integrating an intelligent wearable device, a sensor and an eye movement tracking device, physiological parameters (such as heart rate, blood pressure, oxyhemoglobin saturation, electroencephalogram signals and the like), behavior parameters (such as action frequency, posture change and the like), psychological parameters (such as pressure level, fatigue degree and the like) and environmental parameters (such as temperature, humidity, noise and the like) of an operator are collected in real time; and a multi-dimensional monitoring system is constructed. Collected data is subjected to cleaning, standardization and feature extraction and then is input into a safety state judgment model based on a bidirectional long short-term memory network (BiLSTM), the real-time safety state of an operator is dynamically analyzed, and low-risk, medium-risk and high-risk three-level early warning results are output.

The present disclosure relates to systems and processes for optimizing the detection of a patient's heartbeats, which may be useful in detection of the patient's oxygen saturation, as well as systems and processes for improving and optimizing the PPG signal quality of those patients with highly pigmented skin. In various embodiments, the process may comprise the steps of: receiving, from a radio, red data, infrared (IR) data, and a series of heartbeats associated with a time period; computing a series of peaks of the red data and IR data for the time period; computing a subset of the red data and IR data; estimating an oxygen saturation percentage (SpO2%) for the patient by computing an optical ratio of the red data and IR data included in the subset; and displaying on a computer screen the estimated SpO2% for the patient.

The invention discloses a surface water prediction system and method based on a hydrological optimization Informer model. The method comprises the following steps: collecting multi-source data of an upstream monitoring point and a downstream monitoring point of surface water; preprocessing the multi-source data to obtain preprocessed data; performing feature extraction on the preprocessed data to obtain water quality features and hydrological spatial-temporal features of the upstream monitoring point and the downstream monitoring point, and constructing accumulated dissolved oxygen saturation features; inputting the upstream and downstream water quality characteristics, the hydrological spatial-temporal characteristics and the dissolved oxygen saturation characteristics into a pre-trained multi-modal prediction model of an improved Informer model to obtain a prediction result of the upstream surface water and a prediction result of the downstream surface water; the multi-modal prediction model of the improved Informer model outputs a prediction result of the surface water obtained through fusion; according to the method, the Informer model is optimized, the GRU model is combined, hydrological spatial-temporal characteristics and accumulated dissolved oxygen saturation are introduced by utilizing an attention mechanism, the prediction precision is improved, errors are reduced, and the early warning capability for sudden pollution events is enhanced.

The invention relates to the technical field of blood oxygen detection, in particular to a pulse blood oxygen saturation detection method based on image processing, a transfer learning strategy and a domain adaptation network are introduced, adjustment can be carried out according to personalized physiological parameters of a user, and therefore the applicability to different crowds is improved. Especially for people with deep skin color, the measuring error is obviously reduced, and the error rate is reduced by more than 30%. A set of mechanism for calculating the current signal quality index Q in real time is designed, dynamic calibration is carried out in combination with a Bayesian filtering model, and it is ensured that a reliable blood oxygen saturation degree estimation value can be obtained even under the condition of the low signal-to-noise ratio. And when the signal quality is reduced, the current detection value is compensated by using historical data through the LSTM network prediction module, so that the accuracy and continuity of the result are further ensured.

The invention provides a vehicle-mounted oxygen production control method and device, a vehicle-mounted oxygen production system and electronic equipment, and relates to the technical field of vehicle control. The method comprises the steps that the oxygen partial pressure in a cockpit, the altitude of the environment where the cockpit is located and the oxyhemoglobin saturation of passengers in the cockpit are obtained; determining an oxygen supply demand value based on the oxygen partial pressure, the altitude and the oxyhemoglobin saturation; and based on the oxygen supply demand value, an oxygen generation module is controlled to start oxygen generation or stop oxygen generation. The starting and stopping of the oxygen generation module are controlled based on the oxygen supply demand value, waste caused by starting of the oxygen generation module when oxygen supply is not needed can be avoided, and therefore the energy consumption of vehicle-mounted oxygen generation can be greatly reduced.

The invention discloses a sleep monitoring method and system based on a non-contact video data sequence. The method comprises the steps that S1, video data streams of human body sleep are collected through a camera system; utilizing a YOLOv11 network to obtain face video data and thoracoabdominal video data; s2, the RPPG signal extraction model extracts and obtains an RPPG signal by using the face video data; s3, the breathing signal extraction model extracts thoracic and abdominal micro-motion change characteristics in the thoracic and abdominal video data by using an optical flow method, and noise filtering processing is carried out to obtain thoracic and abdominal motion signals as breathing signals; s4, the oxyhemoglobin saturation extraction model detects and outputs an oxyhemoglobin saturation signal by using the RPPG signal; and S5, performing multi-modal fusion analysis on the multi-physiological index fusion recognition model according to time slice T1 division to obtain a long-time-sequence sleep stage staging result. According to the invention, the physiological index signals are extracted and recognized by adopting the non-contact video data sequence, and the sleep stage staging result with a long time sequence is obtained, so that high-precision sleep monitoring and sleep stage recognition are realized.

The invention relates to the technical field of anesthesia patient physiological monitoring, in particular to an anesthesia preoperative risk assessment method and system, which continuously acquire physiological parameters of an anesthesia patient in a resting state, monitor physiological parameter changes in a dynamic physiological load state, screen physiological parameters exceeding a steady state range and generate a preoperative physiological monitoring data set. According to the method, the individual physiological steady state range is set through data comparison between the resting state and the dynamic physiological load state, accurate screening of parameters such as the heart rate, the blood oxygen saturation degree and the blood pressure is achieved, and the monitoring accuracy is improved. In combination with a load state fluctuation value, a resting mean value and a weight parameter, an individual physiological regulation range is calculated, so that evaluation is more personalized. And the preoperative risk adjustment coefficient is dynamically calculated, so that the risk assessment has the real-time adjustment capability. The heart rate recovery time, the blood oxygen fluctuation amplitude and the blood pressure recovery time are introduced, the physiological load ratio and dynamic load index classification are combined, and the risk assessment fineness is improved.

The invention belongs to the technical field of physiological state estimation, and discloses a blood oxygen estimation method based on combination of successive variational mode decomposition and adaptive filtering, which comprises the following steps of: removing high-frequency noise and baseline drift from a collected pulse wave signal; performing successive variational mode decomposition and adaptive filtering on the pulse wave signal to remove motion artifacts; accurate peak values and valley values are extracted according to the denoised pulse waves; the R value is calculated according to the denoised pulse wave and the extracted peak value and valley value, the blood oxygen saturation degree is solved according to the R value, and the R value refers to the absorbance ratio of the red light and the infrared light in the blood. According to the blood oxygen estimation method based on the combination of the successive variational mode decomposition and the self-adaptive filtering, the effect of removing motion artifact noise of photoelectric volume pulse wave signals is achieved, multi-peak-value joint detection is used, peak values and valley values are accurately extracted, and therefore the R value is determined, the blood oxygen saturation degree is obtained, and the accuracy of blood oxygen estimation is improved. And the precision of estimating the blood oxygen saturation is greatly improved.

The invention discloses an oxygenerator remote control system and method based on the Internet of Things, and belongs to the technical field of intelligent medical equipment and remote health management, and the method comprises the steps: S1, collecting multi-dimensional physiological data of a user in real time through a multi-source physiological signal collection module, a heart rate variability index and a body movement signal; s2, based on the multi-dimensional physiological data, processing is performed through a preset physiological state prediction model, and a unified physiological stress index is solved; s3, determining a predictive oxygen supply flow rate value in combination with the physiological stress index and a preset user basic oxygen supply flow rate; s4, according to the predictive oxygen supply flow velocity value, a control signal for a physical execution component of the oxygen generator is generated so as to dynamically adjust oxygen supply parameters, and conversion from passive compensation to active prediction is achieved.

A wearable device for comprehensive bio-monitoring of physiologic metrics to determine metabolic, pulmonary and cardiac function and oxygen saturation measurements from breathing mask apparatuses. The device non-invasively monitors the physiologic profile of the subject, and is capable of detecting physiologic changes, predicting onset of symptoms, and alerting the wearer or another person or system. In some embodiments, the device comprises both a wearable sensor suite and a portable gas composition and flow analysis system. In preferred embodiments, it comprises a miniaturized non-invasive sensor suite for detecting physiologic changes to detect dangerous breathing or other health conditions. The acquired physiologic profile is used to generate alarms or warnings based on detectable physiological changes, to adjust gas delivery to the subject, alter mission profiles, or to transfer control of the craft or other duties away from a debilitated subject. The device is compact, portable, vehicle independent and non-encumbering to the subject.

The invention discloses an artificial intelligence-based obstructive sleep apnea judgment method, which comprises the following steps of: S1, acquiring the respiratory rate, the heart rate and the oxygen saturation of a user in a sleep period, and constructing a physiological data set; s2, filtering, denoising and cleaning the collected original physiological data set to remove noise and abnormal values; s3, key physiological features are extracted from the preprocessed physiological data set; s4, training a judgment model by utilizing improved deep learning, and performing comprehensive analysis by the judgment model according to the extracted physiological features to judge whether obstructive sleep apnea occurs or not; s5, the system monitors the sleep state of the user in real time, and provides instant feedback or alarm when obstructive sleep apnea is detected; and S6, the system performs analysis according to the physiological features of different users, and provides judgment results and health suggestions for individuals. The accuracy and real-time performance of obstructive sleep apnea judgment are improved, and accurate sleep apnea monitoring and judgment are achieved.

A laparoscopic medical device includes an oximeter sensor at its tip, which allows the making of oxygen saturation measurements laparoscopically. The device can be a unitary design, wherein a laparoscopic element includes electronics for the oximeter sensor at a distal end (e.g., opposite the tip). The device can be a multiple piece design (e.g., two-piece design), where some electronics is in a separate housing from the laparoscopic element, and the pieces (or portions) are removably connected together. The laparoscopic element can be removed and disposed of; so, the electronics can be reused multiple times with replacement laparoscopic elements. The electronics can include a processing unit for control, computation, or display, or any combination of these. However, in an implementation, the electronics can connect wirelessly to other electronics (e.g., another processing unit) for further control, computation, or display, or any combination of these.

The invention discloses an intelligent blood oxygen saturation measuring method and device and electronic equipment, and relates to the field of data processing. According to the method, an infrared light emitter is used for emitting a plurality of emitted light rays with different wavelengths; receiving reflected light rays corresponding to the emitted light rays by utilizing a photoelectric receiver, and converting the reflected light rays into photoelectric signals; extracting a time domain characteristic parameter and a frequency domain characteristic parameter of the photoelectric signal; inputting the time-domain characteristic parameters and the frequency-domain characteristic parameters into a preset blood oxygen saturation degree estimation model to obtain a blood oxygen saturation degree estimation value of the to-be-measured individual; and acquiring historical detection data of the to-be-detected individual, and correcting the blood oxygen saturation degree estimated value by adopting a Kalman filtering algorithm based on the historical detection data to obtain a final blood oxygen saturation degree estimated value. By implementing the technical scheme provided by the invention, the accuracy of blood oxygen saturation measurement is improved.

The invention relates to the technical field of image processing and biological signal detection, discloses a facial physiological detection method and system based on signal quality driven ROI selection, and aims to solve the problem of signal degradation of a traditional fixed geometric ROI in a complex scene. The method comprises the following steps: collecting a user face video stream through a camera and preprocessing the user face video stream; detecting a face bounding box and dividing the face bounding box into a plurality of sub-regions; calculating the signal-to-noise ratio, the periodic intensity and the motion artifact interference degree of each sub-region; screening an optimal sub-region according to a weighted fusion formula to generate a dynamic ROI mask; extracting a pure rPPG signal from the dynamic ROI mask coverage area; detrending and band-pass filtering are carried out on the rPPG signals, and physiological parameters such as the heart rate and the blood oxygen saturation degree are extracted. The system comprises a face video acquisition module, a face region positioning and segmentation module, a signal quality evaluation module, a dynamic ROI selection module, an rPPG signal extraction module and a physiological parameter estimation module. According to the technical scheme, signal degradation caused by local shielding, illumination abrupt change or attitude offset can be effectively avoided, the signal-to-noise ratio and the stability of the rPPG signal are remarkably improved, and the universality and the robustness of the method are enhanced.

The embodiment of the invention provides a continuous blood oxygen monitoring system in extracorporeal circulation and a control method thereof. The continuous blood oxygen monitoring system comprises a vein sensor, an artery sensor, a blood flow sensor, an oxygen sensor, a carbon dioxide sensor, a controller and a display, the vein sensor monitors the vein blood oxygen saturation degree; the artery sensor monitors arterial oxygen saturation and hematocrit; the blood flow sensor monitors the blood flow of the artery pipeline; the oxygen sensor monitors the oxygen concentration of the oxygenator; the carbon dioxide sensor monitors the carbon dioxide concentration of the oxygenator; the display provides an interaction control, responds to a trigger operation acting on the interaction control, sends an interaction instruction to the controller, and updates information displayed in an interaction interface according to the control of the controller; the controller receives the interaction instruction and executes processing corresponding to the interaction instruction; the processing includes controlling display information of the display; the display information comprises information corresponding to the monitoring parameters. The scheme ensures the safety and effectiveness of the treatment process.

The embodiment of the invention provides a control method of an oxygen generation system and an adjustable oxygen generation system, and belongs to the technical field of medical instruments. The control method of the oxygen generation system comprises the steps that 1, the threshold value interval of a pulse rate normal value and the threshold value of an oxyhemoglobin saturation normal value are obtained; 2, receiving a pulse rate monitoring value and a blood oxygen saturation monitoring value of a user of the oxygen generation system; 3, according to the threshold value interval, the threshold value, the received pulse rate monitoring value and the received oxyhemoglobin saturation monitoring value, the oxygen output quantity of the oxygen generation system is controlled, and the oxygen output quantity is the oxygen generation pressure and / or the oxygen output rate. According to the method, the performance parameters of the oxygenerator can be timely and automatically adjusted according to the physiological parameter change of the user of the oxygenerator, so that the requirements of the user at the current moment are met.

The invention discloses a method for diagnosing obstructive sleep apnea hypopnea syndrome, and relates to the technical field of medical diagnos.The method comprises the steps that an airflow curve and an oxyhemoglobin saturation curve of a patient during sleep are collected, all respiratory events are traversed and retrieved from the airflow curve, and according to the occurrence time of each respiratory event, all the respiratory events are determined; finding out a corresponding search window from the blood oxygen saturation curve, calculating the area of the search window of each apnea event, accumulating the areas of all closed areas to obtain an area sum, dividing the area sum by the total sleep time to obtain an index value of the sleep apnea specific hypoxia load, and determining the sleep apnea specific hypoxia load based on the index value and an index threshold value. Obtaining the symptom level of apnea of the patient; the method has the advantages of simple and convenient indexes, rapidness and high accuracy, and can be well applied to screening and diagnosis of the obstructive sleep apnea hypopnea syndrome.

The invention relates to the technical field of water flooding gas reservoirs, in particular to a rock core displacement fluid saturation testing method and a testing device thereof.The method comprises the steps that S1, the original formation pressure and temperature of a gas reservoir are obtained; s2, obtaining a rock core, and testing physical property data of the rock core; then carrying out nuclear magnetic testing on the rock core; s3, saturating the rock core with formation water, and then carrying out nuclear magnetic testing; s4, carrying out gas drive water seepage test on the rock core according to the data in the S1, and obtaining the drive water quantity; s5, performing nuclear magnetic test on the depleted rock core; s6, obtaining the irreducible water saturation of the depleted rock core according to the nuclear magnetic test results of the steps S2, S3 and S5; s7, the total irreducible water saturation of the rock core is obtained according to the rock core physical property data, the displacement water amount and the irreducible water saturation of the rock core after exhaustion; the device comprises a drying oven, a first container, a second container, a core holder, a confining pressure pump, a displacement pump, a back pressure assembly, a receiving container and an electronic balance. The accuracy of fluid saturation determination can be improved.

The invention discloses a mobile plateau oxygen therapy intelligent control system, and belongs to the technical field of medical health. The problem that an existing oxygen supply device is single in function is solved, the functions of data collection, intelligent analysis, oxygen supply control, alarm prompting and the like are integrated, key parameters such as oxygen concentration, heart rate and oxyhemoglobin saturation around a user are monitored in real time, current data are predicted and analyzed through a convolutional neural network model, and the intelligent oxygen supply control system has the advantages that the intelligent oxygen supply control function is achieved. The system intelligently adjusts the output of the oxygen supply equipment according to the analysis result, and it is ensured that a user obtains appropriate oxygen supply in the plateau environment; secondly, when it is detected that the oxygen concentration around the user is lower than a threshold value or equipment breaks down, sound-light alarm prompt is given out; multiple safety protection mechanisms are arranged in the system, it is ensured that automatic shutdown can be achieved under the abnormal condition, meanwhile, an emergency shutdown button is arranged, equipment operation can be rapidly stopped under the emergency condition, and therefore the safety of the equipment and the safety of a user are protected.

The invention discloses a child health information tracking management method and system for a kindergarten institution, and relates to the technical field of kindergarten information management. According to the child health information tracking management method for the kindergarten institution, basic information and health data of each child are collected, the health condition of each time period is evaluated, a time period health index is generated, whether the time period health index of each child is within a normal range or not is judged in real time according to a preset health threshold value, and if the index is abnormal, the kindergarten institution is started. The method comprises the following steps of: immediately marking health abnormity, comprehensively analyzing health, intake, activity and interaction data of the whole day at the end of each day, analyzing daily health comprehensive indexes of each infant, performing health assessment, and taking corresponding health intervention measures according to a result. By continuously tracking and analyzing key health indexes such as the body temperature, the heart rate, the respiration rate and the blood oxygen saturation degree of the infant, the health index of each time period is generated in real time, and a young supporting institution is allowed to recognize potential health risks in real time in the initial stage of the problem.

The present invention relates to a system (100) for monitoring one or more physiological parameters of an individual. The system (100) comprises an optical fibre assembly (110) configured to measure one or more physiological parameters of an individual, and a pressure sensor (120) configured to measure a contact pressure of the optical fibre assembly (110) on the individual. The pressure sensor (120) comprises an optical fibre (122) comprising a transducer fibre Bragg grating (127) embedded in a matrix (121). The matrix (121) is configured to cause longitudinal strain in the transducer fibre Bragg grating (127) in response to the matrix (121) being subject to a transverse load. The one or more physiological parameters that the system (100) is for monitoring may include blood oxygen saturation (Sp O2), capillary refill time (CRT), heart rate, blood flow and CO2 emissions from skin.

The invention discloses an oxyhemoglobin saturation detection method and device, noise reduction equipment, a storage medium and a product, and relates to the technical field of artificial intelligence. The oxyhemoglobin saturation detection method comprises the steps that an initial pulse wave signal collected by photoplethysmography detection equipment is received, and whether a noise signal exists in the initial pulse wave signal or not is judged; if the noise signal exists in the initial pulse wave signal, the initial pulse wave signal is input into a noise reduction model to obtain a target pulse wave signal, and the noise reduction model is obtained through training by taking a historical pulse wave signal as input data and taking the denoised historical pulse wave signal as a label; the target pulse wave signal is sent to the photoplethysmography detection equipment, and the photoplethysmography detection equipment carries out blood oxygen concentration detection based on the target pulse wave signal. The accuracy of blood oxygen saturation detection is improved.

The invention relates to a shale or coal rock gas evaluation method based on a gas-water two-phase flow isotope fractionation model. The shale or coal rock gas evaluation method comprises the following steps: 1, collecting data; 2, establishing a gas well model; 3, establishing a control equation set; 4, coupling the influence of the real gas effect and the effective stress; 5, establishing a gas transmission model and a relative permeability model; 6, establishing a relation between capillary pressure and saturation; 7, considering critical desorption pressure; 8, setting boundary conditions of initial conditions; 9, solving a control equation set; 10, calculating production dynamic parameters and isotope values; 11, performing history fitting; 12, verifying historical fitting quality; 13, predicting productivity; 14, calculating a gas dynamic output proportion; 15, identifying a fractionation inflection point and gas production mechanism conversion; by coupling gas-water two-phase flow, multiple gas transmission mechanisms, stress sensitivity and methane isotope competitive adsorption theories, yield prediction of the deep reservoir and quantitative evaluation of the dynamic proportion of produced gas are realized.

The invention belongs to the technical field of brain function monitoring, and discloses a three-in-one non-invasive brain function monitoring system and method, a medium, equipment and application, and the monitoring method comprises the following steps: monitoring brain oxygen saturation of a critical patient; carrying out transcranial Doppler ultrasonic measurement on intracranial blood vessel blood flow velocity and ultrasonic measurement on the inner diameter of the optic nerve sheath; monitoring a quantitative electroencephalogram of the patient; various brain function monitoring series indexes and continuous changes of the indexes along with disease evolution are obtained, the pathogenic mechanism and pathogenesis of the indexes are found in time, and primary diseases and related complications of the primary diseases are treated. According to the invention, the brain oxygen saturation can avoid too low brain oxygen or low brain oxygen for a long time and too high brain oxygen due to oxygen utilization disorder; cerebral blood flow can be monitored through a transcranial Doppler (TCD) technology to find an optimal craniocerebral perfusion pressure (CPP), and a cerebral blood flow self-adjusting function is enabled to be in an optimal state; the electroencephalogram can avoid early warning of over-sedation or abnormal discharge and the like. Through organic combination of the three, noninvasive, real-time and dynamic monitoring of critical patients is realized.

The invention discloses a non-inductive physical and psychological health monitoring and early warning system and method before a coal miner goes down a well, and belongs to the technical field of coal mine safety production and personnel health monitoring. A physiological monitoring unit comprises a millimeter-wave radar, an infrared camera and an imaging type photoplethysmography device, the millimeter-wave radar is installed in the center of the top of a monitoring channel, and the infrared camera is installed on the imaging type photoplethysmography device; the infrared cameras are symmetrically installed on the two sides of the channel, the imaging type photoplethysmography devices are integrated in the infrared cameras and used for synchronously collecting the core body temperature and the oxyhemoglobin saturation, and the integrated imaging type photoplethysmography devices focus on the forehead and cheek areas through the RGB channel. Reflected light intensity fluctuation signals caused by blood vessel blood volume changes are collected. Through cooperation of the three devices, non-contact synchronous collection of multiple parameters can be completed without deliberate cooperation of workers, comprehensive and continuous basic data are provided for subsequent physical and psychological health analysis, the wellhead passing efficiency is improved, and the cross infection risk of contact type devices is avoided.

The invention relates to the technical field of data processing, in particular to a clinical test data analysis method and system. The method comprises the following steps: presetting observation ranges of blood oxygen saturation data points in a blood oxygen saturation time sequence of a human body and respiratory frequency data points in a respiratory frequency time sequence; eliminating variation coefficient deviation before and after a blood oxygen saturation data point in an observation range of the blood oxygen saturation data point to obtain a mutation index, and obtaining a mutation factor of the blood oxygen saturation data point according to the mutation index and data variation of all adjacent blood oxygen saturation data points in the observation range; calculating false factors of the blood oxygen saturation data points; a corrected target threshold value is obtained through the product of the false factor of the blood oxygen saturation degree data point and a preset threshold value; and the target threshold is used in the Chebyshev inequality to obtain the analysis result of the blood oxygen saturation data point, so that the accuracy of the analysis result is effectively improved.

In the breathing state evaluation model training and breathing state evaluation method and system, breathing-related physiological parameter data is collected; the physiological parameter data comprises a blood oxygen saturation numerical value, a heart rate numerical value, a breathing carbon dioxide concentration numerical value and a breathing rate numerical value; interpreting the physiological parameter data, and giving a breathing state evaluation label corresponding to the physiological parameter data; the breathing state evaluation label comprises an IPI index; inputting the physiological parameter data and the breathing state evaluation label into an artificial intelligence training device, and training by the artificial intelligence training device to obtain a breathing state evaluation feature data set; the breathing state evaluation feature data set is matched with a corresponding artificial intelligence algorithm and is used for breathing state evaluation. The breathing state comprehensive evaluation can be directly carried out based on the complete waveform signal, and the IPI index is closer to reality.

The invention discloses an oxygen therapy instrument control system and method and a storage medium, and the system comprises an oxygen saturation obtaining module which is used for obtaining the current blood oxygen saturation value of a user; the air and oxygen flow control module is used for controlling the mixed air and oxygen flow; the oxygen concentration control module is used for controlling the concentration of oxygen in the air-oxygen gas; and the analysis control module is used for inputting the initial air-oxygen flow and the oxygen concentration, and carrying out stepped control adjustment on the air-oxygen flow and the oxygen concentration according to the current blood oxygen saturation value of the user, so that the equipment parameters of the oxygen therapy instrument gradually approach to the body characteristics of the user. Gradient adjustment and real-time calculation can be carried out, adjustment is accurate, intelligent regulation and control are achieved, it is guaranteed that the oxygen therapy instrument is suitable for the physical condition of a user in real time, real-time manual adjustment is not needed, and discomfort of the user or oxygen waste caused by inapplicable parameters is also avoided.

The invention discloses a non-contact physiological parameter detection method, system and device and a storage medium. The method comprises the steps that non-contact PPG signals are extracted from RGB signals of each group of interested areas; inputting the non-contact PPG signal into the trained denoising network to obtain a denoised non-contact PPG signal corresponding to the current group of regions of interest; inputting the denoised non-contact PPG signals corresponding to all groups of regions of interest into the trained signal fusion network to obtain fused non-contact PPG signals; determining body temperature data of the testee based on the region of interest; inputting the RGB signals of all the regions of interest into the trained random forest model to obtain the oxyhemoglobin saturation of the testee; on the basis of the fused non-contact PPG signal, a respiration signal of the testee is confirmed, and then the respiration rate of the testee is confirmed; the pulse wave signal of the testee is confirmed, and the blood pressure and the pulse rate of the testee are confirmed based on the pulse wave signal.

An apparatus for monitoring an oxygen saturation level of a wearer of the apparatus includes a processor, a memory operably coupled to the processor, a first housing portion, a second housing portion, and a connection member. The first housing portion includes at least one light-emitting diode (LED), and the second housing portion includes a photodetector. The connection member is mechanically coupled to each of the first housing portion and the second housing portion. The apparatus is sized and shaped to be worn about a portion of an ear of a wearer of the apparatus. During operation, the at least one LED emits light in a direction toward the photodetector. A portion of the emitted light passes through the portion of the ear prior to arriving at the photodetector. The photodetector detects a signal in response to the portion of the emitted light, and the memory stores instructions to cause the processor to calculate an oxygen saturation level of the wearer based on the detected signal.