60 results about "Cerebral oxygen" patented technology

The invention discloses a rehabilitation training evaluation system for dealing with schizophrenia patients, and relates to the technical field of data processing, the evaluation system comprises a multi-modal sensing module, an edge intelligent processing module and a dynamic graph network evaluation module; according to the technical key points, neurophysiology, behavior tracks, cognitive functions and environmental parameters are fused to form a'microscopic neural activity-mesoscopic behavior performance-macroscopic environment interaction 'full-dimension evaluation network, for example, the recessive decoupling phenomenon of'reduced brain oxygen metabolism but normal autonomic nerve function' of a negative symptom patient can be synchronously captured, and the accuracy of the evaluation network is improved. The method comprises the following steps of: firstly, quantifying the coordination and causality of data of different dimensions through a dynamic graph network, disclosing a dynamic association path of insufficient activation of a forehead cortex, social attention distraction and cognitive task error rate increase, and providing a visual basis for mechanism research and intervention target selection.

The invention relates to the technical field of intelligent medical systems, and discloses a cerebral apoplexy onset risk assessment and reminding method and system.The method comprises the steps that continuous medical structured detection data are collected, and the data comprise carotid artery blood flow parameters, brain oxygen saturation, heart rate variability and metabolic indexes; inputting a bidirectional LSTM, a differential convolutional network, a wavelet residual network and a multi-layer perceptron to extract nonlinear features; constructing a neural function coupling structure diagram of four nodes of cerebral blood supply, oxygen supply, autonomous regulation and metabolic steady state; calculating inter-node time sequence offset correlation and a stable factor to obtain a coupling anomaly coefficient; and driving the embedded network by using a graph structure and a node feature input mechanism, and outputting a risk state assessment result. According to the method, the neural function coupling structure diagram is constructed and the mechanism is introduced to drive the embedded network, so that high-precision identification of the multi-system collaborative abnormal state and dynamic evaluation of the stroke risk level are realized.

The invention relates to the technical field of medical instruments, in particular to a sleep monitoring system based on a non-invasive brain oxygen saturation monitor, which comprises a monitoring system and is used for synchronously and dynamically monitoring local brain oxygen in real time, and the monitoring system comprises a non-invasive brain oxygen dynamic monitoring unit used for monitoring the brain blood oxygen saturation of a patient in real time by adopting a near infrared spectrum technology; the multi-parameter synchronous analysis unit is used for integrating the brain oxygen data, the electroencephalogram signals, the cerebral blood flow data and the respiratory event indexes; the intelligent risk assessment engine analyzes a brain oxygen change rule based on a deep learning algorithm, and predicts a brain function impairment risk caused by sleep breathing disorder; in the intelligent risk assessment engine, on the basis of a space-time convolutional neural network, brain oxygen time sequence data and spatial distribution characteristics are combined, and a brain hypoxia mode of the OSA patient is recognized; the method has the characteristic of realizing early warning of the brain injury related to sleep breathing disorder through noninvasive brain oxygen monitoring, multi-parameter fusion analysis and intelligent risk assessment.

The invention provides an auxiliary language training system based on artificial intelligence, belongs to the technical field of artificial intelligence, and realizes paradigm innovation of language learning through deep fusion of a quantum-classical hybrid architecture and a multi-modal neuroscience technology. A quantum semantic analysis engine and a cross-language parallel corpus generation module break through culture barriers, and a dynamic knowledge graph is fused with anthropology features and a taboo word weight quantification model, so that the cross-culture semantic accuracy is improved by 78%; a multi-modal synchronous compensation algorithm is combined with brain oxygen metabolism real-time monitoring, cross-modal delay of a VR / AR scene is compressed to be within 70 ms, a neural morphological pronunciation correction module and a 4D bionic tongue model construct a pronunciation-auditory feedback closed loop, the TTS phoneme fidelity of a small language reaches 97.9%, and 39% of language interference is reduced compared with a traditional model. A logic traceability network driven by a quantum entanglement dialogue module can analyze 12 layers of grammar nesting errors, and a dynamic correction path is generated in cooperation with a pulse neural dictionary.

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 digital heritage hosting system based on dynamic authorization and quantum verification and an immortal carrier construction method. The digital heritage hosting system comprises three core modules, namely a quantum time capsule, a dynamic authorization matrix and an immortal interaction engine. According to the system, the state of a user is evaluated in real time through implantable biological monitoring equipment (detecting heart rate variability / brain oxygen saturation), and L1-L3 level operation authority is dynamically switched. And the quantum time capsule encrypts and stores a private key and memory data by adopting an NTRU algorithm, and decrypts by stages through a time lock after death judgment. The innovation points comprise: 1) three-factor biometric authentication (DNA + iris + gait), and the false identification rate is extremely low; according to the digital asset safety storage and condition inheritance interaction method, the digital asset safety storage, condition inheritance and immortal interaction functions are achieved, and heritage types such as virtual property, digital copyright and encrypted assets are covered.

The utility model relates to a monitoring head frame convenient to wear on the head, which comprises a head band, an electroencephalogram electrode, a brain oxygen probe, a TCD support and a fixing band, the head band can adjust the annular shape matched with the head, the electroencephalogram electrode is embedded on the head band and captures the electrical activity of the brain, the brain oxygen probe is arranged on the wearing inner side of the head band and measures the oxyhemoglobin saturation in the brain tissue, and the TCD support is used for supporting the brain. The TCD supports are arranged on the head band and located on the two sides of the head, TCD probes are arranged on the TCD supports and used for monitoring changes of cerebral blood flow, fixing holes are formed in the plate faces of the mounting supports, the fixing holes and the first adjusting holes are arranged up and down, the fixing holes are located above the first adjusting holes, and the two ends of the fixing band penetrate through the fixing holes in the two corresponding mounting supports to be fixed. Velcro tapes are arranged at the two ends of the fixing end, so that the brain oxygen probe, the electroencephalogram electrode and the TCD probe can be tightly attached to the head position, the accuracy of the monitoring result is improved, the fixing belt is fixed through the Velcro tapes, and the monitoring head frame can be adjusted according to different head shapes of different users.

The invention relates to the technical field of medical signal processing, in particular to a brain oxygen entropy-based dynamic blood flow simulation system which comprises a data acquisition module, a structure modeling module, a state monitoring module, a simulation calculation module and an anomaly prediction module. According to the method, through synchronous utilization of brain oxygen saturation and blood flow velocity signals, accurate capture of brain oxygen supply and blood flow dynamic dynamic correlation is achieved, sensitivity of abnormal fluctuation recognition is enhanced, individualization and accuracy of blood flow simulation are improved by combining a brain blood vessel geometric structure and blood vessel elasticity and compliance parameters, and multi-point dynamic coupling is utilized to achieve the purpose of improving the accuracy of blood flow simulation. According to the method, abnormal blood supply state recognition is enhanced, brain blood supply stability evaluation is optimized, the local blood flow micro-dynamic feature reduction degree is improved through dynamic updating of the inertia coefficient and the shear stress, the oxygen entropy fluctuation, the shear stress and the flow velocity gradient are combined, the nonlinear coupling relation is extracted, the abnormal event prediction accuracy is improved, and the brain blood supply stability is improved. And the early warning capability of abnormal cerebral blood supply is enhanced.

The invention discloses an intelligent monitoring system for tumor nursing. The intelligent monitoring system comprises a wearable sensing terminal group, a patient terminal, a cloud platform intelligent analysis center and a medical care terminal. The wearable terminal is used for collecting multi-modal physiological and behavior data such as electroencephalogram, near-infrared brain blood oxygen, heart rate variability, body movement, electrodermal response and gaits; the patient terminal is used for recording subjective symptoms and completing cognition and exercise task evaluation. The cloud platform intelligent analysis center constructs a multi-parameter individualized baseline through data fusion, noise suppression and time alignment, comprehensively analyzes real-time deviation, electroencephalogram abnormality, cognitive deviation and gait change by using a short-term acute early warning model and a long-term trend early warning model, and generates a risk level. The digital twinborn visualization module is used for dynamically displaying the state of the patient, and the medical care terminal performs clinical response based on the graded alarm board. According to the invention, extra-hospital multi-mode continuous monitoring, individualized trend identification and intelligent early warning can be realized, and the real-time performance of follow-up management of brain tumor patients is improved.

The present invention relates to a brain rehabilitation assessment system based on cardiopulmonary resuscitation information. The system includes: a detection module capable of at least detecting the brain oxygen of a patient and a processor capable of controlling the working parameters of the detection module. The detection module is provided with at least one first sensing component capable of emitting visible light with an indicative function and near-infrared light for collecting brain oxygen data. The first sensing component controlled by the processor can coincide the reflection point of the visible light with the reflection point of the near-infrared light on the patient's head. The processor adjusts the emission angle of the near-infrared light element in a manner related to "the distance between the patient and the detection module determined based on the reflection time of the visible light". The system involved in the present application is applicable to patients with head trauma. The system can distinguish the brain oxygen data of the trauma area and the non-trauma area, which is crucial for the assessment and treatment of patients with head trauma. This distinction can help doctors better understand the severity and impact of the trauma.

In some examples, a system is configured to use a neural network algorithm of a cerebral autoregulation model to determine a cerebral autoregulation status of a patient based at least in part on blood pressure of the patient over a period of time and regional cerebral oxygen saturation of the patient over the period of time.

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 invention discloses a rehabilitation training evaluation system for schizophrenia patients, which relates to the field of data processing technology. The evaluation system includes a multimodal perception module, an edge intelligent processing module, and a dynamic graph network evaluation module. The technical key points are: integrating neurophysiology, behavioral trajectories, cognitive functions and environmental parameters to form a full-dimensional evaluation network of "micro-neural activity-meso-behavioral performance-macro-environment interaction". For example, it can simultaneously capture the implicit decoupling phenomenon of "reduced brain oxygen metabolism but normal autonomic nervous function" in patients with negative symptoms, avoiding the missed diagnosis of complex pathological mechanisms by traditional scales. Secondly, through the dynamic graph network, the synergy and causality of data of different dimensions are quantified, revealing the dynamic association path of "insufficient prefrontal cortex activation → social attention distraction → increased cognitive task error rate", providing a visual basis for mechanism research and intervention target selection.

The invention relates to the technical field of neurological rehabilitation, in particular to a transcranial direct current closed-loop regulation and control method based on near-infrared brain oxygen real-time feedback, which comprises the following steps: collecting brain oxygen baseline signals of each region of the whole brain, calculating the mean value and the standard deviation of each brain region, and establishing a whole brain blood oxygen regulation and control threshold matrix of sub-regions and sub-parameters; dynamically adjusting the core target brain region, and adjusting the sampling frequency and the single detection duration according to the fluctuation frequency of the oxyhemoglobin concentration of the core target brain region; according to the signal fluctuation frequency, continuously adapting the detection parameters, and combining the comparison result of the core characteristic parameters and the whole brain blood oxygen regulation threshold matrix, optimizing the transcranial direct current regulation parameters, and outputting optimized data; by means of the mode, dynamic adaptation of the detection parameters and the signal fluctuation characteristics is carried out, and regulation and control collaboration is improved.

The invention discloses a VR rowing system and method based on multi-modal data processing. The system comprises a data processing and analyzing module, a brain oxygen monitoring module, a muscle oxygen monitoring module, an electroencephalogram monitoring module, a myoelectricity monitoring module, a rowing body and a VR display module. Collecting brain oxygen information, muscle oxygen information, electroencephalogram information and myoelectricity information of the user; the brain oxygen information, the muscle oxygen information, the electroencephalogram information and the myoelectricity information are processed through a data processing and analyzing module, and multi-modal fusion information is obtained; training a preset user state recognition model by using the multi-modal fusion information to obtain an optimized user state recognition model; processing the to-be-processed multi-modal fusion information by using the optimized user state recognition model to obtain a multi-modal recognition result; sending the multi-modal recognition result to a user trained on the rowing body; and a user adjusts the resistance of the paddle shaking and carries out VR scene switching through a control handle according to a multi-mode identification result.

The invention discloses a plateau population brain aging comprehensive index determination method and device, a medium and a computer program product, which adopt a 3D-CNN architecture to process nerve image data, improve brain age prediction precision, apply a longitudinal comparative analysis method, realize individualized brain aging trajectory tracking, generate a saliency map, and improve brain age prediction accuracy. And visual abnormal brain region positioning information is provided. And a multi-modal weighted fusion algorithm is adopted, so that data isomerism challenges are overcome, and information complementation and result verification are realized. Brain oxygen saturation parameters are incorporated into a brain aging evaluation system, and the key problem that hypoxia affects brain aging in a plateau environment is solved. A plateau population brain aging norm is established, the problem that plain standards are not applicable is solved, and a plateau brain aging specific mode is disclosed. The integrated evaluation process simplifies the operation steps, reduces the professional threshold, improves the prevention and treatment effect through personalized intervention suggestions, and is beneficial to delaying the brain aging process.

The invention discloses wearable pain relieving equipment and a remote monitoring system thereof. The wearable pain relieving equipment comprises a multi-mode physiological sensor array, a data fusion processing module, a control module, a transcutaneous electrical stimulation output module, a communication module and the remote monitoring system. The multi-mode sensor array collects myoelectricity, skin conductance, body surface temperature, heart rate, brain oxygen and other pain related physiological parameters, the data fusion module generates a pain estimated value, the control module dynamically adjusts the stimulation intensity based on a PID + differential compensation algorithm, and the transcutaneous electrical stimulation module outputs current to intervene in pain. The communication module uploads data to a remote monitoring system, and medical staff can monitor and remotely adjust parameters in real time through a cloud platform. The system realizes real-time monitoring, intelligent control and remote intervention of pain, has the advantages of personalized treatment, data safety, expandability and the like, and is suitable for scenes of postoperative pain management, chronic neuralgia and the like.

The present application relates to the technical field of medical image monitoring, in particular to an intraoperative cerebral oxygen saturation image dynamic monitoring and early warning system and method for elderly patients, comprising a bilateral cerebral oxygen acquisition module, a cerebral oxygen waveform image construction module, a cerebral oxygen image feature extraction module, a hierarchical early warning module and a multi-parameter linkage display module, through the bilateral cerebral oxygen saturation time series signals output by the bilateral near-infrared cerebral oxygen saturation sensors are synthesized into a double-channel cerebral oxygen waveform image aligned with the same time window start and end time and sharing the amplitude scale, three types of geometric morphological features of bilateral cerebral oxygen slope, bilateral cerebral oxygen asymmetry index and relative baseline drop amplitude are uniformly extracted in the image domain, three types of high-risk mode hierarchical triggering of unilateral cerebral oxygen threshold persistence, relative baseline drop and bilateral asymmetry are driven, and the invasive arterial pressure, cardiac output, anesthesia depth index waveform and hemodynamic event characteristic root cause pairing display are jointly presented.

The utility model relates to the technical field of sensor fixing, in particular to a fixing device for a brain oxygen photoelectric sensor. According to the technical scheme, the device comprises an elastic head sleeve, an elastic neck sleeve is fixedly connected to one side of the lower end of the elastic head sleeve, a plurality of transmission lines are fixedly installed at the upper end of the elastic head sleeve, and a plurality of brain oxygen photoelectric sensors are fixedly installed at the upper ends of the transmission lines. When the device is used, the elastic head sleeve is sleeved on the head of a patient, the elastic head sleeve has elasticity and can be tightly attached to the scalp of the patient after being sleeved, then the second clamping hook and the second clamping buckle are fixed on the neck of the patient, and then the first clamping hook and the first clamping buckle are fixed on the jaw of the patient. The whole device can be stably fixed, the position of the device cannot be changed even if some special patients move disorderly and do not cooperate with each other, a plurality of groups of brain oxygen photoelectric sensors arranged on a transmission line can monitor the patients after the patients are fixed, and the thickness of an elastic head sleeve cannot affect the monitoring result.

The invention provides a cerebral apoplexy sudden sign real-time grading alarm method and system based on edge computing, and relates to the technical field of edge computing, and the method comprises the steps: collecting multi-modal physiological sign data in real time through an intelligent monitoring bracelet worn by a patient, the multi-modal physiological sign data comprises heart rate, blood pressure and brain oxygen saturation, and the multi-modal physiological sign data is transmitted to an edge computing gateway deployed in a ward. According to the invention, efficient and accurate monitoring of the stroke high-risk patient is realized.

The application relates to the technical field of medical signal processing, in particular to a blood flow dynamic simulation system based on cerebral oxygen entropy, which comprises a data acquisition module, a structure modeling module, a state monitoring module, a simulation calculation module and an abnormality prediction module.In the application, through synchronous utilization of cerebral oxygen saturation and blood flow velocity signals, accurate capture of the dynamic correlation between cerebral oxygen supply and blood flow dynamics is realized, the sensitivity of abnormal fluctuation identification is enhanced, individualization and accuracy of blood flow simulation are improved in combination with cerebral vascular geometric structure and vascular elasticity and compliance parameters, abnormal state recognition of blood supply is strengthened by utilizing multi-point dynamic coupling, cerebral blood supply stability evaluation is optimized, the degree of restoration of local blood flow microdynamic characteristics is improved through dynamic updating of inertia coefficients and shear stress, the nonlinear coupling relationship is extracted in combination with oxygen entropy fluctuation, shear stress and flow velocity gradient, the accuracy of abnormal event prediction is improved, and the early warning capability of cerebral blood supply abnormality is enhanced.

The invention discloses a non-invasive brain oxygen saturation monitoring method and system. The system is characterized in that a light source driving circuit drives a probe module to generate a light signal with a preset time sequence under the control of a main control unit; the probe module comprises a first light source and a second light source, the same sides of the first light source and the second light source are respectively provided with three detectors which are arranged along a radial direction and are arranged at different intervals, and the three detectors corresponding to the first light source and the three detectors corresponding to the second light source are arranged on the left side and the right side in mirror symmetry; the signal conditioning module is used for processing the detected optical signal to obtain a spectral signal; the analog-to-digital conversion circuit is used for converting the spectral signal into a corresponding digital signal, and then the digital signal is transmitted to the signal preprocessing module through the communication interface under the control of the main control unit; the signal preprocessing module is used for filtering and denoising the received signal and then transmitting the signal to the calculation module to quantitatively calculate the brain oxygen saturation. The brain tissue blood oxygen saturation monitoring efficiency, accuracy and convenience are improved.

The application provides a non-invasive multi-modal brain function monitoring method and device, electronic equipment and storage medium, and relates to the technical field of multi-modal electric digital data processing. The method comprises the following steps: acquiring physiological state information of a measured target and electroencephalogram monitoring data, brain oxygen monitoring data and brain edema monitoring data of the measured target within a preset time length; determining electroencephalogram infection artifacts of the measured target according to the physiological state information, and removing the electroencephalogram infection artifacts from the electroencephalogram monitoring data to obtain real electroencephalogram data; correcting the brain oxygen monitoring data according to the physiological state information and the real electroencephalogram data to obtain real brain oxygen data; determining a brain function level of the measured target based on the physiological state information, the real electroencephalogram data, the real brain oxygen data and the brain edema monitoring data, and performing brain injury early warning according to the brain function level. The application can timely and accurately predict the change of the brain function of a child with severe infection through multi-modal monitoring data.

The invention relates to the technical field of blood oxygen signal acquisition and monitoring, and provides a multi-channel wireless blood oxygen acquisition and monitoring device and a multi-channel wireless blood oxygen acquisition and monitoring method aiming at solving the problems that a wired data transmission mode is adopted to measure a blood oxygen signal in traditional single photoelectric blood oxygen concentration detection and the accuracy of acquired data is poor. A plurality of photoelectric detectors receive LED reflected light of different depths, blood oxygen signals are calculated according to the received reflected light and are output and displayed, the multi-wavelength LEDs avoid interference of melanin, water molecules and other components on the surface layer of the human brain, and the multi-channel photoelectric detectors are used for detecting oxyhemoglobin of different depths of the human brain and the change of the hemoglobin content. Monitoring data are more accurate and suitable for real-time dynamic monitoring of blood oxygen saturation signals and brain oxygen saturation signals of a patient clinically, a wireless transmission function is achieved, blood oxygen saturation of multiple parts such as the brain and fingertips can be monitored in real time, monitoring precision is high, stability is good, wearing is comfortable, and operation is easy and convenient.

This invention relates to the field of sleep monitoring data fusion processing technology, and discloses a sleep monitoring method based on the fusion of non-invasive brain oxygen saturation (AHI) and multiple physiological parameters. The method includes: S1, simultaneously acquiring multiple physiological parameter signals during the subject's sleep; S2, extracting and analyzing the AHI signal to generate multiple characterization markers; S3, identifying respiratory events related to the subject's apnea information from the respiratory signal and pulse oximetry signal, calculating the apnea-hypopnea index (AHI); and performing correlation analysis on the identified respiratory events and multiple characterization markers to calculate a correlation coefficient; S4, obtaining a comprehensive sleep monitoring assessment report based on the correlation coefficient and the AHI to determine the severity of the subject's current respiratory disturbance and the risk of brain tissue hypoxia. By improving the effectiveness of AHI in non-invasive brain oxygen saturation monitoring, the confirmatory nature of non-invasive brain oxygen saturation information in the respiratory correlation diagnosis during sleep monitoring is ensured.

The invention relates to the technical field of neurosurgery medical monitoring equipment, and discloses an integrated multi-parameter monitoring wireless implantable intracranial probe system which comprises a probe interface box, and a probe signal acquisition board, a main control module and a non-invasive blood oxygen detection module are arranged in the probe interface box. The probe signal acquisition board is electrically connected with the probe through a data transmission cable, the main control module is in wireless communication connection with the display terminal, and the probe is integrated with a piezoresistive intracranial pressure sensor, a thermistor temperature sensor, an electrochemical brain oxygen sensor and a graphene-polydopamine composite electrode array. According to the application, direct connection of a lead to monitoring equipment is completely avoided, limitation of doctor nursing operation or patient action caused by cable pulling is fundamentally eliminated, meanwhile, a patient gets rid of constraint of the lead, the head and the body can freely move, nursing and rehabilitation training are facilitated, and patient experience is remarkably improved. The intracranial pressure, intracranial temperature, brain tissue oxygen partial pressure, local brain tissue blood oxygen saturation and rebleeding monitoring can be achieved.

The present application relates to a cardiopulmonary resuscitation system based on brain oxygen information collaborative control. The system comprises: a detection module capable of detecting at least the brain oxygen and heart rate of a patient, a defibrillator and a processor capable of controlling the working parameters of the defibrillator. The processor is configured to: based on the patient being in a state of not recovering spontaneous breathing, when the brain oxygen detection result of the patient detected by the detection module is in the first range representing that the patient is in sufficient brain oxygen, and the cardiopulmonary resuscitation cycle reaches the condition of meeting the defibrillation requirement, control the defibrillator to start working in a gradient increasing energy mode. The system of the present application adjusts the start-up time of the defibrillator and its working parameters after starting based on the changes of brain oxygen information, blood oxygen information or heart rate information, and provides judgment information of chest compression effectiveness for rescuers. Based on the system provided by the present application, the efficiency of emergency treatment of severe cases can be improved.

1. The name of the product of this design: Brain tissue oxygen saturation monitor with a data display graphical user interface. 2. Purpose of this design product: Used in medical and health care, to monitor the oxygen saturation of human brain tissue. 3. The key design point of this appearance design product lies in the content displayed in the interface change state diagram. 4. The picture or photo that best illustrates the key points of the design: Main view of Design 1. 5. Purpose of the graphical user interface: to monitor the oxygen saturation data of human brain tissue, and to display the relevant information of human brain tissue oxygen saturation in the form of waveforms and brain oxygen status diagrams. 6. Other situations that require explanation refer to the following diagrams: Turn on the computer and enter the Design 1 main view, enter the user name and password to successfully register, enter the Design 1 interface change status diagram 1, click the "Personal Center" button on the left to enter the Design 1 interface change status diagram 2; Turn on the computer and enter the Design 2 main view, enter the user name and password to successfully register, enter the Design 2 interface change status diagram 1, click the "Information Registration" button on the left to enter the Design 2 interface change status diagram 2; Turn on the computer and enter the Design 3 main view, enter the user name and password to successfully register, enter the Design 3 interface change status diagram 1, click the "Monitoring Time" button on the left to enter the Design 3 interface change status diagram 2; Turn on the computer and enter the Design 4 main view, enter the user name and password to successfully register, enter the Design 4 interface change status diagram 1, click the "Image Display" button on the left to enter the Design 4 interface change status diagram 2. 7. Designate Design 1 as the base design.

This invention relates to the field of high-altitude environmental health monitoring technology, and particularly to an intelligent fusion analysis method and system for brain oxygen signals in high-altitude environments. This method acquires and fuses multi-channel brain oxygen saturation, multi-dimensional physiological parameters, and time-varying environmental data to mine the synergistic characteristics of oxygen metabolism across brain regions and construct a spatiotemporal evolution tensor. Based on this, a multi-scale, time-dependent hypoxia susceptibility dynamic model is constructed, generating a prospective risk assessment benchmark. Furthermore, risk extrapolation and causal chain reconstruction of brain oxygen evolution are performed, outputting structured prediction results and dynamically recalibrating the model. This achieves accurate, prospective assessment and dynamic tracking of individual brain oxygen risk in high-altitude environments.

The invention provides a head and neck partition multi-mode independent temperature control system for a medical ice cap, which comprises a medical ice cap and an ice cap temperature control subsystem, and is characterized in that the ice cap temperature control subsystem comprises a physiological signal acquisition module for acquiring head data by using a near infrared spectrum sensor and an electroencephalogram monitoring electrode to obtain original monitoring data; the signal processing and decision-making module is used for filtering and standardizing the original monitoring data and calculating local brain oxygen saturation and potential difference signal characteristics; the partition temperature control execution module is used for defining a plurality of cooling modes and carrying out cooling mode selection, cooling adjustment and temperature monitoring alarm according to local brain oxygen saturation and potential difference signal characteristics; and the transmission and visualization module is used for designing a wireless communication mode and an interface layout and carrying out data transmission and visualization display. According to the system, personalized cooling and real-time monitoring of physiological data are achieved, the safety, effectiveness and flexibility of clinical treatment are remarkably improved, the comfort level of a patient is optimized, and the requirements of modern medical treatment are met.