13 results about "Cerebral oxygen" patented technology

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 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.

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 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.

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 application provides a kind of intelligent dimming method and system based on multi-modal physiological feedback, it is related to intelligent lighting and lighting control technical field.The application synchronously acquires eye movement data and near-infrared functional imaging brain oxygen signal under task scene, with eye movement event as anchor point alignment and compensate brain oxygen time delay, obtain time alignment multi-modal data segment;State index reflecting attention, cognitive load and fatigue degree is extracted, individualized baseline is established and dynamically updated, and normalized state feature vector is generated;The feature vector is input into neural network light regulation model, and the target light intensity, correlated color temperature and spatial distribution ratio are output;Based on the target parameter, a joint control instruction is generated, and a short physiological response is collected to form a closed-loop feedback.The application realizes real-time adaptive matching of lighting and individual physiological state, significantly improves the accuracy and human comfort of intelligent lighting.

1. The name of the design product: biological signal acquisition instrument (multi-modal module). 2. The use of the design product: can be plugged into the host, used for collecting physiological signals such as electroencephalogram, cerebral oxygen, near-infrared or electrocardiogram, and realizing signal acquisition of brain-computer interface system. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

This application relates to the field of bioelectrical signal acquisition and brain-computer interface technology, and discloses an electroencephalogram (EEG) acquisition device. It includes a device body, ear clip components, a brain oxygen acquisition module, and a main control module. The EEG acquisition module, ear clip components, and brain oxygen acquisition module are all electrically connected to the main control module. The device body is a flexible, adaptable body, using flexible silicone as a covering layer. The ear clip components are a first ear clip and a second ear clip, symmetrically arranged. The first ear clip serves as the EEG acquisition reference negative electrode, and the second ear clip serves as the environmental interference acquisition end. The second ear clip is electrically connected to the differential amplification module within the main control module. The device body has an embedded magnetic female electrode interface, which serves as a dry electrode for acquiring EEG signals, and / or magnetically connects to external electrode pads for acquiring EEG signals. The device body has multiple preset forehead acquisition points, and the main control module integrates a point configuration switching module to wake up or deactivate corresponding acquisition points.

The application relates to the technical field of signal evaluation, and particularly provides a cerebral oxygen signal quality evaluation method, device, medium, equipment and product. The method can comprise the following steps: detecting cerebral oxygen signals in multiple windows to determine a signal evaluation queue; the signal evaluation queue comprises at least one piece of to-be-evaluated data related to the cerebral oxygen signals in at least one window; in the case that the queue length of the signal evaluation queue is greater than a length threshold, the to-be-evaluated data is evaluated in quality by using multiple signal quality indexes, and evaluation results of each signal quality index in the multiple signal quality indexes are obtained; wherein the multiple signal quality indexes comprise a signal light intensity index, a signal variability index, a signal correlation index or a signal correlation degree index; and whether the cerebral oxygen signals are effective is determined based on the evaluation results of each signal quality index. The application can improve the efficiency and accuracy of cerebral oxygen signal quality evaluation.

The application relates to the field of noninvasive detection technology and discloses a brain computer oxygen monitoring integrated probe, which comprises a contact layer sheet, a plurality of groups of electrode contact sheets and an attached mounting unit. The brain computer oxygen monitoring integrated probe is stacked in the vertical direction through a layered mounting module, electrode lead wire layers, brain oxygen optical element mounting layers and electromagnetic shielding layers are arranged in the vertical direction, the functional structures required by brain electric acquisition and brain oxygen monitoring can coexist in the limited height space of the forehead, the light window of the contact layer sheet and the light hole of the mounting layer sheet form a light well in the vertical direction, the light emitting device and the light sensor are respectively located directly above the light well and keep alternating interval distribution, the space congestion problem caused by simultaneously arranging the brain electric electrode and the brain oxygen optical assembly in a single plane is avoided, and the brain electric electrode and the brain oxygen optical assembly can work in the best acquisition area under the premise of not interfering with each other.

This invention discloses an intelligent state analysis method for anesthetized patients based on physiological data, comprising the following steps: S1, organizing and annotating historical anesthesia data to form executable state recognition rules and establishing a standardized historical case reference library. The beneficial effects of this invention are: by decomposing key interactive substructures such as nerve-circulation, brain-circulation, and respiration-perfusion from dynamic network profiles, coordinating indicators with clear physiological significance, such as baroreflex function index, brain oxygen-blood pressure coupling coefficient, and ventilation-perfusion matching degree, are calculated; these indicators can quantify the coordination of physiological systems under anesthesia from multiple dimensions; the system performs multi-dimensional similarity matching of these real-time indicators with an internalized anesthesia state knowledge base (containing multiple preset state modes), realizing accurate and interpretable independent determination of the anesthesia depth state in three dimensions: sedation, analgesia, and muscle relaxation, overcoming the limitations of traditional single index monitoring.

This invention provides a brain oxygen signal processing method and device based on endogenous low-frequency oscillations, belonging to the field of computer-aided design technology. The method includes: S1, preprocessing and concentration conversion of the original light intensity signal, performing sliding windowing and low-frequency sub-band analysis on the hemoglobin concentration change signal to obtain the low-frequency sub-band signal; S2, extracting the instantaneous phase information and amplitude envelope information of the low-frequency sub-band signal, and determining the amplitude-phase coordination quantity and amplitude envelope coordination quantity; S3, using consistency gating parameters for joint constraints, constructing a low-frequency coupling structure matrix, and generating low-frequency coupling feature parameters; S4, performing quantitative mapping, hierarchical characterization, and confidence output of brain functional states to achieve quantitative characterization of the brain oxygen signal characteristics of the current analysis window. This invention models the coordinated change characteristics of multi-channel brain oxygen signal data in the low-frequency range, determines the coordination and stability of the spatial distribution of brain oxygen signals, and realizes the output of brain oxygen signal feature labels.