69 results about "Conscious State" patented technology

The invention provides an intelligent anesthesia depth monitoring method and system. A plurality of physiological parameter sensors are used for synchronously collecting composite physiological signals of a patient, and meanwhile brain wave signals of the patient in the anesthesia process are obtained; analyzing and processing the anesthesia state by fusing an electroencephalogram spectrum analysis algorithm and a nonlinear kinetic model to obtain a consciousness state map of anesthesia depth and consciousness edge fluctuation; performing real-time evaluation on the current anesthesia depth by using an adaptive threshold algorithm in combination with a Bayesian reasoning framework, and performing prediction processing on the trend change of the anesthesia depth in a future short time by using a long-short term memory neural network to obtain an evaluation result and a prediction trend; the anesthetic infusion rate is automatically adjusted so as to maintain the ideal anesthesia depth, meanwhile, potential risks are subjected to intelligent grading early warning processing, and an anesthesia management strategy is generated. According to the technical scheme provided by the invention, the safety and personalized management level of the anesthesia process are improved.

The invention relates to the technical field of biological consciousness state monitoring, in particular to an emergency patient consciousness state monitoring system based on a bio-electricity signal, and the system obtains a theta rhythm signal, an alpha wave signal and a gamma wave oscillation signal through an electroencephalogram signal acquisition module and a signal extraction module; obtaining an effective phase amplitude coupling event and an occurrence time position thereof through a phase amplitude coupling event time position positioning module; based on a patient consciousness state monitoring module, obtaining a patient consciousness state monitoring index, and fitting the patient consciousness state monitoring index with the time sequence to complete patient consciousness state monitoring. By means of the method, the theta-gamma cross-brain region phase amplitude coupling (PAC) event can be accurately positioned, the limitation that space-time positioning of the PAC event is fuzzy and dynamic tracking lags in the traditional technology is broken through, millisecond-level high-resolution monitoring of the consciousness state of an emergency patient is achieved, and a quantifiable neural electrophysiology basis is provided for real-time intervention of disturbance of consciousness.

The invention discloses a multi-modal data processing method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring multi-modal neural signal data corresponding to a target object; extracting consciousness characteristic parameters from the multi-modal neural signal data; the consciousness feature parameters are converted into consciousness feature vectors, the consciousness feature vectors are fused into a target feature vector, and the target feature vector is a vector used for representing the consciousness state of the target object; inputting the feature vector into a pre-training model of consciousness state classification, and outputting a consciousness state category corresponding to the target object; the pre-training model of consciousness state classification is a model which is obtained through training based on historical sample data of a plurality of patients and is used for determining the consciousness state classification of the to-be-tested person. According to the embodiment of the invention, the problem of low classification accuracy of consciousness states of patients with disturbance of consciousness in the prior art can be solved.

The invention discloses an awareness perception quantum gravitational nerve acceleration unified computing platform and method based on formalized verification, and belongs to the field of high-performance computing, medical AI and quantum information processing. A quantum gravitational coupling neural processing unit (QGCNPU); a consciousness information integral calculation core (phi ICC); formalizing a receipt chain verifier (FRCV); and the mirror reflection symmetry correction module (MRSCM) is used for eliminating the continuous projection mistake and the discrete Boolean mistake through topological equivalence verification of a local observer and a global GodCam visual angle. The system adopts an FPGA + ASIC + quantum processor three-layer heterogeneous architecture, and supports real-time pathological modeling (precision gt; gt) of neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease and ALS; 99.7%), drug target discovery (acceleration by 50 times) and consciousness state monitoring (time resolution lt; and meanwhile, the mathematical proving performance and the clinical auditing performance of the calculation process are ensured, and the requirements of the global 152 billion dollar neural science and technology market and the 89 billion dollar quantum calculation industry are met.

The invention provides a wounded consciousness state evaluation system based on face recognition, and relates to the technical field of health evaluation. Comprising a facial information extraction module, a facial feature analysis module, a consciousness state calculation module, an anomaly detection module and a consciousness state evaluation module. According to the invention, the infrared camera carefully captures the fine movement of the muscles around the eyes, the mouth corner and the frontal part, the accuracy and comprehensiveness of data acquisition are improved, the accuracy and dimension of evaluation are improved by evaluating the blinking frequency, the mouth corner displacement and the frontal muscle stretching amplitude, and by utilizing the extraction of the deformation characteristics and the calculation of the movement amplitude gradient, the accuracy and the comprehensiveness of the evaluation are improved. The time sequence analysis is combined, the evaluation of the consciousness state becomes more sensitive and accurate, potential changes of consciousness can be found in time, and therefore, rich data interpretation is provided for diagnosis and monitoring through quick response, and the density and distribution characteristic analysis of sudden change points, so that the consciousness state can be quickly and accurately evaluated under the condition that a wounded person is not contacted.

This invention discloses an intelligent shore-based rescue method, system, and computer-readable medium. The method involves a first device determining the respective rescue routes of a drone and an unmanned vessel based on a user's distress call. The drone conducts a search and rescue operation according to its route, generating the current location of the person in the water. The first device detects the consciousness state of the person in the water based on real-time image data collected by the drone at the current location. Then, based on the detection results, different surface rescue tasks are performed on the person in the water according to the determined rescue method. Therefore, this embodiment determines different rescue methods based on the consciousness state of the person in the water, which not only enables rapid rescue but also improves the success rate of rescue. This provides an automated rescue solution with intelligent perception, precise positioning, and rapid response, solving the technical problem of low rescue rates for people in the water due to mismatched rescue methods, inaccurate positioning, or untimely rescue in existing technologies.

The invention provides an electroencephalogram consciousness monitoring data analysis method and system applied to anesthesia management. The method comprises the following steps: acquiring EEG signal entropy sequence data of an anesthesia object, carrying out dynamic entropy change analysis on the EEG signal entropy sequence data to obtain an entropy change feature vector of the anesthesia object, carrying out time domain phase coupling modeling on the EEG signal entropy sequence data to obtain a phase synchronization feature matrix of the anesthesia object, and according to the entropy change feature vector and the phase synchronization feature matrix, carrying out dynamic entropy change analysis on the EEG signal entropy sequence data to obtain the EEG signal entropy sequence data of the anesthesia object. Generating consciousness state fusion features of the anesthesia object; according to the consciousness state fusion features, anesthesia state prediction is conducted on the anesthesia object, and the EEG signal entropy of the sampling time sequence nodes of the anesthesia object in the second time period is obtained. According to the method, accurate prediction of the EEG signal entropy of the sampling time sequence node of the anesthetic object in the second time period can be achieved, the anesthetic state of the anesthetic object can be monitored more accurately, the anesthetic dosage can be adjusted in time, and the safety and effectiveness of the operation process are ensured.

To prevent an aircraft accident caused by unconsciousness by continuously tracking a consciousness state of an aircraft pilot.SOLUTION: A device for collecting biometric and posture information for tracking consciousness of a rotorcraft pilot, collects a physiological signal, posture information, etc. of a rotorcraft pilot by comprehensively utilizing cameras, on-body wearable devices, control stick pressure detection sensors, etc. while an aircraft pilot is in flight to track a state of consciousness of the rotorcraft pilot in real time, transmits the collected biometric information to an integrated data processing and storage device with a built-in flight data recorder, and generates a warning signal upon identification of singularity associated with loss of consciousness.SELECTED DRAWING: Figure 1

The invention discloses a medical comprehensive assessment method for old people and related equipment, and relates to the field of health management, and the method comprises the steps: obtaining the basic information of the to-be-assessed old people; carrying out body function state evaluation on the human body to obtain a body function state evaluation result related to the life self-care ability and the falling risk; performing nutrition state evaluation on the old people based on the nutrition evaluation scale to screen the risk of malnutrition; performing psychological state assessment on the old people to obtain psychological state assessment results including cognitive functions, emotional states and consciousness states; and comprehensively integrating the basic information, the body function state evaluation result, the malnutrition evaluation result and the psychological state evaluation result to form an old people comprehensive evaluation report. The evaluation report can reflect the health risk characteristics of the old people from multiple dimensions, and provides a scientific basis for the formulation of subsequent medical schemes, nursing measures or intervention strategies, thereby facilitating the improvement of the pertinence and effectiveness of the health management of the old people.

The present invention provides a system for assessing the state of consciousness of injured persons based on facial recognition, which relates to the field of health assessment technology. It includes a facial information extraction module, a facial feature analysis module, a state of consciousness calculation module, an anomaly detection module, and a state of consciousness assessment module. In the present invention, an infrared camera is used to carefully capture the subtle movements of the muscles around the eyes, corners of the mouth, and forehead, thereby improving the accuracy and comprehensiveness of data collection. By evaluating the blinking frequency, displacement of the corners of the mouth, and stretching amplitude of the forehead muscles, the accuracy and dimension of the assessment are improved. By extracting deformation features and calculating the gradient of motion amplitude, combined with time series analysis, the assessment of the state of consciousness becomes more sensitive and accurate, and is able to detect potential changes in consciousness in a timely manner, thereby responding quickly. The density and distribution feature analysis of mutation points provide rich data interpretation for diagnosis and monitoring, so that the state of consciousness of the injured person can be quickly and accurately assessed without contacting the injured person.

The present invention relates to the technical field of biological consciousness state monitoring, and specifically to an emergency patient consciousness state monitoring system based on bioelectric signals. The system of the present invention uses an EEG signal acquisition module and a signal extraction module to acquire θ rhythm signals, α wave signals, and γ wave oscillation signals; uses a phase amplitude coupling event time position positioning module to acquire effective phase amplitude coupling events and their occurrence time positions; and uses a patient consciousness state monitoring module to obtain patient consciousness state monitoring indicators, and fits the patient consciousness state monitoring indicators with a time series to complete patient consciousness state monitoring. The present invention can accurately locate θ-γ cross-brain region phase amplitude coupling (PAC) events, and overcome the limitations of traditional technologies in fuzzy spatiotemporal positioning of PAC events and delayed dynamic tracking, thereby achieving millisecond-level high-resolution monitoring of emergency patient consciousness states and providing a quantifiable neuroelectrophysiological basis for real-time intervention in consciousness disorders.

The invention belongs to the field of flight personnel state monitoring, and discloses a meta-consciousness ability training method and system based on a neural biofeedback technology. The system can obtain neural activity data directly related to the distraction state in a real and continuous task situation, hysteresis and unreliability caused by dependence on subjective reports or behavioral expressions are avoided, and the accuracy and objectivity of distraction monitoring are improved from the source. The decoding model is embedded into a closed-loop neural feedback training system, so that an acoustic feedback signal can be triggered in time when a distraction state occurs, a trainee is prompted to perceive attention deviation, and the self consciousness state is autonomously regulated and controlled without external guidance. The closed-loop feedback can strengthen a conditioned reflex mechanism paying attention to a regression task, and the self-monitoring and self-adjusting capability of meta-awareness is remarkably improved.

The application provides a prognosis prediction method and system for chronic Doc patients, relates to the technical field of clinical prognosis evaluation, and collects multi-modal data such as neuroimaging, neuroelectrophysiological data, biochemical indexes and clinical data, carries out standardized processing and feature extraction, and fuses spatial features, time sequence features and key features.Combining a trained consciousness state grading evaluation model and a prognosis prediction model, a feature level data set is generated, and the consciousness state grading and prognosis development trend of the patient are accurately predicted.The application effectively integrates the complementary information of multi-modal data, improves the accuracy and reliability of prognosis prediction, and provides scientific support for clinical decision-making, individualized treatment and medical resource optimization.

Provided are a consciousness state detection system and method, wherein the system comprises: a visual stimulation apparatus (110) arranged in a visual field region of a target subject and configured for displaying visual stimulation information so as to perform, on the basis of the visual stimulation information, visual stimulation on the target subject (S310), wherein the visual stimulation information comprises visual field shadow stimulation and / or visual threat stimulation; a feedback behavior collection apparatus (120) connected to a consciousness state determination apparatus (130) and configured for collecting, when the visual stimulation information is displayed, a target feedback behavior of the target subject and sending the target feedback behavior to the consciousness state determination apparatus (S320); and the consciousness state determination apparatus (130), which is configured for receiving the target feedback behavior sent by the feedback behavior collection apparatus (120), and determining, on the basis of the target feedback behavior and a standard feedback behavior, the consciousness state of the target subject (S330). By adopting the technical solutions of the present invention, the consciousness state of the target subject can be quickly, conveniently, and accurately determined.