109 results about "Autonomic nervous system" patented technology

The invention relates to the technical field of intelligent medical treatment, and discloses an AI-based severe patient sepsis early warning method and system. According to the method, a multi-organ interaction mechanism is deeply analyzed by dynamically constructing an organ-level causal network, and early-stage accurate early warning of sepsis is realized: high-frequency physiological waveforms, asynchronous laboratory indexes and treatment intervention data are fused, and the capture ability of microcirculation failure and autonomic nerve decline is improved; the early warning threshold value is dynamically adjusted based on the treatment coverage degree, and the delay and false alarm defects of a fixed threshold value mechanism are effectively overcome; a pathogen targeted therapy map and an organ function support scheme are automatically generated by a graded triggered clinical action chain, and the clinical decision response time is shortened; according to the method, the risk of missed diagnosis is reduced while the early warning sensitivity is improved, and an earlier and more reliable intervention window is provided for critical patients.

In some embodiments, systems and methods can include a wearable device with an electrically conductive skin interface that excites the underlying nerves from a transcutaneous surface stimulator. The device may be sized for a range of user sizes with stimulation electrodes positioned to target the appropriate nerves, such as the peroneal, femoral, saphenous and / or tibial nerves. The stimulation may include burst stimulation, and involve receiving an input relating to autonomic nervous system activity of the patient.

The invention relates to the technical field of medical health monitoring, and discloses a multi-modal data fusion health monitoring analysis early warning method and system, and the method comprises the steps: synchronously collecting motion and heart rate data streams through a wearable device, generating a coupling vector of the motion intensity and the heart rate change rate in a short time window, and carrying out the long-time accumulation to form a coupling vector cluster, and judging the physiological regulation stability by evaluating the change of the morphological dispersion. Micro-motion is converted into a natural probe, through dynamic evolution of a motion-heart rate coupling relation, transition from observation of vital sign values to evaluation of autonomic nerve regulation ability is achieved, early decline of body functions can be captured before conventional indexes are abnormal, and meanwhile evaluation reliability in a complex environment is ensured through frequency domain feature filtering.

The invention provides a cardiac autonomic neurodynamics quantitative evaluation method based on a phase ordering signal averaging technology. The cardiac autonomic neurodynamics quantitative evaluation method comprises an ECG signal preprocessing step, a QRS wave detection and processing step, a phase ordering signal averaging step and an autonomic neurodynamics quantitative analysis step. According to the cardiac autonomic neurodynamics quantitative evaluation method based on the phase ordering signal averaging technology, on the basis of inhibiting aperiodic interference and improving index stability in a complex physiological environment, continuous analysis of cardiac sympathetic nerve activity and cardiac parasympathetic nerve activity is carried out; time-varying CSI and CPI indexes are extracted to realize quantification of cardiac autonomic neurodynamics, and a lightweight algorithm framework is designed to adapt to real-time monitoring requirements of portable equipment.

The invention relates to the technical field of mental state monitoring, in particular to a mental state real-time monitoring system based on intelligent wearable equipment, which comprises a physiological signal analysis module, a voice data analysis module, a mental fluctuation evaluation module, a fatigue boundary judgment module and a mental state analysis module. According to the method, by extracting key physiological and voice signal features, the activity stability of the neural signal and the autonomic nervous system of an individual can be more accurately judged, the stability of the physiological signal is effectively evaluated, and by calculating the fluctuation trend of the mental state and combining physiological and voice data, the accuracy of the physiological signal is improved. Real-time changes of emotion fluctuation and mental load of an individual can be captured more comprehensively, so that mental state monitoring is more comprehensive and accurate, real-time evaluation of mental fatigue is performed according to physiological and voice signal changes, a more objective fatigue judgment basis is provided, the accuracy of mental health state evaluation is enhanced, and the mental health state evaluation efficiency is improved. And more accurate mental health state information is provided for individuals.

The invention discloses a psychological health screening method and system based on a large model, and relates to the technical field of psychological health, and the method comprises the following steps: scale data, micro expression video data and physiological signal data of a user are acquired, a multi-modal data acquisition module is constructed, and the physiological signal data at least comprises EEG (electroencephalogram) and PPG (pulse photoplethysmography); performing preprocessing and feature extraction on the scale data, the micro-expression video data and the physiological signal data; according to the psychological health screening method and system based on the large model, cross validation is carried out from three dimensions of subjective reports, unconscious behaviors and autonomic nerve responses by fusing multi-modal data such as scales, micro expressions, EEG and PPG; the problem that a traditional single scale method is easily influenced by subjective deliberate concealment, memory deviation and social sponsoring effect is fundamentally solved.

The invention discloses an acupuncture intervention method after a pancreatic cancer operation, and aims to solve the problem that autonomic nerve regulation based on heart rate variability in an acupuncture stimulation closed loop is difficult to objectize and safely optimize. Heart rate variability time-frequency and time-domain features and respiratory coherence are extracted based on synchronous compression wavelets, a reliability score is generated, short-time heart rate variability and uncertainty are predicted through a neural state space model, a hierarchical control barrier function is generated through a context gating network, a safe MPC is constructed, and real-time quadratic programming solution is carried out. The heart rate variability enters the target domain and the stimulation parameter change rate and the energy consumption are reduced under the condition that safety constraints such as current, pulse width, charge quantity and impedance are met by combining safety verification and self-adaptive updating, and the reliability and the robustness of closed-loop control are improved.

The invention relates to the technical field of medical instruments, in particular to a multi-mode biological feedback ear vagus nerve self-adaptive stimulation device and method.The device comprises a host, a stimulation electrode, a signal collection bracelet and an electroencephalogram collection module, and the host comprises core hardware configuration and a power management system; the signal acquisition bracelet comprises an ECG module, a PPG module, a GSR module, a six-axis acceleration sensor and the like. The ear vagus nerve stimulation parameter can be dynamically adjusted through real-time analysis of multi-mode data such as electrocardio, electroencephalogram, heart rate variability, respiration-heart rate synchronism and emotional state, personalized precise treatment is achieved, meanwhile, the wearing comfort and the durability of the device are improved, and the application range is wide. The traditional Chinese medicine composition can be used for auxiliary treatment of various diseases such as inflammatory bowel disease, epilepsy, chronic insomnia, depression, chronic pain, anxiety disorder, post-traumatic stress disorder and autonomic nerve dysfunction, and the functions of a nervous system are adjusted and the symptoms of a patient are improved by accurately stimulating the vagus nerve in the auricular concha area.

The invention relates to a method and system for predicting post-induced hypotension of a patient, and belongs to the technical field of hypotension prediction.The method comprises the steps that original data reflecting the cardiovascular autonomic nerve regulation capacity of the patient is obtained; preprocessing the original data to obtain target data, and calculating a target pressure reflex sensitivity BRS and a target pressure reflex effective index BEI based on the target data and the same-direction change sequence of the continuous heartbeat; inputting the target pressure reflex sensitivity BRS, the target pressure reflex effective index BEI and the patient baseline data into a Logistic regression model to obtain a hypotension risk probability; and determining a hypotension risk level of the patient based on the hypotension risk probability and a preset threshold range. According to the method, the target pressure reflex sensitivity BRS and the target pressure reflex effective index BEI serve as predictive factors, so that the probability of predicting hypotension of a patient can be improved before the patient receives anesthesia induction.

The invention discloses a sympathetic cervical spondylosis autonomic nerve regulation enhancing method based on a brain-computer interface, and relates to the technical field of nerve regulation and repair. According to the method, by synchronously collecting electroencephalogram and skin conductance signals and conducting time-frequency domain conjoint analysis and Lempel-Ziv complexity evaluation, accurate quantitative evaluation on sympathetic nerve activity and nerve disorder degree is achieved, double-model collaborative decision-making of machine learning and deep reinforcement learning is utilized, personalized nerve regulation parameters are intelligently generated, and the method has the advantages of being high in accuracy and high in accuracy. High-targeting and safe intervention is implemented through double-target hierarchical regulation and control aiming at neck sympathetic nerves and vagus nerves, and stimulation parameters are dynamically optimized in a closed-loop manner by adopting a genetic algorithm on the basis of real-time feedback of heart rate variability, skin conductance and autonomic nerve balance indexes, so that the stimulation accuracy is improved. Therefore, the sympathetic cervical spondylosis autonomic nerve regulation efficiency and effect are enhanced.

The invention is applied to the technical field of intelligent health and biological feedback, and discloses a VR motion sickness state detection method based on multi-modal physiological parameter fusion, and the detection method comprises the following steps: S1, carrying out data acquisition through a data acquisition module: fixing an electrocardiosignal around a heart in the form of three-lead number electrode points, setting the sampling frequency to be 1024Hz, and setting the sampling time to be 1h; the skin electric signal acquisition is arranged at the tail end of a finger in a 2-lead number electrode point form, the sampling frequency is 64Hz, and the central electric signal and the skin electric signal in the VR operation process are respectively acquired from a heart signal and a finger skin surface layer signal of an operator. According to the VR motion sickness state detection method based on multi-modal physiological parameter fusion, the activity of an autonomic nervous system and the activity of a sympathetic nerve are reflected through electrocardio signals and skin electric signals respectively, physiological reactions of motion sickness are captured from different dimensions, and physiological state information when the motion sickness occurs is extracted more accurately through multi-modal fusion analysis.

The invention provides a fatigue assessment method and device based on cardiac autonomic neurodynamics and brain coupling analysis, and the method comprises the steps: extracting time-varying CPI and CSI features representing cardiac autonomic neurodynamics features through a PRSA technology, carrying out the coupling analysis through different frequency bands of CPI, CSI and EEG, and carrying out the comprehensive, accurate and objective assessment of fatigue. On the basis of overcoming the defects of strong subjectivity and poor real-time performance of a subjective scale, through second-level dynamic quantization of sympathetic nerve and parasympathetic nerve activity states and brain activity coupling states, the limitation of traditional pure dependence on EEG or ECG spectral analysis and a static IPFM model can be effectively solved; the comprehensive and objective evaluation precision of the fatigue severity under the complex physiological state is improved, and the dynamic real-time monitoring requirement of the fatigue state is met.

This invention relates to a treatment device (101) configured to treat epilepsy, the treatment device (101) comprising: a sensor (103) configured to determine a physiological condition of an individual, the sensor including an electrodermal activity sensor configured to determine a galvanic skin response; a storage module (105) configured to store data regarding the psychological state and behavioural information of the individual; one or more mechanisms configured to provide biofeedback and / or tactile stimulation to activate sympathetic nerve activity based on the physiological condition of the individual and the data regarding the psychological state and behavioural information of the individual and to change the individual's autonomic state, wherein the biofeedback mechanism comprises one or more screens configured to display an animation and the tactile stimulation mechanism comprises a vibrating device; and a controller (107) operatively connected to the sensor (103) and the storage module (105), the controller (107) being configured to control the operation of the one or more mechanisms based on the physiological condition of the individual and the data regarding the psychological state and behavioural information of the individual to provide biofeedback and / or tactile stimulation treatment to the individual. In a more general sense, the invention may relate to a treatment device configured noninvasively to treat neurological conditions and / or neuropsychiatric conditions, designed to modulate autonomic nervous system through biofeedback configured to change brain network. The treatment device comprising: physiological sensor, storage piling psychological data and operating controller to effectively provide at least one of biofeedback and tactile stimulation to the individual to curtail neurological and / or neuropsychiatric events

Essentially, the present invention comprises an assembly for transvascular stimulation from within an artery, enabling nerve stimulation to one or more regions of the autonomic nervous system around an artery by a bipolar guidewire having a distal end of a suitable shape, and this stimulation can be performed rapidly or for mapping purposes.

This invention discloses a material with high photothermal conversion efficiency, its preparation method, and its application in neural modulation, belonging to the field of biomedical technology. In this method, liquid metal is ultrasonically spun into nanoscale particles. Using these liquid metal nanoparticles as templates, hollow nanoshells composed of ultra-small metal nanoparticles can be prepared through an electrocoupling reaction with a metal salt. This method is simple, easy to operate, and applicable to various metals. The prepared material with high photothermal conversion efficiency has a hollow structure, a rough surface, and pores. This unique structure endows it with a strong photon trapping ability, significantly enhancing light absorption and exhibiting ultra-high photothermal conversion efficiency. This invention allows for the injection of this material into the nerve, utilizing its excellent photothermal effect for rapid and precise neural modulation, thereby achieving effective prevention and treatment of autonomic nervous system-related diseases, and showing promising application prospects.

This disclosure presents systems and methods for baroreflex activation therapy (BAT) to regulate inflammation by modulating autonomic nervous system activity. Electrical stimulation is delivered to one or more baroreceptors, and real-time physiological signals are monitored, including inflammatory biomarkers (e.g., TNF-α, IFN-γ, IL-1, IL-6, IL-12, CRP) and autonomic parameters such as heart rate variability (HRV). A closed-loop feedback module analyzes biomarker fluctuations and autonomic balance changes and dynamically modifies stimulation parameters, including amplitude, pulse width, frequency, and duty cycle, to suppress systemic inflammation and restore autonomic balance. In certain embodiments, multi-channel stimulation architectures and AI-driven algorithms or machine learning models analyze biomarker trends and historical patient response patterns to optimize therapy. The disclosed BAT systems and methods may be used to treat inflammatory diseases, autoimmune disorders, cancer progression, chronic inflammatory pain conditions, arrhythmias associated with inflammation, and metabolic dysfunction.

The invention relates to the technical field of evaluation of heart rehabilitation curative effects of breast cancer chemotherapy patients, in particular to a method and system for evaluating the heart rehabilitation curative effects of the breast cancer chemotherapy patients, and the method comprises the following steps: continuously obtaining heart rate variability data and skin conductance data of the breast cancer chemotherapy patients; based on the heart rate variability data and the skin conductance data, the activation state of the autonomic nervous system of the patient is judged; according to the activation state of the autonomic nervous system of the patient, quantifying the intensity and duration of the internal emotional state of the patient, and generating an emotional energy index; when the conventional physiological indexes of the patient fluctuate, determining a physiological fluctuation attribution result in combination with the emotional energy index to distinguish whether the physiological fluctuation is derived from heart function change or emotional influence; and evaluating the cardiac rehabilitation effect of the patient based on the physiological fluctuation attribution result. The accuracy of heart rehabilitation curative effect evaluation can be improved.

Embodiments of the present disclosure undertake physiological measurements of a subject whilst the subject is listening to music. The physiological measurements, together with predetermined characteristics of the music, are then used as inputs into a machine learning network, such as a graph convolution neural network (GCNN), which undertakes a classification based on the physiological measurements and musical properties as to whether the subject has a particular disease or pathological condition, such as for example hypertension. The use of the music whilst obtaining the physical measurements resulted in an increase in accuracy of the measurement of the disease or condition prevalence of greater than 10 to 15%. This improvement is due to the modulatory effects of music on the autonomic nervous system augmenting differences between people with distinct autonomic profiles.

Systems and methods for controlling autonomic symptoms or side effects via spinal cord stimulation are discussed. An exemplary neuromodulation system comprises an electrostimulator to provide spinal cord stimulation (SCS) to a neural target, a user interface device to receive a user input including an autonomic symptom and affected anatomy, and a controller circuit to determine or adjust a stimulation parameter based at least on the autonomic symptoms and the affected anatomy. Spinal cord stimulation can be delivered in accordance with the determined or adjusted stimulation parameter to alleviate the autonomic symptom, or to treat or alleviate autonomic disorders.

Methods, systems and devices are provided to stimulate the vestibular system in such a way as to influence the neurological components of the autonomic nervous system and reduce an anxiety level in a subject. A device with one or more electrodes placed over a subject's scalp provides vestibular nerve stimulation (VeNS) to the vestibular nerve, which is then carried into the vestibular nucleus in the brainstem and thereafter transmitted to the neurological components of the autonomic nervous system to reduce a physiological reaction to an anxiety event. The characteristics of the stimulation signal and duration of the treatment are configured to allow the treatment to be delivered before, during or after an anxiety event to potentially prevent or at the very least reduce an anxiety response in the subject.

The invention relates to the technical field of intelligent psychological health monitoring and early warning, and particularly discloses a psychological health early warning method and system based on intelligence, and the method comprises the steps: collecting the skin temperature fluctuation and body movement frequency data of a user in real time through a wearable device in a psychological health monitoring period; independently reflecting autonomic nerve activity intensity and behavior rhythm coordination under emotion induction; key features are extracted in combination with Haar wavelet transform and fast Fourier transform and fused and input into the trained gradient boosting tree model, and quantitative evaluation and intelligent judgment of the psychological stability state of the user are achieved; whether a grading early warning mechanism is triggered or not is judged according to the evaluation result, first-level or second-level mental health early warning is provided, and the system comprises a data acquisition module, an autonomic nervous system response evaluation module, a psychological coordination evaluation module, a psychological state stability evaluation module and an early warning module and has the advantages of being non-invasive, high in precision and high in real-time performance.

The invention provides a physiological state control system, a physiological state control method, and a vibration wave calculation program product capable of reducing burden on a living body and making the autonomic nervous system close to normal. A physiological state control system according to an embodiment of the present invention is provided with: a waveform measurement device that acquires waveform information relating to a living body; a physiological state control device that calculates a vibration wave applied to the living body on the basis of the waveform information acquired by the waveform measurement device; and a drive device that applies the calculated vibration wave from outside the living body to at least one of the carotid bifurcation and the vertebral artery of the living body.

A method and device for modulating the autonomic nervous system adjacent a pericardial space to treat cardiac arrhythmia includes a treatment source arranged to supply a treatment medium, a catheter having an end sized for insertion into the pericardial space, a medium delivery assembly having a distal end arranged to be positioned by the catheter into the pericardium, with the distal end of the delivery assembly comprising a delivery tip arranged to extend away from the distal end of the catheter into the pericardial space. A connector operatively couples the delivery tip of the medium delivery assembly to the treatment source, and the delivery tip of the medium delivery assembly including a plurality of delivery points for delivering the treatment medium at a plurality of treatment areas within the pericardial space. The device performs modulation or ablation of the autonomic nervous system at selected treatment areas within the pericardium.

The invention relates to a composition for use in regulating the autonomic nervous system.

The invention discloses a heart rate variability fatigue detection method and system based on WiFi signals, and relates to the technical field of wireless sensing. The method comprises the following steps: controlling a WiFi transceiver to collect an original CSI signal of an environment in which a target individual is located, and preprocessing the original CSI signal; based on a blind source separation technology, independent source signals are dissociated from the preprocessed CSI signals, and heart signal components are selected through quantitative calculation; a heart beat interval sequence is extracted from the heart signal components, and heart rate variability characteristics reflecting the state of the autonomic nervous system are extracted; and inputting the heart rate variability characteristics into a pre-trained fatigue classification model, and outputting a fatigue state judgment result corresponding to the target individual. According to the method, the existing commercial WiFi facility is utilized, a user does not need to wear equipment, early-stage, objective and non-inductive high-precision recognition of physiological fatigue is realized, meanwhile, non-invasiveness, privacy protection and low cost are considered, and the method has certain popularization value.

A system for monitoring autonomic nervous system (ANS) function in a subject includes at least one sensor configured to acquire a first physiological signal related to heart activity of the subject, one or more additional sensors configured to acquire one or more physiological signals, a processing unit configured to receive, process and analyze the first and additional physiological signals to monitor / detect, in real time, at least one of an autonomic nervous system dysfunction and a change in a physiological state of the subject and determine an output condition based on the detection, and an output mechanism configured to perform, based on the output condition, generating an alert, initiating a treatment, and / or storing data. At least one of the additional sensors is a blood glucose sensor, a respiration sensor, a sudomotor activity sensor, a pulse wave sensor, an electroencephalography (EEG) sensor, an electromyography (EMG) sensor or a motion sensor.

The embodiment of the invention provides an intelligent detection system and device based on ventricular assist equipment, and relates to the technical field of medical instruments.The system comprises the ventricular assist equipment and detection equipment, and the ventricular assist equipment is implanted into the heart of a patient in a percutaneous intervention mode and assists the heart of the patient in blood pumping; the detection device is used for detecting physiological nerve parameters of a patient during operation of the ventricular assist device, and the detection device executes the following intelligent detection method: acquiring a physical measurement signal at the current moment; mapping the physical measurement signal into a target discharge frequency of the baroreceptor according to a preset nonlinear mapping relation; and based on the target discharge frequency, adopting a physiological correlation model to predict the target neural activity of the patient. By applying the scheme provided by the embodiment, the autonomic nerve regulation state of the patient can be accurately and continuously evaluated.

The invention relates to an emotion recognition method based on cross fusion of multiple time-frequency diagrams. Single-path electrocardiosignals are subjected to fine grit decomposition and converted into multi-dimensional time-frequency diagrams so as to construct a multi-view signal description system. Through multi-time-frequency graph fusion and a local-global feature cross fusion mechanism, information of signals under different time scales and frequency resolutions is dynamically integrated, so that complex dynamic states of rapid fluctuation and slow adjustment of the autonomic nervous system are comprehensively captured. Meanwhile, heart rate variability is used as key neuroscience priori knowledge and is directly embedded into a model input and feature learning process. In the aspect of feature extraction, a convolution block and a Transform block are crossed and fused to realize collaborative perception of local subtle changes and global function states, and deep features with higher robustness and higher discrimination are obtained with lower calculation cost.

A moving image acquisition unit (111) acquires moving image data indicating a moving image of the user's face captured by the user using a camera (16). The acquired moving image data is accumulated in a moving image DB (121) of a memory (12). A pulse measurement unit (112) reads the moving image data from the moving image DB (121), and measures vital values including pulse on the basis of the moving image data. A ratio calculation unit (113) calculates the ratio of sympathetic nerves and parasympathetic nerves on the basis of the pulse included in the measured vital values. An activity calculation unit (114) calculates the activity of the autonomic nerves overall on the basis of the pulse included in the measured vital value. A plotting unit (115) plots the state of the user's nervous system indicated by LF / HF and TP on a plane in which LF / HF and TP are the two axes.