568 results about "Stroke" patented technology

The invention discloses a brain-computer hybrid intelligent closed-loop swallowing rehabilitation system for treating dysphagia after stroke, and relates to the field of artificial intelligence medical instruments. The system is composed of a plurality of key modules: an intelligent swallowing brain-computer interface module for accurately identifying a swallowing intention through multi-modal physiological signal acquisition and processing; the intelligent swallowing functional electrical stimulation module is used for finely regulating and controlling stimulation parameters according to the condition of the patient; the AI auxiliary online integrated module is used for realizing non-invasive brain-controlled swallowing and high-precision AI regulation and control; the closed-loop intelligent feedback regulation and control module is used for real-time monitoring, early warning and self-adaptive optimization of electrical stimulation; the cloud platform remote monitoring and data storage module supports remote diagnosis and treatment of doctors; and the man-machine interaction interface display and printing module optimizes doctor-patient interaction. According to the system, a brain-computer interface and FES are combined, a personalized, safe and efficient rehabilitation scheme is provided for a patient based on data driving and an artificial intelligence algorithm, swallowing function recovery can be accelerated, complications are reduced, and the system has great clinical and social values.

The invention discloses an intelligent diagnosis and risk assessment method and system for cerebral apoplexy related to atrial fibrillation, and relates to the technical field of atrial fibrillation detection.The method comprises the steps that multi-dimensional data of atrial fibrillation patients in a clinical information system are integrated, a structured database is generated, and a standardized data set is output; a standardized data set is adopted to train a first machine learning model, and model performance is optimized through parameter joint search and a training set-verification set convergence dynamic monitoring mechanism; performing cross validation on a feature weight sorting result in the optimized diagnosis model and a clinical index risk association degree calculated by a second machine learning model to generate an interaction map; and based on clinical event data containing timestamps in the structured database, adopting a third machine learning model to extract time sequence features, and combining with a survival probability analysis model to generate a risk assessment report. According to the invention, through an intelligent model adjusting and optimizing mechanism, multi-dimensional medical data are effectively integrated, and the recognition precision of the atrial fibrillation related cerebral apoplexy is greatly improved.

The disclosure provides methods for treating a subject in need thereof comprising administering to the subject a therapeutically-effective dose of psilocybin. The methods described herein may be used to treat a variety of diseases, disorders, and conditions. For example, the methods may be used to treat neurocognitive disorders (e.g., Alzheimer's disease, Parkinson's disease), ADHD, Epilepsy, Autism, Sleep-wake disorders, Chronic pain, Inflammatory Disorders, IBD, Stroke, ALS, and / or Multiple Sclerosis.

The disclosure provides methods for treating a subject in need thereof comprising administering to the subject a therapeutically-effective dose of psilocybin. The methods described herein may be used to treat a variety of diseases, disorders, and conditions. For example, the methods may be used to treat neurocognitive disorders (e.g., Alzheimer's disease, Parkinson's disease), ADHD, Epilepsy, Autism, Sleep-wake disorders, Chronic pain, Inflammatory Disorders, IBD, Stroke, ALS, and / or Multiple Sclerosis.

The invention relates to the technical field of medical care informatics, and discloses an intelligent post-stroke cognitive impairment assessment method based on brain network dynamic reconstruction, which comprises the following steps: acquiring multi-modal brain image data of a patient, dynamically compensating the difference between haemodynamic delay and white matter conduction velocity through a nerve-blood vessel coupling model, and calculating the post-stroke cognitive impairment; precise space-time alignment of function and structure signals is realized; a pulse neural network dynamic entropy change model is constructed based on the alignment data, functional connection strength change is coded into a pulse distribution sequence, and Gamma wave band synchronization enhancement and other compensatory features are extracted; constraining rationality of brain network reconstruction by adopting an energy optimal transmission model, and generating a compensatory thermodynamic diagram; and real-time calculation of the edge end is realized through pulse time sequence compression coding. The limitation of traditional static analysis is avoided, the algorithm achieves microsecond response on embedded equipment through the pulse coding technology, and a reliable stroke rehabilitation evaluation tool is provided for primary hospitals.

The invention discloses a multi-priori knowledge fused cerebral apoplexy rehabilitation map convolutional network evaluation method, and belongs to the technical field of cerebral apoplexy rehabilitation evaluation. Firstly, a high-precision prior information matrix is automatically generated through a collaborative and causal relationship automatic reasoning method based on Riemannian manifold geometry and transfer entropy, the problem that in the prior art, engineering depends on artificial features is effectively solved, and interpretable physical prior guidance is provided for a model. Then, through a multi-relation graph construction and attention weighting multi-modal adaptive fusion method, spatio-temporal features and priori knowledge are adaptively fused, an optimized graph structure is constructed, and the representation ability and interpretability of the model to complex joint interaction are improved. And finally, through a space-time diagram convolutional network guided by prior information and a comparative learning collaborative optimization method, the generalization ability and evaluation precision of the model in a small sample scene are remarkably improved through data enhancement and loss function optimization.

The invention discloses an informatization process processing method for a thoracic pain stroke trauma treatment mode, and the method comprises the following steps: 1, information collection and preprocessing: collecting the physiological sign data of a patient through a mobile terminal, and analyzing the physiological sign data based on a deep learning model, so as to obtain a preliminary diagnosis result of an illness state; classifying and marking the patient according to the preliminary diagnosis result of the illness state to obtain a classification and marking result, and uploading the classification and marking result, the physiological sign data and the geographic position information of the patient to a regional medical collaborative server; step 2, multi-center cooperative distribution: after receiving the classification marking result, the physiological sign data and the geographic position information of the patient, a regional medical cooperative server performs calculation processing based on a preset medical resource scheduling model; and step 3, performing a treatment process: sending the optimal treatment path scheme to a medical information system of a target medical center by the regional medical cooperation server, triggering the target medical center to start an emergency plan, and deploying medical resources.

The invention discloses a cerebral apoplexy medical image segmentation method, electronic equipment and a storage medium, and the method comprises the steps: obtaining a multi-modal cerebral apoplexy medical image, carrying out the preprocessing of the obtained image and a label, and obtaining a data set; for the images in the data set, using a CNN encoder and a Transform encoder which are parallel to each other to extract complementary features of each level; performing feature fusion on the complementary features of each level, and inputting the fused features into a pyramid decoder of the corresponding level; the pyramid decoder learns a plurality of features of different scales to obtain multi-scale features of segmentation categories; and distributing a fusion weight to the multi-scale features obtained by each category, carrying out fusion, and taking a fusion result as a final semantic segmentation result of the category. The invention provides a novel CNN-Transform combined network, the network fully utilizes the advantages of the CNN and the Transform and can effectively perform multi-scale feature learning, and the learned multi-scale features are beneficial to improving the segmentation performance.

The present invention relates to methods for remotely tuning treatment parameters in movement disorder therapy systems where the subject and clinician are located remotely from each other. The present invention still further provides methods of quantifying movement disorders for the treatment of patients who exhibit symptoms of such movement disorders including, but not limited to, Parkinson's disease and Parkinsonism, Dystonia, Chorea, and Huntington's disease, Ataxia, Tremor and Essential Tremor, Tourette syndrome, stroke, and the like. The present invention yet further relates to methods of remotely tuning a therapy device using objective quantified movement disorder symptom data to determine the therapy setting or parameters to be transmitted and provided to the subject via his or her therapy device. The present invention also provides treatment and tuning remotely, allowing for home monitoring of subjects.

The invention discloses a monitoring method and system and a related device, which are applied to first electronic equipment, the first electronic equipment is provided with a first circuit, and the first circuit comprises a first electrode, a second electrode, a third electrode, a fourth electrode, an excitation current generation unit and a voltage measurement unit; receiving and responding to a first instruction, and determining that the first electrode and the second electrode are in good contact with skin through a first circuit; first information is determined through the first circuit, the first electrode makes contact with a first position of the user skin, the second electrode makes contact with a second position of the user skin, and the first position and the second position are located at the two ends of the thoracic cavity tissue respectively; and outputting first information, wherein the first information comprises one or more of the following items: cardiac output, stroke output, heart rate, ejection fraction and cardiac function judgment result. Therefore, the heart function condition of the user can be monitored in real time, and the user can conveniently monitor anytime and anywhere.

The atomization device comprises a shell, an upper sleeve body, a medicine bottle, a lower sleeve body and a driving mechanism, the upper sleeve body is detachably arranged at the top of the shell, a first space is formed by the upper sleeve body and the shell, and a nozzle is formed in the top of the upper sleeve body; the medicine bottle is arranged in the first space in a replaceable mode, a piston for sealing liquid is arranged in the medicine bottle, and a nozzle module for atomizing liquid is arranged on the top of the medicine bottle. The lower sleeve body is rotatably arranged at the bottom of the shell and forms a second space with the shell; the driving mechanism is arranged in the second space and partially connected with the lower sleeve body. The driving mechanism comprises a push rod which extends to the piston and is connected with the piston. According to the atomization device, the medicine bottle is efficiently and conveniently replaced, the device can be repeatedly used, and the use cost of a patient is reduced; the medicine bottle and the driving mechanism are separated in two independent spaces, and the medicine bottle is only in contact with the head of the push rod during replacement, so that the influence on the propelling stroke precision or thrust stability of the driving mechanism is reduced or even completely avoided.

The invention belongs to the technical field of rehabilitation training, and particularly relates to an active stroke rehabilitation auxiliary training system which generates a personalized training base line through clinical evaluation data of a patient and guides the patient to cooperatively execute training actions through rehabilitation equipment according to the training base line. Training execution efficiency scores, patient active motion features and equipment auxiliary performance features are analyzed in real time, and rehabilitation equipment auxiliary strength and training task difficulty are dynamically adjusted in the training duration according to the double-feature real-time interaction state and the synchronous training execution efficiency scores; finally, the rehabilitation ability state of the patient is updated according to the multi-dimensional time sequence characteristics of the whole single training process, and a baseline correction instruction of the next training period is output based on the updated rehabilitation ability state, so that the limitation of singly paying attention to patient actions in the past is broken, and the boundary of patient independent effort and equipment assistance in the rehabilitation process is clearly distinguished; and the dynamic adaptability and accuracy of stroke rehabilitation training are effectively improved.

The invention discloses a stroke hand rehabilitation training method based on multi-modal data fusion, particularly relates to the field of hand rehabilitation training, and is used for solving the problems that in the existing rehabilitation process, the motion solidification risk cannot be recognized, and the training scheme is lack of individualized dynamic adjustment. According to the method, hand joint motion features are obtained by constructing a standardized hand function micro-evaluation task, and a personal motion mode baseline is established in combination with dynamic time warping and multi-scale permutation entropy analysis; extracting a neural motion curing index based on the difference change between the current motion mode and the optimal motion mode, and analyzing and generating a function recovery momentum feature by combining the rehabilitation progress gradient and the acceleration inflection point; and fusing the electromyographic signal coupling coordination index to generate a rehabilitation risk score, and when the risk exceeds a dynamic threshold value, triggering adaptive recombination of a training strategy to realize accurate early warning and personalized training regulation and control. Rehabilitation monitoring precision and training pertinence can be effectively improved, and high-quality recovery of stroke hand functions is promoted.

A polygenic risk score (PRS) for coronary artery disease, a construction method therefor, and an application thereof in combination with clinical risk assessment. The present invention first provides an application of a reagent for detecting individual information in preparation of a detection device for assessing the onset risk of the coronary artery disease, wherein the individual information comprises 311 CAD-related single nucleotide polymorphic sites, and the individual information preferably also comprises one or more of BP, BMI, DM, TC and Stroke-related single nucleotide polymorphic sites. The present invention further provides a method for constructing a comprehensive metaPRS for the coronary artery disease. In the present invention, the PRS and the conventional clinical risk factor score are further integrated, such that re-layering of the onset risk of the coronary artery disease can be realized. The present invention is of great significance to primary prevention of the coronary artery disease.

This invention is eyewear (e.g. eyeglasses) with electrodes (e.g. EEG sensors) which collect brain activity data (e.g. electroencephalographic data) which can be used to predict and / or detect health events (e.g. epileptic seizure, stroke, or heart attack) or function as a BCI (Brain-to-Computer Interface) for communication. There can be anterior and posterior electrodes on the eyewear temple and the temple can have an upward and / or inward curving wave or arm. A posterior electrode can have multiple electroconductive protrusions to help penetrate between strands of hair.

Clot material may be removed from a patient and separated from blood so that the blood may be collected using an efficient dual-stroke technique. The methods described herein withdraw clot and blood from a patient during a first stoke of a pump at a first rate, filter the blood to remove clot, and drive the filtered blood into a collection chamber at a second rate that is different from the first rate. The first rate may be optimized to disrupt and remove clot, while the second rate may be optimized to move the blood without damaging, e.g., lysing, the blood.

An exemplary non-contrast computer tomography (CT) system and method are disclosed employing AI-denoiser and dynamic range correction that remaps pixels on a portion of the brain to preserve stroke or net water uptake information in the image to accurately generate a whole brain image that readily show changes in net water uptake that could used to identify earlier stage or outset of a stroke or like injuries or conditions. The exemplary system and method can additionally provide quantification of net water uptake, e.g., for stroke diagnosis, in addition to visualization. The AI-denoiser and dynamic range correction may operate with an image inhomogeneity correction operation that can correct for subtle residual artifacts (e.g., cupping artifacts) that increases with skull thickness.

The invention discloses a preparation method of artemisia apiacea extracellular vesicles, which comprises the following steps: step 1, pre-treating artemisia apiacea, carrying out primary centrifugal treatment, removing large plant tissues and cell debris, carrying out secondary centrifugal treatment, filtering by a needle filter, and collecting; step 2, transferring the filtered suspension to a sucrose density gradient solution, then carrying out third centrifugal treatment, collecting the solution with the concentration of 30% in the layer, and carrying out fourth centrifugal treatment to obtain artemisia apiacea extracellular vesicles; the invention further discloses an artemisia apiacea extracellular vesicle, a pharmaceutical composition for treating cerebral apoplexy, a medicine and application of the artemisia apiacea extracellular vesicle in preparation of the medicine for treating cerebral apoplexy. The naturally-sourced vesicle delivery system provided by the invention is expected to have higher safety and lower toxic and side effects, and the enrichment concentration of the therapeutic component at the focus part of cerebral apoplexy is improved, so that the bioavailability and the treatment efficiency of the medicine are remarkably improved.

The invention relates to the field of medicine synthesis, and discloses a GCG-GLP-1 dual agonist compound. The GCG-GLP-1 dual-agonist compound provided by the invention is used for preparing a pharmaceutical composition for treating diseases, and the application of the pharmaceutical composition in preparing a medicine for treating at least one of the following diseases, the diseases include type II diabetes mellitus, impaired glucose tolerance, type I diabetes mellitus, obesity, hypertension, metabolic syndrome, dyslipidemia, cognitive impairment, atherosclerosis, myocardial infarction, coronary heart disease, cardiovascular disease, stroke, inflammatory bowel syndrome and / or dyspepsia or gastric ulcer, hepatic fibrosis disease and pulmonary fibrosis disease.

The invention relates to the field of medicine synthesis, and discloses a GLP-1 / GIP / GCG tri-agonist compound. The GLP-1 / GIP / GCG three-agonist compound is used for preparing a medicine composition for treating diseases, and the application of the medicine composition in preparing a medicine for treating at least one of the following diseases, namely, the GLP-1 / GIP / GCG three-agonist compound, and the GLP-1 / GIP / GCG three-agonist compound. The diseases include type II diabetes mellitus, impaired glucose tolerance, type I diabetes mellitus, obesity, hypertension, metabolic syndrome, dyslipidemia, cognitive impairment, atherosclerosis, myocardial infarction, coronary heart disease, cardiovascular disease, stroke, inflammatory bowel syndrome and / or dyspepsia or gastric ulcer, hepatic fibrosis disease and pulmonary fibrosis disease.

The invention discloses an application of indole-3-propionic acid as a biomarker in early warning of cognitive impairment after stroke. According to the application disclosed by the invention, the indole-3-propionic acid is confirmed as the biomarker of cognitive impairment after stroke through large-scale screening, and the indole-3-propionic acid belongs to a biomarker of a metabolite type, so that noninvasive sampling is facilitated, content fluctuation in a body can appear in a short time after stroke, and the cognitive impairment can be identified. The risk degree of cognitive impairment can be obtained by detecting within three months after stroke, the time node is earlier than that of conventional clinical diagnosis, and timely discovery and treatment are facilitated.

The invention relates to the field of medicine synthesis, and discloses a GLP-1 / GIP / GCG tri-agonist compound. The GLP-1 / GIP / GCG three-agonist compound is used for preparing a medicine composition for treating diseases, and the application of the medicine composition in preparing a medicine for treating at least one of the following diseases, namely, the GLP-1 / GIP / GCG three-agonist compound, and the GLP-1 / GIP / GCG three-agonist compound. The diseases include type II diabetes mellitus, impaired glucose tolerance, type I diabetes mellitus, obesity, hypertension, metabolic syndrome, dyslipidemia, cognitive impairment, atherosclerosis, myocardial infarction, coronary heart disease, cardiovascular disease, stroke, inflammatory bowel syndrome and / or dyspepsia or gastric ulcer, hepatic fibrosis disease and pulmonary fibrosis disease.

Sublingual or buccal dosage forms comprise at least one antioxidant compound, such as N-acetyl cysteine (NAC), or a pharmaceutically acceptable salt thereof. The sublingual or buccal dosage forms are administered for treating central nervous system (CNS) disorders, such as traumatic brain injury or stroke.

The invention relates to the technical field of rehabilitation evaluation, in particular to a spasm and contracture evaluation method and system based on multi-scale data feature fusion. The method comprises the following steps: collecting data such as biomechanics, surface myoelectricity, muscle-bone ultrasound and clinical information of patients suffering from spasm and contracture after clinical cerebral apoplexy; preprocessing the data, wherein the preprocessing comprises chain equation multiple filling, label coding, normalization processing, feature splicing, data transformation and data enhancement; constructing a deep learning model based on the combination of a CNN network, multi-scale feature fusion and a self-attention mechanism, wherein the deep learning model sequentially comprises a first feature extraction module, a second feature extraction module, a third feature extraction module, a feature fusion module and a classification module; inputting the preprocessed data into the model for training, and obtaining a spasm evaluation deep learning model through multi-round iteration optimization of model parameters; and inputting to-be-evaluated data into the model, and outputting an evaluation result. The method has the advantages that local features are effectively captured, the global dependency relationship is captured, and the model classification and generalization ability is improved.

The present disclosure relates to a model training method, an image reconstruction method, and a related device. A computer device acquires a pre-trained target neural network model, the target neural network model being obtained by training a plurality of groups of training samples by means of a machine learning algorithm, and each group of training samples comprising a CTP image and a CTA image which are paired with each other, wherein the CTP image and the CTA image which are paired with each other correspond to the same selected level of target tissue; a target CTP image is input into the target neural network model, such that the target neural network model reconstructs a target CTA image on the basis of the target CTP image. The blood vessel imaging effect of the target CTA image is close to that of a real CTA image or is even better that that of the real CTA image, thereby providing a real and accurate reference basis for examination of each tissue and organ, and a patient can undergo one less CTA examination, thereby increasing the speed of one-stop CT examination for stroke, avoiding exposure to radiation of one more CTA examination, and reducing one injection of a contrast agent, lowering the risk of side effects generated by the contrast agent.

A combined neuromodulation and / or neurostimulation system for mitigating locomotor deficits of / or neuronal disorders, especially Parkinson's disease, said system comprises: at least one Deep Brain Stimulation System for providing Deep Brain Stimulation to brain tissue of a subject, at least one control unit, configured and adapted to provide stimulation data, at least one stimulation unit, operatively connected to the at least one control unit, the at least one stimulation unit being configured and adapted to deliver epidural electrical stimulation to the dorsal side of the spinal cord of said subject, and at least one implantable pulse generator, wherein the at least one stimulation unit includes one or more electrodes configured to be implanted epidurally, the one or more electrodes being operatively connected to the at least one IPG.

A steering wheel system is disclosed for monitoring a driver's vital signs of a driver. The steering wheel system comprises a steering wheel and sensors integrated into the steering wheel. The sensors are configured to detect one or more driver vital signs. The steering wheel system comprises a memory storing computer executable instructions, and a processor configured to execute the computer executable instructions. The processor receives the one or more vital signs from the array of sensors, wherein the one or more vital signs correspond to cortisol levels, alcohol levels, one or more proteins associated with an occurrence stroke, one or more biomarkers associated with myocardial infarctions, temperature, pulse rate, and oxygen levels. The processor determines a health risk of the driver based at least in part on the vital signs and alerts the driver in response to the health risk exceeding a certain health risk level.

The invention relates to the field of medicine synthesis, and discloses a GLP-1 / GCG dual-agonist compound. The GLP-1 / GCG dual-agonist compound provided by the invention is used for preparing a pharmaceutical composition for treating diseases, and application of the pharmaceutical composition in preparation of a medicine for treating at least one of the following diseases, the diseases include type II diabetes mellitus, impaired glucose tolerance, type I diabetes mellitus, obesity, hypertension, metabolic syndrome, dyslipidemia, cognitive impairment, atherosclerosis, myocardial infarction, coronary heart disease, cardiovascular disease, stroke, inflammatory bowel syndrome and / or dyspepsia or gastric ulcer, hepatic fibrosis disease and pulmonary fibrosis disease.

A robotic massage system includes a robotic arm that is actuated in order to execute a massage plan comprising a plurality of strokes. It further includes a communication interface that receives feedback from a user affecting the massage plan. It further includes a controller that receives state information during execution of the massage plan and modifies the strokes in the massage plan based on the state information and the feedback.

The invention provides a multi-scene body position conversion-based standing-up assisting control method and system for the elderly suffering from stroke. According to the method, firstly, the standing-assisting device is controlled to obtain a fusion sensing result composed of body pressure distribution data and joint movement data, multi-feature coupling analysis is carried out to generate a combined recognition conclusion containing a body position state and a scene type, and then dynamic mode mapping is carried out according to the combined recognition conclusion. Outputting a target control mode matched with the current scene type and the body position, and finally performing power instruction synthesis by utilizing the target control mode to generate a cooperative control signal for driving the standing assisting equipment to execute body position conversion; according to the technical scheme provided by the invention, accurate conversion from standardized control to personalized control is realized, the suitability and the user experience of the standing assisting process are improved, the uncertainty and the individual difference in actual operation are overcome, and the stability, the safety and the adaptability of the body position conversion process are improved.