129 results about "Mental illness" patented technology

The invention relates to the technical field of medical care management, in particular to an intelligent mental disease risk assessment system which comprises a physiological rhythm extraction module, a rhythm alignment module, an interference analysis module, a branch recognition module and an assessment output module. According to the method, the sleep duration and the heart rate change are continuously recorded, the corresponding relation between the sleep rhythm and the heart rate fluctuation is constructed, a quantifiable mental rhythm parameter set is formed, dynamic mapping is established between sleep interruption and the heart rate fluctuation, and the stability of the individual physiological rhythm and the time structure of rhythm deviation are effectively revealed. Anchoring is performed based on a maximum offset day, a time contrast section is established around a specific time point, and differential features of variables in the section are finely extracted, so that micro rhythm disturbance is dynamically captured and measured. A coupling factor evaluation mechanism is constructed by using cross decision logic of sleep time history and heart rate amplitude, and the sensitivity and multi-dimensional analysis ability of rhythm change recognition are enhanced.

The present disclosure relates generally to compounds, their methods of synthesis, and their use in the treatment of mental illness or central nervous system disorders.

The subject matter described herein includes methods, systems, and computer readable media for early detection of a neurodevelopmental or psychiatric disorder using scalable computational behavioral phenotyping. According to one method for early detection of a neurodevelopmental or psychiatric disorder using scalable computational behavioral phenotyping includes obtaining user related information, wherein the user related information includes metrics derived from a user interacting with one or more applications executing on at least one user device; generating, using the user related information and a machine learning based model, a user assessment report including a prediction value indicating a likelihood that the user has a neurodevelopmental or psychiatric (neurodevelopmental / psychiatric) disorder and a prediction confidence value computed using relative contributions of the metrics to the prediction value generated using the machine learning based model; and providing the user assessment report to a display or a data store.

The invention discloses a psychological disease pre-diagnosis information processing method and system, and the method comprises the steps: collecting a multi-modal behavior signal and a physiological parameter signal of a user, and carrying out the differential privacy protection processing based on edge calculation and the noise separation processing based on wavelet transform, obtaining a standardized behavior feature sequence and a time sequence physiological feature vector; extracting behavior node features and psychological state markers from the standardized behavior feature sequence, and constructing a three-dimensional incidence matrix in combination with the time sequence physiological feature vector; and calculating a potential risk probability based on a graph neural network model, generating a pre-diagnosis grading result, fusing objective behavior environment data through a progressive protocol, outputting a personalized intervention strategy, and finally generating a comprehensive pre-diagnosis report. According to the method, accurate modeling of psychological-physiological-behavior dynamic association is realized through dynamic knowledge graph construction and cross-modal fusion analysis, meanwhile, data privacy protection is considered, and the accuracy and practicability of psychological health monitoring are effectively improved.

The invention relates to the field of psychological disease early warning, and discloses a psychological disease early warning method and system based on artificial intelligence, and the method comprises the steps: carrying out the feature extraction and data fusion of collected and preprocessed physiological and behavior data, carrying out the emotion analysis of the emotional state of a user through the fused data, and carrying out the early warning of psychological diseases. The method comprises the following steps: preliminarily judging whether individualized emotion is abnormal or not, comparing physiological features and behavior features of abnormal emotion according to an analysis result of emotion abnormality, performing time sequence analysis on the physiological features and behavior features of known psychological disease symptoms, detecting whether a user has psychological diseases or not, and further evaluating and analyzing the severity of the diseases. According to the method and the system, the disease is subjected to graded early warning, so that the user is helped to realize own emotion change, the psychological disease is discovered and intervened as soon as possible, the analysis and detection of the psychological state are more accurate and reliable, the detection efficiency of the psychological disease is improved, and the disease risk is reduced.

The present application relates to a sustained release delivery composition of a vesicular monoamine transporter type 2 (VMAT2) inhibitor, a deuterated derivative thereof, a pharmaceutically acceptable salt thereof, an active metabolite thereof, or a prodrug thereof for treatment of hyperkinetic movement disorders including, but not limited to, tardive dyskinesia (TD), Huntington's disease (HD) chorea, tremors, dystonia, chorea, tics, myoclonus, stereotypies, restless legs syndrome, and various other disorders with abnormal involuntary movements. The present application also relates to a sustained release delivery composition of an antipsychotic agent, a pharmaceutically acceptable salt thereof, an active metabolite thereof, or a prodrug thereof for treatment of schizophrenia, bipolar disorder, and other psychiatric diseases or disorders. The method of making or using the composition is also disclosed.

An apparatus and a method for controlling a pharmaceutical mixer of a medication for Attention Deficit Hyperactivity Disorder (ADHD) based on an assessment of a mental health state of an adolescent. The method comprises: collecting physical information of a user; verifying survey questions regarding mental health depending on the physical information and real-time brain activity data; forming additional survey questions after having verified the answers and calculating a prediction rate of an appearance of symptoms of a mental illness by using AI models; dynamically selecting the most suitable AI model for mental health assessment; verifying a set of survey questions including a plurality of sub-questions depending on the calculated prediction rate; and; outputting result data by adjusting the prediction rate; and transmitting a control signal to the pharmaceutical mixer for the ADHD medicine based on the assessment of the mental health state.

A method for assessing the mental state of a subject based on physiological data, a storage medium, and a device. The method comprises: presenting to a subject at least one task in a first composite task, wherein the first composite task comprises at least two types of tasks (S101); and acquiring at least two pieces of physiological data of the subject during first composite task execution, so as to perform auxiliary assessment on the tendency of mental illnesses of the subject on the basis of analysis results of the at least two pieces of physiological data (S102). Therefore, auxiliary assessment can be efficiently and accurately performed on the tendency of mental illnesses of the subject, especially mental illnesses with similar symptoms.

The invention discloses a mental disease classification method fusing prior knowledge and a multi-mode self-attention mechanism, and belongs to the technical field of medical image processing. In order to solve the problems that in the current mental disease classification process, biomarker information is dispersed, and reproducibility is insufficient, multi-mode nerve image data, field priori knowledge and the intelligent analysis ability of a large language model are fully fused, and existing mental disease biomarkers are integrated, optimized and utilized. And related medical knowledge is efficiently extracted and integrated by using a large language model, so that efficient and accurate classification of mental diseases is realized. The method provides an innovative technical path and theoretical support for precise diagnosis and mechanism research of mental disorders.

The invention provides a PCR (polymerase chain reaction) method for rapidly screening effective donors for FMT (fibronectin) treatment of depression, which comprises the following steps: (1) collecting excrement samples of the donors, and extracting total microbial genome DNA (deoxyribonucleic acid) of the excrement samples; (2) designing six primer pairs according to a specific conserved sequence of a target strain; (3) taking the extracted donor excrement DNA as a PCR (Polymerase Chain Reaction) template, and adding a primer pair for amplification; (4) observing a PCR result through electrophoresis; and if each target band is positive in the PCR electrophoresis result of the donor sample, determining that the donor contains the target strain, and determining that the donor is an effective donor for FMT treatment of depression. The effective donor suitable for FMT treatment of depression is screened out by detecting whether the donor faeces contain three key probiotics closely related to depression symptom relieving or not, a basis is provided for microbial therapy of mental diseases such as depression, and important clinical application value is achieved.

The invention relates to bacteria of the species Lactobacillus paracasei and / or compositions comprising Lactobacillus paracasei for use in preventing and / or treating a mental illness, a symptom affecting mental health and / or a condition associated with chronic stress, in a mammal. The invention further relates to methods and uses of said bacteria of the species Lactobacillus paracasei and / or compositions. The invention can be applied in restoring, maintaining, and / or promoting mental (including cognitive) health and has potential applications, inter alia, in the area of dietary and food supplements, medicaments and pharmaceuticals.

The application discloses a mental health evaluation method and system based on brain area electric stimulation, relates to the technical field of medical and health information science, and creatively integrates brain area electric stimulation into mental health evaluation. The basic cognitive level and neural plasticity potential of a measured person are objectively quantified through comprehensive scores before and after brain area electric stimulation, so that corresponding suitable mental health evaluation test questions are selected based on the basic cognitive level and neural plasticity potential, and the precision, sensitivity of corresponding mental tests and the mental comfort of the measured person are significantly improved. A decay quantization model of a stimulating current from an electrode to the brain is given, the decay quantization model is used to accurately control the electric quantity, and the maximum beneficial effect is realized under the condition of guaranteeing health and safety. Historical data accumulated in the application process can be effectively used to solve medical problems, such as the influence of brain area electric stimulation on child neural development evaluation, early warning of mental illness and brain function reinforcement.

The present disclosure relates to indole derivatives of general Formula (I), to processes for their preparation, to compositions including them and to their use in activation of a serotonin receptors in a cell, as well as to treating diseases, disorders, or conditions by activation of a serotonin receptors in a cell. The diseases, disorders, or conditions include, for example, psychosis, mental illnesses, and central nervous system (CNS) disorders. Formula (I)

The invention discloses a depression detection method based on emotion electroencephalogram signal joint features and related equipment, and relates to the technical field of mental disease auxiliary diagnosis. In combination with a two-dimensional convolutional neural network trained by using Focal Loss as a loss function and an encoder with a Transformer structure with a multi-head self-attention mechanism, high-order multi-dimensional joint modeling is performed on the emotion electroencephalogram signals, joint depth features of the emotion electroencephalogram signals in three dimensions of a time sequence, brain region distribution and frequency components are mined, and the emotion electroencephalogram signals are obtained. The accuracy and generalization ability of depression detection are improved, efficient, accurate and automatic recognition of depression is achieved, and therefore the accuracy of clinical diagnosis of depression is improved.

The invention discloses a ketamine derivative and application thereof in treatment of mental diseases, and belongs to the technical field of medicines. The compound or the pharmaceutical composition thereof provided by the invention can obviously improve the expression quantity of nerve cells BDNF, promote the growth of neurite, inhibit NMDA receptor signals and treat acute and chronic depression, has improved oral bioavailability compared with ketamine, and can be used for treating mental diseases such as depression.

The invention provides a microbial marker and a prediction model for schizophrenia with social anxiety disorder. The microbial marker is a Bacteroides microorganism in saliva. The relevance between the relative abundance of Bacteroides microorganisms in saliva and social anxiety disorder is found for the first time. A Nomogram clinical prediction mode is formed by taking the specific microbial marker as a microbial marker in combination with a children bad experience scale and 6-hydroxymelatonin and 5-hydroxyindoleacetic acid in serum, so that objective biological indexes can be provided for early diagnosis and monitoring of whether schizophrenia is accompanied by social anxiety disorder or not; errors of subjective evaluation are reduced; moreover, the oral saliva sample has the obvious advantage of being easy to collect for psychiatric patients, the working difficulty of medical staff can be greatly reduced, and revolutionary changes of prediction, diagnosis and treatment of schizophrenia accompanied with social anxiety disorder are expected to be brought.

The invention belongs to the technical field of probiotics, and particularly relates to a probiotic composition capable of improving emotion and a preparation method and application of the probiotic composition capable of improving emotion. The composition comprises bifidobacterium pseudolongum, Adellomyces aldelii, microbacter cecum, streptococcus thermophilus, Ackermann mucophilus and intestinal pasteurella, and the probiotic composition capable of improving emotion and the preparation method and application of the probiotic composition capable of improving emotion and the preparation method and application of the probiotic composition capable of improving emotion and the probiotic composition capable of improving emotion and the probiotic composition capable of improving emotion and the probiotic composition capable of improving emotion. The obtained probiotic composition has a remarkable improvement effect on animal depression and anxiety behaviors caused by chronic social contusion stress, and the technical problem that in the prior art, depression drugs cannot target intestinal flora metabolite regulation and accurate intervention of neurotransmitter balance at the same time is solved. The probiotic composition can quickly and enduringly improve depression and anxiety behaviors caused by chronic stress, has better safety, and can be used for preventing and treating depression and related mental diseases thereof.

The mental illness recognition system based on the optical flow features collected by a visual sensor comprises a mental illness expert consultation video data preprocessing module, a facial stress unit extraction module, an optical flow change feature unit construction module, a classification model construction module and a patient mental illness category recognition module connected in sequence. The mental illness expert consultation video data preprocessing module feeds the patient facial picture to the facial stress unit extraction module. The facial stress unit extraction module feeds the optical flow calculation method and the patient facial picture sequence to the optical flow change feature unit construction module. The optical flow change feature unit construction module feeds the optical flow change feature unit to the classification model construction module and the patient mental illness category recognition module respectively. The classification model construction module feeds the classification model to the patient mental illness category recognition module. The mental illness and normal sample classification recognition is realized under the condition that the user facial video has good clarity.

To provide a compound useful for the treatment of mental disorders, such as a depressive condition including unipolar and bipolar depressive conditions, for example, but not limited to, depression, depression from generalized anxiety, major depression, treatment resistant depression, and postpartum depression.SOLUTION: The present invention provides a tryptamine prodrug compound represented by the following formula.SELECTED DRAWING: Figure 1

The invention belongs to the technical field of small animal mental disease diagnosis, and provides a neuroimaging-based small animal mental disease diagnosis system, which comprises an image data acquisition and preprocessing module for performing multi-modal imaging on a small animal by using high-precision neuroimaging equipment, acquiring neuroimaging data, preprocessing the acquired image data, and acquiring neuroimaging data; comprising the steps of denoising, registration, segmentation and the like so as to improve data quality; a feature extraction and analysis module; according to the invention, the resolution and the signal-to-noise ratio of the image data are improved through the multi-modal neural imaging technology, and a reliable data basis is provided for accurate diagnosis; image features are automatically extracted and analyzed through a deep learning algorithm, human intervention is reduced, and the accuracy and efficiency of diagnosis are improved; a personalized diagnosis model is constructed, individual differences of small animals are considered, and more accurate diagnosis is realized; through introduction of the cloud data management platform, centralized storage, sharing and cooperative analysis of data are realized.

This invention relates to the use of (4-benzylpiperazin-1-yl)-[2-(3-methylbutylamino)pyridin-3-yl]methanone (NSI-189) or a pharmaceutically acceptable salt thereof in the treatment of a psychiatric condition in which depressive symptoms are prominent, including major depressive disorder (MDD), bipolar disorder, post-traumatic stress disorder, substance use disorder, and depression-related aspects of schizophrenia (e.g. negative symptoms) in select patients who exhibit impaired learning and / or memory. The invention also relates to the use of NSI-189 or a pharmaceutically acceptable salt thereof in the treatment of a psychiatric condition in which depressive symptoms are prominent, including major depressive disorder (MDD), in select patients who exhibit impaired learning and / or memory or certain EEG characteristics.

Administration of pentadecanoylcarnitine or pentadecanoic acid is provided for prevention, management or treatment of aggression, allergies, allergic rhinitis, Alzheimer's disease, anxiety and anxiety disorders, amyotrophic lateral sclerosis, arthritis, asthma, atherosclerosis, attention-deficit hyperactivity disorder, bipoloar disorder, brain damage, cancer, cardiovascular disease, cholestatic pruritis, depression, chronic obstructive pulmonary disease (COPD), cocaine abuse, cough, dermatitis, depression, drug-seeking behavior, gastrointestinal disorders, facial erythema associated with rosacea, glaucoma, hepatic diseases, hyperactive bladder, hypersensitivity disorders, hypertension, impulsivity, inflammation, mental disorders and conditions, metabolic disorders, migraines, nasal and sinus congestion, nausea, neuropathic pain with and symptoms of multiple sclerosis, neurological and neuropsychiatric disorders, obesity, obsessive-compulsive disorders, opioid-induced respiratory depression, osteoarthritis, pain, Parkinson disease, pathological gambling, peptic ulcers, schizophrenia, sleep disorders, spinal cord injury, tardive dyskinesia, tics and behavioral problems with Tourette's syndrome; as well as for supporting appetite, cardiovascular health, hematologic health, memory, metabolic health, mood, prolonged REM sleep, renal health, sexuality, sociability and metabolic, hematological, renal, and weight loss.

The invention relates to a novel compound as a 5-HT2A receptor inverse agonist, and a preparation method and a pharmaceutical composition thereof. The invention also relates to application of the compound or the pharmaceutical composition in preparation of drugs for treating 5-HT2A receptor related diseases, wherein the diseases comprise non-motor symptoms caused by Parkinson's disease, such as delusional disorder, hallusion, depression, anxiety, cognitive disorder and sleep disorder; dementia-related mental disorders; major depression; or negative symptoms of schizophrenia and the like.

The invention relates to the field of intelligent medical treatment, and provides an eye movement information collecting and processing method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out eyeball track detection on a user, and obtaining track detection data; calculating an error rate of the trajectory detection data and calculating a shake rate of the trajectory detection data; if the error rate and the shake rate of the track detection data meet the set requirements, eye movement information is obtained through calculation based on the track detection data, and the eye movement information is used for detecting mental diseases of the user. In the prior art, there is no method for collecting eye movement information and carrying out refined data processing on the eye movement information, the scheme of the invention can improve the accuracy of the obtained eye movement information.

The application discloses a kind of psychological disease pre-diagnosis information processing method and system, method includes: the multi-modal behavior signal and physiological parameter signal of user are collected, and respectively carry out the differential privacy protection processing based on edge computing and the noise separation processing based on wavelet transform, obtain standardized behavior characteristic sequence and time sequence physiological characteristic vector;Behavior node feature and psychological state marker are extracted from standardized behavior characteristic sequence, and three-dimensional association matrix is constructed in combination with time sequence physiological characteristic vector;Potential risk probability is calculated based on graph neural network model, generates pre-diagnosis grading result, and through gradual protocol fusion objective behavior environment data, output personalized intervention strategy, finally generate comprehensive pre-diagnosis report.The application realizes the accurate modeling of psychological-physiological-behavior dynamic association by dynamic knowledge graph construction and cross-modal fusion analysis, while giving consideration to data privacy protection, effectively improves the accuracy and practicality of mental health monitoring.

The present invention provides a method for identifying mental illness based on pulse structure-function brain network coupling, which belongs to the field of intelligent auxiliary medical diagnosis technology and effectively solves the technical problem of the neurobiological mechanism between structural connection and functional connection that is often ignored in the traditional diagnosis of mental illness. Its technical solution is: first, functional and structural brain networks are extracted from functional magnetic resonance imaging and diffusion tensor imaging; then, the information feature maps of these two brain networks are extracted through BrainNetCNN; then a pulse coupled neural network is constructed to learn the brain structure-function coupling mechanism, so as to derive the pulse structure-function coupling; finally, the obtained coupling information is input into the classification layer to obtain the disease identification result, and the cross-entropy loss function is used to train and optimize the result. The beneficial effects of the present invention are: the present invention helps to deeply understand the neural mechanism of mental illness and has a wide range of application prospects in clinical applications.

The present invention relates to a novel compound as a 5-HT 2A receptor inverse agonist, a method for preparing the same and a pharmaceutical composition. It also relates to the use of the compound or the pharmaceutical composition in the manufacture of a medicament for treating 5-HT 2A receptor related diseases, including non-motor symptoms of Parkinson's disease: delusions, hallucinations, depression, anxiety, cognitive impairment, sleep disorders; dementia-related psychiatric disorders; major depressive disorder; or negative symptoms of schizophrenia, etc.

Methods of using a pharmaceutical composition comprising ebastine and alprazolam for treating patients suffering from one or more psychiatric disorders, such as major depressive disorder, generalized anxiety disorder, mild chronic depression, premenstrual dysphoric disorder are disclosed.

The present invention relates to a nitrogen-containing heterocyclic compound derivative and its use. The compound according to the present invention can effectively improve synaptic plasticity without side effects, thereby exerting therapeutic effects on various neurological disorders such as neurodegenerative diseases, neurodegenerative pathologies, neuropsychiatric disorders, memory loss, cognitive dysfunction / injury, and extinction learning disorders.