188 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 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 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 invention relates to novel bacteria of the species Lactobacillus plantarum and to compositions comprising Lactobacillus plantarum, and methods and uses of said compositions for preventing and / or treating mental illness, symptoms affecting mental health and / or conditions associated with chronic stress, in a mammal. 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 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 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 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 mania psychiatric patient restraining bed which comprises a sickbed, a trunk limiting and restraining structure and a leg pressing and fixing device are arranged on the sickbed, the trunk limiting and restraining structure is installed on the sickbed in a clamped mode, and the leg pressing and fixing device is installed on the sickbed in a clamped and sliding mode. The invention belongs to the technical field of psychiatric restraint beds. The invention provides a mania psychiatric patient restraint bed in order to achieve the effects that restraint equipment autonomously limits the movement range of a patient, gradually reduces the movement space of the patient and prevents the patient from struggling to cause injury to other people or himself / herself. The movement range of the upper body is limited, the struggling movement range of the patient is reduced, the movement range of the upper body can be completely limited by matching with the bandage, the movement space of the legs is limited by matching with the pressing automatic tightening structures of the legs, and therefore excessive struggling of the mental patient is avoided.

The invention provides an artificial intelligence technology-based eye movement mental disease detection system, which comprises an image acquisition unit, and is characterized in that the image acquisition unit comprises a camera device, an image processing module, a control module and a data storage module; the camera equipment is used for collecting eye actions of a to-be-tested person, including eyeball actions and eyeball actions, and collecting head actions of the to-be-tested person at the same time; the image processing module is used for judging whether the head of the to-be-detected person moves or not according to the eye actions and the head actions collected by the camera equipment; judging whether the head shakes or not by analyzing the head actions, if so, judging whether the eye actions are influenced by the head shaking or not, filtering eye pictures influenced by the head shaking, and retaining the eye pictures during the head rest period; and carrying out image analysis on the retained eye picture in the head static period, carrying out image analysis on the eye action subareas where the eye actions are located, and outputting an eye fundus image, eyeball actions and eyeball actions.

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 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.

Provided herein are alpha5-containing GABAA receptor agonists and pharmaceutical compositions and methods of treatment of cognitive and mood symptoms in neurodegenerative and neuropsychiatric disorders using them.

Lactam compounds of Formula I and their use for the treatment of neurological and psychiatric disorders including schizophrenia, bipolar disorder, anxiety disorder and insomnia is disclosed.

The invention relates to a mental disease category identification method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring multi-modal data of a target patient; performing feature extraction on each type of modal data to obtain a feature vector of each type of modal data, and generating a multi-modal fusion feature based on the feature vector of each type of modal data; matching the multi-modal fusion feature with a pre-constructed informatization expression mode of pathological expressions of various mental diseases, and determining a target informatization expression mode; and determining the mental disease category of the target patient according to the target informatization expression mode. The mental disease category of the patient can be effectively identified, and meanwhile, various evaluation models do not need to be trained respectively.

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.

Disclosed are pharmaceutical preparations comprising bromantane or an analogue of bromantane, and methods of using said preparations for pharmacotherapy to alleviate withdrawal syndrome and prevent relapse in the treatment of stimulant use disorder, to transition patients off medications that have abuse or addiction liabilities, or to facilitate extinction learning in the treatment of mental disorders.

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