551 results about "Dementia" patented technology

This disclosure relates to dosage forms comprising bupropion hydrochloride, another salt form of bupropion, or the free base form of bupropion; dextromethorphan hydrobromide, another salt form of dextromethorphan, or the free base form of dextromethorphan, and a polymer. In some embodiments, the dosage form has no significant dose dumping of bupropion in the presence of ethanol in vitro. In some embodiments, the dosage form does not have a food effect for bupropion or dextromethorphan when taken with a high-fat meal in human subjects. Some embodiments include a method of treating a nervous system condition (such as depression, e.g., major depressive disorder, including treatment-resistant depression, agitation associated with Alzheimer's disease (or agitation associated with dementia of the Alzheimer's type), agitation associated with dementia, anxiety (or generalized anxiety disorder), neuropathic pain, or peripheral diabetic neuropathic pain) comprising, administering a dosage form described herein to a human being in need thereof.

This disclosure relates to dosage forms comprising bupropion hydrochloride, another salt form of bupropion, or the free base form of bupropion; dextromethorphan hydrobromide, another salt form of dextromethorphan, or the free base form of dextromethorphan, and a polymer. In some embodiments, the dosage form has no significant dose dumping of bupropion in the presence of ethanol in vitro. In some embodiments, the dosage form does not have a food effect for bupropion or dextromethorphan when taken with a high-fat meal in human subjects. Some embodiments include a method of treating a nervous system condition (such as depression, e.g., major depressive disorder, including treatment-resistant depression, agitation associated with Alzheimer's disease (or agitation associated with dementia of the Alzheimer's type), agitation associated with dementia, anxiety (or generalized anxiety disorder), neuropathic pain, or peripheral diabetic neuropathic pain) comprising, administering a dosage form described herein to a human being in need thereof.

This disclosure relates to dosage forms comprising bupropion hydrochloride, another salt form of bupropion, or the free base form of bupropion; dextromethorphan hydrobromide, another salt form of dextromethorphan, or the free base form of dextromethorphan, and a polymer. In some embodiments, the dosage form has no significant dose dumping of bupropion in the presence of ethanol in vitro. In some embodiments, the dosage form does not have a food effect for bupropion or dextromethorphan when taken with a high-fat meal in human subjects. Some embodiments include a method of treating a nervous system condition (such as depression, e.g., major depressive disorder, including treatment-resistant depression, agitation associated with Alzheimer's disease (or agitation associated with dementia of the Alzheimer's type), agitation associated with dementia, anxiety (or generalized anxiety disorder), neuropathic pain, or peripheral diabetic neuropathic pain) comprising, administering a dosage form described herein to a human being in need thereof.

This disclosure relates to dosage forms comprising bupropion hydrochloride, another salt form of bupropion, or the free base form of bupropion; dextromethorphan hydrobromide, another salt form of dextromethorphan, or the free base form of dextromethorphan, and a polymer. In some embodiments, the dosage form has no significant dose dumping of bupropion in the presence of ethanol in vitro. In some embodiments, the dosage form does not have a food effect for bupropion or dextromethorphan when taken with a high-fat meal in human subjects. Some embodiments include a method of treating a nervous system condition (such as depression, e.g., major depressive disorder, including treatment-resistant depression, agitation associated with Alzheimer's disease (or agitation associated with dementia of the Alzheimer's type), agitation associated with dementia, anxiety (or generalized anxiety disorder), neuropathic pain, or peripheral diabetic neuropathic pain) comprising, administering a dosage form described herein to a human being in need thereof.

The embodiment of the invention relates to a processing method and device of an Alzheimer disease risk prediction model. The method comprises the steps that DT I-ALPS feature information of dementia crowds and healthy crowds of a specified age group is obtained in a big data collection and volunteer recruitment mode, and a corresponding model data set is constructed and recorded as a first data set; constructing a three-classification prediction model for predicting the risk of the Alzheimer's disease as an Alzheimer's disease risk prediction model corresponding to a specified age group; training an Alzheimer disease risk prediction model based on the first data set; after model training is finished, DT I-ALPS feature information, input by the user, of any tested person of the specified age group is input into the Alzheimer disease risk prediction model for prediction, and a corresponding classification probability vector is obtained and fed back to the current user. According to the invention, prediction accuracy and prediction stability can be improved.

This disclosure relates to dosage forms comprising bupropion hydrochloride, another salt form of bupropion, or the free base form of bupropion; dextromethorphan hydrobromide, another salt form of dextromethorphan, or the free base form of dextromethorphan, and a polymer. In some embodiments, the dosage form has no significant dose dumping of bupropion in the presence of ethanol in vitro. In some embodiments, the dosage form does not have a food effect for bupropion or dextromethorphan when taken with a high-fat meal in human subjects. Some embodiments include a method of treating a nervous system condition (such as depression, e.g., major depressive disorder, including treatment-resistant depression, agitation associated with Alzheimer's disease (or agitation associated with dementia of the Alzheimer's type), agitation associated with dementia, anxiety (or generalized anxiety disorder), neuropathic pain, or peripheral diabetic neuropathic pain) comprising, administering a dosage form described herein to a human being in need thereof.

This disclosure relates to dosage forms comprising bupropion hydrochloride, another salt form of bupropion, or the free base form of bupropion; dextromethorphan hydrobromide, another salt form of dextromethorphan, or the free base form of dextromethorphan, and a polymer. In some embodiments, the dosage form has no significant dose dumping of bupropion in the presence of ethanol in vitro. In some embodiments, the dosage form does not have a food effect for bupropion or dextromethorphan when taken with a high-fat meal in human subjects. Some embodiments include a method of treating a nervous system condition (such as depression, e.g., major depressive disorder, including treatment-resistant depression, agitation associated with Alzheimer's disease (or agitation associated with dementia of the Alzheimer's type), agitation associated with dementia, anxiety (or generalized anxiety disorder), neuropathic pain, or peripheral diabetic neuropathic pain) comprising, administering a dosage form described herein to a human being in need thereof.

The invention provides an Alzheimer disease auxiliary accurate identification method and system based on a multi-omics marker network and an adaptive support vector machine. Accurate identification of Alzheimer's disease and other types of dementia is realized through a marker network based on five modal data and an adaptive support vector machine model. According to the method, multi-source heterogeneous data such as blood, urine, neuroimaging, electrophysiology and clinical evaluation are fused, specific markers are analyzed and screened by adopting a weighted gene co-expression network, and cross-modal feature interactive learning is realized through a self-attention mechanism. An online learning mechanism is introduced to enable the model to adapt to new data distribution, and the contribution degree of each marker to diagnosis is output in combination with an interpretability module. Finally, multi-center data synchronization and model optimization are realized by means of a cloud platform, the accuracy, specificity and early diagnosis capability of AD diagnosis and identification and the adaptability of the model are remarkably improved, the limitation of the prior art is overcome, and doctors are assisted to diagnose and treat the Alzheimer's disease.

The present disclosure provides methods to quantify and analyze various CSF Tau species and the use thereof to measure pathological features and / or clinical symptoms of tauopathies, including determining the amount of time to dementia due to Alzheimer's disease, determining the time from dementia onset, staging Alzheimer's disease, guiding treatment decisions, and evaluate the clinical efficacy of certain therapeutic interventions.

The invention discloses an intelligent cognitive assessment method and system based on a virtual reality environment. According to the method, through accurate eye movement calibration and electroencephalogram calibration, resting-state electroencephalogram information, digital cognitive evaluation task parameters and eyeball movement track parameters of a subject in a virtual reality environment are collected, and through professional preprocessing and feature extraction, deep analysis and fusion are conducted on data through a common-attention multi-mode feature noise reduction fusion model. Through training and prediction of the neural network model, the cognitive function state of the subject can be effectively evaluated, the accuracy and efficiency of cognitive evaluation are improved, and meanwhile, the user experience is optimized. By utilizing the method, early recognition of cognitive impairment is facilitated, a scientific basis is provided for clinical diagnosis and intervention, and the method is of great significance in preventing and delaying dementia of old people.

The present application provides a light treatment device for suppressing or preventing Alzheimer's disease. A light treatment device includes a carrier structure and an array of near-infrared irradiation units. The bearing mechanism forms an accommodating space for the head of the object and bears the array of the near-infrared irradiation units. The array of near-infrared irradiation units is configured such that near-infrared light is emitted into the accommodation space, when the head of the subject is in place, an irradiation space range covering at least the anterior upper cranial portion, the top cranial portion, the left cranial portion and the right cranial portion is formed, and the time-average total irradiation power of the head cover portion acting on the head of the subject is 27.5 W or more, 31 W or more, 40 W or more, or 60 W or more, and the irradiation power of the head cover portion acting on the head of the subject is 27.5 W or more, 31 W or more, 40 W or more, or 60 W or more. Or more than 70W, and the space-time average optical power density irradiated to each part does not exceed 230mW / cm < 2 >. The light treatment device does not depend on nasal and ocular irradiation, achieves an optimized treatment effect on AD patients from MCI to dementia during the course of treatment, and not only effectively maintains the treatment effect but also continuously increases the treatment effect when the light treatment is interrupted.

The invention provides novel dosing regimens for Leuco-Methylthioninium (LMT) compounds which maximise the proportion of subjects in which the MT concentration will exceed concentrations in which therapeutic efficacy in relation to treatment of neurodegenerative disorders such as Alzheimer's disease and rontotemporal dementias can be achieved, while maintaining a desirable clinical profile. Also provided are LMT-containing dosage units and other compositions.

This disclosure relates to dosage forms comprising bupropion hydrochloride, another salt form of bupropion, or the free base form of bupropion; dextromethorphan hydrobromide, another salt form of dextromethorphan, or the free base form of dextromethorphan, and a polymer. In some embodiments, the dosage form has no significant dose dumping of bupropion in the presence of ethanol in vitro. In some embodiments, the dosage form does not have a food effect for bupropion or dextromethorphan when taken with a high-fat meal in human subjects. Some embodiments include a method of treating a nervous system condition (such as depression, e.g., major depressive disorder, including treatment-resistant depression, agitation associated with Alzheimer's disease (or agitation associated with dementia of the Alzheimer's type), agitation associated with dementia, anxiety (or generalized anxiety disorder), neuropathic pain, or peripheral diabetic neuropathic pain) comprising, administering a dosage form described herein to a human being in need thereof.

The invention discloses a dementia identification method based on brain computer network space cross attention fusion. The dementia identification method comprises the steps that resting-state electroencephalogram signals are acquired, preprocessing and brain network construction are carried out, the frequency band power ratio is calculated, and a training set and a test set are divided; the brain network fuses the spatial information, and spatial features are obtained through an isotropic graph neural network and a local feature enhancement module; the frequency band power ratio is coded by a multi-layer perceptron to obtain frequency spectrum statistical characteristics; a bidirectional cross attention module is input, and complementary fusion features are extracted; and performing mixed pooling and splicing on the complementary fusion features, then sending the fused features to a Chebyshev Kolmogorov-Arnold network classifier, and outputting an Alzheimer's disease / frontotemporal dementia / health control (AD / FTD / HC) classification result and a cognitive scale evaluation score (MMSE). According to the method, the multi-feature complementary information is effectively integrated through joint modeling of the spatial diagram features and the global spectrum features, and the accuracy, stability and generalization ability of AD and FTD classification in a complex brain network are improved.

The invention relates to an intelligent defecation system and a using method thereof, and the intelligent defecation system comprises an implantable anus valve which is used for controlling defecation; the pressure sensor is used for monitoring the pressure generated in the anus area during defecation or fart in real time; the implantable power supply is used for supplying power to the implantable anus valve and the pressure sensor; the wireless charging inner module is used for charging the implantable power supply; the control chip is used for receiving the pressure data of the pressure sensor and the electric quantity data of the implantable power supply and controlling the opening and closing of the implantable anus valve by controlling the on-off of the implantable power supply; and the control system is used for receiving the signal from the control chip and sending an instruction to the control chip. According to the intelligent defecation system and the using method thereof, intelligent defecation control is achieved, operation is easy, defecation of disabled old people defecating anywhere due to dementia and patients with anal sphincter dysfunction or anus resection caused by specific diseases are controlled, fecal incontinence is avoided, and life quality is improved.

The invention discloses a dementia intervention scheme recommendation method and system based on a knowledge graph, and relates to the technical field of intelligent medical treatment and artificial intelligence. And constructing a dementia intervention knowledge graph containing patients, symptoms, intervention measures and environmental elements. And performing intelligent semantic reasoning on the short-term state, the long-term behavior mode and the nursing environment of the patient by fusing multi-level reasoning and situational reasoning, generating a candidate intervention scheme matched with the current state of the patient, and outputting a personalized recommendation result. In the intervention implementation process, the knowledge graph association relation is dynamically updated based on patient behavior feedback and symptom changes, and continuous optimization and self-adaptive adjustment of an intervention scheme are achieved. According to the method, the individuation level, long-term adaptability and safety of dementia intervention recommendation are improved, and the method is suitable for clinical and long-term nursing scenes.

Provided is a data processing system capable of detecting that a user may have initial symptoms of dementia.　The data processing system comprises: a necklace-type terminal including a microphone that collects a user utterance of a wearer, a collection unit that collects an output of the microphone, and a communication unit that transmits the output of the microphone collected by the collection unit to an external device; and a data processing device. The data processing device includes: an input unit that receives the user utterance collected by the microphone; and a processing unit that, when a remark indicating a sign of dementia is included in the user utterance, notifies a preset notification destination that the wearer may have dementia.

Described are RNAi agents, compositions that include RNAi agents, and methods for inhibition of a microtubule associated protein tau (MAPT) gene. The MAPT RNAi agents and RNAi agent conjugates disclosed herein inhibit the expression of a MAPT gene. The MAPT RNAi agents are conjugated to an antigen binding protein that may enable subcutaneous delivery of the RNAi agents by facilitating crossing of the blood brain barrier (BBB). Pharmaceutical compositions that include one or more MAPT RNAi agents, optionally with one or more additional therapeutics, are also described. Delivery of the described MAPT RNAi agents to central nervous system (CNS) tissue, in vivo, provides for inhibition of MAPT gene expression and a reduction in MAPT activity, which can provide a therapeutic benefit to subjects, including human subjects, for the treatment of various diseases including Alzheimer's disease, Frontotemporal lobar degeneration dementia (FTLD), Progressive supranuclear palsy, and other tauopathies.

In an embodiment, a system for digital engagement is disclosed that is configured to operate an application for a patient with dementia. The application includes at least one applied virtual environment. The system is further configured to evaluate input of the patient based on a mixed model for observing digital engagement, and to engage the patient with the application using dialogue delivered by at least one virtual avatar, the virtual avatar being supported by artificial intelligence and the dialogue being determined based on the evaluated input. The system is further configured to log and evaluate progress data of the patient and to provide feedback and support based on the evaluated progress data.

Provided are compounds, methods, and pharmaceutical compositions for reducing the amount or activity of PRNP RNA in a cell or animal, and in certain instances reducing the amount of PrP protein in a cell or animal. Such compounds, methods, and pharmaceutical compositions are useful to ameliorate at least one symptom or hallmark of a neurodegenerative disease. Such symptoms and hallmarks spongiform changes in the brain, development of abnormal protein aggregates, neuronal loss, markers of neuronal loss, rapidly progressing dementia, and death. Such neurodegenerative diseases include prion diseases, Creutzfeldt-Jakob disease (CJD), variant Creutzfeldt-Jakob Disease (vCJD), familial Creutzfeldt-Jakob Disease (fCJD), Gerstmann-Straussler-Scheinker syndrome, fatal familial insomnia, kuru, Alzheimer's disease, or Parkinson's disease.

The invention discloses a daily life activity ability assessment method and system based on a multi-branch space-time fusion network. The method comprises the steps of collecting motion data of a to-be-evaluated object, performing segmentation, noise reduction and standardization preprocessing, and extracting time-frequency domain features and motion deviation degree, motion similarity index and bilateral symmetry index provided by the invention; obtaining a uniform Bhattacharyya index scale score; and taking the motion feature data set and the clinical score as input, performing training based on a multi-branch space-time fusion algorithm, constructing a multi-task prediction model, and realizing automatic evaluation of the ADL. According to the method, the multi-branch space-time fusion network is innovatively introduced, the relevance between tasks is fully utilized, the spatial feature extraction capability is enhanced in combination with the graph neural network, adaptive fusion of the features is realized through a cross-layer interactive attention mechanism, the model prediction precision and evaluation reliability are remarkably improved, and the method is suitable for large-scale popularization and application. And an effective technical support is provided for rehabilitation evaluation and personalized treatment of patients with dyskinesia and disability and dementia.

Devices, systems, and methods for a treating dementia or Alzheimer's disease in a subject in need thereof. In one example, combined auditory and visual stimuli having a frequency of about 20 Hz to about 60 Hz, and more specifically about 40 Hz, are non-invasively delivered to the subject to induce synchronized gamma oscillations in at least one brain region of the subject. In particular, pursuant to various treatment and exposure protocols, combined auditory and visual stimulation (as opposed to auditory or visual stimulation alone) promotes a microglia response in the medial prefrontal cortex (mPFC). More generally, combined auditory and visual stimulation induces an extended microglia clustering response in the auditory cortex, the visual cortex, and the mPFC.

An analytics computing device is provided. The analytics computing device includes a processor in communication with a database. The database configured to store electronic health record (EHR) data including structured EHR data and unstructured EHR data for a patient. The processor is configured to retrieve the EHR data from the database. The processor is further configured to parse, using a natural language processing model, the unstructured EHR data to retrieve one or more indicator phrases, the one or more indicator phrases correlated to an Alzheimer's disease (AD) diagnosis. The processor is further configured to identify, using a predictive model, the patient as being at risk for AD based on the retrieved indicator phrases and on the structured EHR data.

A method for performing predictive operations, the method comprising receiving a classification dataset comprising clock drawing images, generating, using a classifier, one or more classification outputs, the one or more classification outputs comprising one or more identifications of dementia or non-dementia for respective ones of clock drawing images. The classifier comprises one or more weights based on a latent space associated with a relevance factor variational autoencoder (RF-VAE). The RF-VAE comprises an encoder configured to generate the latent space. The RF-VAE comprises a decoder configured to generate reconstructions of the second one or more clock drawings based on the latent space. The latent space comprises one or more latent dimensions representative of one or more unique aspects of variation associated with the second one or more clock drawings. The one or more latent dimensions comprise minimal total correlation between the one or more latent dimensions and two dimensions.

In the homes where elderly people are accustomed to living, the knee joints are subjected to a lot of stress when going up and down stairs, especially when going down them, which causes frequent falls and can lead to serious health problems such as fractures, hospitalization, and even becoming bedridden or experiencing the progression of dementia. [Solution] Hydraulic bags containing hydraulic oil are placed under the treads of each staircase, and the hydraulic bags are connected to each other by hoses with control valves. When the operating lever inside the handrail is gripped, the wire opens the control valve, and the hydraulic oil is pushed out by the user's weight, causing the treads to descend. The pushed-out hydraulic oil is injected into an empty hydraulic bag container on the floor below, causing the treads on the lower floor to rise and be at the same floor height. This provides an inexpensive, non-powered elevator "specialized for descending," allowing users to easily descend to the floor below without bending their knees.

Provided is a cognitive impairment determination method that discloses a model for determining cognitive impairment based on a gait feature value measured by an accelerometer attached to a subject, discloses a configuration for determining cognitive impairment by using a model including a mathematical linear regression equation that includes a gait speed and step time variability as predictors by receiving personal data and gait data, easily and quickly screens for cognitive impairment, such as dementia, regardless of a root cause, and accurately determines even cognitive impairment in an early stage.

This method for evaluating the risk of Alzheimer-type dementia comprises: a step for extracting DNA from a test sample; a step for identifying bacterial species contained in the test sample on the basis of information on the sequence of the extracted DNA; a step for outputting the abundance of each of bacterial species belonging to a first group and bacterial species belonging to a second group among bacteria contained in the test sample, or outputting the relative abundance ratio between the bacterial species belonging to the first group and the bacterial species belonging to the second group; and an evaluation step for evaluating the abundances or the abundance ratio. The test sample is a fecal sample. The first group includes bacterial species involved in Alzheimer-type dementia. The second group includes bacterial species involved in the suppression of Alzheimer-type dementia.

To provide an AI system capable of estimating severity of dementia and / or depression in a subject on the basis of information obtained outside a hospital.SOLUTION: A method of creating teacher data for an AI system for estimating severity of dementia and / or depression is provided. Information to be used as teacher data for the AI system can be acquired from a site where a user receives prescribed drugs or from an application on a mobile terminal used by the user. The teacher data at least includes a face picture of the user, and a prescription, instruction, or information that enables estimation of dementia and / or depression in the user.SELECTED DRAWING: Figure 1

The present invention relates to a system and method configured for analysing acoustic parameters of speech to detect, diagnose, predict and / or monitor progression of a condition, disorder, or disease, and more particularly, any of paediatric and adult neurological and central nervous system conditions including but not limited to low back pain, multiple sclerosis, stroke, seizures, Alzheimer's disease, Parkinson's disease, dementia, motor neuron disease, muscular atrophy, acquired brain injury, cancers involving neurological deficits, paediatric developmental conditions and rare genetic disorders such as spinal muscular atrophy. The system and method extracts a first formant data set from words spoken by an individual and uses these to classify the vowels in the words on a first computing device, such as a mobile smart phone equipped with a microphone into which an individual speaks. The system stores at least some of these frequencies for the vowel formants in a second formant data set as a recorded file and provides the second formant data set as input to acoustic metrics to generate score data from which an assessment is made to determine the articulation level of the vowels in the words spoken by the individual, allowing allow for detection, diagnosis, prediction and / or monitoring progression of the condition, disorder, or disease.