1255 results about "Non invasive" patented technology

A non-invasive physiological sensor system implemented as a smart watch or other wearable device includes an emitter for emitting light and a detector for collecting light after the light interacts with a tissue of a wearer. The system can measure light intensity at one or more radial distances to estimate attenuation parameter values that can be used to correct physiological parameter bias across subjects. In addition or alternatively, the system can determine whether a detector is positioned sufficiently proximate to an obstructing tissue (for example, an artery or vein) so as to cause inaccurate measurements by the detector.

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and / or track coronary artery disease.

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and / or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and / or dynamically identify one or more features, such as plaque and vessels, and / or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and / or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and / or quantified parameters.

Systems and methods of facilitating determination of risk of coronary artery disease (CAD) based at least in part on one or more measurements derived from non-invasive medical image analysis. The methods can include accessing a non-invasive generated medical image, identifying one or more arteries, identifying, regions of plaque within an artery, analyzing the regions of plaque to identify low density non-calcified plaque, non-calcified plaque, or calcified plaque based at least in part on density, determining a distance from identified regions of low density non-calcified plaque to one or more of a lumen wall or vessel wall, determining embeddedness of the regions of low density non-calcified plaque by one or more of non-calcified plaque or calcified plaque, determining a shape of the more regions of low density non-calcified plaque, and generating a display of the analysis to facilitate determination of one or more of a risk of CAD of the subject.

Systems and methods of facilitating determination of risk of coronary artery disease (CAD) based at least in part on one or more measurements derived from non-invasive medical image analysis. The methods can include accessing a non-invasive generated medical image, identifying one or more arteries, identifying, regions of plaque within an artery, analyzing the regions of plaque to identify low density non-calcified plaque, non-calcified plaque, or calcified plaque based at least in part on density, determining a distance from identified regions of low density non-calcified plaque to one or more of a lumen wall or vessel wall, determining embeddedness of the regions of low density non-calcified plaque by one or more of non-calcified plaque or calcified plaque, determining a shape of the more regions of low density non-calcified plaque, and generating a display of the analysis to facilitate determination of one or more of a risk of CAD of the subject.

A histotripsy therapy system configured for the treatment of tissue is provided, which may include any number of features. Provided herein are systems and methods that provide efficacious non-invasive and minimally invasive therapeutic, diagnostic and research procedures. In particular, provided herein are optimized systems and methods that provide targeted, efficacious histotripsy in a variety of different regions and under a variety of different conditions without causing undesired tissue damage to intervening / non-target tissues or structures.

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and / or track coronary artery disease.

Provided are multi-wavelength phototherapy devices, systems and methods for the treatment of a disorder or disease, including multi-wavelength low level light therapy (“PBM”), in particular to multi-wavelength PBM and other phototherapy systems and methods for improving functionality in and / or restoring functionality to a cell and / or tissue through the coordinated and targeted delivery to the cell or tissue of two or more doses of light having distinct wavelengths, wherein the two or more doses of light, when delivered in a coordinated fashion, can stimulate the activity of two or more light sensitive factors that, when activated, provide and / or enhance a desired target cell functionality. Ophthalmic phototherapy devices, systems, and treatment methods to expose an eye to selected multi-wavelengths of light to promote the healing of damaged or diseased eye tissue. The devices include a housing having an interior; an eyepiece disposed on the housing and configured and arranged for placement of an eye of the patient adjacent the eyepiece; a first light source producing a first light beam having a first therapeutic wavelength and disposed within the housing; a second light source producing a second light beam having a second therapeutic wavelength and disposed within the housing, where the second therapeutic wavelength differs from the first therapeutic wavelength by at least 25 nm.

The invention relates to the technical field of medical diagnosis, in particular to a dysphagia detection and automatic scoring system based on a high-resolution acoustic sensor. Comprising a three-dimensional curved surface type acoustic sensing array module, a self-adaptive environment noise compensation module, a swallowing stage dynamic segmentation module, a multi-dimensional feature extraction engine, a swallowing abnormal mode classifier and a dynamic weight scoring model. A self-adaptive environment noise compensation module, a time-frequency domain feature extraction module and a dynamic weight scoring model are combined, the swallowing process is monitored and scored in real time, the system automatically identifies and analyzes acoustic features of an oral cavity preparation period, a pharyngeal period and an esophageal period, and through multi-dimensional feature fusion, dynamic weighting and neural network optimization, the swallowing process is monitored and scored in real time. The method has the advantages of being non-invasive, easy and convenient to operate, high in real-time performance and the like, and can be widely applied to early screening, evaluation and follow-up visit of clinical dysphagia.

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and / or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and / or dynamically identify one or more features, such as plaque and vessels, and / or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and / or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and / or quantified parameters.

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and / or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and / or dynamically identify one or more features, such as plaque and vessels, and / or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and / or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and / or quantified parameters.

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and / or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and / or dynamically identify one or more features, such as plaque and vessels, and / or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, perform computational fluid dynamics analysis, facilitate assessment of risk of heart disease and coronary artery disease, enhance drug development, determine a CAD risk factor goal, provide atherosclerosis and vascular morphology characterization, and determine indication of myocardial risk, and / or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and / or quantified parameters.

The invention provides a surveying device and method for an internal structure of a coating, and relates to the technical field of surveying. The surveying device comprises an acquisition system used for acquiring coordinate information of muons, and the coordinate information comprises intersection point coordinates of the muons and the acquisition system; the positioning time service system is connected with the acquisition system and is used for recording the position information of the acquisition system; the control system is respectively connected with the acquisition system and the positioning time service system, and is used for obtaining a structure image of the internal structure of the to-be-detected coating according to the coordinate information and the position information, and judging the condition of the internal structure of the to-be-detected coating according to the structure image; wherein the to-be-detected coating is located at the upper part of the underground space; and the mobile carrier can move in the underground space, and the acquisition system, the positioning time service system and the control system are fixed on the mobile carrier. The surveying device can efficiently detect the condition of the internal structure of the to-be-detected coating in real time in a non-invasive mode, and the safety of the operation period and the construction period of the underground space is guaranteed.

A platform for characterizing biomolecules, biological tissue sections, viruses, or other particles of interest in a non-invasive, high-throughput, cost-effective, and label-free manner. The platform includes a merged set of imaging modalities including and capable of interferometric microscopy and wide-field or confocal microscopy (such as, for example, a wide-field super-resolution surface enhanced Raman spectroscopy, SERS), although some aspects may be employed with data sets only received from wide-field or confocal microscopy. Related devices, systems, methods, techniques, and variations to the same are also provided.

A medical monitoring system comprises a wearable garment incorporating multiple physiological sensors for real-time patient monitoring. The garment integrates an embedded processing unit that receives sensor data and transmits it wirelessly to a base station or remote server. A multi-modal physiological signal processing unit analyses the data to generate composite physiological indices, including metabolic rate, work of breathing, and fall risk assessments. The garment includes optional monitoring features such as transcutaneous carbon dioxide measurement, electrocardiography, pulse oximetry, blood pressure monitoring, and accelerometer - gyroscope-based motion tracking. The system provides early-warning alerts for clinical deterioration, enabling proactive therapeutic interventions. A wireless communication module ensures real-time data transmission, supporting remote monitoring and integration with hospital networks. The garment's modular design allows for non-invasive physiological assessment while maintaining patient mobility, making it suitable for critical care, ambulatory monitoring, and telemedicine applications.

Devices and methods are disclosed for treating tissue with microwave energy. Such devices and methods are able to treat cavities or surface tissue by creating one or more area or volumetric lesions. Also disclosed are flexible, low-profile devices that can be inserted non-invasively or minimally invasively near or into the target tissue as well as microwave antennas designed to generate ablation profiles that can ablate a large area or a large volume of target tissue in a single ablation. The devices include antennas wherein the field profile generated by an antenna is tailored and optimized for a particular clinical application. The antennas use unique properties of microwaves such as interaction of a microwave field with a metallic object and the use of additional shaping elements to shape the microwave field.

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and / or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and / or dynamically identify one or more features, such as plaque and vessels, and / or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and / or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and / or quantified parameters.

A method includes administering a non-invasive stimulus to a subject having a frequency of about 35 Hz to about 45 Hz to induce synchronized gamma oscillations in at least one brain region of the subject.

Methods and apparatus for changing a brain state of a person from an initial brain state to a target brain state are described. The method includes receiving information characterizing the initial brain state, the information including a structural composition and a functional architecture of the brain, estimating based, at least in part, on the received information, a potential for the brain to change from the initial brain state to the target brain state, determining based, at least in part, on the received information and the estimated potential for the brain to change from the initial brain state to the target brain state, a non-invasive brain stimulation protocol, and controlling at least one non-invasive brain stimulation device to stimulate the brain according to the non-invasive brain stimulation protocol. The method also includes using brain information to inform the design of computational general artificial intelligence agents.

The invention provides a scoliosis screening method and system, and relates to the technical field of medical artificial intelligence, human body image data on a low-light detection garment worn by a patient is collected, the human body image data is preprocessed and sent to an SSD module, the SSD module is used for predicting the position of a low-light light source, and a scoliosis detection result is obtained. The key point detection module is used for detecting human body scoliosis, high-precision detection frame information in the detection result is used as a basis, a human body posture result predicted by the key point detection module is restrained and corrected, then human body scoliosis grading is performed, a human body scoliosis detection result is displayed and fed back to a patient, high-precision detection of scoliosis is achieved, and the system has the advantages of high efficiency, non-invasiveness and light weight; the scoliosis early detection rate and grading intervention precision can be remarkably improved, and the problems that traditional medical diagnosis is low in efficiency, large in radiation risk, insufficient in precision and difficult to operate on embedded equipment with limited resources are solved.

Systems and methods of facilitating determination of risk of coronary artery disease (CAD) based at least in part on one or more measurements derived from non-invasive medical image analysis. The methods can include accessing a non-invasive generated medical image, identifying one or more arteries, identifying, regions of plaque within an artery, analyzing the regions of plaque to identify low density non-calcified plaque, non-calcified plaque, or calcified plaque based at least in part on density, determining a distance from identified regions of low density non-calcified plaque to one or more of a lumen wall or vessel wall, determining embeddedness of the regions of low density non-calcified plaque by one or more of non-calcified plaque or calcified plaque, determining a shape of the more regions of low density non-calcified plaque, and generating a display of the analysis to facilitate determination of one or more of a risk of CAD of the subject.

The present invention relates to a portable device (100) for ocular diagnostic and disease detection in non-invasive manner, the device (100) comprises an image capturing module (10) positioned at a first end of the device (100), the image capturing module (10) captures high resolution images of patient's eye, an illumination module (20) configured to encompass the image capturing module (10), the illumination module (20) provides uniform illumination on the patient's eye, at least one auxiliary part removably coupled with the illumination module (20) by a plurality of mounting provisions (23) provisioned on the illumination module (20).

A patient management system can include an implantable neurostimulation device configured to deliver vagus nerve stimulation (VNS) therapy to a patient and a non-invasive, external monitoring device comprising at least one sensor for detecting indicators of seizure or depression in the patient. In an example, the external monitoring device is configured to use information from the at least one sensor to detect a seizure event or a seizure precursor event, audibly ask questions of the patient and / or provide behavioral modification commands to the patient, and / or control the neurostimulation device to deliver the VNS therapy to the patient in response to a detected seizure event, seizure precursor event, or progression of depression symptoms.

Provided herein are apparatuses, systems and methods for non-invasively assessing synaptic dysfunction in a patient with Alzheimer's Disease. Transcranial magnetic stimulation (TMS) is applied to at least one brain region of the patient. A plurality of TMS evoked potentials generated in response to the TMS applied to the at least one brain region of the patient is recorded with a plurality of electroencephalography (EEG) electrodes. At least one characteristic of the plurality of TMS evoked potentials is analyzed to assess synaptic dysfunction in the patient. An indication of the synaptic dysfunction assessment of the patient is output.

A multiplanar motion management system to aid in administering non-invasive radiation therapies. The disclosed devices and techniques enable clinicians to accurately monitor the position and motion of the heart with respect to a reference situation of the simulation stage. In addition, information is provided about the respiratory phase of the patient as well as about possible drifts of the anatomical structures. This information can be used by the clinician to interrupt the radiation treatment manually when necessary. The information can also be used to automatically, and in real-time, provide the appropriate gating signals to the therapy machine. The disclosed system may be configured to cover all motion aspects required during a typical radiotherapy workflow with just one device, from patient setup (inter-fraction motion monitoring) to cardiac and respiratory motion monitoring during the treatment (intra-fraction motion monitoring).

The present disclosure, in some aspects, provides one or more biomarkers (e.g., plasma biomarkers or circulating biomarkers) for Facioscapulohumeral muscular dystrophy (FSHD). In some embodiments, a biomarker (e.g., plasma biomarkers or circulating biomarkers) described herein is regulated by DUX4. Methods (e.g., non-invasive methods) of using the biomarkers, e.g., for detection (e.g., early detection) and monitoring patient as well as treatment efficacy are also provided. The present disclosure, in other aspects, provides one or more biomarkers (e.g., transcriptome biomarkers) for Facioscapulohumeral muscular dystrophy (FSHD). In some embodiments, a biomarker (e.g., transcriptome biomarkers) described herein is regulated by DUX4. Methods of using the biomarkers, e.g., for detection (e.g., early detection) and monitoring patient as well as treatment efficacy are also provided.

A method for performing classification of a severity of at least one liver disease from non-invasive radiographic images is disclosed. The method comprises: providing radiographic images of slices of an abdomen of a patient; pre-processing said radiographic images by: segmenting a liver and a spleen, thus achieving a spleen binary mask and a liver binary mask per slice, and normalizing said images with each other, thus achieving normalized radiographic images per slice; for each slice, from the liver binary mask and said normalized radiographic images, extracting a liver parameter; from at least one spleen binary mask, extracting a spleen parameter; and classifying, in function of both parameters and by help of a trained Machine Learning model, the severity of the at least one liver disease between one among a group of liver disease at early stage and a group of liver disease at advanced stage.

Devices and methods for the non-invasive stimulation of nerves, such as the vagus nerve, include a housing and an electrode coupled to the housing. The electrode is configured to be positioned adjacent to, or in contact with, an outer skin surface of a patient. A source of energy is coupled to the housing and operably coupled to the electrode. The source of energy emits an electrical impulse to the electrode such that the electrical impulse passes through the outer skin surface of the patient to a nerve at a target region in the patient sufficient to modulate the nerve. The electrical impulse comprises burst periods and constant periods, wherein each burst period includes 2 to 20 pulses and has a duration of less than 20,000 microseconds.

A method for performing classification of the severity of at least one liver disease from non-invasive radiographic images is disclosed. The method includes: providing radiographic images of slices of the abdomen of a patient; pre-processing the radiographic images by: segmenting liver and spleen, thus achieving a spleen binary mask and a liver binary mask per slice, and normalizing the images with each other, thus achieving normalized radiographic images per slice; for each slice, from the liver binary mask and the normalized radiographic images, extracting a liver parameter; from at least one spleen binary mask, extracting a spleen parameter; and classifying, in function of both parameters and by help of a trained Machine Learning model, the severity of liver disease between one among a group of liver disease at early stage and a group of liver disease at advanced stage.

A method for predicting a cardiac index (CI) for a patient includes receiving a set of a measurements from the patient that characterizes an anatomical condition, a physical condition, a physiological condition, or a combination thereof. The method also includes receiving a non-invasive physiological measurement from the patient. The method also includes performing feature extraction on the non-invasive physiological measurement to produce one or more extracted features. The method also includes combining the set of measurements and the extracted features to produce a dataframe. The method also includes predicting the CI for the patient. The CI is predicted using a prediction model based upon the dataframe.