2901 results about "Medical systems" patented technology

This invention presents a multisensor-connected, AI-enabled telehealth system for assisting healthcare providers with differential diagnosis and patients with early health concern detection. The system comprises a multi-sensor medical device with at least seven sensors, a secure cloud-based platform, and an interactive telehealth module. The device preprocesses and securely transmits patient information to the cloud platform, where an ensemble of deep learning models analyzes the data to generate ranked potential diagnoses with likelihood scores. The telehealth module facilitates communication between providers, patients, and the cloud platform, presenting visualizations and receiving feedback. The system continuously updates and fine-tunes its models using incremental learning algorithms, adapting to new data while retaining previous knowledge. It also generates alerts for providers and patients when deviations from normal physiological patterns are detected, accompanied by explainable AI visualizations.

The invention discloses a data analysis platform management method and system, and belongs to the technical field of computer data processing, and the method comprises the steps: obtaining multi-source heterogeneous data from a medical information system; establishing a cross-system data association model, performing dynamic feature extraction and weight distribution on multi-source heterogeneous data, and outputting a resource supply-demand relationship graph; analyzing the resource supply-demand relation graph, and identifying business conflicts in medical resource scheduling; generating a conflict solution of the business conflict based on a multi-objective optimization algorithm, and generating an execution instruction; and issuing an execution instruction to the target medical system, verifying an execution result of the execution instruction, and updating system parameters. According to the method, a cross-system dynamic modeling and multi-objective optimization strategy is adopted, and a closed-loop verification mechanism and a multi-source heterogeneous data fusion technology are combined, so that intelligent prediction, accurate scheduling and self-learning optimization of medical resource conflicts can be realized, full-process traceable execution of high-value consumables is ensured, and the resource utilization efficiency and the emergency response capability are comprehensively improved.

A medical system includes an elongate instrument, a tracking system, and one or more processors. The tracking system is disposed along at least a portion of the elongate instrument. The one or more processors are coupled to the tracking system and are configured to: generate a plurality of linked bounded-surface elements corresponding to a set of connected passageways of a patient anatomy; receive shape information from the tracking system, the shape information indicating a shape of at least a portion of the elongate instrument when the portion is disposed in the set of connected passageways; register the shape information to the plurality of linked bounded-surface elements; and based on the registering, display a composite image including an instrument image of the elongate instrument displayed within a model of the set of connected passageways.

An application management system may provide, while a user device detects a beacon associated with a medical system, a user of the user device with access to a first set of medical session features of an application executed by the user device. The application management system may also provide, while the user device does not detect the beacon, the user with access to a second set of medical session features of the application, the second set of medical session features being different from the first set of medical session features.

A robotic medical system includes a post being substantially vertical and coupled to a base; a robotic drive having a socket for receiving the post; and at least one tapered interface shaped and oriented to engage the socket to prevent rotation of the robotic drive about at least one axis.

A robotic medical system for performing a vascular procedure includes a procedure rail having a drive surface oriented along a generally vertical plane, a rail adjustment system configured to couple to a patient support table and having one or more movable arm segments, a fluidics system, and a plurality of catheter hubs operatively coupled to the procedure rail and configured to be axially translated along the drive surface along a longitudinal axis of the procedure rail. At least one of the plurality of catheter hubs is in fluid communication with the fluidics system, the at least one of the plurality of catheter hubs having a hemostasis valve and a catheter in communication with the hemostasis valve.

Medical systems and devices include an elongate probe configured for insertion into a patient, where the elongate probe includes an atraumatic tip and where the atraumatic tip can include one or more of a loop, a curl, coil, a flexible distal region, and a steerable distal region. The distal region can be configured to transition away from a first shape toward a second shape upon insertion of the elongate probe within the patient. The optical fiber can include sensing core fibers configured to facilitate a determination of a physical state of the elongate probe. The elongate probe can also be configured to project illuminating light away from a distal end and receive imaging light at the distal end. The elongate probe can include a catheter.

This disclosure is directed to techniques for detecting and mitigating inaccurate sensing in a medical system. In some examples, one or more sensors of the medical system may include at least one electrode configured to sense an impedance of a portion of a patient's body proximate to the electrode and processing circuitry of the medical system may detect an inaccuracy in the data corresponding to the one or more patient physiological parameters based upon data including at least the sensed impedance of the portion of the patient body; correct at least a portion of the inaccuracy in the data corresponding to the one or more patient physiological parameters; and generate, for display on a display device, output data indicating the inaccuracy in the data corresponding to the one or more patient physiological parameters.

The invention discloses an ophthalmologic operation real-time navigation system and method based on dynamic visual field tracking, and relates to the technical field of medical systems. Comprising the following steps: matching operation data closest to a current operation from a database, and generating standard operation navigation of the current operation; the real-time image of the operation process is compared with the image of the standard operation navigation in real time, the step of the current operation is determined, and meanwhile subsequent image navigation of the operation of the patient is displayed; generating a spatial mapping matrix between an eyeball movement track and a target region by combining target region boundary data of preoperative OCT image segmentation and an intra-operative navigation coordinate system; the virtual navigation path of the surgical instrument is dynamically corrected according to the real-time eyeball movement track, so that the surgical instrument is aligned with the target area, the spatial relation between the instrument and the target area can be visually mastered through the overlapping display of the three-dimensional virtual path and the real-time image, unconscious displacement or physiological tremor of a patient in an operation is actively adapted, and the operation accuracy is improved. And the continuous accuracy of the navigation path is ensured.

The invention discloses an osteoarticular disease rehabilitation training optimization system, and relates to the field of medical training, and the system comprises an authority control module which is used for connecting an electronic medical system, obtaining the reading authority of historical and current medical data of a patient, and obtaining the instruction control and data reading authority of each functional module; the multimode acquisition module is used for acquiring pathological bone joints, associated musculoskeletal data and personal basic data through the authority control module, and converting original data into feature vectors of muscle activation degree, bone joint activity degree and skeleton stress distribution of a corresponding area of a patient body; by integrating medical data, musculoskeletal features and economic condition information of a patient, a personalized model is constructed to output an optimal adaptive training item and specific data thereof, the compensatory load of a non-ill-conditioned joint is evaluated, and timely intervention is performed through a fusing mechanism when abnormity is monitored in real time, so that the safety is ensured.

In one embodiment, a medical system includes a catheter configured to be inserted into a chamber of a heart of a living subject, and including multiple electrodes configured to capture electrical activity from electrical activation signals propagating in tissue of the chamber, a display, and processing circuitry configured to automatically select bipolar signals to be captured into an electro-anatomical map from respective electrode pairs of the multiple electrodes responsively to an alignment of the respective electrode pairs with a direction of propagation of the electrical activation signals, and render the electro-anatomical map to the display.

The invention relates to the technical field of medical systems, and particularly discloses an anesthesia complication prediction model construction method based on deep learning, and the method comprises the following steps: S1, obtaining multi-source heterogeneous anesthesia medical data; s2, constructing a multi-modal feature fusion module; s3, designing a hierarchical deep neural network architecture which comprises sub-networks for processing different modal data in parallel and a full-connection prediction layer fusing multi-modal features; s4, continuously outputting a complication probability curve in a sliding time window mode by adopting a dynamic risk trajectory prediction mechanism instead of a single static prediction result; and S5, deploying a clinical real-time decision interface, and mapping a prediction result to an anesthesia monitoring equipment alarm system in real time. A bidirectional LSTM + 1D-CNN hybrid encoder and a cross-modal attention mechanism are adopted, time sequence dependence of physiological signals and spatio-temporal characteristics of operation events are synchronously captured, deep semantic fusion of multi-source data is achieved, and the characterization capacity of a model for precursor characteristics of complications is improved.

A fluid management system for use in a tissue resection procedure includes a controller. An inflow pump is operated by the controller and configured to provide fluid inflow through a flow path to a site in patient's body. An outflow pump is operated by the controller and configured to provide fluid outflow through a flow path from the site in patient's body. A motor driven resecting device may be provided for resecting tissue at the site. The controller is configured to actuate an inflow pump and an outflow pump in response to various signals and various algorithms are provided to provide malfunction warnings and assure safe operation.

A medical system includes a medical device and a display for displaying a plurality of visual elements. The plurality of visual elements are associated with functions of the medical device. The medical system also includes a plurality of visual profiles for facilitating in controlling visual appearance of the plurality of visual elements displayed on the display, and a visual profile selector for selecting at least one of the plurality of visual profiles based on a state of the medical device.

Systems and methods for designing and implementing patient-specific surgical procedures and / or medical devices are disclosed. In some embodiments, a method includes receiving a patient data set of a patient. The patient data set is compared to a plurality of reference patient data sets, wherein each of the plurality of reference patient data sets is associated with a corresponding reference patient. A subset of the plurality of reference patient data sets is selected based, at least partly, on similarity to the patient data set and treatment outcome of the corresponding reference patient. Based on the selected subset, at least one surgical procedure or medical device design for treating the patient is generated.

A medical robotic system and method of operating such comprises taking intraoperative external image data of a patient anatomy, and using that image data to generate a modeling adjustment for a control system of the medical robotic system (e.g., updating anatomic model and / or refining instrument registration), and / or adjust a procedure control aspect (e.g., regulating substance or therapy delivery, improving targeting, and / or tracking performance).

The invention relates to the technical field of medical systems, in particular to an intelligent gastrointestinal postoperative intestinal obstruction diagnosis and intervention decision-making system and method, and the system comprises a data preprocessing module, a multi-modal data fusion module, a gastrointestinal function recovery model construction module, a self-adaptive progressive reinforcement learning optimization module AHRL and a diagnosis and intervention recommendation module. The self-adaptive progressive reinforcement learning optimization module optimizes an intervention strategy layer by layer through a five-layer progressive algorithm from the steps of dynamic adjustment of feature weights, recursive state propagation, layered accumulation optimization, symptom similarity matrix generation, progressive weight reverse feedback and the like, deep fusion of key symptoms by multi-modal data is achieved, and the accuracy of the key symptoms is improved. And the intervention scheme is updated in real time according to the patient state change. In the intervention decision recommendation module, the system generates personalized diagnosis suggestions based on the optimized strategy, carries out real-time risk assessment, and provides continuous and dynamic intervention support for the patient.

The invention relates to the technical field of intelligent medical systems, and discloses a cerebral apoplexy onset risk assessment and reminding method and system.The method comprises the steps that continuous medical structured detection data are collected, and the data comprise carotid artery blood flow parameters, brain oxygen saturation, heart rate variability and metabolic indexes; inputting a bidirectional LSTM, a differential convolutional network, a wavelet residual network and a multi-layer perceptron to extract nonlinear features; constructing a neural function coupling structure diagram of four nodes of cerebral blood supply, oxygen supply, autonomous regulation and metabolic steady state; calculating inter-node time sequence offset correlation and a stable factor to obtain a coupling anomaly coefficient; and driving the embedded network by using a graph structure and a node feature input mechanism, and outputting a risk state assessment result. According to the method, the neural function coupling structure diagram is constructed and the mechanism is introduced to drive the embedded network, so that high-precision identification of the multi-system collaborative abnormal state and dynamic evaluation of the stroke risk level are realized.

The invention provides a bone image superposition presentation method and system based on an augmented reality technology, and relates to the technical field of intelligent medical systems.The method comprises the steps that fracture image data for a fracture area of a patient are acquired, and the fracture image data comprise a CT image, an X-ray image and a light field image; analyzing a light model corresponding to the light field image; the light model provides propagation information of light in a fracture area space of a patient; determining multi-modal fusion features corresponding to the fracture image data based on a light model and a feature fusion network; the feature fusion network adopts a convolutional neural network; reconstructing a three-dimensional model of the fracture part based on the multi-modal fusion features; and aligning and calibrating the reconstructed three-dimensional model of the fracture part and the fracture area of the patient in the actual operation scene. Therefore, the augmented reality technology, the light model and the feature fusion network are comprehensively applied, the three-dimensional model of the fracture part is accurately overlaid and presented in real time in a real operation scene space, and the accuracy and efficiency of the operation can be remarkably improved.

The invention discloses a medical knowledge constrained multi-modal time series data dynamic evaluation method and a wearable medical system. According to the method, a mixed perception architecture is constructed through an improved Swin-Transform time sequence encoder and a graph neural network, a medical priori mask matrix is embedded to constrain an attention mechanism, and time sequence feature extraction and cross-parameter correlation modeling of multi-modal physiological signals are enhanced; a dynamic quality evaluation model is designed, data integrity, cross-modal consistency and diagnosis effectiveness indexes are fused, an evaluation weight is adjusted in real time in combination with an adaptive weight function, and quantitative association of data quality and clinical diagnosis confidence is achieved; and when the motion artifacts or pathological conflicts are judged to exist, starting an abnormal positioning and correcting mechanism. According to the method, noise such as motion artifacts and interference can be monitored at any time, the attention to different indexes is adjusted in real time according to the risk level, and the pathological recognition accuracy and clinical credibility are improved by fusing multi-mode perception of medical knowledge.

Disclosed herein are medical systems, pads, and methods for exchanging thermal energy between a circulating fluid and a patient. Some pads are configured multiple uses on the same patient or across multiple different patients. Some pads include multiple layers of hydrogel disposed on one or both sides a fluid compartment. Removable hydrogel layers expose other hydrogel layers for subsequent uses of the pad. Removable storage liners encapsulate one or multiple hydrogel layers. Separation liners between adjacent hydrogel layers isolate the adjacent hydrogels from each other and removal of the separation liner extends the operational life a hydrogel layer. Adhesive patches secure the pads to the patient including adhesive patches extending through openings of a pad. Some pads are configured for disinfection, sterilization and / or laundering. In an embodiment, the fluid is air and a vacuum within a compartment of the pad secures the pad to the patient.

The invention relates to the technical field of medical system management, and particularly provides an outpatient medical insurance chronic disease medical data processing system based on artificial intelligence NLP. The system comprises a knowledge graph construction component which is configured to integrate multi-source heterogeneous data such as medical records, medical insurance and signs, perform cleaning, normalization and structural processing on the data through an NLP technology, and construct a chronic disease medical data knowledge graph; the diagnosis and treatment scheme matching component is configured to perform semantic analysis on the medical insurance policy document and the diagnosis and treatment guide through an NLP technology, and match a diagnosis and treatment scheme and a medical insurance reimbursement path in combination with the actual illness state and the medical insurance reimbursement record of the patient; the analysis and early warning assembly is configured to analyze the long-term health data of the chronic disease patient, identify potential health risks and development trends, and provide personalized health management suggestions and early warning prompts. According to the method, multi-source data integration and knowledge graph construction are achieved through the NLP technology, and the problem of data heterogeneity and the semantic association requirement are solved.

The invention discloses a multidisciplinary combined diagnosis and treatment method and system, relates to the technical field of intelligent medical systems, and solves the problems that traditional manual consultation is low in efficiency and is greatly interfered by human factors, simple system recommendation is inaccurate, and diagnosis and treatment requirements of patients are difficult to meet. The method comprises the steps of generating a consultation scheme based on a preset matching degree standard, an illness condition and a diagnosis and treatment specification, triggering a payment process after system compliance verification, and locking consultation resources after payment succeeds; according to the illness state emergency degree of the patient, expert scheduling information and hospital resource occupation condition, intelligent scheduling is carried out to generate a consultation time arrangement, and meanwhile, consultation invitation and detailed information are sent to related experts; and after the consultation is finished, the system arranges text records, fuses expert opinions, generates a structured consultation report and pushes the structured consultation report to a patient end. The method has the advantages that intelligent management of multidisciplinary joint diagnosis and treatment is achieved, medical resource configuration is optimized, diagnosis and treatment efficiency and accuracy are improved, and medical experience of patients is improved.

Embodiments of the present disclosure provide a medical system and method. The medical system includes an equipment room, a plurality of medical rooms, the imaging device, and a plurality of shielding doors. The imaging device includes the movable imaging component. The movable imaging component is shared by the plurality of medical rooms, and the movable imaging component is configured to move between the equipment room and the plurality of medical rooms. For each of the plurality of shielding doors, the shielding door is provided between one of the plurality of medical rooms and the equipment room.

The invention discloses a mild cognitive impairment brain rehabilitation training device and system in the technical field of cognitive nerve rehabilitation, and the device comprises a multi-modal data fusion module, a personalized training task generation module, a multi-sensory stimulation presentation module and a real-time adaptive regulation and control module. And the personalized training task generation module is used for dynamically generating a personalized narrative training task fusing the user interest theme and the cognitive training target by utilizing a reinforcement learning algorithm based on the user cognitive weak domain evaluation result and the user personal interest and life narrative content obtained through natural language processing. Clinical data of a patient and real-time electroencephalogram and behavior data are fused, a narrative training task deeply fused with life experience and interest of the patient is dynamically generated, the difficulty of the training task is automatically adjusted according to real-time physiological indexes, meanwhile, seamless connection with a medical system is achieved through digital biomarkers, and the training efficiency is improved. And the precision and compliance of rehabilitation training are obviously improved.

The present invention discloses a method, device, storage medium, and medical system for generating a restoration dental model. Among them, the method comprises: obtaining the restoration type of the tooth to be restored, wherein the restoration type includes at least one of the following: tooth implant type, crown restoration type, and inlay restoration type; determining the key points of the tooth to be restored based on the restoration type, where the key points of the tooth to be restored are used to represent the characteristics of the tooth to be restored; determining the restoration dental model based on the restoration type and the key points of the tooth to be restored. The present invention solves the technical problem of low efficiency of making restoration dental models artificially in related technologies.

A grounded virtual portal to interface with a robotic medical system is provided. The system can include an input controller coupled to a first structure via a plurality of linkages. The first structure can be mechanically coupled to a base structure. The input controller can control an object of a medical environment. A head mounted display can be coupled to a second structure extending the base structure. The head mounted display can be configured to render an extended reality environment corresponding to the medical environment. A processor can establish a grounded reference frame for the input controller to be maintained in the extended reality environment rendered via the head mounted display, and configure, based on the plurality of linkages and the grounded reference frame, a force scaler function for bidirectional force delivery between the input controller and the object of the medical environment.

The invention relates to the technical field of medical systems, in particular to a multi-disease fusion prediction method and system, and the method comprises the steps: obtaining a medical sequence code, and outputting a disease vector; obtaining a gating memory model, obtaining a doctor-seeing time interval, and configuring an additional time gate based on the doctor-seeing time interval and the disease vector; updating the gated memory model based on a time gate to obtain a health memory state and a context disease hiding state; aggregating the context disease hiding states to obtain aggregation states, calculating attention scores corresponding to the aggregation states, and outputting patient disease states based on the attention scores and the aggregation states; demographic statistical characteristics are obtained, and integration is carried out in combination with the disease state of the patient to obtain a combined vector; and mapping the combined vector to disease risk probability distribution to obtain a prediction result. The method and the device have the effect of predicting various diseases through the general data.

A medical system includes a wearable medical device configured to be worn by a patient, remote server(s), and a mobile device. The mobile device includes at least one processor and a display, the at least one processor being configured to establish communication between the mobile device, the wearable medical device, and the remote server(s) when the mobile device is powered on and within a predetermined range of the wearable medical device. The at least one processor is further configured to provide an interactive survey on the display to receive one or more user inputs, update a graphical user interface on the display based on the one or more user inputs, and cause one or more patient engagement features to be displayed on the display. Upon establishing communication between the mobile device, the wearable medical device, and the remote server(s), patient data is transmitted to the remote server(s).

In one example, a medical device may include a handle including a proximal portion and a distal portion, and the proximal portion may pivot relative to the distal portion. The medical device may also include an insertion portion coupled to the distal portion of the handle and configured to be positioned within a body lumen; and an articulation wire extending from the handle through the insertion portion. Pivoting of the proximal portion of the handle relative to the distal portion of the handle may move the articulation wire relative to the insertion portion to bend a distal portion of the insertion portion.