152 results about "Treatment parameters" patented technology

The invention relates to an Agent AI-based full-process intelligent radiotherapy system and a working method thereof, the system comprises a treatment Agent, a feedback Agent and a QA Agent, the feedback Agent is connected with the treatment Agent, the input of the treatment Agent is multi-modal data, and an initial radiotherapy scheme is dynamically output through deep learning and an evolutionary algorithm; the feedback Agent is connected with the multi-sensor system and used for monitoring user state data of the patient in real time, correspondingly adjusting treatment parameters according to an initial treatment scheme and outputting an optimized treatment scheme; and the QA Agent is used for monitoring key parameters in the treatment process, performing early treatment verification and later quality evaluation, and outputting a quality assurance report. Compared with the prior art, multi-Agent mutual cooperation is designed, multi-modal data are integrated, full-process automation from treatment scheme determination, data acquisition, target region sketching, plan generation, treatment execution to QA is achieved, dependence on manual intervention can be reduced, and treatment individuation and efficiency are improved.

The invention relates to the technical field of medical information processing, in particular to a type 2 diabetes precise typing and dynamic treatment system which comprises a clinical feature extraction module, a metabolism dynamic modeling module, a precise typing module, a treatment parameter generation module and a dynamic treatment output module. Wherein the clinical feature extraction module is used for collecting a multi-dimensional clinical data set of a patient for continuous 14 days; the metabolism dynamic modeling module is used for extracting blood glucose fluctuation characteristics and pancreas islet function compensation characteristics; the precise typing module is used for dividing metabolism-driven subtypes to which the patients belong through a clustering algorithm; the treatment parameter generation module is used for mapping a subtype-treatment rule base and outputting a matched personalized treatment parameter combination; and the dynamic treatment output module outputs a dynamic treatment scheme. According to the invention, through a dynamic treatment mechanism based on typing, linkage control of individual difference identification and real-time adjustment of the medication scheme of the type 2 diabetes patients is realized, and the accuracy and adaptability of treatment are improved.

The invention relates to the technical field of medical treatment, and discloses a knee joint knee protection treatment personalized planning system based on multi-modal data fusion. A data acquisition and preprocessing module of the system acquires a multi-modal data stream of the knee joint of a patient in real time and generates a standardized data packet; the treatment event identification module is used for automatically identifying and verifying key treatment events from the standardized data packet and generating a treatment event sequence; the historical treatment path query module queries a distributed database and extracts treatment modes of similar patients; the graph matching and path generation module is used for calculating the similarity between the current treatment event sequence and a historical treatment mode, generating a fusion treatment path when the similarity exceeds a threshold value and storing the fusion treatment path to the block chain network; the abnormity monitoring and analysis module monitors abnormal event points in the fusion treatment path in real time, triggers a path decomposition mechanism and performs multi-dimensional performance analysis; and the personalized scheme generation module is used for dynamically adjusting treatment parameters and generating a personalized treatment planning scheme.

The invention discloses a multi-mode closed-loop feedback thumbtack needle electrical stimulation anti-depression system, belongs to the technical field of drug delivery systems, and particularly relates to collaborative treatment of acupoint stimulation and drug sustained release. The problems that in the prior art, cooperation of acupoint stimulation and medicine slow release cannot be achieved, and further improvement of the treatment effect is limited are solved. The system comprises an AI regulation and control module and a collaborative treatment module. The AI regulation and control module predicts treatment parameters; and the collaborative treatment module is used for carrying out collaborative treatment of acupoint electrical stimulation and skin administration on the patient based on the predicted treatment parameters. The multi-mode closed-loop feedback thumbtack needle electrical stimulation anti-depression system is suitable for collaborative treatment of acupoint stimulation and drug sustained release.

The invention provides a brain-computer interface-based TMS and VR collaborative rehabilitation training system, which is characterized in that a multi-mode collaborative positioning module is used for collecting VR interaction data and electroencephalogram data and determining the optimal stimulation state of a subject; the motion intention analysis module is used for matching a rehabilitation mode according to the collected data and in combination with the type of the subject; and the closed-loop rehabilitation interaction module is used for adjusting parameters of the TMS equipment according to the rehabilitation mode and stimulating the final stimulation area under the optimal stimulation state of the subject. For a mild stroke patient, the system dynamically monitors the plastic change of the autonomic nerve and adaptively adjusts the treatment parameters according to the plastic change of the autonomic nerve; for a severe stroke patient, the virtual reality situation is combined to effectively induce motor imagery and synchronously collect and analyze electroencephalogram signals, closed-loop nerve regulation is achieved, synchronous accurate intervention and curative effect optimization of the severe stroke patient are achieved, and an intelligent solution is provided for rehabilitation treatment of the nerve function of the severe stroke patient.

The invention discloses a control method of a hemorrhoid electrolytic treatment device, and belongs to the technical field of electrolytic treatment, a main control unit receives treatment parameters such as female hemorrhoid diameter or hemorrhoid size and grade, calls a treatment parameter set established based on clinical / experimental data from a memory, determines target output current and treatment time in a range of 0-50mA, and sends the target output current and treatment time to a control unit; the constant-current output module is controlled to output direct-current treatment current; output current and voltage are collected in real time through a current detection module, load impedance is calculated, and protection is triggered when the load impedance is abnormal; meanwhile, discrete integration is carried out on the actual output current to obtain accumulated treatment charge quantity, and when a target charge quantity threshold value is reached, treatment is automatically terminated, and treatment data are recorded. According to the invention, high-precision constant-current control and quantitative management based on total charge quantity in the hemorrhoid electrolytic treatment process are realized, and the treatment efficiency and repeatability are improved on the premise of ensuring safety.

A system may include a processor-based system including at least one processor and memory comprising instructions. When executed by the processor-based system, the instructions cause the processor-based system to: access metrics of a subject who is being treated with a therapy that includes a magnetic non-parallel electric field (MNPEF) therapy or a magnetic non-parallel magnetic field (MNPMF) therapy, wherein the accessed metrics include at least one analyte, the at least one analyte including one or more of blood glucose data, lactate data, or pyruvate data, free fatty acid data, cholesterol data, and compliance data for complying with the therapy; use the accessed metrics as an input to a machine learning algorithm that is configured to determine a set of therapy parameters for the therapy, and program a controller operably connected to at least one energy field system to deliver the therapy according to the determined set of therapy parameters.

The invention relates to an intelligent self-adaptive shock wave treatment system for chronic pelvic pain syndrome. The system comprises an ultrasonic image acquisition module used for acquiring ultrasonic image data of a pelvic region of a patient; the focused shock wave therapeutic apparatus is used for generating and outputting focused shock waves for treatment; the focused shock wave therapeutic apparatus is integrated with a pressure sensor which is used for detecting pressure data in real time when the therapeutic head is in contact with the skin. The five-axis mechanical arm is used for carrying a probe and a treatment head of the ultrasonic image acquisition module and controlling spatial poses and movement of the probe and the treatment head; and the central control module is used for determining treatment parameters according to the ultrasonic image data and the pressure data, and controlling the five-axis mechanical arm and the focused shock wave therapeutic apparatus to perform treatment based on the treatment parameters. Manual intervention can be reduced, the automatic treatment process is achieved, the positioning precision is improved, and individual physiological changes are dynamically adapted.

The invention relates to an integrated control method and system for a critical patient, a medium and equipment, and relates to the technical field of equipment control, and the method comprises the steps: obtaining the actual vital sign data of at least one monitoring dimension of a target patient on a first-aid stretcher through a defibrillation monitor; if the actual vital sign data is abnormal, determining the corresponding monitoring dimension as an actual abnormal vital sign dimension, and obtaining a plurality of historical dimensions with abnormal vital sign data and a plurality of started historical first-aid devices when a historical patient starts the first-aid devices; based on the historical dimension, the historical first-aid equipment and the at least one actual abnormal sign dimension, determining whether the target patient needs to start the first-aid equipment; if it is determined that the target patient needs to start the first-aid equipment, at least one device suitable for starting is determined from all the first-aid equipment, and suitable treatment parameters of all the devices suitable for starting are determined. The method has the effect of reducing the safety risk of the patient in the transferring process.

This invention relates to a method and system for evaluating parameters in the fabrication of a scoliosis orthosis. First, the initial position of the robotic arm is calculated based on the user's own treatment parameters. Then, the force applied to the robotic arm is continuously increased in preset steps until the maximum tolerable thrust position is found. Next, the relevant parameters of the maximum thrust position are used to convert the correction parameters, and the obtained correction parameters are input into a model to obtain the current correction model. The correction model and its associated parameters are sent to the orthotist to assist in orthosis design. In this invention, the orthotist can intuitively understand the quantitative relationship between the degree of contact between the orthosis and the body, the corrective force, and the spinal correction effect. Combined with the patient's surface images and spinal X-rays, the orthosis design is performed, reducing the problems encountered by the orthotist during the design process regarding the required pressure or the appropriate distance the orthosis needs to be close to the body to determine the resulting spinal deformation.

This invention discloses a lung care system for airway clearance based on ultrasound technology, belonging to the field of airway clearance technology. The system includes a data acquisition module, a risk assessment and control module, an ultrasound treatment parameter matching module, an ultrasound treatment execution module, a real-time feedback and control module, and a data storage module. This invention solves the problem that existing technologies cannot collect efficacy-related data in real time during treatment, nor can they dynamically adjust treatment plans based on efficacy data. This invention can dynamically adjust ultrasound treatment parameters according to the patient's real-time airway function status, achieving data-driven precision nursing, significantly improving airway clearance effects, reducing the risk of complications caused by sputum residue, avoiding ineffective treatment and over-intervention, shortening the treatment cycle, improving nursing efficiency, significantly reducing the risk of treatment-related adverse events, and enhancing the safety and reliability of lung care.

To provide a screen display device and method for medical equipment.SOLUTION: Wherein the processor generates a first screen showing a status object related to the operation of the medical device and displays the first screen on the display, and generates a second screen showing an adjustment object for adjusting the operation parameter of the medical device and displays the second screen on the display when it is determined that an interaction event has occurred, when the interaction of the user with the adjustment object on the second screen is detected, the operation parameter corresponding to the adjustment object is adjusted based on the input value corresponding to the detected interaction, and the operation of the medical device is controlled based on the adjusted operation parameter.SELECTED DRAWING: Figure 1

The disclosure relates to methods and systems for automatically determining and generating human skin attributes and attribute maps by a skin diagnostic and aesthetic processing system. The disclosure proposes a process for automated determination of various skin attributes by using one or more trained models that use the determined skin attributes to identify processing parameters of an energy-based processing system.

This invention discloses an automatic control method and system for a MI-E expectorant machine, comprising: analyzing real-time respiratory data of a patient during the use of the expectorant machine to determine the applicable operating mode of the expectorant machine; diagnosing the consistency between the current operating mode of the expectorant machine and the applicable operating mode, wherein, if the diagnosis result is inconsistent, a working mode switching command is generated to switch the current operating mode of the expectorant machine to the applicable operating mode; or, if the diagnosis result is consistent, a treatment parameter adjustment command is generated to optimize the treatment parameters corresponding to the current operating mode of the expectorant machine. This invention achieves automatic control of the MI-E expectorant machine, effectively improving treatment safety and efficiency.

A method for determining settings for cooled radiofrequency ablation (CRFA) system includes obtaining historical CRFA data associated with a plurality of patients previously treated using the CRFA system, wherein the historical CRFA data includes patient characteristics, operating parameters of the CRFA system, and treatment outcomes associated with each of the plurality of patients; training an ensemble machine learning model to predict success of CRFA procedures based on the historical CRFA data; determining a first set of operating parameters for the CRFA system using the trained ensemble machine learning model, wherein the first set of operating parameters comprise settings of the CRFA system that are determined to affect the success of CRFA procedures; and determining a value or a range of values for each of the first set of operating parameters for use in CRFA treatment procedures using a decision tree-based model.

The invention belongs to the field of radiotherapy auxiliary instruments, and particularly relates to a transportation method and system for assisting a radiotherapy patient in taking and placing a positioning pad. The system is connected with a storage chamber, an accelerator chamber, a CT chamber and a waste chamber through a transportation track, and a transportation robot automatically transports a positioning pad along the track. The robot is provided with a multi-joint mechanical arm, a scanner and a clamping jaw, and positioning pads at different positions in the storage cabinet can be accurately stored and taken. The method comprises the following steps: pasting a unique bar code for each positioning pad, and distributing a storage position through an information system; during treatment, the cushion is automatically called according to a Mosaiq instruction, and after treatment, the cushion is automatically reset and treatment parameters are updated; after treatment, the device is automatically transferred to a waste chamber. And the integrity of the cushion is monitored in real time by adopting a pressure sensor. According to the invention, the whole-process non-contact management of the positioning pad is realized, the problems of disordered access, mistaken access, difficulty in finding and the like are effectively solved, and the radiotherapy management efficiency is remarkably improved.

The application discloses a female stress urinary incontinence acupuncture treatment optimization method based on multi-modal data fusion, and belongs to the technical field of intelligent auxiliary medical treatment. The method comprises the following steps: through a three-level representation learning subnetwork comprising modal difference extraction, cross-modal attention alignment and fusion feature enhancement, unified representation learning is performed on multi-source data such as patient baseline features, pelvic floor image sequences, electromyographic signals and curative effect indexes; based on the representation and treatment parameters, a dynamic time sequence kernel fusion method is used to predict the treatment state change trend of the patient at multiple future time points; finally, a state-scheme cross attention mechanism is introduced, and combined with the prediction result and historical treatment scheme features, an individualized acupuncture acupoint, manipulation strength and treatment cycle optimization suggestion is adaptively output. The application realizes an end-to-end intelligent diagnosis and treatment closed loop from data fusion, curative effect prediction to scheme recommendation, and improves the accuracy and clinical effect of acupuncture treatment.

The invention discloses a microneedle array control system and method for a radio frequency microneedle therapeutic apparatus, and relates to the technical field of microneedle arrays. Therapeutic data of a therapeutic record are extracted and combined with a puncture feedback training group to generate a therapeutic time sequence training set; a treatment parameter dynamic model is generated through training of a double-layer LSTM time sequence regression model; based on an initial puncture parameter model in the skin feature library and a dynamic response model in the dynamic response feature library, acquiring a real-time skin image in the treatment process, calculating a real-time to-be-treated area score, generating a real-time initial puncture parameter, calculating a real-time regulation and control parameter through the dynamic response model, and when puncture succeeds, performing real-time regulation and control on the real-time to-be-treated area score; and collecting the puncture feedback training group, inputting the puncture feedback training group into the treatment parameter dynamic model, generating real-time treatment parameters, uploading the real-time treatment parameters to the radio frequency microneedle treatment instrument equipment, and executing radio frequency treatment operation according to the real-time treatment parameters.

Various techniques related to post-treatment parameters of patients are described. An example method includes identifying a segment of an electrocardiogram (ECG) of an individual, wherein the segment is detected during a time interval that begins when an electrical shock is output to the individual's heart. The method further includes identifying a parameter of the electrical shock and generating a report including the segment of the ECG and indicating the parameter of the electrical shock. The report is output or transmitted to an external device.

The invention relates to the technical field of medical electronic equipment control, and discloses a data consistency control method and system for a short-wave therapeutic apparatus. According to the method, target treatment parameters issued by an upper computer are received and dynamically mapped into hardware configuration parameters including oscillator control words and power amplifier bias voltage control codes. A logic verification rule is established based on circuit physical characteristics, and data logic consistency among hardware configuration parameters is ensured. After logic verification is passed, hardware configuration parameters are sent to related circuits, actual execution parameters are read in real time for consistency comparison, and parameter loading and output control are triggered only when comparison is passed. According to the invention, through triple mechanisms of dynamic mapping, logic verification and consistency comparison, the treatment accuracy and safety of the short-wave therapeutic apparatus are effectively improved.

The present application belongs to the technical field of temperature monitoring, and specifically relates to a temperature monitoring system and method based on high-energy red light therapy. The present application can comprehensively understand the temperature condition of the treatment area through the two-dimensional processing of surface and deep temperature information, find abnormal areas in real time and take accurate temperature control measures, effectively avoid overheating or overcooling, ensure treatment safety, adjust treatment parameters such as red light power and treatment time according to the specific needs of different treatment areas through dynamic monitoring and feedback mechanism, realize personalized temperature control, ensure that each area obtains the most suitable treatment conditions, and improve treatment effect. Through dynamic regulation and feedback mechanism, a closed-loop control system is formed, and real-time temperature feedback adjustment can continuously optimize the treatment temperature distribution, ensuring the continuity and stability of the treatment effect.

The invention discloses a complication early warning method, device and system and a medium, and relates to the field of medical monitoring equipment.The individual information of patients is obtained, the weight proportion of physiological parameters in a complication early warning model is adjusted according to the individual information, the individual difference of the patients is considered, and the individuation degree of the complication early warning model is improved; inputting real-time physiological parameters, collected in the dialysis process, of the patient and real-time treatment parameters of a dialysis machine into the updated complication early-warning model, outputting the probability of occurrence of target complication, and ensuring that a prediction result fits the current state of the patient; the deviation degree of each real-time physiological parameter is calculated according to the real-time physiological parameter and the individualized baseline value corresponding to each real-time physiological parameter, and the individualized precision is improved; complication early warning is performed by integrating the occurrence probability of the target complication and the deviation degree of the physiological parameters corresponding to the target complication, and double-factor complementary verification is performed, so that false alarm and missing alarm caused by a single index are remarkably weakened, and the accuracy of complication early warning is improved.

The invention provides an energy type robot treatment system and method for AI driving, the system comprises a robot arm, a multi-mode sensor kit and an AI control unit, and an end effector capable of generating treatment energy is installed at the tail end of the robot arm. A trained machine learning model on an AI control unit is used for processing real-time data collected by a multi-mode sensor suite from a treatment part, and the machine learning model is combined with pre-loaded patient data to generate a predictive control signal; the AI-driven control can achieve accurate and selective ablation of cancer tissue while minimizing incidental damage to surrounding healthy tissue, so as to improve the therapeutic effect, by dynamically adjusting the therapeutic parameters and height position parameters of the end effector.

In certain example embodiments, a system and / or method of guiding transitions between therapy modes in connection with the treatment and / or diagnosis of a patient for a respiratory disorder is / are provided. Respiratory disorder treatment according to a first therapy mode is provided. Input indicating a second therapy mode to be transitioned to following provision of the first therapy mode is received, with the second therapy mode being different from the first therapy mode. At least one default treatment parameter suitable for the second therapy mode is assigned or calculated. Each default treatment parameter of the second therapy mode is presented, with each default treatment parameter being adjustable by an operator during the presenting. Transitioning from the first therapy mode to the second therapy mode is performed by providing respiratory disorder treatment in accordance with the second therapy mode and each default treatment parameter and any adjustments made thereto prior to the transitioning. Advantageously, the chances of a patient being disturbed by transitioning from mode-to-mode are reduced.

The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning / artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.

In some embodiments, there is provided a method of automating radiation therapy treatment planning. The method may include receiving at least an objective for a control structure associated with a plurality of organs-at-risk; optimizing, using a first machine learning model configured as an optimization engine, a treatment plan including the control structure and the objective; selecting, based on one or more scores, at least a first organ‐at‐risk to enable objective adjustment; adjusting, using a second machine learning model using a continuous action space, one or more objective parameters for the selected first organ‐at‐risk; and re-optimizing, using the first machine learning model configured as the optimization engine, the treatment plan including the adjusted one or more objective parameters for the selected first organ‐at‐risk; and outputting the re-optimized treatment plan including one or more treatment parameters. Related systems, methods, and articles of manufacture are also disclosed.

The invention discloses a control method of an oxygen-enriched synergistic cold therapy cabin system. S1; the temperature T1INT in the cold therapy cabin, the ambient temperature T2INT outside the cold therapy cabin, the temperature T3INT of the evaporator and the temperature T4INT of the condenser are acquired by the sensor; s2; by monitoring the T1INI, the T2INI, the T3INI and the T4INI, the load state of the cold therapy cabin is judged, and the current operation stage of the current oxygen-enriched collaborative cold therapy cabin system is judged; the invention provides an oxygen-enriched collaborative cold therapy system control method, which is used for controlling each system of a cold therapy cabin to realize ultralow-temperature cold therapy combining oxygen-enriched recovery, photodynamic therapy and local position enhanced cold therapy, thermal load in the cabin has time-varying characteristics during cold therapy, the thermal load is modeled through a prediction algorithm, and the time-varying characteristics of the thermal load in the cabin are improved. Variables in a future time period are predicted and optimized, an in-cabin environment system is a nonlinear coupling system, a PID neural network optimized by an ant lion algorithm is adopted to control in-cabin treatment parameters and survival parameters, and it is ensured that a patient receives safe and effective physical treatment in the cabin.

The invention relates to a parameter power-off recovery method, system and device for a sleep respirator and a medium, and the method comprises the steps: identifying whether the sleep respirator has abnormal power-off or not through status bit verification, and introducing a timestamp comparison logic of large-capacity SD card backup and EEPROM storage and a multi-verification mechanism cooperative judgment strategy. The latest and complete treatment parameter data can be accurately selected when the equipment is electrified and initialized each time, so that the parameter recovery reliability of the sleep breathing machine in an abnormal power failure or data damage scene is effectively improved, the data loss risk caused by a fault of a single storage medium is avoided, and the system stability and the treatment continuity are remarkably enhanced; especially in medical equipment running for a long time, data consistency and recovery accuracy are crucial.