220 results about "Pain management" patented technology

The invention relates to the technical field of data management, in particular to an intelligent home pain management system based on an internet hospital. Comprising a wearable monitoring unit used for acquiring various physiological data of a patient; the internet hospital unit is used for analyzing pain laws according to various physiological data of the patient; according to the system, the physiological state of a patient at home is tracked in real time through the wearable monitoring unit, various data of the physiological state of the patient are transmitted to the Internet hospital unit, an individual database of the patient is established in an Internet hospital, medical staff can conveniently check the treatment stage and the medicine use condition of the patient through the remote management unit, and the medical staff can conveniently check the treatment stage and the medicine use condition. The method effectively solves the problem that a pain patient still needs to dictate a plurality of conditions during disease incidence to a doctor during revisit, is favorable for further improving the doctor seeing efficiency of the patient, has a prevention effect, and can give an alarm when the change trend of data characteristics approaches to a pain attack critical value according to the change of various physiological data characteristics of the patient. And making a prediction to remind the patient to take preventive measures.

The invention discloses a whole-process patient self-control analgesia management platform and method based on artificial intelligence, and relates to the related field of analgesia management, and the platform comprises a multi-source data interaction module which is used for building a time sequence standard data set; the information configuration module is used for starting the self-control analgesia pump; the AI pain evaluation module is used for generating a pain scoring result; and the identification early warning module is used for generating graded early warning. The technical problems of insufficient safety and unstable effect in the analgesia management process due to dependence on a fixed dose threshold and lagged artificial pain assessment in traditional patient self-control analgesia management are solved, the whole-process pain management platform based on artificial intelligence is constructed, multi-source data can be analyzed in real time, and the pain management efficiency is improved. And the pain state of the patient is dynamically evaluated, and the parameters of the analgesia pump are automatically adjusted, so that the technical effects of personalized analgesia management and safety and effectiveness in the analgesia process are realized.

The invention provides a pain assessment system and method based on multi-modal physiological signals. The system comprises a multi-modal signal acquisition module, a signal preprocessing module, a multi-modal feature extraction module, a deep fusion analysis module, an individualized calibration module and a result output and early warning module. By synchronously collecting and analyzing multi-dimensional data such as facial expressions, sound features, physiological signs and behavior responses and combining deep learning and multi-modal information fusion technologies, objective quantitative evaluation and real-time monitoring of the pain degree are achieved, and accurate decision support is provided for clinical pain management.

The invention discloses a personalized child postoperative pain management method and system, and relates to the technical field of pain management. A personalized child postoperative pain management system comprises a data acquisition module, a development evaluation module, a sample management module, a pain evaluation module, a scheme matching module and a feedback adjustment module. According to the invention, by combining objective assessment and subjective assessment, comprehensive acquisition and integration of multi-dimensional data are realized, and the accuracy of pain assessment is greatly improved; through psychological development and physiological development stage evaluation, weighted analysis is carried out on patients, it is ensured that individual characteristics of children are fully considered in a pain evaluation result and a management scheme, and the pertinence and scientificity of pain management are remarkably improved.

The invention discloses a pain management method based on bioelectrical impedance data and a machine learning algorithm, and relates to the technical field of medical health, and the method comprises the steps: carrying out the phase delay analysis of an impedance phase spectrum matrix, calculating the change rate of a phase angle of each frequency point along with time, and obtaining the maximum phase lag time; according to the temperature field sequence and the maximum phase lag time, time-space registration is carried out through a multi-modal data fusion method and impedance modulus changes of the corresponding areas, and a pain biomarker feature library is generated; through a bidirectional LSTM and a cross attention fusion method, time sequence modeling and cross-modal correlation analysis are carried out on bioelectricity signal characteristics extracted by a sliding window and historical pain data, a dynamic evolution rule of pain development is captured, a pain management triple containing pain intensity, intervention response and prognosis evaluation is generated, and a pain management result is obtained. And a quantitative basis is provided for personalized treatment.

The invention relates to the technical field of intelligent medical treatment, in particular to an abdominal postoperative pain intelligent medical management system based on a JBI mode. The system comprises a platform application layer which is used for providing a user interface and an interaction mode, and medical staff and patients can access and use various services provided by a platform service layer; the platform service layer is used for monitoring and analyzing the pain level of a patient in real time, giving an alarm when the pain level is abnormal, and formulating and adjusting an analgesia strategy according to the pain level; and the evaluation feedback unit is used for formulating an evaluation index for the result of the platform service layer and optimizing the service according to the result of the index. The system not only records the pain score and accompanying symptoms of the patient, but also performs customized pain assessment according to different types of patients, so that the working efficiency of medical personnel is improved, the treatment compliance and satisfaction of the patient are enhanced, and finally the overall pain management level and the life quality of the patient are improved.

An interactive pain management system is provided comprising a laser treatment device and an application executing on the device that receives entry of identification information for a first patient and receives entry of a body region to receive treatment. The system also receives entry of a present pain level experienced in the body region, accesses stored information describing previously reported conditions of the first patient and based on the received entries and the accessed store information, determines a treatment regimen for the first patient. The laser treatment device executes the treatment regimen by manual administration by the first patient or a qualified technician. The system requests entry of the first patient's present condition, the condition comprising one of feeling worse, feeling better, and experiencing no change since an immediately previous treatment. Changes in the condition of the first patient are incorporated into the determination of the treatment regimen.

The invention provides an artificial intelligence spinal nerve regulation and control system and method based on a multi-modal physiology-nerve-experience closed loop, and relates to the technical field of medical instruments, the system comprises an implantable stimulation and sensing subsystem, a body surface and wearable sensing subsystem, a communication and time synchronization subsystem and a control processing unit, the implantable stimulation and sensing subsystem, the body surface / wearable sensing subsystem and the control processing unit are in communication connection in pairs through the communication and time synchronization subsystem. According to the method, the fundamental limitation that in the prior art, only dosage is maintained, and brain and subjective experience is ignored is broken through, and more stable, more efficient and more personalized accurate pain management is realized through multi-modal fusion and hierarchical cooperative control.

The invention relates to the technical field of nursing information management, and particularly discloses a cancer patient home pain management decision-making system based on a patient report outcome, which is used for solving the challenges of uneven data quality, slow update feedback speed, large and diverse data volume and the like in pain management of cancer patients in a home environment. The system comprises an intelligent sensing and data aggregation module, a cloud server, a distributed computing and data processing module, an intelligent decision support module and a user interaction feedback module. Noise and abnormal values can be removed through dynamic data cleaning and data standardization, data consistency is ensured through multi-source data fusion, real-time data is analyzed through large-scale data analysis and an LSTM model, future pain states and risks of cancer patients are predicted, personalized management suggestions are generated, and the efficiency and effect of home pain management are improved.

The invention belongs to the technical field of medicine preparation, and relates to PLGA gel used as an injectable long-acting local anesthesia medicine as well as application and a preparation method of the PLGA gel. The PLGA gel comprises the PLGA gel which is loaded with superparamagnetic Fe3O4 particles and a small molecule local anesthetic, namely, levobupivacaine (Levobupi). The PLGA hydrogel containing Fe3O4 and levobupivacaine can be used as an injectable long-acting local anesthesia medicine, and the hydrogel can be changed from liquid to solid after being injected into a living body, so that the release efficiency of the medicine is slowed down, and the local action time of the hydrogel is prolonged. In addition, the hydrogel can undergo a phase change from a solid state to a liquid state under magnetocaloric therapy (MHT), increase pore diameter, promote release of levobupivacaine, and provide enhanced pain relief in vivo. Compared with the prior art, the invention has the beneficial effects of simple synthesis and easy industrialization. The drug release rate is adjusted through the phase change of the hydrogel, super-long-acting analgesia is realized, and the analgesia time is gt; 20 days. The gel can be loaded with various local anesthesia drugs such as L-bupivacaine, and pain management can be carried out on various pain scenes clinically.

The invention discloses an AI-based personalized pain management system and method, and the system comprises a multi-dimensional data collection module which is used for collecting multi-dimensional monitoring data including user physiological state data, motion data and location information data, and bio-electricity signal sensing data in real time; the pain type identification module is used for performing feature extraction on the physiological state data and the bio-electricity signal sensing data and identifying the pain type and the pain level of the user in combination with basic information of the user; the pain trend prediction module is used for performing time sequence analysis based on the pain type, the pain level and the multi-dimensional monitoring data, and predicting the pain trend of the user in a future preset time period; and the feedback evaluation module is used for outputting a pain management evaluation report of the user according to the pain type, the pain level and the pain trend. According to the invention, accurate monitoring, assessment and intervention of pain can be realized, so that pain management is more intelligent and personalized, and help is provided for improving the life quality of a user.

The invention relates to an intelligent high-voltage pulse electrical stimulation system and a control method, and solves the problems of poor individual suitability, low positioning precision and weak safety in the prior art. The system obtains body surface point cloud through a split scanning module (infrared / TOF), and dynamic mapping of an anatomical structure is achieved in combination with a medical image template library (the error is smaller than 1.2 mm); dynamically adjusting a high-voltage pulse (0-1200V) based on a BMI-impedance model, and adopting an improved KNN algorithm to match a discharge scheme; three-level safety protection is innovated, and dangerous area protection is achieved through impedance sudden change detection, displacement compensation and phase counteracting (electric field attenuation is larger than 99.9%). Clinical verifications show that the positioning precision is + / -0.5 mm, the pain relief rate of obese patients (BMI = 32) is 92%, and the false touch rate is less than 0.01%. Accurate targeting and safe regulation and control are achieved, and the method is suitable for the fields of muscle rehabilitation, pain management and the like.

The invention discloses a pain grade evaluation method and an evaluation system thereof. According to the method and the system, the pain condition of the patient can be comprehensively and accurately evaluated by integrating various evaluation tools. The combined use of e-VAS, EIAS, AIS and PMS not only considers the intensity and physiological influence of pain, but also covers the influence of psychological state and life quality, thereby providing a multi-dimensional pain assessment perspective for medical staff. And meanwhile, by introducing digital and remote monitoring technologies, the convenience and efficiency of pain management are greatly improved. The digital operation of the e-VAS is simple and visual, the patient can easily complete self-evaluation, and the remote monitoring system allows the patient to continue to participate in pain management after being discharged from the hospital and keep continuous communication with a medical team. The continuity and convenience not only improve the treatment compliance of the patient, but also enable the medical staff to adjust the treatment scheme in time so as to cope with the dynamic change of the pain, thereby achieving the effects of optimizing the patient experience and enhancing the treatment effect.

The invention provides a pain expected deviation evaluation system and method, and relates to the technical field of pain management and electrophysiological signal processing. An experiment normal form containing three clue types of'determined high pain ', 'determined low pain' and'uncertainty 'is established. In the aspect of subjective pain expectation deviation evaluation, the AUC of a determined high pain scene and the AUC of an uncertain scene and the AUC of a determined low pain scene and the AUC of an uncertain scene are compared respectively, and the AUC difference between the two scenes is analyzed. In the electrophysiological data analysis, based on the decoding accuracy of the signal detection theory, the decoding accuracy of the situations of'uncertainty ', 'determined high pain' and'determined low pain 'is compared, the difference is quantified and calculated, and an objective pain expected deviation index is obtained. The subjective pain expected deviation is combined with the objective electrophysiological signal for the first time, the limitation that the traditional method only depends on subjective evaluation is overcome, subjective prejudice and individual difference interference are avoided, and the comprehensiveness, reliability and repeatability of pain expected deviation evaluation are improved.

The invention discloses an intelligent drug delivery pain management bracelet, and relates to the fields of wearable equipment, transdermal drug delivery and biological signal processing. The bracelet is integrated with a multi-mode biosensor which comprises a temperature sensor, a pressure sensor, a heart rate sensor, a blood oxygen sensor and a skin electric response sensor, and physiological data related to pain can be collected in real time. Through an embedded microcontroller and a machine learning algorithm, a pain intensity evaluation model is constructed, and real-time evaluation of the pain state of a patient is realized. Based on the pain intensity and the physiological state of a patient, a drug release strategy is dynamically adjusted through an intelligent algorithm, and drugs are released painlessly and accurately through a micro-needle transdermal drug delivery technology, so that the patient obtains the optimal treatment effect. And the functions of data storage, historical analysis and remote doctor monitoring can be expanded. The hand ring is convenient to operate, comfortable to use and suitable for various pain management scenes such as chronic pain and postoperative pain, and the personalized level of pain treatment and patient compliance are remarkably improved.

The invention discloses a temperature-adjustable analgesic method for cooling dorsal root ganglion, which is characterized in that according to the characteristics of complicated anatomical structure and extremely small size of the dorsal root ganglion, a miniature thermoelectric refrigeration device which is small in size, capable of being embedded in vivo, high in biocompatibility, wide in refrigeration range and capable of being stably fixed is designed. Meanwhile, the device has the characteristics of capability of quantitatively regulating and controlling the refrigerating temperature, no external refrigerating cycle, low cost and the like; besides, under the condition that the nerve structure is not damaged, the device can effectively slow down inherent nerve activity and inhibit abnormal discharge of neurons, so that the device is used for gently cooling and regulating DRG to relieve chronic pain. The invention not only opens up a brand-new treatment way for chronic pain patients who have been addicted or tolerated to drugs, but also is expected to be expanded to the field of pain management of animals such as pets and racing horses.

An implantable device for controllably delivering neural stimuli, comprising a stimulus source configured to provide neural stimuli to be delivered via one or more stimulus electrodes to a neural pathway of a patient; measurement circuitry configured to capture signal windows from signals sensed on the neural pathway by one or more measurement electrodes subsequent to respective neural stimuli; and a control unit. The control unit is configured to: control the stimulus source to provide a direct current (DC) pulse according to a stimulus intensity parameter; control the stimulus source to provide a titration pulse in order to evoke a neural response from the neural pathway; measure an intensity of an evoked neural response in a captured signal window subsequent to the titration pulse; and adjust, using a feedback controller, the stimulus intensity parameter so as to maintain the measured intensity at or near a target value.

The invention relates to a gouty arthritis patient pain management method and system based on an MDT management mode, and the method comprises the steps: automatically collecting the multivariate clinical data of a patient through integrating an existing information system of a hospital, carrying out the cleaning, standardization and structural processing through a special data preprocessing module, and carrying out the cleaning, standardization and structural processing. A machine learning prediction model trained by historical data is utilized to automatically generate a personalized MDT nursing plan, tasks are intelligently distributed to corresponding team members by means of a workflow engine, the execution condition is continuously monitored in the intervention process, and the nursing scheme is dynamically adjusted based on clinical data and prediction results which are periodically updated. And a complete'monitoring-prediction-intervention-reevaluation 'closed-loop management process is formed. The problems that a traditional MDT mode depends on manpower, efficiency is low, and decision-making lacks data support are effectively solved, and the accuracy, the collaboration and the continuity of pain management and wound surface nursing of the gouty calculus combined infection patient are improved.

The invention discloses a nerve postoperative pain monitoring and feedback method and system, and relates to the technical field of medical information, and the method comprises the following components: a data acquisition step, a digital twin model construction step, a pain simulation step, a visualization and interaction step and a feedback and scheme making step. By constructing the digital twinborn model of the postoperative body of the patient, the postoperative physiological structure, the nerve function state and the pain-related physiological mechanism of the patient can be accurately simulated, and based on the model, a doctor can simulate different treatment schemes and pain responses under external stimulation, so that a more personalized pain management scheme is formulated, and the pain management efficiency is improved. According to the personalized management mode, the accuracy of pain management is remarkably improved, postoperative pain of the patient can be relieved more effectively, and the treatment experience and satisfaction degree of the patient are improved.

Systems and methods are provided for patient monitoring and / or treatment. The system may include one or more sensors configured to measure electroencephalogram (EEG) and skin electrical signals of a patient subjected to at least one anesthetic and at least one analgesic during a surgical medical procedure. The system may also include a processor operably coupled to the one or more sensors. The processor is configured to receive the electroencephalogram and skin electrical signals, and to generate a report indicative of a real-time injury sensory status of the patient during a surgical medical procedure when the patient is subjected to at least one anesthetic using the electroencephalogram or skin electrical signals, and to generate a pain management plan based on a desired post-surgical outcome.

The invention discloses a postoperative pain degree sensor and an ovum extraction operation pain monitoring system, and belongs to the field of postoperative health monitoring and intelligent nursing equipment. The sensor comprises a flexible substrate, and a skin electric response sensing unit, a temperature sensing unit, a myoelectricity sensing unit, a micro-pressure sensing unit, a signal processing circuit and a wireless communication module which are integrated on the flexible substrate, the monitoring system comprises an edge processing module, a pain index evaluation module, an interaction terminal and a data recording module. The system evaluates the postoperative pain level based on the multi-channel physiological signals, real-time quantification and alarm prompt of the pain state are achieved, and the postoperative nursing response efficiency is improved. The scheme is suitable for assisting pain management after reproductive ovum extraction, and has the advantages of high sensitivity, low delay, structural flexibility and system closed loop.

Medical devices, systems, and methods for pain management and other applications may apply cooling with at least one probe inserted through an exposed skin surface of skin. The cooling may remodel one or more target tissues so as to effect a desired change in composition of the target tissue and / or a change in its behavior, often to interfere with transmission of pain signals along sensory nerves. Alternative embodiments may interfere with the function of motor nerves, the function of contractile muscles, and / or some other tissue included in the contractile function chain so as to inhibit muscle contraction and thereby alleviate associated pain. In some embodiments, other sources of pain such as components of the spine (optionally including herniated disks) may be treated.

The invention relates to the technical field of medical data management, and particularly discloses an acute postoperative pain assessment and management decision-making system based on a patient report result, which is used for solving multiple challenges facing postoperative acute pain management, including subjectivity of a traditional assessment method, lack of personalized treatment, insufficient intervention coordination and lack of real-time monitoring ability. The problems that an existing decision support system is insufficient in intelligence and complex in user interaction experience, so that the efficiency of medical staff is low, and finally rehabilitation and life quality of a patient are affected are solved, and the system comprises a patient pain data collection module, a data analysis and processing module, a decision support module and a user interface. The data analysis processing module analyzes the collected data by adopting a machine learning algorithm so as to evaluate the severity of the pain; according to the invention, individualized pain assessment is realized through a machine learning algorithm, patient pain data is analyzed in real time, a management scheme is rapidly adjusted, patient satisfaction is improved, a pain management scheme is optimized, and manual intervention is reduced.

The invention provides a child burn dressing change pain management method and system based on tactile and auditory stimulation. The method comprises the following steps: constructing a personalized pain management model, and collecting multi-modal data of a patient; and extracting fusion multi-modal data features, and generating tactile and auditory stimulation parameters by using a reinforcement learning model after obtaining fusion features. And the parameters are applied to touch and hearing devices, and personalized stimulation is synchronously applied during dressing change. Cooperative regulation and control of tactile and auditory stimulation are realized by means of multi-modal data fusion and reinforcement learning models, that is, time domain, emotion and electroencephalogram features are deeply fused to generate fusion features, and tactile and auditory parameter joint action vectors are generated through an Actor network based on the fusion features. Through multi-mode information interaction, the tactile stimulation inhibits wound pain signal conduction, the auditory stimulation adjusts amygdaloid nucleus emotional response, the analgesia efficiency is improved through cooperation of the tactile stimulation and the auditory stimulation, and the tolerance threshold value of children to single stimulation is reduced.

According to the intelligent green light phototherapy glasses and the intelligent adaptation method thereof, a narrow-band green light LED light source with the central wavelength being 530 + / -5 nm is adopted, and individualized pain management is achieved in combination with heart rate variability, electrodermal response and pupil dynamic monitoring. A multi-source sensor and a micro control panel are arranged in the glasses, physiological data are collected in real time, the illumination intensity, frequency and irradiation mode are dynamically adjusted through an artificial intelligence algorithm, and a closed-loop phototherapy control system is constructed. The device supports Bluetooth / Wi-Fi connection, interacts with a mobile terminal APP, and realizes data recording, curative effect evaluation and remote monitoring. The system has multiple safety mechanisms such as constant-current driving, temperature feedback, over-illumination protection and posture detection, and long-term wearing safety is ensured. Through the regulation effect of green light on pain neural pathways, a safe, portable and intelligent chronic pain non-drug treatment means is provided under the condition that daily activities are not interfered, and high compliance and a remarkable analgesic effect are achieved.

The invention provides a nano-drug carrier and a drug release system, the nano-drug carrier comprises a drug loading core and a responsive shell arranged outside the drug loading core, and the drug loading core is loaded with a nano-drug; the surface of the responsive shell is modified with a targeting ligand, and the targeting ligand can specifically target pain-related cells or tissues. According to the nano-drug carrier and the drug release system provided by the invention, precise long-acting treatment of chronic pain is realized through combination of an environment-responsive carrier and an active targeting technology. The technology can significantly improve local accumulation of the medicine and reduce systemic toxicity, and is suitable for management of intractable pains such as neuropathic pains and osteoarthritis.

The invention provides a real-time pain monitoring and feedback system, which belongs to the technical field of medical equipment and comprises a pain biomarker monitoring module, an external environment monitoring module, a data transmission module, a data processing and analysis module, a feedback module, a medical professional support module, an intelligent reminding module and a continuous learning and optimization module. The real-time pain monitoring and feedback system provided by the invention provides a more efficient, personalized and dynamic pain management method for patients and medical staff. Compared with a traditional method, the system not only improves the effect of pain management, but also improves the overall medical experience, and provides a basis for future medical research and technical development.

The invention relates to the field of pain management and rehabilitation treatment, in particular to a painless ward construction method and system based on big data, and aims to improve pain management efficiency and fracture patient rehabilitation quality through big data and artificial intelligence means. By integrating various information technologies, an artificial intelligence algorithm and a big data analysis technology, the functions of encrypted storage of fracture patient information, multi-dimensional pain assessment, personalized analgesia scheme formulation, real-time monitoring and early warning, comprehensive assessment of recovery conditions and the like are realized. Meanwhile, the method also considers the prediction of the pain trend and the intelligent generation of the training plan, solves the problems that the making of most rehabilitation training plans at present still depends on the experience and judgment of professionals and is lack of scientificity and systematicness, and provides a brand new solution for pain management and rehabilitation treatment based on big data.

According to the clinical pain management decision support system and the training method based on the severe games, the pain management process is standardized by using the functions of warning, decision making, data storage and the like of the clinical pain management decision support system, a standardized pain nursing document is automatically generated, and timeliness and safety of pain management of a patient are guaranteed. In addition, a relaxed game training mode is adopted, so that clinical medical staff can relieve pain for the patient in a real and safe environment, more learning and practicing opportunities can be provided for the clinical medical staff, the effect better than that of a traditional learning mode is obtained, and the patient cannot be hurt; meanwhile, by means of emerging technical means, skills are trained, professional knowledge is learned or professional guidance is sought anytime and anywhere, the availability of medical professional learning resources is improved, clinical medical staff are not limited by time and space, and the time and economic cost for mastering professional skills is reduced.

Systems, methods, and computer-readable media for and improvement rehabilitation infrastructure. For example, a method may include using, inter alia, objective data to optimize treatment plans to support user progression during rehabilitation for the purpose of assisting in determining AI-driven interventions by using machine learning to generate at least one data signature. In some embodiments, a method may perform AI-driven interventions via optimization of treatment plans in order to support user progression during rehabilitation by performing, based on data signatures related to medically-associated events, selective data injection. Some other embodiments use evidence-based research to enable AI and machine learning to select and modify treatment plans in real-time at scale. Further, the improved rehabilitation infrastructure enables, via pain management, user compliance with treatment plans.