95 results about "Care protocols" patented technology

The invention discloses an integrated management system and method for postoperative care of orthopedic patients, and relates to the technical field of medical treatment. Comprising a bone mineral density dynamic monitoring value, six-dimensional mechanical parameters of a joint movement track, emotion spectrum characteristics in voice interaction, microenvironment temperature and humidity changes collected by wearable equipment and skin surface pressure distribution; inputting the recovery data into a multi-modal decision-making model based on orthopedic biomechanics improvement, and generating a nursing scheme including a skeleton stress safety interval, a virtual rehabilitation scene dynamic parameter and an interdisciplinary intervention priority; the scheme parameters are dynamically optimized through a layered reinforcement learning framework special for the orthopedics department, and the deformation logic of the 3D printing brace and the correction strategy of the nursing robot are synchronously controlled; based on the postoperative complication space-time prediction map, a multidisciplinary collaborative response instruction strictly matched with the rehabilitation stage of the patient is triggered.

The invention relates to the technical field of traditional Chinese medicine nursing or health improvement, in particular to a method for generating a traditional Chinese medicine personalized nursing scheme for preventive treatment of diseases. The method comprises the following steps: firstly, screening out all initial reference individuals of a current individual based on a similar condition between corresponding physique information of the individuals; further determining all concerned symptoms and corresponding concerned coefficients of the current individual according to the universality and change condition of each symptom of the current individual in the initial reference individual; screening out all reference individuals according to the attention coefficient of the common attention symptom of the current individual and each initial reference individual; and finally, generating a personalized nursing scheme of the current individual based on the nursing schemes of all the reference individuals. According to the method and the device, the reference individuals capable of providing similar nursing references are accurately screened out from the historical disease prevention individuals based on the similar physical conditions of the individuals and the similar conditions of the symptoms which are mainly concerned during nursing, so that the generation effect of the personalized scheme of the current individual is improved.

The invention discloses a rehabilitation nursing intelligent monitoring method and system based on image acquisition, and belongs to the technical field of rehabilitation nursing intelligent monitoring, and the method comprises the steps: collecting limb image data of a patient and a synchronous pain response value to generate a monitoring model; processing the current image data based on a monitoring model to evaluate and output a pain risk value; analyzing the fluctuation trend of a pain response curve formed based on the pain risk value to generate and output a nursing scheme; collecting subsequent image data in the process of executing the nursing scheme, monitoring a limb recovery state and outputting recovery feedback information to adjust the nursing scheme; according to the method, continuous assessment of pain risks is achieved by establishing quantitative association of visual features and pain responses, the nursing scheme is generated based on dynamic fluctuation trend analysis, a closed-loop management process is formed by recovering feedback information, and the efficiency and safety of rehabilitation nursing are improved.

The invention relates to a traditional Chinese medicine nursing data intelligent management method and system, and the method comprises the steps: collecting traditional Chinese medicine nursing data, and converting the traditional Chinese medicine nursing data into structured semantic data and a standardized sign data set; constructing a dynamic knowledge graph according to the structured semantic data and the standardized physical sign data set; constructing a syndrome evolution model based on the dynamic knowledge graph, and generating an initial nursing scheme; conflict detection and intervention effect prediction are carried out on the initial nursing scheme, and a self-adaptive strategy feedback model is formed based on evaluation data after nursing implementation; generating nursing decision suggestions by utilizing case reasoning according to the self-adaptive strategy feedback model and the dynamic knowledge graph; in the execution process of the steps, federal learning is adopted to realize distributed processing of data, and a differential privacy mechanism is combined to guarantee dynamic desensitization and privacy security of the traditional Chinese medicine nursing data. The intelligent effect of traditional Chinese medicine data management can be improved.

The invention discloses a hypertension nursing system based on a remote AI monitoring technology, and particularly relates to the technical field of telemedicine, the hypertension nursing system comprises a data acquisition module, a data fusion module, a risk assessment module, a dynamic intervention module and a cloud management module, and physiological data, behavior data and environmental data are acquired through heterogeneous sensors; the method comprises the following steps: preprocessing the data, transmitting the preprocessed data to a data fusion module and a cloud management module, carrying out alignment and feature extraction on heterogeneous data from different sources to obtain comprehensive risk assessment features, carrying out blood pressure fluctuation risk prediction through an LSTM model, aggregating multi-center cases through cloud federated learning, and generating personalized long-term risk scores. Performing risk level judgment according to the long-term health risk score of the patient, outputting a customized nursing scheme in combination with historical data of the patient, performing privacy protection and storage on the collected data, supporting consultation between the patient and a doctor, automatically generating a dialogue abstract, and updating the dialogue abstract to an electronic health file.

The invention relates to the technical field of intelligent medical care, and discloses a drainage port nursing recommendation method and system for a patient with bile leakage. The system comprises a data acquisition module used for acquiring bile drainage data and state data of skin around a drainage port in real time; the cloud decision module is internally provided with a nursing scheme recommendation model associated with a bile leakage nursing knowledge graph, and is used for carrying out fusion analysis on the multi-modal data and generating a personalized nursing plan; the local execution terminal is used for receiving and displaying the nursing plan and guiding nursing personnel to execute and record actual nursing operation data; and the closed-loop feedback module is used for returning the actual execution data and the post-nursing state data so as to optimize the nursing scheme recommendation model and the bile leakage nursing knowledge graph. The technical problems that in traditional nursing, evaluation is subjective, decision-making depends on experience, execution is not standard, and knowledge is difficult to accumulate are solved, and standardization, individuation and continuous self-optimization of bile leakage drainage opening nursing are achieved.

The invention provides a multi-mode intelligent analysis internal fistula postoperative rehabilitation nursing method and system, and belongs to the technical field of medical nursing and artificial intelligence crossing. The application aims to solve the problems of single monitoring dimension, subjective risk judgment and static homogenization of the nursing scheme in the existing internal arteriovenous fistula postoperative nursing. The method comprises the following steps: acquiring multi-modal data related to a wound state and a hemodynamic state of an internal arteriovenous fistula; processing the multi-modal data to generate standardized feature data which can be analyzed; generating a risk assessment result about the health condition of the internal arteriovenous fistula; and a preset nursing scheme is dynamically adjusted based on a risk assessment result. According to the method and the device, multi-modal data are fused and an intelligent algorithm is used for collaborative analysis, so that the accuracy and early stage of risk identification can be realized, the individuation and high efficiency of a nursing scheme are realized, and the nursing quality is improved.

The invention discloses a neurosurgery postoperative care system and method based on AI, and particularly relates to the technical field of medical care. According to the method, the basic parameter set and the characteristic parameter set of the patient are constructed, the basic parameter set is encoded, nursing cases of the same type of patients in the nursing database are accurately matched, and the adaptive scheme is screened; further calculating an effect-like comprehensive coefficient, namely preferentially selecting a scheme which is highly matched with the individual characteristics of the current patient and has an excellent effect as a preliminary scheme by combining the deviation degree of the physiological indexes of the patient and the case, the complication score of the case, the recovery efficiency, the rehabilitation score and the like, and sending the preliminary scheme to medical personnel to secondarily edit the preliminary scheme; finally, a personalized nursing scheme completely fitting the individual condition of the patient is formed, and the problems that in the prior art, most of traditional nursing schemes are formulated by medical staff based on a universal nursing guide, the formulating efficiency is greatly reduced, and the nursing effect cannot be guaranteed are solved.

The present application relates to the technical field of medical auxiliary decision-making, in particular to a system and method for generating individualized nursing plans based on comprehensive assessment of the elderly. In the present application, by collecting multi-class physiological time series data of the elderly in a specific life scene and extracting the periodic fluctuation characteristics, the subtle change trend of the daily rhythm can be accurately identified. Further, by comparing the rhythm deviation degree and persistence in different time periods, the dynamic influence of the progress of chronic diseases on the physiological state is revealed. In combination with the trend change rate and its directionality, the interaction mode between physiological changes and chronic disease indicators is depicted in continuous observation, thereby realizing the measurement of the coupling adaptation degree between individual physiological response and chronic disease condition. Through normalized amplitude difference and matching interval screening, the individual physical ability and chronic disease adaptation label are accurately assigned. Then, the adaptation priority of each intervention element in the individual is comprehensively measured in a multi-dimensional scoring manner, and a nursing intervention combination for a specific population state is constructed.

The application discloses a traditional Chinese medicine chronic disease family nursing method based on a cloud platform, relates to the technical field of intelligent health services, and comprises the following steps: performing deep fusion and intelligent analysis on a family nursing data package by constructing a virtual patient model, generating personalized data of patient physiological indexes and traditional Chinese medicine syndrome states, generating a customized family nursing candidate scheme based on the personalized data of the patient physiological indexes and the traditional Chinese medicine syndrome states, combining behavior prediction analysis, intelligently evaluating and real-time feeding back, and forming a traditional Chinese medicine chronic disease family nursing management scheme according to a nursing scheme set, combining physiological index and symptom data analysis correction. The application can accurately reflect the current health state of a patient by collecting physiological data and traditional Chinese medicine syndrome information of the patient, combining family environment data, constructing a dynamically updated virtual patient model, and realizing the personalization and dynamic adaptation of a nursing scheme.

The invention provides an individualized nursing scheme intelligent generation method and system based on big data, and relates to the technical field of individualized nursing scheme intelligent generation. Multi-source health data of a target nursing object is collected, feature coding is carried out on the multi-source health data, and a structured health file is generated; performing similar mapping on the health state of the target nursing object according to the diagnosis mapping table and the structured health file to obtain a health state set, and determining an individualized state index according to the health state set; state difference detection is carried out according to the real-time monitoring data and the structured health record, a state change trend vector is generated, fusion analysis is carried out according to the state change trend vector and the individualized state index, and a dynamic health intervention index is generated; and generating an individualized nursing scheme of the target nursing object according to the dynamic health intervention index. According to the invention, the dynamic adaptation of the nursing scheme and the real-time health state of the patient can be realized, and the accuracy and timeliness of the nursing scheme are improved.

The application discloses a kind of free skin flap postoperative nursing scheme evaluation and early warning method based on multi-modal monitoring data fusion, it is related to intelligent medical care technical field, for solving the problem that existing monitoring cannot distinguish vascular pathological crisis and nursing environment interference.First, a multi-dimensional time-varying state matrix containing physiological drive and nursing environment characteristics is constructed, realizing the time sequence alignment of heterogeneous data;Subsequently, the pressure-flow conduction characteristics are analyzed, and the blood flow conduction efficiency index reflecting the inherent patency of blood vessels is extracted;At the same time, a physical gain mapping is established based on nursing parameters, and the theoretical target perfusion trajectory under the current nursing state is deduced;Finally, the dynamic residual vector is calculated and combined with the conduction efficiency index for joint determination, accurately identifying vascular structural occlusion and functional inhibition of nursing program, achieving accurate tracing of postoperative crisis and dynamic evaluation of nursing program.

The invention discloses an illness state nursing method based on patient body data, and relates to the technical field of medical nursing, and the method comprises the steps: obtaining the physiological data of a patient in real time through a body data collection device, and carrying out the preprocessing and feature extraction of the collected physiological data; evaluating the preprocessed physiological data of the patient by training a deep learning model, and carrying out illness state classification on obtained illness state results; based on the illness state assessment result and illness state classification, analyzing nursing requirements; and after a nursing demand is determined, a personalized nursing scheme is generated. By introducing the deep learning model, performing preprocessing and feature extraction on the acquired physiological data, and dynamically generating the personalized nursing scheme based on the illness state classification result, the illness state of the patient can be evaluated more accurately, and the nursing plan is adjusted in time according to real-time data change, so that the nursing accuracy and personalization are improved, and the nursing efficiency is improved. The obvious advantages are realized.

The embodiment of the invention provides a hospitalized patient falling risk assessment method, device and equipment and a storage medium, the method is applied to the technical field of hospitalized patient management, and the method comprises the steps: obtaining multi-dimensional assessment information corresponding to a target patient; the multi-dimensional evaluation information comprises evaluation information corresponding to basic daily life activity information, evaluation information corresponding to fall risk evaluation scale information and evaluation information corresponding to a medical advice medication list; inputting the multi-dimensional assessment information into a risk assessment model for risk prediction, and obtaining a target risk prediction result; generating a target nursing scheme based on the target risk prediction result and the multi-dimensional evaluation information; and managing the target patient based on the target nursing scheme. According to the embodiment of the invention, the falling risk assessment efficiency of the inpatient can be improved, and the falling occurrence rate of the inpatient is reduced.

A monitoring system for care protocols, comprising sensors connected to electronic devices to input data from a patient, where sensors measure critical values from a patient; an interface for receiving data and allowing users to write and change process control in real time; a processor connected to the interface to receive input parameters, wherein the processor calculates output values based on the input parameters compared to the critical value to determine whether the output values are outside acceptable range; means for setting critical values, ranges of critical value, and alarm points when the critical values are outside of the range; where the interface receives critical patient parameters and the interface includes a manual input and a machine input from one or more sensors; and wherein the system calculates and monitors critical steps or values for a patient and enables the output values for monitoring or display, in real time.

The invention relates to the technical field of nursing service and artificial intelligence, in particular to a nursing scheme recommendation method based on customer portrait data analysis. The method comprises the following steps: S1, collecting basic and historical nursing information of a user; s2, constructing a multi-layer label graph and generating a user portrait; s3, generating a candidate nursing path set based on the semantic path; s4, extracting nursing schemes adopted by the users with the similar portraits; s5, constructing a reward function fusing the score and the structure information; s6, obtaining user feedback and dynamically adjusting the weight of the path structure; and S7, outputting a recommendation scheme with the highest matching degree based on an optimization result. Structured and unstructured information is fused to construct a semantic graph, a reward function is constructed in combination with similar user schemes and multi-dimensional feedback, a path structure is dynamically optimized, and the matching performance and the adaptivity of recommendation schemes are improved; and through score sorting and environmental interference elimination, the intelligent level of nursing recommendation and the resource adaptation efficiency are improved, and the application range is widened.

The invention relates to an infectious tophus ulcer wound nursing scheme assessment method and system, and the method comprises the steps: collecting the standardized electronic medical record data of a patient through a medical information system, including demostatistics, wound characteristics, laboratory inspection index sequences and nursing records; after structured processing, timestamp unification and missing value filling are conducted on the data, the data are input into a pre-trained deep learning model, expected wound healing probabilities, predicted healing time and complication risk scores corresponding to different nursing schemes are output, then a comprehensive assessment report is generated, the report is stored in a database, and a visual query interface is provided. And meanwhile, collecting actual nursing result data for continuous optimization and updating of the model. According to the invention, quantitative evaluation and prediction of the nursing scheme are realized, clinical decision making is effectively assisted, and the accuracy of nursing management and the resource utilization efficiency are improved.

The invention relates to the technical field of medical nursing, and discloses a patient wound intelligent identification method for surgical nursing. According to the method, an image sequence including a visible light wave band, an infrared wave band and an ultraviolet wave band is obtained through image acquisition equipment, and various information of a wound can be comprehensively covered; performing multi-scale feature fusion processing on the data, extracting texture, color and depth features, and constructing a wound feature description matrix; performing semantic segmentation by using a dynamic graph convolutional network based on the matrix to generate a semantic mask; inputting the mask into a pre-trained wound state evaluation model, analyzing a dynamic change trend, and outputting a wound healing stage and an abnormal index; and finally, generating a wound nursing scheme containing dressing change frequency, dressing types and antibiotic use guidance according to a result. The wound state can be comprehensively and accurately identified, a scientific nursing scheme is provided, and the surgical nursing quality and efficiency are improved.

The invention discloses an optical fiber sensing cardiovascular postoperative wound intelligent monitoring and nursing system, and relates to the technical field of medical monitoring and nursing, and the system comprises an optical fiber sensing array module which is customized for different cardiovascular operations and comprises distributed and point type optical fibers; the multi-parameter data acquisition module is used for receiving a signal by using a two-channel demodulator, performing high-frequency data acquisition after interference removal, and synchronizing patient information and vital signs; the wound state analysis module is used for adjusting a threshold value according to the individual condition of the patient and judging the wound state by using an improved support vector machine; the intelligent nursing suggestion module generates a nursing scheme according to the state; according to the user interaction module, the medical care terminal displays data and states, and the patient terminal has voice reminding and AR guidance; and the data storage and update module adopts a three-level storage architecture and periodically updates an algorithm and a nursing scheme library. According to the system, the wound monitoring accuracy and continuity are improved, the medical care management efficiency is optimized, the autonomous nursing ability of a patient is enhanced, and the risk of postoperative wound complications is reduced.

The application discloses an orthopedic nursing scheme intelligent question and answer system and method, relates to the technical field of natural language processing, and comprises the following steps: correcting transcription errors and colloquial expressions in orthopedic nursing consultation sentences, marking nursing semantic elements and missing items, and generating a standard question element set; comparing and clustering semantic representations to position the standard question element set in a standard question category, screening complementary nursing evidence based on maximum marginal correlation, and generating an evidence routing group; combining the missing items in the standard question element set, using natural language reasoning to determine the semantic relationship between nursing suggestions and evidence fragments in the evidence routing group, and generating a reply verification set; using dependency syntax analysis and knowledge graph path verification to analyze the nursing semantic roles in the reply verification set, resolving nursing contraindication conflicts, and generating a risk-corrected reply set. The application verifies and analyzes nursing objects, nursing behaviors, nursing conditions and semantic polarity, and improves the accuracy, interpretability and safety of orthopedic nursing intelligent question and answer.

The application discloses an AI-based neurosurgery postoperative nursing system and method, and particularly relates to the technical field of medical care; the application is characterized in that a patient basic parameter set and a characteristic parameter set are constructed, the basic parameter set is coded, nursing cases of the same type of patients in a nursing database are accurately matched, and an adaptive scheme is screened; a comprehensive coefficient is further calculated, i.e., the deviation degree of physiological indexes of the patient and the case, the complication score of the case, the recovery efficiency, the rehabilitation score, etc., a scheme that is highly adaptive to the individual characteristics of the current patient and has an optimal effect is preferentially selected as a preliminary scheme, and the preliminary scheme is sent to medical staff for secondary editing, so that a personalized nursing scheme that completely fits the individual condition of the patient is finally formed, and the problem that, in the prior art, a traditional nursing scheme is mostly formulated by medical staff based on a general nursing guideline, the formulation efficiency is greatly reduced, and the nursing effect cannot be guaranteed is solved.

The present application belongs to the technical field of neonatal intensive care, and specifically relates to a PI monitoring system and method applied to neonatal intensive care. The present application can accurately assess PI risk by real-time collection of key physiological data of newborns, issue early warnings before injury formation, improve monitoring efficiency, ensure the accuracy and comprehensiveness of monitoring data by using pressure detection point offset compensation and body surface temperature and humidity compensation, provide customized risk assessment and nursing plans for different individual differences of newborns, construct a comprehensive PI risk assessment model by combining multiple key factors such as pressure distribution, offset information and temperature and humidity, improve the reliability and scientificity of risk prediction, provide timely nursing strategies and optimize intervention plans, effectively reduce the incidence of PI in newborns, and improve medical quality and the health prognosis of newborns.

The invention discloses a personalized nursing scheme generation system for hepatitis patients. The personalized nursing scheme generation system comprises a signal acquisition and processing unit, a dynamic decision-making unit and a feedback optimization unit, the signal acquisition and processing unit adopts a flexible wearable hepatic region monitoring patch and a bio-impedance spectroscopy sensor array, acquires data of electrophysiological signals and metabolic characteristics of a patient in real time, and eliminates medical environmental noise from the data; the dynamic decision-making unit is used for cooperatively transmitting data by integrating a fractal antenna array and a medical special LoRaWAN protocol, establishing a three-layer cascade decision-making model, integrating patient medical history, gene detection data and clinical guidelines, and generating a personalized nursing scheme; the feedback optimization unit carries out dynamic optimization processing on the personalized nursing scheme; the multi-modal data of electrophysiological signals, metabolic characteristics, medical history and gene detection are fused to generate a highly personalized nursing scheme, so that patient requirements can be accurately matched, and the accuracy and pertinence of the nursing scheme are improved.

The invention relates to the technical field of intelligent nursing, and discloses a disease intelligent nursing auxiliary system based on evidence-based data, comprising: an evidence-based knowledge base module integrating multi-source evidence-based data to form a specialized knowledge graph; the model training optimization module carries out base model field fine tuning and multi-algorithm fusion according to the multi-source evidence-based data so as to carry out intelligent decision-making assistance and generate a personalized nursing scheme; the multi-scene intelligent interaction module carries out knowledge pushing, consultation and question answering through multi-terminal interaction; the full-period nursing management module performs staged nursing execution and dynamically adjusts a nursing plan; the quality control early warning module carries out risk early warning, medication verification and flow quality control; and the multi-dimensional effect evaluation module generates a multi-level evaluation report, and drives update of the evidence-based knowledge base and algorithm iteration. According to the invention, an accurate and adaptive whole-cycle nursing scheme and standardized guidance are provided, the nursing risk is reduced by means of real-time quality control early warning, and the treatment compliance and medical experience of a patient are improved.

An object of the system according to the embodiment is to analyze customer data, evaluate frailty risk, and propose individually optimized care.SOLUTION: A system includes a collection part, an analysis part, a proposal part, a data combination part, and a data management part. The collection unit collects customer data. The analysis unit analyzes the data collected by the collection unit and evaluates a frailty risk. The proposal unit proposes individually-optimized care based on the evaluation result obtained by the analysis unit. The data combiner combines the anonymized data of the enterprise and the platform. The data management unit manages the customer data in an environment where privacy protection is emphasized.SELECTED DRAWING: Figure 1

The invention provides a multifunctional digestive endoscope nursing scheme generation method and system, and belongs to the technical field of intelligent medical nursing and human-computer interaction. The method comprises the steps that after a target patient is determined, a pre-examination guidance scheme is determined based on first feedback information of the target patient, and the target patient is a patient needing digestive endoscopy; acquiring second feedback information of the target patient on the pre-examination guidance scheme, and determining an in-examination intervention scheme based on the second feedback information; and after the digestive endoscopy is finished, sending a post-examination nursing scheme to the target patient. The system comprises a pre-examination guidance scheme generation subsystem, an in-examination intervention scheme generation subsystem, a post-examination nursing scheme generation subsystem and a physical instrument used in the digestive endoscopy process, and is used for realizing the method. According to the technical scheme, the bad emotion of the patient can be eliminated, the treatment compliance is improved, and the examination is smoother, so that the accuracy of the examination result is ensured, and the improvement of the clinical treatment efficiency is ensured.

The invention discloses a stoma patient nursing service evaluation adjusting system, which belongs to the technical field of stoma nursing and comprises a data acquisition module, a nursing analysis module and a psychological evaluation module. The data acquisition module is used for performing data acquisition on a stoma of a patient to obtain stoma acquisition data; the nursing analysis module is used for analyzing the stoma collection data of the patient and generating a nursing scheme; carrying out releasability description on the nursing scheme, obtaining scheme supplement data of the nursing scheme, and displaying the nursing scheme and the scheme supplement data to the patient; the psychological assessment module is used for performing psychological assessment on the patient, identifying patient information and collecting supplementary psychological data according to the patient information; performing psychological assessment on the patient according to the basic psychological assessment mode to obtain a psychological assessment result; and calibrating the psychological assessment result according to the supplementary psychological data to obtain a calibration result, and performing corresponding processing according to the calibration result.

The invention provides a thyroid tumor postoperative intelligent nursing system based on multi-dimensional health data, and relates to the field of medical data processing, and the system comprises a map building module which is used for building a thyroid tumor postoperative complication map; the information acquisition module is used for acquiring multi-dimensional health data of the patient; the scheme generation module is used for determining a thyroid tumor postoperative nursing scheme according to the multi-dimensional health data of the patient and the thyroid tumor postoperative complication atlas; the state monitoring module is used for collecting thyroid tumor postoperative real-time state information of the patient according to the thyroid tumor postoperative nursing scheme of the patient; the nursing prompting module is used for carrying out nursing risk prompting according to the thyroid tumor postoperative real-time state information and the thyroid tumor postoperative complication atlas of the patient; the recurrence follow-up visit module is used for obtaining complication monitoring information of the patient and conducting follow-up visit prompting, and the intelligent nursing system has the advantages that personalized intelligent nursing after the thyroid tumor operation is achieved, and the real-time performance and quality of nursing are improved.

The application discloses an obstetrics and gynecology information processing method and system based on the Internet, relates to the technical field of Internet, and integrates feature data set F by extracting and processing data set D, so that the nursing scheme is more personalized and dynamic. By establishing a time series analysis algorithm, the system can calculate the adjustment index C reflecting the fluctuation of the health state of the lying-in woman, match it with the health fluctuation evaluation threshold TZ, generate a nursing control suggestion and a nursing scheme corresponding to the health state of the lying-in woman, and thus avoid the disadvantage that the nursing scheme cannot follow the health change of the lying-in woman in real time. In addition, an effect monitoring mechanism is introduced, the change trend of the adjustment index C is calculated, the effect execution index R is generated, the execution effect of the nursing scheme is continuously evaluated, and the effect of the nursing scheme is ensured to always meet the health needs of the lying-in woman. The nursing plan is matched with the actual recovery state of the lying-in woman, and thus the recovery effect of the lying-in woman is improved.

A wearable treatment and analysis module is provided. The module is positioned on or near a body surface region of interest. The module provides remote access to sensor data, treatment administration, and / or other health care regimens via a network connection with a user device and / or management system.