10 results about "Clinical staff" patented technology

The invention belongs to the technical field of cognitive impairment intervention evaluation, and particularly relates to an evaluation system and method applied to cognitive impairment intervention. According to the method, the cognitive state is evaluated and the training tasks are allocated based on the real data of the user in the natural life scene, so that the one-sidedness of only depending on a laboratory or one-time evaluation is avoided, the training and intervention are closer to the real demand and life situation of the user, and the training efficiency is improved through multi-source data fusion. The influence of single signal noise or accidental fluctuation on judgment is reduced, the robustness and objectivity of evaluation are improved, indexes such as cognitive performance, intervention indexes and deviation degree are numeralized, long-term tracking and transverse comparison of the effects of different intervention measures are facilitated, interpretable quantitative evidences are provided for clinical personnel, and the accuracy of evaluation is improved. Intervention indexes are calculated in real time, intervention measures are automatically adjusted or reselected according to feedback results, and a quick-response closed-loop system is formed, so that the time from problem discovery to effective intervention is shortened, and the intervention conversion rate is increased.

The invention discloses a medical insurance payment-oriented disease type cost benchmark model establishment method and application. The method comprises the steps of collecting medical insurance or hospital historical disease type settlement data; performing standardization processing on historical disease category settlement data, and performing data statistics on charging items according to disease categories; establishing a disease cost benchmark model, and calculating benchmark frequency and benchmark number of the disease by using historical disease settlement data; adjusting the obtained benchmark frequency and benchmark number by using a large language model to obtain recommended benchmark frequency and benchmark number; in combination with diagnosis and treatment specifications of professional clinical personnel and clinical habits of an overall planning area, the recommended benchmark frequency and benchmark number are manually adjusted to obtain disease benchmark values, and the disease benchmark values are added into a disease data set. Through the constructed case cost benchmark model, disease cost standardization management is promoted through benchmark management, diagnosis and treatment behavior standardization and medical insurance payment cost management and control are achieved, and the balance between compliance medical treatment and economical medical treatment is achieved.

The invention discloses an anesthesia induction method and device and an anesthesia machine, and relates to the technical field of anesthesia induction. The anesthesia induction method comprises the following steps: acquiring brain wave signal data, arterial pressure signal data and airway intervention data of a set patient; based on a pre-trained anesthesia state evaluation model and in combination with brain wave signal data and arterial pressure signal data of the set patient, an induction depth response characteristic value of the set patient is analyzed; based on airway intervention data of a set patient and analysis of an induction stability characteristic value of the set patient, induction recommendation processing is performed on the set patient based on an induction depth response characteristic value and the induction stability characteristic value, so that the overall induction state of the patient is dynamically and comprehensively reflected, and a clear evaluation result is provided; clinical personnel are helped to timely judge whether a patient reaches a safe intubation and maintenance level or not, so that the risk of insufficient or excessive induction is reduced, and the safety of anesthesia induction is remarkably improved.

According to the intelligent monitoring system for the general anesthesia resuscitation stage, by arranging the monitoring equipment module, the intelligent audio module, the muscle monitoring module and the monitoring information analysis module, multi-source collection and comprehensive analysis of physiological data and action information of a patient are achieved. When monitoring data meet preset conditions, the system can automatically generate a calling trigger signal, drive an audio module to call speech or drive a muscle monitoring module to perform string stimulation, and judge consciousness recovery of a patient in combination with commanding actions collected by a camera and a grip strength sensor. Through the mode, the system not only improves the intelligent level of monitoring the patient in the resuscitation period, but also can generate a prompt signal in time to remind clinical personnel when the patient has abnormal actions or voice expression is uncomfortable, so that the risk in the resuscitation period is effectively reduced, and the safety and comfort of the patient are improved.

The application provides a kind of affected side spatial stratification activation and multi-modal unilateral spatial neglect (USN) cognitive function evaluation and training intelligent system, aiming at solving the pain points such as low efficiency of evaluation, training homogeneity, effect difficult to transfer in USN patient rehabilitation, and building a whole-process intelligent rehabilitation system of "accurate evaluation-personalized training-dynamic optimization-effect transfer". Through the combination of rapid quantitative evaluation system, behavior data and electroencephalogram signal, the objective grading of USN severity is realized, which gets rid of artificial dependence and greatly improves the evaluation efficiency and accuracy; through the whole-process automatic operation and machine learning self-adaptive optimization, the operation cost of clinical personnel is reduced, the rehabilitation effect is traceable and evaluable, and an accurate and personalized intelligent rehabilitation system is built, which provides a whole-process solution for USN patients and has important significance for promoting the intelligent development of post-stroke neurological dysfunction rehabilitation.

A health monitoring system for the autonomous support of elderly people, the system comprising the following: a variety of Internet of Medical Things (IoMT) sensors, including at least one wearable physiological sensor, one or more environmental sensor units, a mobility tracking device and a medication intake module, wherein the IoMT sensors are configured to continuously collect physiological, environmental, behavioral and medication use data; an edge processing device that includes an embedded processor and a lightweight machine learning inference unit configured to perform real-time anomaly detection and generate local alerts in the absence of cloud connectivity; a cloud-based analytics engine comprising one or more deep learning models configured to perform longitudinal health modeling, population-level clustering, and predictive risk forecasting using historical and real-time data; and a multi-channel communication unit configured to securely transmit notifications, reports, and emergency triggers to nursing staff, clinical staff, family members, and emergency services, wherein the edge processing device includes a dedicated hardware accelerator selected from a field-programmable gate array (FPGA), the accelerator being optimized to perform low-latency computations, including fall detection, arrhythmia detection, and respiratory abnormality monitoring, within a processing window of less than 200 milliseconds;and wherein the wearable physiological sensor is designed as a wrist-worn or patch-based device comprising a set of sensor elements, including an electrocardiography (ECG) electrode, a photoplethysmography (PPG) sensor for SpO2 measurement, a three-axis accelerometer, a gyroscope, and a skin temperature probe, the device further being configured to integrate raw signal data streams through a multimodal fusion technique performed locally on the edge device to minimize noise, compensate for motion artifacts, and improve the specificity of anomaly detection across multiple concurrent parameters.

A method for managing alarm events associated with patients assigned to clinical staff members. The method includes detecting an alarm event associated with a patient clinical status using a patient information system, identifying an assigned clinical staff member, and detecting the staff member's current location using a position tracking system. A user output subsystem includes a real time output channel and a post-hoc output channel, and wherein information relating to the detected alarm event is selectively output to the identified at least one clinical staff member by means of the first output channel or the second output channel in dependence upon the detected current location of the identified clinical staff member.

A method for controlling user interfacing with a patient information system. The method includes tracking (12), by means of a position tracking system (40), a position of at least one clinical staff member (82); detecting (14) a trigger event; obtaining (16) information from a patient information system (50) in response to the trigger event, wherein the patient information system is configured to provide access to information related to a plurality of patients; identifying (18) one or more output devices (62_n) from a plurality of output devices (62_1,...,62_N) based on a detected position of the at least one clinical staff member (82), wherein each of the plurality of output devices is operable to output clinical information to a user; and causing (20) the obtained information to be communicated to the identified one or more output devices.

The invention discloses an AI auxiliary sample sharing method and system. The AI auxiliary sample sharing method comprises the following steps: searching in a dialogue form between a GUI (Graphical User Interface) and a system; the AI intelligent matching module is used for carrying out semantic analysis on a query request submitted by a user based on a deep learning algorithm, and intelligently screening clinical special disease biological samples meeting user requirements from a clinical special disease biological sample database; personalized recommendation of the user can be provided according to historical behaviors and preferences of the user and currently inquired context information, and matching precision and efficiency are improved; by adopting the method, the efficiency of inquiring the required clinical special disease biological sample by clinical personnel can be greatly improved, so that the overall clinical research test efficiency is improved.

An internal fistula needle for hemodialysis treatment relates to the technical field of medical instruments and comprises an internal fistula needle tube, the tail of the internal fistula needle tube is in threaded connection with a screw cap, the head of the internal fistula needle tube is provided with a first needle head, a branch tube is communicated and fixed to the position, close to the first needle head, of the internal fistula needle tube, and the tail of the branch tube is provided with a second needle head. According to the internal fistula needle for hemodialysis treatment, when blood needs to be drawn in the dialysis process of a patient, the risk that a pipeline is polluted can be reduced, a transfer needle tube is not needed, cost can be saved, operation is easy and fast, the risk of errors is reduced, meanwhile, the internal fistula needle can be used for hemodialysis treatment, and the internal fistula needle can be used for hemodialysis treatment. The blood loss risk in the operation process is greatly reduced, the risk that large external force is generated on the pipeline is not likely to happen, operation of clinical personnel is better facilitated, using is safer, adverse events such as needle pricking injury and blood loss can be reduced, and the effect of improving the comfort level, the satisfaction degree and the nursing quality of a patient is achieved.