142 results about "Patient status" patented technology

The invention provides an intelligent pre-examination triage method based on multi-modal data and edge calculation, and relates to the technical field of multi-modal data, and the method comprises the steps: collecting the facial expression, wound part, sound and physiological signals of a patient through medical equipment; multi-modal features are extracted by using a deep learning network and dynamic weighted fusion is carried out to obtain a patient state evaluation result; performing data time sequence alignment and feature extraction based on edge nodes, dynamically adjusting calculation precision and realizing task migration; multi-source data are collected for time sequence alignment calibration and feature fusion, the emergency degree is calculated, and group damage distribution is predicted. According to the method, real-time processing and dynamic optimization of multi-modal data are realized, and the accuracy and efficiency of pre-examination triage are improved.

The invention discloses an intelligent dynamic triage system and method for emergency patients. The triage system comprises a data acquisition module used for acquiring basic information, physiological parameters and historical records of patients; the artificial intelligence analysis module generates a preliminary triage result; the Internet of Things connection module collects hospital resource data in real time; the central control processing unit is connected with each module to receive data; the dynamic grading decision-making module divides the patients into critical symptoms, severe symptoms, subcritical symptoms and common symptoms; the resource allocation module dynamically generates a resource allocation scheme according to the grading result; the diagnosis and treatment process management module tracks the whole process of the patient and updates state data; when the state of the patient changes, the system transmits data to the artificial intelligence analysis module again for evaluation, triggers the grading decision and resource allocation module, dynamically updates the triage priority and the resource allocation scheme, and achieves closed-loop feedback and continuous optimization.

The invention provides a first-aid information processing method and system based on multi-source data fusion. The method comprises the following steps of: performing deep association matching and modeling on an emergency event by utilizing a multi-source heterogeneous data stream, a geographic position, a timestamp and environmental perception data which are acquired in real time to obtain a dynamic emergency event situation model; according to the dynamic first-aid event situation model, a resource optimization algorithm is adopted to evaluate and select the most suitable first-aid resource, and a first-aid resource configuration scheme and instant guidance information are obtained; updating the state of the patient based on the first-aid resource allocation scheme and the instant guidance information, and obtaining a dynamically adjusted first-aid process and an optimized path scheme through geographic information system path planning analysis, first-aid strategy adjustment and resource allocation path optimization; and integrating various feedback data related to the dynamically adjusted emergency process and the optimized path scheme, carrying out post analysis, and generating an optimized guide. According to the technical scheme provided by the invention, the first-aid information processing efficiency is greatly improved.

The invention relates to the technical field of physiological status monitoring, in particular to a rehabilitation assessment method and system based on patient status awareness, and the method comprises the following steps: collecting myoelectricity, heart rate and skin conductance signal data of a patient, normalizing time sequence data, setting a time window, calculating a mean value and a mean square error, and analyzing a signal covariance variation trend. And generating a cross-domain signal stability list. According to the method, the physiological signals of the patient are collected and analyzed, the method has important significance on improvement of the rehabilitation effect, the physiological signals such as myoelectricity, heart rate and skin conductance are collected and analyzed in real time, tiny changes of the state of the patient can be carefully captured, more accurate state evaluation and rehabilitation progress monitoring are achieved, and the rehabilitation effect is improved. The accuracy of data processing and the efficiency of signal decoding are ensured by analyzing the signal stability and optimizing and adjusting the time window, and the rehabilitation scheme is further adjusted according to the specific response of the patient, so that the rehabilitation process is more personalized and targeted.

The invention relates to a patient examination item recommendation method based on a medical knowledge graph. The method comprises the steps that firstly, historical data in the medical field is acquired, key information is extracted from the historical data to generate an entity relation triple, and then a medical knowledge graph is constructed; then, generating a patient state sub-graph based on patient input information, processing the medical knowledge graph by adopting an improved TransD model, and determining unique representation of an entity-relationship pair; mapping the patient state sub-map to a unique representation space, obtaining vector representation of a patient and an examination item related entity, and calculating a similarity value between vectors to obtain a similarity value matrix; and finally, performing priority ranking on the inspection items according to the matrix, and generating a final recommendation list through threshold screening and combination with graph neural network verification, optimization and adjustment of priorities. By adopting the method, examination items can be accurately recommended for patients, doctors are assisted to improve the treatment efficiency, the queuing time of the patients is shortened, and the medical experience of the patients is remarkably improved.

The invention relates to the technical field of medical informatization, and provides an information digital management system and method based on an intensive care medicine department, and the system comprises a data collection module, a data processing module, and a visualization and alarm module. The data acquisition module obtains a patient monitoring data set, and each patient corresponds to a monitoring data sequence. The data processing module executes the following operations on each patient: determining a target monitoring data sequence and four associated monitoring periods including a first monitoring period, a second monitoring period, a third monitoring period and a fourth monitoring period group, and generating a corresponding monitoring subset; generating an early warning signal through a disease deterioration early warning model; and if the signal is abnormal, analyzing an abnormal reason and an influence range, and generating a structured disease condition comprehensive report. And the visualization and alarm module dynamically displays the state of the patient according to the report, and performs graded alarm on the critical area. The system realizes accurate early warning and monitoring through multi-cycle data fusion analysis and three-dimensional visualization.

The invention provides a patient state auxiliary judgment and posture adjustment method, device and system, and relates to the technical field of medical equipment. The method comprises the following steps: acquiring real-time state data of a patient; generating a three-dimensional posture model and emotion parameters of the current body posture of the patient based on the real-time state data; according to the difference degree of the preset target posture and the three-dimensional posture model, a posture adjustment instruction is generated in combination with a manual adjustment instruction of a doctor; and based on the posture adjustment instruction, prompting the patient to adjust the posture until the difference degree is smaller than a preset threshold value and the emotion parameters are in a target emotion range and lasts for a preset duration, and confirming that the patient completes examination preparation. Through the technical scheme provided by the invention, the problems that accurate state judgment is difficult to obtain and posture auxiliary adjustment cannot be performed on the patient before the patient is examined are solved, the accuracy of state perception of the patient and the efficiency of posture adjustment are improved, and the examination experience of the patient is improved.

The invention relates to the technical field of medical informatization, in particular to a ward distress call method and system based on intelligent medical treatment, and the method comprises the steps: obtaining patient state data collected by a plurality of sensors in a ward; receiving a ward help-calling instruction; constructing a multi-modal data fusion matrix based on the patient state data; executing random matrix transformation and feature extraction according to the multi-modal data fusion matrix; based on the extracted features, topological feature mapping and anomaly detection are carried out; executing group theory base risk assessment according to the topological features; calculating a chaotic power system early warning index based on a group theory risk assessment result; determining a call-for-help judgment result according to the early warning index; a corresponding response strategy is executed based on the call-for-help judgment result, the system can comprehensively grasp the state of the patient through the multi-modal data fusion technology, and the evaluation accuracy is greatly improved. And secondly, the robustness of the system is enhanced by random matrix transformation, so that the system can cope with a complex and changeable medical environment.

Disclosed is a system that includes a computer-readable medium (CRM) coupling a variety of devices. The variety of devices can include one or more patient wearable sensor devices, a paired patient device, and a patient devices docking station. The system can also include a smart patient care cart, a nurse station, a lift tracker station, and / or an agnostic aggregation station. The system can also include a patient datastore, a facility datastore, a caregiver datastore, a device datastore, a patient state datastore, a patient management datastore, a facility management datastore, a caregiver management datastore, an electronic health record (EHR) system datastore, a health / fitness datastore, and an agnostic aggregation datastore.

The invention provides an intelligent bed detection method and system, relates to the technical field of medical care, and is suitable for an intelligent bed, the intelligent bed comprises a bed and a bedside guardrail, the bed is provided with a corresponding first sensor, the bedside guardrail is provided with an intelligent detector, and the intelligent detector comprises a sensor assembly. A first sensor signal collected by the first sensor and a guardrail state signal, collected by the sensor assembly, of the bedside guardrail are preprocessed to obtain first sensor information and guardrail state information; predicting a patient state of a patient corresponding to the intelligent bed through a pre-trained patient state recognition model, the first sensor information and the guardrail state information; if the patient is in the off-bed state, counting off-bed time when the patient state is in the off-bed state in real time, and detecting whether the off-bed time reaches a target off-bed time threshold value matched with the patient or not; and if yes, outputting early warning information, so that the patient state can be mastered by paying attention to the behavior actions of the patient and the use state of the sickbed, the patient safety is ensured, and the nursing quality is improved.

The invention relates to the technical field of physiological parameter monitoring, in particular to a patient physiological feature monitoring method based on nursing sampling data. Comprising the following steps: acquiring body temperature, pulse and systolic pressure data in different periods, marking time and sources to generate a period-divided sequence, dividing sampling frequencies in combination with parameter variation and historical data to generate hierarchical labels, identifying trend directions to construct a classification list, extracting time node marking trends to generate a positioning table, and marking the time node marking trends according to the positioning table. And integrating the frequency trend relationship to construct an atlas identification set. According to the method, the anomaly tracking efficiency is improved by integrating parameter data in different time periods and marking source time, enhancing data relevance, dynamically evaluating parameter change characteristics and historical fluctuation levels, dividing adaptive sampling frequencies, optimizing monitoring density and reducing redundancy, identifying trend directions and classifying structures, and constructing positioning labels; the spectrum identification is constructed by integrating the frequency and trend relation, real-time early warning is supported, the nursing strategy and the patient state are synchronized, and high-time-efficiency accurate intervention is supported.

A digital healthcare ecosystem to transform patient care with real-time queue management, including: an appointment and laboratory test booking module configured to allow patients to easily book and schedule doctor consultations and diagnostic tests; a healthcare provider module configured to manage appointments, patient records, billing, internal laboratory and pharmacy integration, and operational analytics, with the healthcare provider module configured to manage dashboard features for physicians, hospital administrators, and laboratory technicians to monitor and update patient status; a real-time queue management module coupled to the healthcare provider module and the appointment and laboratory test booking module, wherein the real-time queue management module is configured to assign a digital token number to patients upon booking once accepted by the healthcare provider module, wherein the real-time queue management module is configured to update the queue position of patients using time-stamped data; a patient interface configured to allow patients to view real-time queue updates, book appointments, and access lab reports using the digital token number; a notification system configured to send notifications to patients and physicians regarding appointment reminders, queue progress, and follow-up instructions; a cloud-based server configured to securely store patient data and enable seamless communication between the patient interface and the healthcare provider module; a display unit configured to show estimated waiting times and notify patients when it is their turn; and a dynamic scheduling module configured to take into account physician availability, patient preferences, and historical data to minimize waiting times and avoid overbooking.

The invention discloses an outpatient service management method and system based on an HIS system, belongs to the technical field of computers, and achieves precise triage and personalized treatment path recommendation by integrating multi-dimensional state information of a patient and real-time department data and combining a dynamic path planning algorithm. The method has the advantages of improving triage accuracy, optimizing treatment path planning and improving outpatient service management efficiency.

The invention discloses an intelligent service system for advanced cancer pain, which comprises an analgesia device, a massage piece, a driving source and borneol, and is characterized in that the borneol is positioned on the inner side surface of a mounting seat and is used for contacting with a cooling massage ball; the pushing module is used for pushing a predetermined examination quantization table to the patient every day, and the examination quantization table at least comprises one or more of the following items: diet condition, sleep condition, body pain condition, self-cognitive ability and mental state; the evaluation module obtains a patient state evaluation result according to the data of the patient on the examination quantification table, pushes a management scheme to the patient according to the evaluation result, adjusts an analgesia scheme of the analgesia device, and periodically obtains daily living conditions of the patient through a pushing module; and a personalized and centralized pain intervention scheme is formed through the evaluation module, so that on one hand, the life quality of the patient is evaluated in time, and on the other hand, the specific change condition can be conveniently checked through a quantitative mode, and the specific condition of the patient can be improved in a targeted manner.

A system and method for processing vital information are provided. The system includes a memory, a processor, and a display. The processor performs following operations: acquiring patient data of a patient; analyzing the patient data to obtain multiple analysis results, wherein the multiple analysis results at least include a first trend of change for first information and a second trend of change for second information extracted from the patient data; determining whether the first trend of change and the second trend of change satisfy a preset condition; determining a patient state of a patient related to the preset condition when the preset condition is satisfied; and displaying indication information which indicates a patient state, the first trend of change and the second trend of change. A correlation between various trend of changes of patient data is taken into consideration in determination of the patient state, which improves the determination accuracy.

The invention discloses an intelligent monitoring system for tumor nursing. The intelligent monitoring system comprises a wearable sensing terminal group, a patient terminal, a cloud platform intelligent analysis center and a medical care terminal. The wearable terminal is used for collecting multi-modal physiological and behavior data such as electroencephalogram, near-infrared brain blood oxygen, heart rate variability, body movement, electrodermal response and gaits; the patient terminal is used for recording subjective symptoms and completing cognition and exercise task evaluation. The cloud platform intelligent analysis center constructs a multi-parameter individualized baseline through data fusion, noise suppression and time alignment, comprehensively analyzes real-time deviation, electroencephalogram abnormality, cognitive deviation and gait change by using a short-term acute early warning model and a long-term trend early warning model, and generates a risk level. The digital twinborn visualization module is used for dynamically displaying the state of the patient, and the medical care terminal performs clinical response based on the graded alarm board. According to the invention, extra-hospital multi-mode continuous monitoring, individualized trend identification and intelligent early warning can be realized, and the real-time performance of follow-up management of brain tumor patients is improved.

The invention discloses a medical data analysis early warning method and system based on inverse reinforcement learning and sequence data dynamic modeling, and the method comprises the following steps: obtaining electronic health record data, and constructing a related data set; according to the constructed data set, a Markov process model is established according to the patient state and the treatment measures, a reward function capable of evaluating the effectiveness of the treatment measures is constructed based on the patient trajectory probability of a trajectory space, and each trajectory in the trajectory space is a state-action pair sequence formed by the patient state and the treatment measures; training the inverse reinforcement learning model by using the data set to obtain an optimal reward function; and obtaining a state prediction value of the current state of the patient after corresponding treatment measures are taken by using the optimal reward function, and if the state prediction value exceeds a set threshold value, carrying out early warning. According to the method, the adaptability to the dynamic change of the patient condition in the medical data analysis and prediction process is improved, and the accuracy of patient state prediction is improved.

The invention relates to the technical field of medical information smart wards, in particular to a smart ward management method and system based on the Internet of Things. Environmental parameters in a smart ward and physiological parameters of a patient in the smart ward are obtained; performing comprehensive analysis according to the environmental parameters and the physiological parameters to obtain corresponding analysis results; and according to an analysis result, a control instruction used for adjusting environment equipment in the smart ward is generated and / or corresponding guidance information is sent to the management end, so that the ward environment and the patient state are combined, and integrity and collaboration are realized. Intelligent management and real-time monitoring and response of the ward are realized through the control instruction and / or guidance information, the timeliness of medical services is improved, dynamic allocation of medical resources is facilitated, the resource utilization efficiency is improved, the operation process is greatly simplified, and the use experience of medical staff and patients is improved.

The invention relates to an intelligent platform management system carrying infusion port patients, and relates to the technical field of data management, and the system comprises a monitoring unit which is used for collecting impedance data, temperature data and medicine use time sequence data; the intelligent analysis unit is used for constructing a dynamic health baseline of the patient, calling a preset machine learning model based on the dynamic health baseline and outputting a complication risk level of the patient; the closed-loop execution unit is used for triggering a three-dimensional life behavior guidance scheme matched with the patient state based on the complication risk level, calculating a corresponding infusion port maintenance period based on the real-time smoothness score, and generating a medicine supply instruction in combination with medicine use time sequence data; and the hierarchical interaction platform is used for generating an early warning view containing the risk level of the patient and the key attention information based on the complication risk level, and pushing maintenance appointment suggestions and planning contents at the patient side based on the maintenance period of the infusion port. The system can improve the management efficiency and safety of the patients in the infusion port.

The invention discloses a visual asynchronous event triggering and calling method based on a medical information system, which comprises the following steps of: asynchronously acquiring multi-source data streams such as clinical events, equipment monitoring, doctor advice execution and patient states in the medical information system to form a multi-source asynchronous medical data stream set; generating a system event triggering association group based on the set and creating an asynchronous event scheduling strategy table; performing system event association degree calculation on the data stream to obtain a multi-dimensional asynchronous event association matrix; and carrying out system asynchronous time delay compensation and event chain visualization processing on the incidence matrix based on the scheduling strategy table, and finally generating a dynamic asynchronous event correlation topological graph. According to the invention, by constructing a system event detection operator set, establishing cross-flow system relevance calculation and establishing a priority-based asynchronous scheduling optimization mechanism, intelligent triggering, calling and early warning functions of medical system events are realized.

Systems, methods, and computer-readable media for providing a decision support solution to medical professionals to optimize medical care through data monitoring and feedback treatment are provided herein. In another embodiment, a computer-implemented method for modeling patient outcomes resulting from treatment in a specific medical area includes receiving patient-specific data associated with a patient, determining a plurality of possible patient states under which the patient can be categorized, a current patient state under which the patient can be categorized and determining probabilities of the patient transitioning from any of the possible patient states to every other possible patient state.

A system for assessing a patient’s emotional state, for example anxiety, stress or distress levels, comprises: an imaging means which is operative to obtain at least one image of a gesture of the patient during a consultation with a clinician and to output gesture data indicative of the at least one gesture. An input terminal receives clinician input data from a clinician and patient status data is supplied which may be indicative of patient trauma. An artificial neural network determines a qualitative assessment of a patient’s emotional state based on a data matrix of the clinician input data and patient status data and a comparison of gesture data with a database of gesture data. A processor determines a patient emotional state and when a threshold in the patient emotional state is exceeded, and causes an alert to be transmitted. The gesture may be a facial gesture.

A system for the remote patient assessment and monitoring system that collects and analyzes eye-gaze information for the purposes of identifying users that show symptoms of cognitive impairment. The system administers tasks to a user via the user's computing device. A camera captures the performance of the tasks by the user. The system then verifies synchronization and then analyzes the captured performance image data to determine a patient status for the user. The system applies calibration and normalization processes to ensure that the tasks are properly presented and that the user data can be used regardless of changes to resolution, hardware, display or other factors.

To provide an information processing device which allows management of screen display of states of multiple patients selected in remote rehabilitation.SOLUTION: An information processing device comprises: a reservation data acquisition part 1201 for acquiring rehabilitation reservation data indicating reservation of rehabilitation for each of one or more patients; a display condition acquisition part 1202 for acquiring a display condition which indicates conditions related to one or more patients, the conditions capable of being simultaneously displayed on one rehabilitation monitoring screen out of multiple rehabilitation monitoring screens for displaying information related to patients who undergo rehabilitation; a rehabilitation start information acquisition part 1204 for acquiring rehabilitation start information which indicates that each patient starts undergoing of rehabilitation; a rehabilitation finish information acquisition part 1205 for acquiring rehabilitation finish information indicating that each patient finishes undergoing of rehabilitation; and a display information creation part 1206 for creating monitor screen display information for displaying the information related to patients who are undergoing rehabilitation on the rehabilitation monitoring screen on the basis of the rehabilitation reservation data, the display condition, the rehabilitation start information and the rehabilitation finish information.SELECTED DRAWING: Figure 2

The invention discloses a multi-source information warning and reminding system and method for a smart ward, and the system comprises a data collection and processing module, a data fusion and analysis module, a data warning and reminding module, a warning data storage module, and a user interaction module. The data fusion and analysis module is connected with the data collection and processing module and the data warning and reminding module, and the warning data storage module and the user interaction module are both connected with the data warning and reminding module. By integrating the Internet of Things equipment and the hospital information system, the state of a patient is comprehensively perceived, the data fusion and intelligent analysis technology is utilized to carry out accurate risk study and judgment, efficient warning is realized through a collaborative distribution mechanism, the system is continuously self-optimized according to processing feedback of medical staff, and the medical staff can carry out medical care on the patient. An intelligent clinical decision support closed loop is constructed, conversion from passive response to active early warning is realized, and the method has the characteristics of comprehensiveness, accuracy and high efficiency.

Systems, devices, and methods including a processor having addressable memory, where the processor is configured to: collect, via a set of sensors, biological signals related to patient status; collect, via an environmental monitoring device, environmental data associated with an environment of the patient; store, locally via a secure encrypted local database, the collected biological signals and the collected environmental data; detect an abnormality in the collected biological signals; increase measurement frequency of the biological signals by the set of sensors based on the detected abnormality; detect an error in the collected biological signals; determine whether the detected error in the collected biological signals of the current reading is due to environmental factors; correct the determined error in the collected biological signals; and transmit the error corrected collected biological signals as encrypted data.

A corridor display unit is configured for mounting to a surface of a corridor in a hospital or health care facility. The corridor display unit includes one or more flat panel displays and a mounting frame that outlines and encloses the flat panel display. To annunciate information about patient status or location status to caregivers, the flat panel display can display an annunciation image rendered from image files that may include a textual component and a graphical component. The annunciation image may also include real-time data and prerecorded data about the patient status or the location status.

An alarm notification system can enable a clinician to respond to an alarm notification received via a computing device, which may have more advanced functionality than a pager. The clinician's device can include a notification client which can respond to alarm notifications. The notification client can also provide one or more user interfaces that enable the clinician to view information about an alarm, such as information about a patient's status, physiological parameter values, trend data, audio / video of the patient, combinations of the same, or the like. Further, the notification client can provide functionality for a clinician to respond to an alarm, annotate an alarm, and / or indicate that the clinician can or cannot respond to the alarm, among other features. In addition, the clinician device can also (or instead) include an admit module that provides for automatic association of a patient to a device or location.

The invention provides an ICU patient remote ward-round system and method based on VR, and the system achieves the immersive remote presentation of the state of an ICU patient through high-precision data synchronization, multi-mode interaction design and a low-delay rendering architecture, remarkably improves the doctor-patient communication efficiency and the psychological pacifying effect of family members, and improves the patient experience. And a brand-new digital solution is provided for an intensive care scene. A doctor can quickly position the abnormal states of multiple patients through a VR scene (for example, the doctor can check the breathing amplitudes of the patients in 10 wards at the same time), and the ward round efficiency is improved by 300% (the traditional polling ward round needs 15 minutes for each patient, and the VR system only needs 3 minutes). Clinical tests show that after VR is used for visiting, the score of an anxiety scale (GAD-7) of family members of a patient is averagely reduced, and the score is mainly attributed to'real contact feeling 'and vital sign transparency caused by tactile interaction.

The invention relates to the technical field of data processing, and particularly provides a hospital guide method, system and device based on multi-modal data and a storage medium, and the method comprises the steps: obtaining the multi-modal data which is provided by a patient and comprises texts, medical images and physiological signals; extracting each modal feature vector and fusing the modal feature vectors into a unified patient state characterization vector; on the basis, confidence distribution of the target department is calculated through a probabilistic reasoning model; if the result does not reach the termination condition, iteratively executing the following core steps: calculating the information gain of each potential action in the predefined action set, obtaining new data according to the optimal action, updating the state of the patient and recalculating the confidence coefficient; and finally, outputting a hospital guide result meeting a termination condition. According to the invention, through multi-modal fusion and dynamic interaction decision making, the accuracy and efficiency of intelligent hospital guide are effectively improved.