Human-computer interaction virtual-real simulation method and system of intestinal nutrition nursing teaching system

Abstract

The invention provides a human-computer interaction virtual-real simulation method and system of an intestinal nutrition nursing teaching system, and relates to the technical field of virtual interaction teaching. By integrating a force feedback glove, a bioelectric sensor and a pressure detector, multi-mode interaction data acquisition including intubation angle deviation, maximum force application pressure value and step interval time is realized; the operation feedback dimension and immersion are improved; the system is combined with a scene construction and intelligent guide module, when the detection operation goodness of fit is lower than a preset threshold value or the process completion degree is insufficient, force feedback vector correction and cognitive prompt are triggered, and standard attitude and step memory are guided; and the comprehensive evaluation module summarizes key indexes to calculate a total operation score, performs defect positioning and training suggestion matching on low-score behaviors, generates a structured visual learning report, constructs a cognition-operation-feedback closed loop, and solves the problems of single interactive feedback, insufficient teaching structuralization and lack of feedback mechanisms.

Description

Technical Field

[0001] The present invention relates to the technical field of virtual interactive teaching, and in particular to a human-computer interactive virtual-reality simulation method and system for an intestinal nutrition nursing teaching system. Background Art

[0002] Intestinal nursing education originated from practical teaching within nursing courses. With the growing demand for clinical nursing and the development of virtual simulation technology, it has gradually evolved into a virtual teaching system that integrates multimedia instruction, scenario simulation, and interactive training. This system's advantage lies in its integration of real-world clinical cases and an immersive interactive experience. It not only enhances learners' practical skills but also allows for repeated training and immediate feedback in a risk-free environment, significantly optimizing teaching efficiency and safety.

[0003] In the prior art, the publication number is CN118015893A, and the name is a nursing staff training and virtual simulation operating system and method; this belongs to the field of nursing staff training technology, and discloses a nursing staff training and virtual simulation operating system and method, the nursing staff training and virtual simulation operating system and method system includes: virtual reality equipment, human simulator equipment, data transmission module, data processing equipment, and cloud server. The present invention can combine the advantages of human simulator teaching, virtual reality teaching and online learning to achieve full-process simulation and feedback of nursing operations, and provide immersive, realistic, interactive, feedback-oriented, intelligent evaluation and personalized guidance of nursing training and education; at the same time, the present invention determines the evaluation indicators of nursing training based on the nursing staff operation data through the nursing staff operation evaluation method; uses the hierarchical analysis method to determine the weight of each evaluation indicator; based on the evaluation indicator and the weight of each evaluation indicator, determines the relative value of the indicator; and uses the relative value of the indicator to effectively evaluate the training quality.

[0004] Although the existing virtual simulation system has a relatively complete technical structure and data processing capabilities, its interactive mode has the following technical shortcomings when applied to the intestinal nursing teaching system:

[0005] 1. The interactive feedback is single and lacks a multimodal physiological response mechanism;

[0006] 2. The teaching content is not structured enough, and the interaction does not reflect the connection between step-by-step guidance and knowledge points;

[0007] 3. Interactive evaluation feedback lacks dynamic collaboration and teacher-student interaction functions.

[0008] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the Invention

[0009] The purpose of the present invention is to provide a human-computer interaction virtual-reality simulation method and system for an enteral nutrition nursing teaching system to solve the problems raised in the above background technology.

[0010] To achieve the above object, the present invention provides the following technical solutions:

[0011] The human-computer interactive virtual-reality simulation system for the enteral nutrition nursing teaching system includes a scenario construction module, an interactive perception module, a data processing module, an intelligent guidance module, and a comprehensive evaluation module;

[0012] The scenario construction module is used to build a virtual nursing teaching environment, integrating a visual rendering system with a multimodal force feedback device to simulate changes in vital signs, including intestinal tension and spasm, and generate virtual operation scenarios corresponding to standard operating procedures;

[0013] The interactive perception module is used to collect interactive data of nursing trainees during virtual operations through force feedback gloves, bioelectric sensors, and pressure detectors, including intubation angle deviation, maximum applied force pressure value, and time interval between steps, and summarize them to construct an operational behavior set;

[0014] The data processing module is used to perform multi-dimensional calculations on the set of operation behaviors, generate and evaluate the operation consistency Cwh, and measure the conformity between the operation posture and the mechanics. At the same time, it calculates the evaluation process completion Lwc to evaluate the consistency and rhythm rationality of the operation steps.

[0015] The intelligent guidance module is used to trigger the correction mechanism, including force feedback vector correction instructions, when abnormal operation consistency Cwh and process completion Lwc are detected;

[0016] The comprehensive evaluation module calculates and evaluates the total operation score Scl based on the operation consistency Cwh and process completion Lwc, generates periodic feedback results, outputs defect location information and training suggestions, and generates corresponding training progress charts and reports.

[0017] Preferably, the scenario construction module integrates 3D modeling technology with a force feedback simulation engine to interactively model the anatomical structure of the intestine, and uses a visual rendering system to present physiological characteristics including changes in intestinal wall tension, segmental spasms, and dynamic responses of mucosal folds. At the same time, standard nursing procedures including lubrication, intubation, perfusion, and recovery are divided into triggerable scenario events, and the corresponding virtual operation content is loaded in real time.

[0018] Secondly, the operating feel is dynamically adjusted by cooperating with the force feedback device, and corresponding reverse resistance, vibration feedback and viscosity simulation force field are applied according to different operating parts and physiological states.

[0019] Preferably, the interactive perception module constructs a multimodal acquisition channel by jointly building a wearable force feedback glove, a bioelectric sensor, and a pressure detector to monitor the nursing trainees' operation movements and physiological responses during virtual intestinal care in real time;

[0020] The force feedback glove is used to collect spatial trajectory and posture data during the intubation process and calculate the intubation angle deviation; the pressure detector is used to measure the maximum pressure value applied by the hand at different stages; the bioelectric sensor is used to record the time interval between each step in the operation rhythm, and expands the collection of skin electrical changes and muscle electrical signals to assist in identifying the trainee's state of tension or fatigue;

[0021] The collected multi-source data are time synchronized and feature extracted, and integrated into a complete set of operation behaviors.

[0022] Preferably, the data processing module includes an operation posture evaluation unit;

[0023] The operation posture evaluation unit extracts the intubation angle deviation Cwa and the maximum applied force pressure value Cwb from the operation behavior set and performs dimensionless processing to calculate the operation consistency Cwh;

[0024] Based on expert experience, historical high-level operation samples and data statistical analysis, a reference standard is set to obtain the operation consistency threshold C, and then compared and evaluated with the operation consistency Cwh;

[0025] If the operation consistency Cwh ≥ the operation consistency threshold C, the training is considered to have met the standard and the system does not trigger the correction guidance;

[0026] If the operation consistency Cwh is less than the operation consistency threshold C, the intelligent guidance module is triggered to intervene and perform real-time correction and cognitive compensation.

[0027] Preferably, the data processing module further includes a process rhythm evaluation unit;

[0028] The process rhythm evaluation unit extracts the time interval Ti between each step in the set of operation behaviors and calculates the process completion degree Lwc;

[0029] The process completion threshold L is preset based on the execution model of the standard teaching process, the average operation time and accuracy rate specified in the teaching syllabus, and the qualified baseline set after analyzing historical excellent operation data;

[0030] Compare and evaluate the process completion threshold L and the process completion degree Lwc; the specific contents are as follows:

[0031] If the process completion degree Lwc ≥ the process completion threshold L, it means that the trainee has a good overall perception of the operation and control over the process;

[0032] If the process completion degree Lwc is less than the process completion threshold L, the system will push prompts and training suggestions through the intelligent guidance module to help students fill in the process gaps.

[0033] Preferably, the intelligent guidance module includes a vector correction unit;

[0034] The vector correction unit is used to generate a three-dimensional force feedback vector correction command based on the deviation between the actual operation trajectory and the standard path when it detects that the operation consistency Cwh is lower than the set threshold C. This command acts on the operator's hand in real time through the force feedback glove, guiding the operator's hand to adjust its spatial posture and force direction, helping them to adhere to the correct intubation angle and advancement path, achieving refined operation training.

[0035] Preferably, the intelligent guidance module further includes a cognitive prompting unit;

[0036] The cognitive prompt unit is used to identify the steps that the trainees have missed or are in the wrong order when the process completion degree Lwc is lower than the threshold L, and automatically push the dynamic anatomical structure demonstration, operation process animation or voice prompt corresponding to this stage to enhance their cognitive compensation ability for the step knowledge points and operation rhythm, while supporting interactive pause and review functions.

[0037] Preferably, the comprehensive evaluation module includes a scoring analysis unit;

[0038] The scoring analysis unit is used to receive the operation consistency Cwh and process completion Lwc indicators from the data processing module, and calculate the total operation score Scl based on the weight model;

[0039] Based on the statistical data of clinical expert scores over the years, and in accordance with the standardized nursing skills training manual and the preset operation specifications, combined with the learning curve and training achievement rate of most trainees, the preset total operation threshold S is calculated and compared with the total operation score Scl for evaluation;

[0040] The specific evaluation contents are as follows:

[0041] When the total operation score Scl ≥ the calculated operation total threshold S, the operation is considered to meet the standard;

[0042] When the total operation score Scl is less than the calculated operation total threshold S, the operation is judged to be substandard. At this time, the defect analysis process is initiated to conduct a fine-grained review of the entire operation process;

[0043] When an operation is determined to be substandard, the defect analysis process, including backtracking logs, event type classification, time node association, and defect label generation, is carried out in sequence to automatically locate the specific defect link.

[0044] Based on the standard operation database, semantic matching is performed on defects, matching suggestion templates are called, and personalized training suggestions are dynamically generated; multiple suggestions are combined and output at the same time.

[0045] Preferably, the score analysis unit further includes a report generation unit;

[0046] The report generation unit is used to integrate the scoring analysis results and operation behavior logs to output stage-by-stage learning feedback reports, including: scoring summary, key defect description, personalized training suggestions, as well as visual operation trajectory charts, scoring trend charts, and learning progress charts;

[0047] The report is displayed in real time and can be exported for teacher evaluation and student self-examination.

[0048] The human-computer interaction virtual-reality simulation method of the enteral nutrition nursing teaching system includes the following steps:

[0049] Step 1: Build a virtual nursing teaching environment, integrating a visual rendering system with a multimodal force feedback device to simulate changes in vital signs, including intestinal tension and spasticity, and generate virtual operation scenarios corresponding to standard operating procedures;

[0050] Step 2: Use force feedback gloves, bioelectric sensors, and pressure detectors to collect interactive data from nursing trainees during virtual operations, including intubation angle deviation, maximum applied force pressure, and the time interval between steps, and summarize them to construct an operation behavior set;

[0051] Step 3: Perform multi-dimensional calculations on the set of operation behaviors to generate and evaluate the operation consistency Cwh, measuring the consistency between the operation posture and the mechanical properties. At the same time, calculate the evaluation process completion Lwc to evaluate the consistency and rhythm of the operation steps.

[0052] Step 4: When the operation consistency Cwh and process completion Lwc are detected to be abnormal, the correction mechanism is triggered respectively, including the force feedback vector correction instruction;

[0053] Step 5: Based on the operation consistency Cwh and process completion Lwc, calculate and evaluate the total operation score Scl, generate phased feedback results, output defect location information and training suggestions, and generate corresponding training progress charts and reports.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] The system solves the problems of single interactive feedback and lack of multimodal physiological response mechanism. By introducing an interactive perception module that integrates force feedback gloves, bioelectric sensors and pressure detectors, it realizes the synchronous acquisition of multi-channel data such as intubation angle deviation Δθ, maximum force pressure value Pmax and operation step interval Δt. The system can sense and record the changes in posture, force application behavior and physiological state of trainees during the operation, construct a full-dimensional operation behavior set, and provide high-quality basic data for subsequent posture evaluation and rhythm analysis. In addition, the combination of visual rendering and tactile feedback enhances the operator's immersion and sense of reality during the interaction, effectively overcoming the problems of single feedback dimension and weak operation feel in traditional virtual simulation teaching.

[0056] The present invention further solves the problems of insufficient structuring of teaching content and the lack of correlation between step guidance and knowledge points in interaction. By constructing a scenario construction module, dynamic simulation modeling of intestinal physiological states including tension changes and spasm responses is carried out, and force feedback is combined to simulate different operation stages, including changes in the feel of lubrication, intubation, perfusion and recovery. The intelligent guidance module is provided with a vector correction unit and a cognitive prompt unit, which respectively monitor the operation consistency Cwh and the process completion Lwc in real time. When Cwh is less than the threshold C or Lwc is less than the threshold L, force feedback correction and step demonstration guidance are triggered respectively. The system can generate three-dimensional vector correction instructions according to the current operation position, deviation type and standard path deviation degree, and push corresponding anatomical structure animation and voice prompts at the same time, so that students can form a clear mapping relationship between knowledge points, steps and techniques, and realize a complete link closed loop from cognition to action.

[0057] The present invention also solves the problem that interactive evaluation feedback lacks dynamic collaboration and teacher-student interaction functions; the data processing module calculates Cwh and Lwc respectively through operation posture evaluation and process rhythm evaluation, and then the scoring analysis unit calculates the total operation score Scl based on the comprehensive weight, and then compares it with the preset total threshold S; if Scl is less than S, the defect analysis process is automatically started, and the steps of log backtracking, event classification, node association and defect label generation are performed based on the data in the operation behavior log; then, based on the historical templates in the standard operation database, the defect type is matched to output personalized training suggestions, such as "strengthen navigation training in the intestinal bend area" or "it is recommended to turn on the continuous guided rehearsal function"; the final report generation unit generates a complete stage report including score summary, defect location, suggestion content and visual charts, supports real-time display and export, and is used for teacher evaluation and student self-inspection, realizing the linkage mechanism of evaluation, feedback and optimization training. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 This is a schematic diagram of the overall system framework of the present invention;

[0059] Figure 2Schematic diagram of the overall method of the present invention. DETAILED DESCRIPTION

[0060] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to specific embodiments.

[0061] It should be noted that, unless otherwise defined, the technical or scientific terms used in the present invention should have the usual meanings understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative position relationships. When the absolute position of the object being described changes, the relative position relationship may also change accordingly.

[0062] Example 1:

[0063] See also Figure 1 , the present invention provides a human-computer interactive virtual-reality simulation system for an enteral nutrition nursing teaching system, comprising a scene construction module, an interactive perception module, a data processing module, an intelligent guidance module and a comprehensive evaluation module;

[0064] The scenario construction module is used to build a virtual nursing teaching environment, integrating a visual rendering system with a multimodal force feedback device to simulate changes in vital signs, including intestinal tension and spasm, and generate virtual operation scenarios corresponding to standard operating procedures;

[0065] The interactive perception module is used to collect interactive data of nursing trainees during virtual operations through force feedback gloves, bioelectric sensors, and pressure detectors, including intubation angle deviation, maximum applied force pressure value, and time interval between steps, and summarize them to construct an operational behavior set;

[0066] The data processing module is used to perform multi-dimensional calculations on the set of operation behaviors, generate and evaluate the operation consistency Cwh, and measure the conformity between the operation posture and the mechanics. At the same time, it calculates the evaluation process completion Lwc to evaluate the consistency and rhythm rationality of the operation steps.

[0067] The intelligent guidance module is used to trigger the correction mechanism, including force feedback vector correction instructions, when abnormal operation consistency Cwh and process completion Lwc are detected;

[0068] The comprehensive evaluation module calculates and evaluates the total operation score Scl based on the operation consistency Cwh and process completion Lwc, generates periodic feedback results, outputs defect location information and training suggestions, and generates corresponding training progress charts and reports.

[0069] In this implementation, the scene construction module restores the virtual intestinal environment through 3D modeling and visual rendering, enhancing the operational realism and perceptual immersion;

[0070] The interactive perception module is based on the intubation angle deviation Cwa, the maximum force pressure value Cwb and the step interval time T i Collect interactive behavior data to achieve synchronous perception of operational actions and physiological responses;

[0071] The data processing module calculates the operation consistency Cwh and process completion Lwc, scientifically evaluating operation accuracy and process control capabilities. The intelligent guidance module automatically triggers corrective feedback when the operation consistency Cwh falls below the threshold C or the process completion Lwc falls below the threshold L, enabling real-time intervention and cognitive compensation.

[0072] The comprehensive evaluation module generates an overall operation score Scl based on the operation consistency Cwh and process completion Lwc, outputs defect localization results including a force exceeding the limit by 23% during the perfusion phase, and training recommendations including the need to strengthen navigation training in intestinal bends, and generates visual charts to support phased learning analysis and self-advanced training.

[0073] Example 2

[0074] The scenario construction module integrates 3D modeling technology with a force feedback simulation engine to interactively model the intestinal anatomical structure. It uses a visual rendering system to present physiological characteristics, including changes in intestinal wall tension, segmental spasms, and dynamic reactions of mucosal folds. It also divides standard nursing procedures, including lubrication, intubation, perfusion, and retrieval, into triggerable scenario events, loading corresponding virtual operation content in real time.

[0075] Secondly, the operating feel is dynamically adjusted by cooperating with the force feedback device, and corresponding reverse resistance, vibration feedback and viscosity simulation force field are applied according to different operating parts and physiological states.

[0076] The interactive perception module uses wearable force feedback gloves, bioelectric sensors, and pressure detectors to build a multimodal acquisition channel to monitor the nursing trainees' movements and physiological responses during virtual intestinal care in real time.

[0077] The force feedback glove is used to collect spatial trajectory and posture data during the intubation process and calculate the intubation angle deviation; the pressure detector is used to measure the maximum pressure value applied by the hand at different stages; the bioelectric sensor is used to record the time interval between each step in the operation rhythm, and expands the collection of skin electrical changes and muscle electrical signals to assist in identifying the trainee's state of tension or fatigue;

[0078] The collected multi-source data are time synchronized and feature extracted, and integrated into a complete set of operation behaviors.

[0079] In this embodiment, the scene construction module uses three-dimensional modeling technology and a force feedback simulation engine to achieve interactive modeling of the intestinal anatomical structure, and uses a visual rendering system to dynamically present physiological characteristics such as changes in intestinal wall tension, segmental spasms, and mucosal wrinkles. In conjunction with the standard operating procedures, nodes such as lubrication, intubation, perfusion, and recovery are divided into triggerable events, and virtual content and multimodal tactile feedback are loaded in real time, including reverse resistance, vibration feedback, and viscous simulation force fields, effectively improving the operational immersion and tactile realism; the interactive perception module combines force feedback gloves, bioelectric sensors, and pressure detectors to construct a multimodal acquisition channel, and obtains key indicators such as intubation angle deviation, maximum force pressure value, and step interval time in real time. It also expands the collection of skin electricity and electromyography signals to identify tension or fatigue states, realizing high-fidelity interactive behavior data collection; this module collaboratively realizes the construction of the virtual operating environment and the collection of data entry, and is the basic core link for subsequent system calculation analysis and intelligent feedback.

[0080] Example 3

[0081] The data processing module includes an operation posture evaluation unit;

[0082] The operation posture evaluation unit extracts the intubation angle deviation Cwa and the maximum applied force pressure value Cwb from the operation behavior set and performs dimensionless processing to calculate the operation consistency Cwh. The specific calculation formula is as follows:

[0083]

[0084] Where, Cwa max is the maximum permissible angular deviation, C std is the standard applied pressure value;

[0085] Based on expert experience, historical high-level operation samples and data statistical analysis, a reference standard is set to obtain the operation consistency threshold C, and then compared and evaluated with the operation consistency Cwh;

[0086] If the operation consistency Cwh ≥ the operation consistency threshold C, the training is considered to have met the standard and the system does not trigger the correction guidance;

[0087] If the operation consistency Cwh is less than the operation consistency threshold C, the intelligent guidance module is triggered to intervene and perform real-time correction and cognitive compensation.

[0088] The data processing module also includes a process rhythm assessment unit;

[0089] The process rhythm evaluation unit extracts the time interval Ti between each step in the set of operation behaviors and calculates the process completion degree Lwc. The specific calculation formula is as follows:

[0090]

[0091] Where, T std is the standard step interval time, n is the total number of operation steps;

[0092] The process completion threshold L is preset based on the execution model of the standard teaching process, the average operation time and accuracy rate specified in the teaching syllabus, and the qualified baseline set after analyzing historical excellent operation data;

[0093] Compare and evaluate the process completion threshold L and the process completion degree Lwc; the specific contents are as follows:

[0094] If the process completion degree Lwc ≥ the process completion threshold L, it means that the trainee has a good overall perception of the operation and control over the process;

[0095] If the process completion degree Lwc is less than the process completion threshold L, the system will push prompts and training suggestions through the intelligent guidance module to help students fill in the process gaps.

[0096] In this embodiment, the data processing module includes an operation posture evaluation unit and a process rhythm evaluation unit. The operation posture evaluation unit extracts the intubation angle deviation Cwa and the maximum force pressure value Cwb from the operation behavior set and performs dimensionless processing to calculate the operation consistency Cwh, which is used to measure the trainee's standardization in posture control and mechanical pressure. If the operation consistency Cwh is greater than or equal to the operation consistency threshold C, it indicates that the posture force is reasonable. If it is lower, the intelligent guidance module is triggered to perform real-time correction.

[0097] The process rhythm assessment unit calculates the process completion degree Lwc by extracting the time interval Ti between each step and combining it with the standard step interval time and the total number of steps n. This degree reflects the rhythm control and process integrity of the operation. If the process completion degree Lwc is greater than or equal to the process completion threshold L, it indicates good operational consistency. If it is lower, the system will push cognitive compensation suggestions and auxiliary training.

[0098] The parameter intubation angle deviation Cwa represents the spatial posture deviation, the maximum force pressure value Cwb reflects the safety of force application, the time interval Ti reflects the smoothness of operation, the operation consistency Cwh and the process completion degree Lwc respectively evaluate the operation quality and process control. As the core data analysis link, this module realizes the transformation from data collection to evaluation indicator generation, providing basic support for subsequent intelligent feedback and scoring.

[0099] Example 4

[0100] The intelligent guidance module includes a vector correction unit;

[0101] The vector correction unit is used to generate a three-dimensional force feedback vector correction command based on the deviation between the actual operation trajectory and the standard path when it detects that the operation consistency Cwh is lower than the set threshold C. This command acts on the operator's hand in real time through the force feedback glove, guiding the operator's hand to adjust its spatial posture and force direction, helping them to adhere to the correct intubation angle and advancement path, achieving refined operation training.

[0102] The intelligent guidance module also includes a cognitive prompting unit;

[0103] The cognitive prompt unit is used to identify the steps that the trainees have missed or are in the wrong order when the process completion degree Lwc is lower than the threshold L, and automatically push the dynamic anatomical structure demonstration, operation process animation or voice prompt corresponding to this stage to enhance their cognitive compensation ability for the step knowledge points and operation rhythm, while supporting interactive pause and review functions.

[0104] In this embodiment, the intelligent guidance module consists of a vector correction unit and a cognitive prompt unit. When the vector correction unit detects that the operation fit Cwh is lower than the set threshold C, it generates a three-dimensional force feedback vector correction instruction based on the spatial deviation between the actual operation trajectory and the standard path, and acts on the operator's hand in real time through the force feedback glove, guiding it to adjust the posture direction and force direction at the same time, so that the intubation operation is closer to the standard trajectory and angle, thereby achieving high-precision spatial operation training; when the process completion degree Lwc is lower than the threshold L, the cognitive prompt unit can intelligently identify the student's omitted or incorrect operation steps, and push multimodal feedback such as corresponding anatomical structure demonstration, operation process animation or voice prompts to enhance their cognitive grasp of knowledge points and operation rhythm, while supporting interactive pause and review functions to improve learning flexibility and personalized adaptability; through a multi-level, dual-channel feedback mechanism, this module realizes operation closed-loop optimization in the two dimensions of posture behavior and cognitive understanding, significantly enhancing the system's real-time guidance ability and correction adaptability in virtual-reality interactive training, and improving the overall teaching effectiveness.

[0105] Example 5

[0106] The comprehensive assessment module includes a scoring analysis unit;

[0107] The scoring analysis unit is used to receive the operation consistency Cwh and process completion Lwc indicators from the data processing module, and calculate the total operation score Scl based on the weight model:

[0108]

[0109] Based on the statistical data of clinical expert scores over the years, and in accordance with the standardized nursing skills training manual and the preset operation specifications, combined with the learning curve and training achievement rate of most trainees, the preset total operation threshold S is calculated and compared with the total operation score Scl for evaluation;

[0110] The specific evaluation contents are as follows:

[0111] When the total operation score Scl ≥ the calculated operation total threshold S, the operation is considered to meet the standard;

[0112] When the total operation score Scl is less than the calculated operation total threshold S, the operation is judged to be substandard. At this time, the defect analysis process is initiated to conduct a fine-grained review of the entire operation process;

[0113] When an operation is determined to be substandard, the defect analysis process, including backtracking logs, event type classification, time node association, and defect label generation, is carried out in sequence to automatically locate the specific defect link.

[0114] Based on the standard operation database, semantic matching is performed on defects, matching suggestion templates are called, and personalized training suggestions are dynamically generated; multiple suggestions are combined and output at the same time.

[0115] Preferably, the score analysis unit further includes a report generation unit;

[0116] The report generation unit is used to integrate the scoring analysis results and operation behavior logs to output stage-by-stage learning feedback reports, including: scoring summary, key defect description, personalized training suggestions, as well as visual operation trajectory charts, scoring trend charts, and learning progress charts;

[0117] The report is displayed in real time and can be exported for teacher evaluation and student self-examination.

[0118] In this embodiment, the comprehensive evaluation module constructs a complete evaluation and feedback system through a scoring analysis unit and a report generation unit. The scoring analysis unit receives the operation consistency Cwh and process completion Lwc indicators, and combines historical expert scoring data, nursing standards, and student training rules to calculate the total operation score Scl through a weighted model to measure the comprehensive performance of the nursing operation in the two dimensions of posture rationality and process integrity. When the total operation score Scl is lower than the calculated operation total threshold S, the defect analysis process is automatically initiated. The operation log is combined to perform backtracking, event classification and time node association, generate defect labels and locate specific problem steps, and then match the suggestion template based on the standard operation database to form a targeted training plan and output multiple suggestions in combination. The report generation unit integrates the scoring data with the operation behavior log to output a staged learning feedback report, including a score summary, key defect description, personalized training suggestions, a visual trajectory diagram, a score trend diagram, and a learning progress chart. It is displayed in real time and can be exported for teaching evaluation and student review. This module realizes quantitative evaluation of training quality and closed-loop tracking of the process, helping teachers accurately grasp teaching effectiveness and helping students achieve continuous, visual, and feedback-based learning progress.

[0119] The logic for generating personalized training suggestions is as follows:

[0120] Problem → suggestion matching mechanism, calling recommendation strategies based on problem type and severity.

[0121] Example 6

[0122] The human-computer interaction virtual-reality simulation method of the enteral nutrition nursing teaching system includes the following steps:

[0123] Step 1: Build a virtual nursing teaching environment, integrating a visual rendering system with a multimodal force feedback device to simulate changes in vital signs, including intestinal tension and spasticity, and generate virtual operation scenarios corresponding to standard operating procedures;

[0124] Step 2: Use force feedback gloves, bioelectric sensors, and pressure detectors to collect interactive data from nursing trainees during virtual operations, including intubation angle deviation, maximum applied force pressure, and the time interval between steps, and summarize them to construct an operation behavior set;

[0125] Step 3: Perform multi-dimensional calculations on the set of operation behaviors to generate and evaluate the operation consistency Cwh, measuring the consistency between the operation posture and the mechanical properties. At the same time, calculate the evaluation process completion Lwc to evaluate the consistency and rhythm of the operation steps.

[0126] Step 4: When the operation consistency Cwh and process completion Lwc are detected to be abnormal, the correction mechanism is triggered respectively, including the force feedback vector correction instruction;

[0127] Step 5: Based on the operation consistency Cwh and process completion Lwc, calculate and evaluate the total operation score Scl, generate phased feedback results, output defect location information and training suggestions, and generate corresponding training progress charts and reports.

[0128] It should be noted that all calculation formulas in this application document utilize, including but not limited to, regression analysis within machine learning algorithms to deeply analyze the collected parameters and identify their natural trends and interrelationships. Professional software, such as Python's Scikit-learn library or the R language, is used to automatically generate mathematical models that match the data. Model performance is then objectively evaluated through methods such as cross-validation, combined with continuous feedback and optimization to ensure that the created formulas truly reflect the inherent laws of the data, thereby guaranteeing their validity and accuracy, and ensuring that the calculation process complies with the constraints of natural laws rather than being based on artificially set rules.

[0129] The technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of various embodiments of the present invention.

[0130] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0131] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0132] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. The human-computer interactive virtual-reality simulation system of the enteral nutrition nursing teaching system is characterized by: It includes scenario construction module, interactive perception module, data processing module, intelligent guidance module and comprehensive evaluation module; The scenario construction module is used to build a virtual nursing teaching environment, integrating a visual rendering system with a multimodal force feedback device to simulate changes in vital signs, including intestinal tension and spasm, and generate virtual operation scenarios corresponding to standard operating procedures; The interactive perception module is used to collect interactive data of nursing trainees during virtual operations through force feedback gloves, bioelectric sensors, and pressure detectors, including intubation angle deviation, maximum applied force pressure value, and time interval between steps, and summarize them to construct an operational behavior set; The data processing module is used to perform multi-dimensional calculations on the set of operation behaviors, generate and evaluate the operation consistency Cwh, and measure the conformity between the operation posture and the mechanics. At the same time, it calculates the evaluation process completion Lwc to evaluate the consistency and rhythm rationality of the operation steps. The intelligent guidance module is used to trigger the correction mechanism, including force feedback vector correction instructions, when abnormal operation consistency Cwh and process completion Lwc are detected; The comprehensive evaluation module calculates and evaluates the total operation score Scl based on the operation consistency Cwh and process completion Lwc, generates periodic feedback results, outputs defect location information and training suggestions, and generates corresponding training progress charts and reports.

2. The human-computer interaction virtual-reality simulation system of the enteral nutrition nursing teaching system according to claim 1 is characterized by: The scenario construction module integrates 3D modeling technology with a force feedback simulation engine to interactively model the intestinal anatomical structure. It uses a visual rendering system to present physiological characteristics, including changes in intestinal wall tension, segmental spasms, and dynamic reactions of mucosal folds. It also divides standard nursing procedures, including lubrication, intubation, perfusion, and retrieval, into triggerable scenario events, loading corresponding virtual operation content in real time. Secondly, the operating feel is dynamically adjusted by cooperating with the force feedback device, and corresponding reverse resistance, vibration feedback and viscosity simulation force field are applied according to different operating parts and physiological states.

3. The human-computer interaction virtual-reality simulation system of the enteral nutrition nursing teaching system according to claim 2 is characterized by: The interactive perception module uses wearable force feedback gloves, bioelectric sensors, and pressure detectors to build a multimodal acquisition channel to monitor the nursing trainees' movements and physiological responses during virtual intestinal care in real time. The force feedback glove is used to collect spatial trajectory and posture data during the intubation process and calculate the intubation angle deviation; the pressure detector is used to measure the maximum pressure value applied by the hand at different stages; the bioelectric sensor is used to record the time interval between each step in the operation rhythm, and expands the collection of skin electrical changes and muscle electrical signals to assist in identifying the trainee's state of tension or fatigue; The collected multi-source data are time synchronized and feature extracted, and integrated into a complete set of operation behaviors.

4. The human-computer interaction virtual-reality simulation system of the enteral nutrition nursing teaching system according to claim 3 is characterized by: The data processing module includes an operation posture evaluation unit; The operation posture evaluation unit extracts the intubation angle deviation Cwa and the maximum applied force pressure value Cwb from the operation behavior set and performs dimensionless processing to calculate the operation consistency Cwh; Based on expert experience, historical high-level operation samples and data statistical analysis, a reference standard is set to obtain the operation consistency threshold C, and then compared and evaluated with the operation consistency Cwh; If the operation consistency Cwh ≥ the operation consistency threshold C, the training is considered to have met the standard and the system does not trigger the correction guidance; If the operation consistency Cwh is less than the operation consistency threshold C, the intelligent guidance module is triggered to intervene and perform real-time correction and cognitive compensation.

5. The human-computer interaction virtual-reality simulation system of the enteral nutrition nursing teaching system according to claim 4 is characterized by: The data processing module also includes a process rhythm assessment unit; The process rhythm evaluation unit extracts the time interval Ti between each step in the set of operation behaviors and calculates the process completion degree Lwc; The process completion threshold L is preset based on the execution model of the standard teaching process, the average operation time and accuracy rate specified in the teaching syllabus, and the qualified baseline set after analyzing historical excellent operation data; Compare and evaluate the process completion threshold L and the process completion degree Lwc; the specific contents are as follows: If the process completion degree Lwc ≥ the process completion threshold L, it means that the trainee has a good overall perception of the operation and control over the process; If the process completion degree Lwc is less than the process completion threshold L, the system will push prompts and training suggestions through the intelligent guidance module to help students fill in the process loopholes.

6. The human-computer interaction virtual-reality simulation system of the enteral nutrition nursing teaching system according to claim 5 is characterized by: The intelligent guidance module includes a vector correction unit; The vector correction unit is used to generate a three-dimensional force feedback vector correction command based on the deviation between the actual operation trajectory and the standard path when it detects that the operation consistency Cwh is lower than the set threshold C. This command acts on the operator's hand in real time through the force feedback glove, guiding the operator's hand to adjust its spatial posture and force direction, helping them to adhere to the correct intubation angle and advancement path, achieving refined operation training.

7. The human-computer interactive virtual-reality simulation system for the enteral nutrition nursing teaching system according to claim 6 is characterized by: The intelligent guidance module also includes a cognitive prompting unit; The cognitive prompt unit is used to identify the steps that the trainees have missed or are in the wrong order when the process completion degree Lwc is lower than the threshold L, and automatically push the dynamic anatomical structure demonstration, operation process animation or voice prompt corresponding to this stage to enhance their cognitive compensation ability for the step knowledge points and operation rhythm, while supporting interactive pause and review functions.

8. The human-computer interactive virtual-reality simulation system for the enteral nutrition nursing teaching system according to claim 7 is characterized by: The comprehensive assessment module includes a scoring analysis unit; The scoring analysis unit is used to receive the operation consistency Cwh and process completion Lwc indicators from the data processing module and calculate the total operation score based on the weight model; Based on the statistical data of clinical expert scores over the years, and in accordance with the standardized nursing skills training manual and the preset operation specifications, combined with the learning curve and training achievement rate of most trainees, the preset total operation threshold S is calculated and compared with the total operation score Scl for evaluation; The specific evaluation contents are as follows: When the total operation score Scl ≥ the calculated operation total threshold S, the operation is considered to meet the standard; When the total operation score Scl is less than the calculated operation total threshold S, the operation is judged to be substandard. At this time, the defect analysis process is initiated to conduct a fine-grained review of the entire operation process; When an operation is determined to be substandard, the defect analysis process, including backtracking logs, event type classification, time node association, and defect label generation, is carried out in sequence to automatically locate the specific defect link. Based on the standard operation database, semantic matching is performed on defects, matching suggestion templates are called, and personalized training suggestions are dynamically generated; multiple suggestions are combined and output at the same time.

9. The human-computer interactive virtual-reality simulation system for enteral nutrition nursing teaching system according to claim 8, characterized in that: The scoring analysis unit also includes a report generation unit; The report generation unit is used to integrate the scoring analysis results and operation behavior logs to output stage-by-stage learning feedback reports, including: scoring summary, key defect description, personalized training suggestions, as well as visual operation trajectory charts, scoring trend charts, and learning progress charts; The report is displayed in real time and can be exported for teacher evaluation and student self-examination.

10. A human-computer interaction virtual-reality simulation method for an enteral nutrition nursing teaching system, characterized by: The human-computer interaction virtual-reality simulation method of the enteral nutrition nursing teaching system is used to execute the human-computer interaction virtual-reality simulation system of the enteral nutrition nursing teaching system according to any one of claims 1 to 9, comprising: Step 1: Build a virtual nursing teaching environment, integrating a visual rendering system with a multimodal force feedback device to simulate changes in vital signs, including intestinal tension and spasticity, and generate virtual operation scenarios corresponding to standard operating procedures; Step 2: Use force feedback gloves, bioelectric sensors, and pressure detectors to collect interactive data from nursing trainees during virtual operations, including intubation angle deviation, maximum applied force pressure, and the time interval between steps, and summarize them to construct an operation behavior set; Step 3: Perform multi-dimensional calculations on the set of operation behaviors to generate and evaluate the operation consistency Cwh, measuring the consistency between the operation posture and the mechanical properties. At the same time, calculate the evaluation process completion Lwc to evaluate the consistency and rhythm of the operation steps. Step 4: When the operation consistency Cwh and process completion Lwc are detected to be abnormal, the correction mechanism is triggered respectively, including the force feedback vector correction instruction; Step 5: Based on the operation consistency Cwh and process completion Lwc, calculate and evaluate the total operation score Scl, generate phased feedback results, output defect location information and training suggestions, and generate corresponding training progress charts and reports.

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