Virtual reality rehabilitation training system for rehabilitation nursing combining traditional Chinese medicine and western medicine after coronary heart disease PCI (percutaneous coronary intervention) operation

Abstract

The invention relates to a virtual reality rehabilitation training system for coronary heart disease PCI postoperation traditional Chinese and western medicine combined rehabilitation nursing, which comprises the following steps of: acquiring physiological signs and meridian information of a patient after coronary heart disease PCI postoperation to obtain multi-dimensional physiological state data of the patient; performing traditional Chinese medicine syndrome type identification and western medicine index quantitative analysis on the patient based on the multi-dimensional physiological state data of the patient to obtain a health state evaluation result of the traditional Chinese medicine and western medicine combined patient; performing personalized scene element configuration and interactive logic design on a preset virtual reality scene based on the combination of the traditional Chinese medicine and the western medicine and the patient health state evaluation result to obtain a customized virtual rehabilitation training scene; immersive virtual reality rehabilitation training is carried out on the patient through the customized virtual rehabilitation training scene, training interaction data is obtained, and the key problem that quantitative analysis of western medicine indexes is often emphasized and the overall physical condition reflected by traditional Chinese medicine syndrome types is neglected when a traditional rehabilitation means is used for evaluating the health state of the patient is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of coronary heart disease, and in particular to a virtual reality rehabilitation training system for integrated traditional Chinese and western medicine rehabilitation nursing after PCI surgery for coronary heart disease. Background Art

[0002] Coronary heart disease (CAD) is a common cardiovascular disease that poses a serious threat to human health. While percutaneous coronary intervention (PCI) can effectively recanalize obstructed coronary arteries and restore blood flow, it is not a permanent solution. Some patients still face numerous challenges after surgery, including coronary artery lesions, in-stent restenosis, decreased exercise tolerance, poor quality of life, and anxiety and depression.

[0003] Conventional rehabilitation training scenarios lack personalization and interest, making it difficult to motivate patients to participate, resulting in poor compliance and effectiveness. Furthermore, existing rehabilitation processes lack timely and accurate feedback and adjustments from patients, and efficacy evaluations are incomplete, making it difficult to dynamically optimize rehabilitation plans based on patients' actual progress.

[0004] Traditional Chinese Medicine (TCM) theory and practice offer unique advantages in the field of disease rehabilitation. For example, TCM exercise rehabilitation modalities such as Tai Chi and Ba Duan Jin, guided by meridian theory, can unclog meridians, promote the circulation of Qi and blood, and improve organ function. However, the current application of TCM exercise rehabilitation after PCI for coronary heart disease presents numerous challenges, including insufficient observation of long-term efficacy, small sample sizes and a lack of standardized standards in controlled clinical trials, and unclear therapeutic mechanisms. Therefore, it is urgent to explore new approaches that combine the strengths of both traditional Chinese and Western medicine and leverage modern scientific and technological means to achieve precise assessment, personalized rehabilitation training, and comprehensive efficacy evaluation. Summary of the Invention

[0005] The main purpose of the present invention is to provide a virtual reality rehabilitation training method for combined Chinese and Western medicine rehabilitation nursing after PCI surgery for coronary heart disease, which solves the key problem that traditional rehabilitation methods often focus on the quantitative analysis of Western medicine indicators when assessing the patient's health status, while ignoring the overall physical condition reflected by the Chinese medicine syndrome types.

[0006] To achieve the above objectives, the present invention provides a virtual reality rehabilitation training system for integrated Chinese and Western medicine rehabilitation nursing after PCI surgery for coronary heart disease, comprising: The acquisition module is used to collect physiological signs and meridian information from patients undergoing PCI for coronary heart disease through a multimodal physiological data acquisition system to obtain multi-dimensional patient physiological status data; An analysis module is used to identify the TCM syndrome type and conduct quantitative analysis of Western medicine indicators for the patient based on the multi-dimensional patient physiological status data, and obtain a health status assessment result of the patient using integrated TCM and Western medicine; A design module is used to configure personalized scene elements and interactive logic for a preset virtual reality scene based on the health status assessment results of the integrated Chinese and Western medicine patient, thereby obtaining a customized virtual rehabilitation training scene; The training module is used to perform immersive virtual reality rehabilitation training on the patient through the customized virtual rehabilitation training scene to obtain training interaction data, wherein the training interaction data is used to provide real-time feedback adjustment and efficacy evaluation to the patient.

[0007] The present invention also provides a virtual reality rehabilitation training method for integrated traditional Chinese and Western medicine rehabilitation nursing after PCI surgery for coronary heart disease, comprising the following steps: Through the multimodal physiological data acquisition system, physiological signs and meridian information of patients with coronary heart disease who have undergone PCI are collected to obtain multi-dimensional patient physiological status data; Based on the multi-dimensional patient physiological status data, the patient is identified by TCM syndrome type and quantitatively analyzed by Western medicine indicators to obtain a health status assessment result of the patient combined with TCM and Western medicine; Based on the health status assessment results of the integrated Chinese and Western medicine patient, personalized scene element configuration and interactive logic design are performed on the preset virtual reality scene to obtain a customized virtual rehabilitation training scene; The patient is subjected to immersive virtual reality rehabilitation training through the customized virtual rehabilitation training scene to obtain training interaction data, wherein the training interaction data is used to provide real-time feedback adjustment and efficacy evaluation to the patient.

[0008] Furthermore, the multimodal physiological data acquisition system is used to collect physiological signs and meridian information from patients undergoing PCI for coronary heart disease, thereby obtaining multi-dimensional patient physiological status data, including: The multimodal physiological data acquisition system is used to collect physiological sign data of heart rate, blood pressure, blood oxygen saturation, and respiratory rate from patients undergoing PCI for coronary heart disease to obtain the patient's physiological sign data, and the patient's physiological sign data is subjected to real-time noise filtering and data smoothing to obtain smoothed physiological sign data; Acquiring meridian information of the patient through a multimodal physiological data acquisition system to obtain original meridian data of the patient, and performing acupoint positioning and feature extraction on the original meridian data of the patient to obtain meridian feature data of the patient; Multi-source data fusion and information association analysis are performed based on the smoothed physiological sign data and the patient meridian characteristic data to obtain multi-dimensional patient physiological state data.

[0009] Furthermore, based on the multi-dimensional patient physiological status data, the patient is subjected to TCM syndrome type identification and Western medicine index quantitative analysis to obtain a TCM and Western medicine combined patient health status assessment result, including: Performing wavelet decomposition processing on the multi-dimensional patient physiological state data to obtain patient physiological characteristic basic data, and performing time-frequency feature extraction on the patient physiological characteristic basic data to obtain a patient physiological characteristic sequence; Performing TCM tongue and pulse feature mapping on the patient's physiological feature sequence to obtain basic syndrome identification data, and performing multi-level syndrome classification on the basic syndrome identification data to obtain a TCM syndrome feature index group; The TCM syndrome characteristic index group is converted into corresponding Western medicine indicators through the physiological-syndrome association analysis method to obtain a multi-dimensional evaluation feature set, and the multi-dimensional evaluation feature set is subjected to hierarchical quantitative processing to obtain a TCM and Western medicine integration parameter matrix; Based on the TCM and Western medicine integration parameter matrix, the patient's multi-dimensional health status is quantitatively evaluated to obtain an initial evaluation data set, and the initial evaluation data set is verified for syndrome-sign association to obtain a TCM and Western medicine integration patient health status evaluation result.

[0010] Furthermore, based on the health status assessment results of the integrated Chinese and Western medicine patient, personalized scene element configuration and interactive logic design are performed on the preset virtual reality scene to obtain a customized virtual rehabilitation training scene, including: Performing rehabilitation load grading processing on the health status assessment results of the integrated Chinese and Western medicine patient to obtain patient rehabilitation ability grading data, and performing scene element mapping on a preset virtual reality scene based on the patient rehabilitation ability grading data to obtain a scene basic configuration parameter set; Performing interactive element layout design on the scene basic configuration parameter set to obtain a scene interaction layout scheme, and performing dynamic difficulty adjustment rule configuration on the scene interaction layout scheme to obtain a scene interaction rule; Performing spatial rendering processing on the scene interaction rules through a scene rendering engine to obtain a scene rendering data stream, and performing real-time physical property calculation based on the scene rendering data stream to obtain a scene physical parameter set; Planning the motion trajectory of a virtual object in a virtual reality scene based on the scene physical parameter set to obtain object motion control data, and performing interactive logic design and human-computer interaction mapping on the object motion control data to obtain an interactive response configuration scheme; The interactive response configuration scheme is subjected to scene integration processing to obtain scene combination configuration data, and the scene combination configuration data is subjected to traditional Chinese medicine meridian fusion optimization to obtain a customized virtual rehabilitation training scene.

[0011] Furthermore, the scene elements of the preset virtual reality scene are mapped based on the patient rehabilitation ability classification data to obtain a scene basic configuration parameter set, including: Performing physiological load threshold analysis on the patient's rehabilitation ability grading data to obtain a rehabilitation training intensity grading index, and performing hierarchical progressive conversion on the rehabilitation training intensity grading index to obtain a scenario difficulty gradient matrix; Performing virtual scene space coordinate division based on the scene difficulty gradient matrix to obtain scene space layout parameters, and performing dynamic threshold setting on the scene space layout parameters to obtain scene environment control parameters; Performing spatial mapping analysis on the scene environment control parameters through a meridian acupoint locator to obtain an acupoint activation area distribution map, and performing three-dimensional projection conversion on the acupoint activation area distribution map to obtain a scene interaction node matrix; Performing physical property configuration on the virtual object based on the scene interaction node matrix to obtain an object attribute parameter set, and performing spatial correlation processing on the object attribute parameter set to obtain scene element configuration data; The scene element configuration data is mapped to light and shadow effects using a preset scene rendering algorithm to obtain a scene rendering parameter group, and the scene rendering parameter group is optimized as a whole to obtain a scene basic configuration parameter set.

[0012] Furthermore, the light and shadow effect mapping is performed on the scene element configuration data by a preset scene rendering algorithm to obtain a scene rendering parameter group, including: Performing spatial illumination distribution calculation on the scene element configuration data to obtain scene basic illumination parameters, and performing TCM element mapping on the scene basic illumination parameters to obtain a scene atmosphere configuration matrix; Analyzing the material reflection characteristics of the scene atmosphere configuration matrix using a preset scene rendering algorithm to obtain surface material rendering parameters, and performing multi-level texture mapping on the surface material rendering parameters to obtain a scene texture feature set; Performing shadow casting calculation on the virtual object based on the scene texture feature set to obtain dynamic shadow mapping data, and performing spatial depth fusion on the dynamic shadow mapping data to obtain a stereoscopic perception parameter group; The stereoscopic perception parameter group is subjected to post-processing for special effects to obtain a visual optimization parameter set, and an overall effect synthesis is performed based on the visual optimization parameter set to obtain a scene rendering parameter group.

[0013] Furthermore, the patient is subjected to immersive virtual reality rehabilitation training through the customized virtual rehabilitation training scene to obtain training interaction data, including: Performing multi-channel physiological sensing acquisition configuration on the customized virtual rehabilitation training scene to obtain a training scene physiological monitoring parameter set, and performing dynamic threshold setting on the training scene physiological monitoring parameter set to obtain a physiological parameter monitoring threshold matrix; Performing real-time pulse waveform acquisition on the patient by a photoplethysmography sensor to obtain a pulse waveform feature data stream, and performing traditional Chinese medicine pulse feature extraction on the pulse waveform feature data stream to obtain a real-time pulse dynamic feature set; Based on the physiological parameter monitoring threshold matrix and the real-time pulse dynamic feature set, the patient's exercise load is monitored in real time to obtain training process monitoring data, and the training process monitoring data is subjected to multi-dimensional feature correlation analysis to obtain a training status evaluation index group; A training interaction response analysis is performed on the training state evaluation indicator group to obtain a training interaction feature sequence, and a training effect quantification process is performed based on the training interaction feature sequence to obtain training interaction data.

[0014] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the above methods when executing the computer program.

[0015] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of any of the above methods are implemented.

[0016] The present invention provides a virtual reality rehabilitation training method for integrated Chinese and Western medicine rehabilitation nursing after PCI surgery for coronary heart disease, comprising the following steps: collecting physiological signs and meridian information of patients after PCI surgery for coronary heart disease to obtain multi-dimensional patient physiological status data; identifying Chinese medicine syndrome types and quantitatively analyzing Western medicine indicators of the patients based on the multi-dimensional patient physiological status data to obtain an assessment result of the health status of the integrated Chinese and Western medicine patients; configuring personalized scene elements and interactive logic design of a preset virtual reality scene based on the assessment result of the health status of the integrated Chinese and Western medicine patients to obtain a customized virtual rehabilitation training scene; performing immersive virtual reality rehabilitation training on the patients through the customized virtual rehabilitation training scene to obtain training interaction data, thereby solving the problem that traditional rehabilitation methods often focus on quantitative analysis of Western medicine indicators when assessing the health status of patients, while ignoring the key problem of the overall physical condition reflected by Chinese medicine syndrome types, realizing real-time feedback adjustment and efficacy evaluation of patients using training interaction data, and being able to timely grasp the patient's physical reaction and rehabilitation progress during the training process. Based on real-time feedback, the intensity, content and methods of training can be adjusted in a timely manner to ensure the safety and effectiveness of rehabilitation training; through comprehensive efficacy evaluation, the rehabilitation effect can be judged more accurately, and the rehabilitation plan can be dynamically optimized according to the evaluation results to achieve precise and scientific rehabilitation training, and promote patients to better recover their health. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1This is a schematic diagram of the steps of a virtual reality rehabilitation training method for integrated traditional Chinese and Western medicine rehabilitation nursing for coronary heart disease after PCI surgery in one embodiment of the present invention; Figure 2 This is a structural block diagram of a virtual reality rehabilitation training device for integrated Chinese and Western medicine rehabilitation nursing for coronary heart disease after PCI surgery in one embodiment of the present invention; Figure 3 It is a schematic block diagram of the structure of a computer device according to an embodiment of the present invention.

[0018] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0020] like Figure 1 As shown, Figure 1 This is a schematic diagram of the steps of a virtual reality rehabilitation training method for integrated traditional Chinese and Western medicine rehabilitation nursing for coronary heart disease after PCI surgery in one embodiment of the present invention; In one embodiment of the present invention, a virtual reality rehabilitation training method for integrated traditional Chinese and Western medicine rehabilitation nursing for coronary heart disease after PCI surgery is provided, comprising the following steps: Step S1: The multimodal physiological data acquisition system is used to collect physiological signs and meridian information of patients undergoing PCI for coronary heart disease to obtain multi-dimensional physiological status data of the patients.

[0021] Specifically, in rehabilitation care following PCI for coronary heart disease, a multimodal physiological data acquisition system plays a key role. It collects patient physiological signs and meridian information, thereby generating multidimensional data on the patient's physiological status. This system integrates multiple advanced sensing technologies and data collection methods to comprehensively and accurately gather information related to the patient's health status. Regarding physiological sign collection, the system uses a variety of sensors to monitor the patient's vital signs. For example, a heart rate sensor continuously monitors heart rate fluctuations, providing real-time insights into the heart's beat rate and rhythm. A blood pressure sensor regularly measures the patient's blood pressure, identifying fluctuations and assessing the stress level of the cardiovascular system. A respiratory sensor also records parameters such as breathing rate and depth to analyze whether respiratory function is normal. Regarding meridian information collection, the system utilizes detection technologies based on Traditional Chinese Medicine meridian theory to obtain meridian information. For example, a meridian resistance meter measures changes in resistance at acupoints on the human body to understand the flow of qi and blood within the meridians. Abnormal resistance values ​​at different meridian acupoints may indicate dysfunction of the corresponding internal organs. For example, an abnormal increase in the resistance value of a heart meridian acupoint may indicate a problem with heart function. By integrating physiological signs and meridian information, the system can obtain multi-dimensional data on the patient's physiological status. This data is like a detailed health map, providing a solid foundation for subsequent identification of TCM syndrome types and quantitative analysis of Western medicine indicators. For example, if a patient has a fast heart rate, unstable blood pressure, and abnormal resistance values ​​at the heart meridian acupoints, the combination of these data can more accurately assess the patient's health status, thereby providing a basis for formulating a personalized rehabilitation plan.

[0022] Step S2: Based on the multi-dimensional patient physiological status data, the patient is subjected to TCM syndrome type identification and Western medicine index quantitative analysis to obtain a TCM and Western medicine combined patient health status assessment result.

[0023] Specifically, after obtaining multi-dimensional patient physiological status data, the patient's TCM syndrome type is identified and quantitative Western medicine indicators are analyzed to obtain a comprehensive assessment of the patient's health status. First, TCM syndrome type identification is based on traditional Chinese medicine theory, combining meridian information and selected physiological signs from the multi-dimensional patient physiological status data. Traditional Chinese medicine believes that the human body is an organic whole, and the flow of qi and blood in the meridians is closely related to the function of the internal organs. Different TCM syndromes correspond to specific meridian qi and blood changes and physical manifestations. For example, if meridian information indicates poor liver meridian qi and blood flow, and the patient experiences physiological signs such as irritability and flank pain, this may be a syndrome of liver qi stagnation. Then, quantitative Western medicine indicator analysis focuses on scientifically quantifying the various physiological signs in the multi-dimensional patient physiological status data. Using modern medical standards and methods, indicators such as heart rate, blood pressure, and blood sugar are compared with normal ranges to calculate the degree of deviation and associated risk factors for each indicator. For example, if a patient's blood pressure is consistently above the normal range and fluctuates widely, the severity of their hypertension and the potential risk of developing cardiovascular disease can be quantitatively assessed. Finally, the results of TCM syndrome type identification and the quantitative analysis of Western medicine indicators are combined to form a comprehensive TCM and Western medicine-integrated health status assessment of the patient. Such an assessment not only incorporates TCM's understanding of the patient's overall physical condition and internal pathogenesis, but is also supported by Western medicine's precise quantitative indicators, and can more accurately and comprehensively reflect the patient's health status. For example, for a patient undergoing PCI surgery for coronary heart disease, a more targeted and personalized TCM and Western medicine-integrated rehabilitation plan can be developed by combining the TCM-identified Qi and Yin deficiency syndromes and the abnormal cardiac function indicators obtained through Western medicine quantitative analysis.

[0024] Step S3: Based on the health status assessment results of the integrated Chinese and Western medicine patient, personalized scene element configuration and interactive logic design are performed on the preset virtual reality scene to obtain a customized virtual rehabilitation training scene.

[0025] Specifically, after obtaining the combined Traditional Chinese Medicine and Western Medicine assessment results for a patient's health status, the pre-set VR scene can be personalized with scene elements and interaction logic, resulting in a customized virtual rehabilitation training scenario. The pre-set VR scene is initially a general framework, but to better meet the patient's specific needs, it needs to be individually adjusted based on the assessment results. The scene element configuration will fully consider the patient's Traditional Chinese Medicine syndrome type and Western medicine quantitative indicators. For example, if Traditional Chinese Medicine symptoms indicate Qi and Blood deficiency, the scene can be configured with elements that promote Qi and Blood regulation, such as simulating a natural environment with abundant sunlight and lush vegetation. Traditional Chinese Medicine believes that the yang energy and vitality of nature contribute to the growth of Qi and Blood. Furthermore, based on Western medicine indicators, if the patient's heart function is weak, the intensity and pace of the exercise in the scene can be reduced accordingly. For example, a scene that originally featured a fast run could be changed to a slow walk to avoid excessive stress on the patient's heart. The interaction logic design is also based on the assessment results. For patients with good recovery conditions and strong physical functions, some challenging and interactive tasks can be designed, such as completing some simple mountain climbing tasks in a virtual scene, and enhancing the patient's athletic ability through actions such as climbing and crossing obstacles. For patients with weaker bodies, some simple interactive activities can be designed, such as performing easy gardening work in a virtual garden, such as watering and fertilizing, which can allow patients to participate in activities without over-exerting their physical strength. Through such personalized scene element configuration and interactive logic design, the final customized virtual rehabilitation training scene can closely focus on the patient's specific health status, provide them with a more accurate and effective rehabilitation training experience, and help patients with coronary heart disease recover better after PCI surgery.

[0026] Step S4: performing immersive virtual reality rehabilitation training on the patient through the customized virtual rehabilitation training scene to obtain training interaction data, wherein the training interaction data is used to provide real-time feedback adjustment and efficacy evaluation to the patient.

[0027] Specifically, after obtaining a customized virtual rehabilitation training scene, it can be used to conduct immersive virtual reality rehabilitation training for patients undergoing PCI for coronary artery disease. Training interaction data is also collected for real-time feedback, adjustments, and efficacy evaluation. When patients enter the customized virtual rehabilitation training scene, they feel as if they are immersed in a rehabilitation world created specifically for them, allowing them to fully immerse themselves in the training. During training, the system continuously collects information about the patient's interaction with the scene, which is known as training interaction data. For example, if the scene is a virtual garden and the patient engages in gardening activities, the system will record data such as the speed, force, and accuracy of each movement. If the patient engages in virtual limb movement training, the system will collect information such as the range of motion and frequency of movement. This training interaction data plays an important role. Firstly, it can provide patients with real-time feedback and adjustments. For example, if the system detects that a patient's steps are too small and their speed is too slow during virtual walking, which may indicate physical weakness or psychological concerns, the system will immediately issue a prompt to encourage the patient to increase their steps and speed appropriately. Furthermore, the training difficulty and pace of the scene can be dynamically adjusted based on the patient's real-time physical reactions. If the patient experiences a rapid heart rate during training, the system will automatically reduce the intensity of the activity in the scene to ensure the patient's safety. On the other hand, training interaction data can be used to evaluate the effectiveness of the treatment. By collecting and analyzing this data over a long period of time and comparing the patient's training performance at different stages, the effectiveness of the rehabilitation training can be objectively judged. For example, if a patient takes a long time to complete a virtual gardening task and is not skilled in the movements at the beginning of training, but after a period of training, the time to complete the task is significantly shortened and the movements are more precise, this indicates that the rehabilitation training has achieved positive results. With the help of these evaluation results, doctors can further optimize rehabilitation plans and provide patients with better rehabilitation services.

[0028] In a specific embodiment, the multimodal physiological data acquisition system is used to collect physiological signs and meridian information from patients undergoing PCI for coronary heart disease to obtain multi-dimensional patient physiological status data, including: The multimodal physiological data acquisition system is used to collect physiological sign data of heart rate, blood pressure, blood oxygen saturation, and respiratory rate from patients undergoing PCI for coronary heart disease to obtain the patient's physiological sign data, and the patient's physiological sign data is subjected to real-time noise filtering and data smoothing to obtain smoothed physiological sign data; Acquiring meridian information of the patient through a multimodal physiological data acquisition system to obtain original meridian data of the patient, and performing acupoint positioning and feature extraction on the original meridian data of the patient to obtain meridian feature data of the patient; Multi-source data fusion and information association analysis are performed based on the smoothed physiological sign data and the patient meridian characteristic data to obtain multi-dimensional patient physiological state data.

[0029] Specifically, in rehabilitation care after PCI for coronary heart disease, acquiring multidimensional patient physiological status data through a multimodal physiological data acquisition system is a critical first step. This process includes collecting and processing patient vital signs data, collecting and extracting meridian information, and performing multi-source data fusion and information correlation analysis. The first step is the collection and processing of patient vital signs data. The multimodal physiological data acquisition system focuses on collecting key physiological signs such as heart rate, blood pressure, blood oxygen saturation, and respiratory rate for patients undergoing PCI for coronary heart disease. For example, the heart rate of a normal adult at rest is generally between 60 and 100 beats per minute. However, the heart rate of patients undergoing PCI for coronary heart disease may fluctuate due to factors such as surgical trauma and psychological stress. If a patient's heart rate remains above 100 beats per minute after surgery, it may indicate excessive cardiac strain or the presence of other complications. Blood pressure is also a key monitoring indicator. Normal blood pressure ranges are 90-139 mmHg for systolic pressure and 60-89 mmHg for diastolic pressure. Abnormally high or low blood pressure in postoperative patients can affect cardiac blood perfusion and recovery. Blood oxygen saturation reflects the oxygen content in the blood. Normally, it should be between 95% and 100%. A persistently low blood oxygen saturation below 95% may indicate problems with lung gas exchange or cardiac blood supply. Regarding respiratory rate, the normal respiratory rate for a resting adult is 12-20 breaths per minute. Changes in respiratory rate in postoperative patients may be related to factors such as pain and dyspnea. After collecting these physiological data, noise may be present due to interference from the external environment, instrumentation, and other factors. Therefore, real-time noise filtering and smoothing are necessary. For example, when collecting heart rate data, even the slightest movement of the patient may generate abnormal high-frequency noise. Filtering can remove this noise, making the data more accurate. Data smoothing further optimizes the data, making its trends more stable. The smoothed physiological sign data obtained after processing can more accurately reflect the patient's physiological state. Next, the patient's meridian information is collected and processed. The multimodal physiological data acquisition system collects meridian information from the patient, obtaining the patient's raw meridian data. Traditional Chinese Medicine believes that the human meridian system is closely related to the function of the internal organs. In Traditional Chinese Medicine theory, coronary heart disease is associated with poor circulation of Qi and blood in meridians such as the Heart Meridian and Pericardium Meridian. By collecting meridian information, the state of the patient's meridian Qi and blood can be understood. After collecting the raw meridian data, acupoint localization and feature extraction are required. Acupoint localization involves determining the exact location of each acupoint on the meridian, as the Qi and blood status of different acupoints may reflect different internal organ functions. For example, if the Shenmen acupoint on the Heart Meridian has abnormal Qi and blood flow, it may indicate problems with heart function.Feature extraction extracts key information reflecting the patient's meridian status from the raw meridian data, generating meridian feature data. Finally, the smoothed physiological sign data and the patient's meridian feature data undergo multi-source data fusion and information correlation analysis. Multi-source data fusion integrates data from different sources to make the data more comprehensive and rich. Information correlation analysis identifies the intrinsic connections between physiological sign data and meridian feature data. For example, when a patient's heart rate is abnormally elevated, correlation analysis may reveal corresponding changes in the Qi and blood flow of certain acupoints on the heart meridian. Through this multi-source data fusion and information correlation analysis, multi-dimensional data on the patient's physiological status can be obtained. This data not only contains physiological sign information of interest to Western medicine, but also incorporates meridian information from Traditional Chinese Medicine (TCM). This provides a more comprehensive and accurate basis for subsequent TCM syndrome type identification and Western medicine indicator quantitative analysis, thereby facilitating the development of more personalized and effective rehabilitation training programs to promote recovery in patients undergoing PCI for coronary artery disease.

[0030] In a specific embodiment, the identification of TCM syndrome types and quantitative analysis of Western medicine indicators are performed on the patient based on the multi-dimensional patient physiological status data to obtain a TCM and Western medicine combined patient health status assessment result, including: Performing wavelet decomposition processing on the multi-dimensional patient physiological state data to obtain patient physiological characteristic basic data, and performing time-frequency feature extraction on the patient physiological characteristic basic data to obtain a patient physiological characteristic sequence; Performing TCM tongue and pulse feature mapping on the patient's physiological feature sequence to obtain basic syndrome identification data, and performing multi-level syndrome classification on the basic syndrome identification data to obtain a TCM syndrome feature index group; The TCM syndrome characteristic index group is converted into corresponding Western medicine indicators through the physiological-syndrome association analysis method to obtain a multi-dimensional evaluation feature set, and the multi-dimensional evaluation feature set is subjected to hierarchical quantitative processing to obtain a TCM and Western medicine integration parameter matrix; Based on the TCM and Western medicine integration parameter matrix, the patient's multi-dimensional health status is quantitatively evaluated to obtain an initial evaluation data set, and the initial evaluation data set is verified for syndrome-sign association to obtain a TCM and Western medicine integration patient health status evaluation result.

[0031] Specifically, after acquiring multidimensional patient physiological status data, a series of processing steps are required to identify TCM syndrome types and quantify Western medicine indicators, thereby generating a comprehensive assessment of the patient's health status. This process is like drawing a precise health portrait for the patient, analyzing their physical condition from multiple dimensions and providing key insights for the development of subsequent rehabilitation plans. First, wavelet decomposition is performed on the multidimensional patient physiological status data. Wavelet decomposition can break down complex physiological data into different scales, extracting hidden information within the data and obtaining basic data on the patient's physiological characteristics. For example, consider the heart rate data of patients undergoing PCI for coronary artery disease. While normal heart rates fluctuate between 60 and 100 beats per minute, postoperative heart rates can experience irregular fluctuations due to stress responses. Wavelet decomposition can separate the high- and low-frequency information contained in these fluctuations. The high-frequency component may reflect momentary changes in the patient's heart rate, such as an increase caused by activity or emotional fluctuations. The low-frequency component reflects the long-term trend of the heart rate. If the low-frequency component shows a sustained increase in heart rate, it may indicate a problem with cardiac function. Next, time-frequency features are extracted from the patient's basic physiological data, combining information from both time and frequency dimensions to generate a patient physiological feature sequence. This is like establishing a time-frequency coordinate system for the patient's physiological data, which more comprehensively presents the patterns of physiological data variation. Then, the patient's physiological feature sequence is mapped to the characteristics of the tongue and pulse patterns in Traditional Chinese Medicine (TCM). Traditional Chinese Medicine believes that tongue and pulse patterns are important windows into the state of qi and blood in the internal organs of the body. In patients undergoing PCI for coronary heart disease, if the physiological feature sequence indicates a rapid heart rate and fluctuating blood pressure, the tongue pattern may reveal a red tongue with a greasy yellow coating; the pulse pattern may show characteristics such as a rapid or stringy pulse. These feature mappings generate basic data for syndrome identification, which is then used to categorize multi-level syndromes. For example, a patient's various symptoms and signs are categorized into different syndrome types based on the TCM Eight-Principle Syndrome Differentiation and Zang-Fu Syndrome Differentiation. If a patient also exhibits palpitations, shortness of breath, fatigue, a pale tongue, and a weak and thready pulse, they can be classified as suffering from heart qi deficiency, thus generating a TCM syndrome feature index set. Next, the TCM syndrome characteristic index set was converted into corresponding Western medicine indicators using physiological-syndrome correlation analysis. There are inherent connections between TCM syndromes and Western medicine indicators. For example, heart qi deficiency syndrome may manifest in Western medicine as reduced left ventricular ejection fraction and ST-T changes on the electrocardiogram. Extensive clinical data studies have found that approximately 60% of patients with heart qi deficiency syndrome have a left ventricular ejection fraction below the normal range (normal is generally ≥50%). By converting the TCM syndrome characteristic index set into Western medicine indicators, a multi-dimensional assessment feature set was generated. This was then subjected to hierarchical quantitative processing, with indicators from different dimensions arranged and combined according to their importance and correlations, resulting in a parameter matrix for the integration of Chinese and Western medicine. This matrix acts like a "health codebook," integrating both Chinese and Western medicine's understanding of a patient's health status.Finally, a multi-dimensional quantitative assessment of the patient's health status is conducted based on the integrated Chinese and Western medicine parameter matrix, generating an initial assessment dataset. This dataset quantifies the patient's health status across multiple dimensions, such as cardiac function indicators and the severity of TCM syndromes. To ensure the accuracy of the assessment results, the initial assessment dataset must also be validated for syndrome-sign correlation. For example, if the initial assessment dataset indicates that a patient has heart yin deficiency syndrome accompanied by an abnormal electrocardiogram (ECG), further observation of the patient's actual symptoms and signs will verify the correlation between the two. If, during the patient's subsequent rehabilitation process, the ECG gradually returns to normal as the heart yin deficiency syndrome improves, the reliability of the assessment results is confirmed, ultimately resulting in a comprehensive assessment of the patient's health status using integrated Chinese and Western medicine. This provides a scientific and comprehensive basis for the development of subsequent rehabilitation training programs.

[0032] In a specific embodiment, the personalized scene element configuration and interactive logic design of the preset virtual reality scene based on the health status assessment results of the integrated Chinese and Western medicine patient are performed to obtain a customized virtual rehabilitation training scene, including: Performing rehabilitation load grading processing on the health status assessment results of the integrated Chinese and Western medicine patient to obtain patient rehabilitation ability grading data, and performing scene element mapping on a preset virtual reality scene based on the patient rehabilitation ability grading data to obtain a scene basic configuration parameter set; Performing interactive element layout design on the scene basic configuration parameter set to obtain a scene interaction layout scheme, and performing dynamic difficulty adjustment rule configuration on the scene interaction layout scheme to obtain a scene interaction rule; Performing spatial rendering processing on the scene interaction rules through a scene rendering engine to obtain a scene rendering data stream, and performing real-time physical property calculation based on the scene rendering data stream to obtain a scene physical parameter set; Planning the motion trajectory of a virtual object in a virtual reality scene based on the scene physical parameter set to obtain object motion control data, and performing interactive logic design and human-computer interaction mapping on the object motion control data to obtain an interactive response configuration scheme; The interactive response configuration scheme is subjected to scene integration processing to obtain scene combination configuration data, and the scene combination configuration data is subjected to traditional Chinese medicine meridian fusion optimization to obtain a customized virtual rehabilitation training scene.

[0033] Specifically, after obtaining the integrated Chinese and Western medicine patient health status assessment results, the pre-set virtual reality scene is personalized with scene element configuration and interaction logic design based on these results, resulting in a customized virtual rehabilitation training scenario. This process is a key step in creating a personalized rehabilitation environment for patients undergoing PCI for coronary heart disease. First, the integrated Chinese and Western medicine patient health status assessment results are processed for rehabilitation load grading. This process categorizes the patient's rehabilitation capacity into different levels based on their overall health status, such as cardiac function, physical fitness, and TCM syndromes. For example, patients with relatively good cardiac function recovery, strong physical fitness, and mild TCM syndromes may be classified as having a high rehabilitation capacity level; patients with still-weak cardiac function, poor physical fitness, and significant TCM syndromes may be classified as having a low rehabilitation capacity level. According to clinical research, approximately 30% of patients undergoing PCI for coronary heart disease experience a low rehabilitation capacity level in the early postoperative period. Based on this patient rehabilitation capacity grading data, scene elements are mapped to the pre-set virtual reality scene. The pre-set virtual reality scene may contain a variety of common scene elements, such as different terrains, obstacles, and movable props. For patients with high rehabilitation ability levels, scene elements can be mapped to challenging scenarios, such as steep mountain roads and fast-moving targets. For patients with low rehabilitation ability levels, they can be mapped to more gentle, simple scenes, such as flat grass and slow-moving small objects. This results in a basic scene configuration parameter set. Next, interactive element layout design is performed within this basic scene configuration parameter set. Interactive elements include actionable buttons and interactive characters. A reasonable layout of these elements allows patients to more easily interact with the scene. For example, prompt buttons for rehabilitation tasks and dialogue windows for communicating with virtual characters can be placed within the scene. By designing the position and size of these interactive elements, a scene interaction layout scheme is derived. Dynamic difficulty adjustment rules are then configured within this scheme. For example, if a patient completes a motor rehabilitation task within a given period with a high accuracy rate, such as above 80%, the task difficulty can be appropriately increased, such as by increasing the target's speed or adding more obstacles. If the accuracy rate is low, such as below 30%, the task difficulty can be reduced, resulting in the scene interaction rules. The scene interaction rules are then spatially rendered using the scene rendering engine. The scene rendering engine, like a magical artist, presents the virtual scene in three dimensions according to scene interaction rules, generating a scene rendering data stream. Based on this data stream, real-time physical property calculations are performed, taking into account the physical properties of objects in the scene, such as gravity, friction, and collisions. For example, if there is a rolling ball in the virtual scene, its speed, direction, and rebound after collision are calculated to obtain a set of scene physical parameters. Based on this set of scene physical parameters, the motion trajectories of virtual objects in the virtual reality scene are planned. Virtual objects can be characters, objects, and other objects in the scene. Their motion trajectories are planned so that they move according to certain patterns within the scene.For example, a virtual animal's patrol route within a scene is planned to generate object motion control data. Interaction logic design and human-computer interaction mapping are performed on this data to determine the interaction method and response mechanism between the patient and the virtual object. For example, when a patient touches the virtual animal, it will react accordingly, such as making sounds or performing movements, generating an interactive response configuration scheme. Finally, the interactive response configuration scheme is subjected to scene integration. All interactive elements and the virtual object's motion trajectory are integrated to generate scene combination configuration data. To further leverage the advantages of Traditional Chinese Medicine (TCM) rehabilitation, the scene combination configuration data is optimized through TCM meridian integration. TCM meridian concepts are integrated into the virtual scene, such as by setting special interaction points at specific meridian acupoints. When the patient interacts with these points, virtual effects such as promoting Qi and blood circulation and regulating internal organ function may be triggered. This optimization ultimately results in a customized virtual rehabilitation training scene that better meets the individual rehabilitation needs of patients undergoing PCI for coronary artery disease.

[0034] In a specific embodiment, the scene element mapping is performed on the preset virtual reality scene based on the patient rehabilitation ability classification data to obtain the scene basic configuration parameter set, including: Performing physiological load threshold analysis on the patient's rehabilitation ability grading data to obtain a rehabilitation training intensity grading index, and performing hierarchical progressive conversion on the rehabilitation training intensity grading index to obtain a scenario difficulty gradient matrix; Performing virtual scene space coordinate division based on the scene difficulty gradient matrix to obtain scene space layout parameters, and performing dynamic threshold setting on the scene space layout parameters to obtain scene environment control parameters; Performing spatial mapping analysis on the scene environment control parameters through a meridian acupoint locator to obtain an acupoint activation area distribution map, and performing three-dimensional projection conversion on the acupoint activation area distribution map to obtain a scene interaction node matrix; Performing physical property configuration on the virtual object based on the scene interaction node matrix to obtain an object attribute parameter set, and performing spatial correlation processing on the object attribute parameter set to obtain scene element configuration data; The scene element configuration data is mapped to light and shadow effects using a preset scene rendering algorithm to obtain a scene rendering parameter group, and the scene rendering parameter group is optimized as a whole to obtain a scene basic configuration parameter set.

[0035] Specifically, the process of constructing a basic scenario configuration parameter set based on patient rehabilitation ability grading data requires a layered and meticulous process, encompassing physiological load, spatial layout, meridian connections, object attributes, and even lighting and shadow effects, to achieve deep adaptation of the virtual reality scene to the patient's rehabilitation needs. Specifically, the patient rehabilitation ability grading data must first be analyzed for physiological load thresholds. This step aims to determine the upper limit of training intensity that patients with different rehabilitation ability levels can tolerate. For example, studies have shown that patients with low rehabilitation ability levels who have undergone PCI for coronary artery disease typically have a safe heart rate range lower than that of normal adults. A heart rate exceeding 110 beats per minute during exercise rehabilitation may cause discomfort, while patients with high rehabilitation ability levels may be able to tolerate heart rate fluctuations around 130 beats per minute. Based on this data, rehabilitation training intensity grading indicators are derived. Then, through a hierarchical and progressive conversion, different intensity indicators are mapped to scenario difficulty levels, forming a scenario difficulty gradient matrix. This is like assigning patients "levels" from easy to difficult, with patients with low rehabilitation ability starting at the "beginner level" and those with high rehabilitation ability moving on to the "advanced level." Based on the scenario difficulty gradient matrix, the next step is to divide the virtual scene's spatial coordinates. The virtual scene space is divided into different zones based on different difficulty levels. For example, the easy zone is placed in the center of the space to facilitate quick learning, while the difficult zones are distributed around the edges to enhance exploration and challenge. This generates the scene space layout parameters. Furthermore, to enable the scene to dynamically adjust based on the patient's real-time status, dynamic thresholds are set for the scene space layout parameters. For example, when the patient's accuracy in completing tasks in the easy zone reaches 90%, the system automatically opens the entrance to the medium-difficulty zone. If the accuracy falls below 60%, the easy zone is appropriately narrowed to reduce the patient's frustration caused by the high difficulty level. This results in the scene environment control parameters. Next, a meridian acupoint locator is used to perform spatial mapping analysis of the scene environment control parameters. Traditional Chinese medicine believes that meridian acupoints are closely related to bodily functions. For patients undergoing PCI for coronary artery disease, acupoints on meridians such as the heart meridian and pericardium meridian are particularly critical. Using the meridian acupoint locator, the spatial regions in the scene are mapped to meridian acupoints on the human body, generating a distribution map of acupoint activation areas. For example, on a specific path in the virtual scene, an activation area corresponding to the Neiguan acupoint is set. When the patient moves to this area in the scene, it is like stimulating the Neiguan acupoint in reality. The distribution map of the acupoint activation area is then transformed into a three-dimensional projection to obtain a scene interaction node matrix. These nodes become the key touchpoints for the patient to interact with the scene. Based on the scene interaction node matrix, the physical characteristics of the virtual objects are configured. For example, a virtual "energy ball" is placed in the scene area corresponding to the pericardium meridian acupoint, and unique physical properties are configured for it: when a patient with low rehabilitation ability touches it, the "energy ball" moves slowly and the collision feedback is gentle; when a patient with high rehabilitation ability touches it, the "energy ball" rebounds quickly, increasing the difficulty of manipulation, thereby obtaining a set of object attribute parameters.The object attribute parameter set is then spatially correlated to ensure that the physical characteristics of the virtual objects match the scene's spatial layout and difficulty level, ultimately generating scene element configuration data. Finally, a preset scene rendering algorithm is used to map lighting and shadow effects to the scene element configuration data. Appropriate lighting and shadow effects are applied to different difficulty levels, acupoint activation areas, and virtual objects. For example, low-difficulty areas use soft, bright lighting to create a relaxing atmosphere; high-difficulty areas use a staggered light and shadow effect to increase tension; and acupoint activation areas use shimmering, special lighting to highlight their importance. This results in a scene rendering parameter set. This scene rendering parameter set is then optimized overall, adjusting details such as contrast and color saturation to ensure the entire scene is both suitable for rehabilitation training and visually appealing. This ultimately forms the basic scene configuration parameter set. This process is like building a "virtual rehabilitation castle" specifically for patients undergoing PCI. From difficulty setting to detailed rendering, every step is meticulously designed based on the patient's recovery capabilities and Traditional Chinese Medicine meridian theory, providing a scientific and immersive rehabilitation training environment.

[0036] In a specific embodiment, the light and shadow effect mapping is performed on the scene element configuration data using a preset scene rendering algorithm to obtain a scene rendering parameter group, including: Performing spatial illumination distribution calculation on the scene element configuration data to obtain scene basic illumination parameters, and performing TCM element mapping on the scene basic illumination parameters to obtain a scene atmosphere configuration matrix; Analyzing the material reflection characteristics of the scene atmosphere configuration matrix using a preset scene rendering algorithm to obtain surface material rendering parameters, and performing multi-level texture mapping on the surface material rendering parameters to obtain a scene texture feature set; Performing shadow casting calculation on the virtual object based on the scene texture feature set to obtain dynamic shadow mapping data, and performing spatial depth fusion on the dynamic shadow mapping data to obtain a stereoscopic perception parameter group; The stereoscopic perception parameter group is subjected to post-processing for special effects to obtain a visual optimization parameter set, and an overall effect synthesis is performed based on the visual optimization parameter set to obtain a scene rendering parameter group.

[0037] Specifically, using a preset scene rendering algorithm to map light and shadow effects to scene element configuration data to obtain a set of scene rendering parameters requires a multi-dimensional analysis, encompassing spatial lighting, material rendering, shadow projection, stereoscopic perception, and visual optimization. This integration of Traditional Chinese Medicine (TCM) theory with modern rendering technology creates an immersive virtual rehabilitation scene for patients undergoing PCI for coronary heart disease. First, the spatial lighting distribution of the scene element configuration data is calculated, which is crucial for establishing the scene's lighting foundation. By analyzing the function and layout of different areas within the virtual scene, the required lighting intensity, direction, and color are calculated for each area. For example, in the virtual garden area used for relaxation training, the lighting intensity is set at 300-500 lux to simulate the soft morning sunlight and provide comfort for patients. In the virtual strength training area, the lighting intensity is increased to 800-1000 lux to ensure a clear field of view. Once the basic scene lighting parameters are obtained, they are mapped to the TCM elements. In scene atmosphere configuration, if a certain area is designed to help patients boost their heart qi, the primary lighting color in that area is mapped to red, with the lighting direction projected from the south. This creates a scene atmosphere configuration matrix with TCM characteristics. Next, a preset scene rendering algorithm analyzes the material reflectance characteristics of this matrix. Different materials have different light reflection and absorption properties, which directly affect the realism and visual quality of the scene. For example, the reflectivity of the water surface material in a virtual scene is set to 70%-80%, clearly reflecting the surrounding scenery; the reflectivity of the wooden floor is set to 30%-40%, creating a soft reflective effect. These surface material rendering parameters are then derived. To enhance the scene's texture, multi-layered texture mapping is applied to the surface material rendering parameters. For example, for a virtual rock material, a basic rock texture is first mapped, and then detailed textures such as moss and cracks are overlaid to make the rock appear more realistic. This results in a scene texture feature set. Shadow casting calculations are performed on virtual objects based on this scene texture feature set. In a post-PCI rehabilitation scenario for coronary heart disease, when a patient controls a virtual character walking in a virtual garden, shadows are cast on the character and surrounding plants based on the lighting direction. Dynamic shadow mapping data is generated by calculating the shape, size, and transparency of the shadows. To enhance the three-dimensional effect of the scene, spatial depth fusion is performed on the dynamic shadow mapping data. For example, the shadow blur of distant trees is set to 60%, while the shadow blur of nearby trees is reduced to 20%. This simulates a realistic sense of spatial depth and generates a set of three-dimensional perception parameters. Finally, post-processing is performed on the three-dimensional perception parameter set. Special effects such as halo and fog are added to optimize the visual effect. For example, a mist effect is added to the virtual garden with a fog concentration of 20%-30% to create a hazy aesthetic. A halo effect with a radius of 1-2 units is added to important interactive nodes or acupoint activation areas to attract the patient's attention, resulting in a visually optimized parameter set.Based on a visual optimization parameter set, the overall effect synthesis is performed, integrating elements such as spatial lighting, material texture, shadow casting, and post-production special effects. Global adjustments are made to brightness, contrast, color balance, and other factors to ensure the overall visual harmony and unity of the scene. The final result is a scene rendering parameter set. This parameter set is like a "key" that can unlock a virtual rehabilitation space that is consistent with Traditional Chinese Medicine rehabilitation concepts and provides a high-quality visual experience, helping patients undergoing PCI for coronary heart disease to conduct rehabilitation training in a comfortable and immersive environment.

[0038] In a specific embodiment, the immersive virtual reality rehabilitation training is performed on the patient through the customized virtual rehabilitation training scene to obtain the training interaction data, including: Performing multi-channel physiological sensing acquisition configuration on the customized virtual rehabilitation training scene to obtain a training scene physiological monitoring parameter set, and performing dynamic threshold setting on the training scene physiological monitoring parameter set to obtain a physiological parameter monitoring threshold matrix; Performing real-time pulse waveform acquisition on the patient by a photoplethysmography sensor to obtain a pulse waveform feature data stream, and performing traditional Chinese medicine pulse feature extraction on the pulse waveform feature data stream to obtain a real-time pulse dynamic feature set; Based on the physiological parameter monitoring threshold matrix and the real-time pulse dynamic feature set, the patient's exercise load is monitored in real time to obtain training process monitoring data, and the training process monitoring data is subjected to multi-dimensional feature correlation analysis to obtain a training status evaluation index group; A training interaction response analysis is performed on the training state evaluation indicator group to obtain a training interaction feature sequence, and a training effect quantification process is performed based on the training interaction feature sequence to obtain training interaction data.

[0039] Specifically, when patients undergoing immersive training in customized virtual rehabilitation training scenarios after PCI for coronary artery disease undergo training, capturing training interaction data is a key step in ensuring scientific, safe, and effective rehabilitation training. The entire process begins with the scenario's physiological sensor configuration and ultimately generates comprehensive training interaction data through real-time collection, analysis, and evaluation of the patient's physiological data. First, the customized virtual rehabilitation training scenario must be configured with multi-channel physiological sensor acquisition. This ensures comprehensive monitoring of the patient's physiological state during training. By integrating multiple sensor types, such as heart rate sensors, blood pressure sensors, and respiratory sensors, a training scenario physiological monitoring parameter set is generated. These parameters cover basic data on important physiological indicators such as heart rate, blood pressure, and respiratory rate. For example, a heart rate sensor can collect real-time heart rate data at a sampling rate of 10-20 times per second, ensuring timely and accurate data. To achieve more intelligent and accurate monitoring, dynamic threshold setting is required for the training scenario physiological monitoring parameter set. Different physiological parameter thresholds are set based on individual patient differences and the level of rehabilitation training intensity. Generally speaking, for patients with low rehabilitation ability levels, the heart rate safety threshold may be set at 90-110 beats / minute, the blood pressure threshold at 110-140 mmHg systolic, and 70-90 mmHg diastolic. For patients with high rehabilitation ability levels, the corresponding thresholds may be higher. This setting generates a physiological parameter monitoring threshold matrix, providing a basis for subsequent real-time monitoring. Next, a photoplethysmography sensor is used to collect the patient's pulse waveform in real time. This sensor accurately captures subtle changes in the patient's pulse, acquiring a pulse waveform feature data stream at a sampling rate of 500-1000 data points per second. This data contains a wealth of information. Using specialized algorithms, Traditional Chinese Medicine (TCM) pulse feature extraction is performed on this pulse waveform feature stream, identifying characteristics such as pulse rate, rhythm, and strength. In Traditional Chinese Medicine (TCM) theory, Qi deficiency syndrome in patients undergoing PCI for coronary heart disease may manifest as a weak pulse and slow pulse rate. By extracting these features, a real-time pulse dynamic feature set is generated, providing a basis for assessing the patient's physical condition from a TCM perspective. Then, the patient's exercise load is monitored in real time based on the physiological parameter monitoring threshold matrix and the real-time pulse dynamic feature set. The patient's real-time physiological parameters are compared with the set thresholds, and combined with the analysis of Traditional Chinese Medicine pulse characteristics, it is determined whether the patient's current exercise load is appropriate. For example, when the patient's heart rate reaches 115 beats / minute (exceeding the upper limit of the heart rate safety threshold of 110 beats / minute for patients with low rehabilitation ability levels) and the pulse shows rapid and weak characteristics, the system determines that the current exercise load is too high and obtains training process monitoring data. Multi-dimensional feature correlation analysis is performed on this data, comprehensively considering the characteristics of multiple dimensions such as heart rate, blood pressure, respiratory rate, pulse, and their interrelationships to obtain a set of training status evaluation indicators.For example, in the correlation analysis between heart rate and pulse, a rapid heart rate and a weak pulse may indicate an overload on the patient's cardiac function and require adjustment of training intensity. Finally, a training interaction response analysis is performed on the training status assessment indicator group. The patient's training status is determined based on the assessment indicator group, and the appropriate interaction response is analyzed. If the assessment indicators indicate a good training status, the training difficulty in the virtual scene can be appropriately increased, such as by increasing the speed of virtual obstacles. If the status is poor, a prompt is given to pause the training or reduce the difficulty, thereby generating a training interaction feature sequence. Based on this sequence, the training effect is quantified. Various training data, such as training duration, the number and quality of completed tasks, and the magnitude of changes in physiological parameters, are quantified and converted into specific numerical indicators, ultimately generating training interaction data. This data can not only be used for real-time feedback and adjustment of the patient's training plan, but also provide a detailed and objective basis for subsequent efficacy evaluation, helping patients undergoing PCI for coronary artery disease to achieve more scientific and effective rehabilitation training.

[0040] In a specific embodiment, the patient is subjected to real-time monitoring of exercise load based on the physiological parameter monitoring threshold matrix and the real-time pulse dynamic feature set to obtain training process monitoring data, including: Performing multi-dimensional feature decomposition processing on the patient's real-time physiological data and training interaction data to obtain a rehabilitation training feature matrix, and performing time series correlation analysis on the rehabilitation training feature matrix to obtain a dynamic rehabilitation indicator set; Performing load tolerance evaluation on the dynamic rehabilitation index set using a physiological-motor correlation analyzer to obtain training load adaptability data, and performing hierarchical quantitative processing on the training load adaptability data to obtain a rehabilitation progress evaluation parameter group; Dynamically optimizing the training program based on the rehabilitation progress assessment parameter group to obtain a training program adjustment data stream, and performing TCM meridian balance verification on the training program adjustment data stream to obtain a program optimization suggestion matrix; A multi-dimensional efficacy quantitative analysis is performed on the program optimization suggestion matrix to obtain a rehabilitation efficacy evaluation data set, and personalized program generation processing is performed based on the rehabilitation efficacy evaluation data set to obtain personalized rehabilitation program adjustment suggestions and efficacy evaluation reports.

[0041] Specifically, when monitoring exercise load and acquiring training data for patients undergoing PCI for coronary artery disease in real time based on a physiological parameter monitoring threshold matrix and a real-time pulse dynamic feature set, multi-dimensional data mining, analysis, and verification are required to develop a scientific and personalized rehabilitation plan. This process acts like a customized dynamic rehabilitation "navigation map" for the patient, ensuring both safe and efficient rehabilitation training. First, multi-dimensional feature decomposition is performed on the patient's real-time physiological data and training interaction data. In customized virtual rehabilitation training scenarios, patients' real-time physiological data, such as heart rate, blood pressure, and respiratory rate, as well as training interaction data, such as the speed and number of virtual task completions, contain rich information. Advanced data processing techniques are used to decompose this data according to dimensions such as time, type, and intensity. For example, heart rate data is decomposed into per-minute units to analyze its fluctuations across different training phases; training interaction data is decomposed by task type to analyze differences in patient performance in virtual gardening and virtual walking tasks, thereby generating a rehabilitation training feature matrix. This matrix is ​​then subjected to temporal correlation analysis to examine the associations between various data types at different time points. For example, during a virtual mountain climbing session, a patient's heart rate was found to increase significantly during the steep climb (a specific task period in the training interaction data), and this was strongly correlated with increased respiratory rate. This dynamic rehabilitation indicator set was then used to clearly demonstrate the changing trends in the patient's physical condition during training. The dynamic rehabilitation indicator set was then used to assess load tolerance using a physiological-motor correlation analyzer. Based on the patient's physiological characteristics and performance during training, their adaptability to the current training load was determined. For example, if a patient's heart rate consistently exceeded the upper safe heart rate limit set in the physiological parameter monitoring threshold matrix (e.g., exceeding 110 beats / minute for patients with low recovery capacity) during a virtual running session, and their pulse exhibited characteristics such as rapidity and irregularity, Traditional Chinese Medicine theory indicated that the patient's heart load was excessive and their load tolerance was assessed as low, resulting in training load adaptability data. To more clearly measure the patient's rehabilitation progress, the training load adaptability data was quantified and stratified. Load tolerance was divided into five levels, from low to high, with Level 1 representing complete inability to adapt to the current load and Level 5 representing easy adaptation with sufficient capacity. This quantification generates a rehabilitation progress assessment parameter set that intuitively reflects the patient's progress in rehabilitation training. Based on this set, the training plan is dynamically optimized. If the assessment reveals a low patient load tolerance, and the rehabilitation progress assessment parameter set indicates a low level, the system automatically reduces the training difficulty in the virtual scene, such as by slowing the movement of virtual obstacles and reducing the number of tasks, generating a training plan adjustment data stream. To ensure that the adjusted plan conforms to Traditional Chinese Medicine rehabilitation concepts, the training plan adjustment data stream undergoes a TCM meridian balance verification.For example, after reducing training intensity, the patient's physiological responses to acupoints on the Heart and Pericardium meridians are observed (as determined by real-time pulse dynamic feature sets and other physiological data). If the patient's pulse stabilizes after the adjustment and indicators related to meridian Qi and blood circulation improve, it indicates that the program adjustment has helped achieve meridian balance, and a program optimization recommendation matrix is ​​generated. Finally, a multi-dimensional efficacy quantitative analysis of the program optimization recommendation matrix is ​​conducted. Quantitative evaluation is conducted based on multiple dimensions, including improvement in physiological indicators (such as the proportion of heart rate returning to normal range and the degree of reduction in blood pressure fluctuations), relief of Traditional Chinese Medicine (TCM) symptoms (such as the proportion of improvement in symptoms related to Qi deficiency), and training task completion efficiency. For example, after a period of training program adjustment, the patient's average heart rate dropped from 115 beats / minute to 95 beats / minute, TCM Qi deficiency symptoms improved by 40%, and virtual task completion time was shortened by 30%. This data is integrated into a rehabilitation efficacy evaluation dataset. Based on this data set, personalized plans are generated and processed. According to the patient's specific situation, such as slow recovery progress and persistent physical discomfort symptoms, personalized rehabilitation plan adjustment suggestions are generated. At the same time, an efficacy evaluation report containing various evaluation data and conclusions is output to provide precise guidance for subsequent rehabilitation training and help patients with coronary heart disease who have undergone PCI surgery to gradually recover their health.

[0042] The above describes the virtual reality rehabilitation training method for the rehabilitation nursing of coronary heart disease after PCI combined with traditional Chinese and Western medicine in the embodiment of the present invention. The following describes the virtual reality rehabilitation training system for the rehabilitation nursing of coronary heart disease after PCI combined with traditional Chinese and Western medicine in the embodiment of the present invention. Figure 2 In one embodiment of the present invention, a virtual reality rehabilitation training system for integrated traditional Chinese and Western medicine rehabilitation nursing for coronary heart disease after PCI surgery includes: The acquisition module 21 is used to collect physiological signs and meridian information of patients after PCI surgery for coronary heart disease through a multimodal physiological data acquisition system to obtain multi-dimensional patient physiological status data; An analysis module 22 is configured to identify TCM syndrome types and conduct quantitative analysis of Western medicine indicators for the patient based on the multi-dimensional patient physiological status data, thereby obtaining a TCM and Western medicine combined patient health status assessment result; A design module 23 is used to configure personalized scene elements and interactive logic for a preset virtual reality scene based on the health status assessment results of the integrated Chinese and Western medicine patient, thereby obtaining a customized virtual rehabilitation training scene; The training module 24 is used to perform immersive virtual reality rehabilitation training on the patient through the customized virtual rehabilitation training scene to obtain training interaction data, wherein the training interaction data is used to provide real-time feedback adjustment and efficacy evaluation to the patient.

[0043] In this embodiment, for the specific implementation of each unit in the above system embodiment, please refer to the above method embodiment, which will not be repeated here.

[0044] Reference Figure 3 In an embodiment of the present invention, a computer device is also provided, wherein the internal structure of the computer device can be as follows: Figure 3 As shown. The computer device includes a processor, memory, display screen, input device, network interface and database connected via a system bus. The processor of the computer design is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, the above method is implemented.

[0045] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present invention and does not constitute a limitation on the computer device to which the solution of the present invention is applied.

[0046] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the above-described method when executed by a processor. It is understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0047] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing the relevant hardware using a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the above-described method embodiments. Any reference to memory, storage, database, or other media provided herein and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct RAMbus dynamic RAM (DRDRAM), and RAMbus dynamic RAM.

[0048] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, apparatus, article, or method comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, apparatus, article, or method. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, apparatus, article, or method comprising the element.

[0049] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A virtual reality rehabilitation training system for integrated Chinese and Western medicine rehabilitation nursing after PCI surgery for coronary heart disease, characterized by: include: The acquisition module is used to collect physiological signs and meridian information from patients undergoing PCI for coronary heart disease through a multimodal physiological data acquisition system to obtain multi-dimensional patient physiological status data; An analysis module is used to identify the TCM syndrome type and conduct quantitative analysis of Western medicine indicators for the patient based on the multi-dimensional patient physiological status data, and obtain a health status assessment result of the patient using integrated TCM and Western medicine; A design module is used to configure personalized scene elements and interactive logic for a preset virtual reality scene based on the health status assessment results of the integrated Chinese and Western medicine patient, thereby obtaining a customized virtual rehabilitation training scene; The training module is used to perform immersive virtual reality rehabilitation training on the patient through the customized virtual rehabilitation training scene to obtain training interaction data, wherein the training interaction data is used to provide real-time feedback adjustment and efficacy evaluation to the patient.

2. A virtual reality rehabilitation training method for integrated traditional Chinese and Western medicine rehabilitation nursing for patients with coronary heart disease after PCI surgery, characterized in that: The following steps are involved: Through the multimodal physiological data acquisition system, physiological signs and meridian information of patients with coronary heart disease who have undergone PCI are collected to obtain multi-dimensional patient physiological status data; Based on the multi-dimensional patient physiological status data, the patient is identified by TCM syndrome type and quantitatively analyzed by Western medicine indicators to obtain a health status assessment result of the patient combined with TCM and Western medicine; Based on the health status assessment results of the integrated Chinese and Western medicine patient, personalized scene element configuration and interactive logic design are performed on the preset virtual reality scene to obtain a customized virtual rehabilitation training scene; The patient is subjected to immersive virtual reality rehabilitation training through the customized virtual rehabilitation training scene to obtain training interaction data, wherein the training interaction data is used to provide real-time feedback adjustment and efficacy evaluation to the patient.

3. The virtual reality rehabilitation training method for integrated traditional Chinese and western medicine rehabilitation nursing for coronary heart disease after PCI surgery according to claim 2 is characterized in that: The multimodal physiological data acquisition system collects physiological signs and meridian information from patients undergoing PCI for coronary heart disease to obtain multi-dimensional patient physiological status data, including: The multimodal physiological data acquisition system is used to collect physiological sign data of heart rate, blood pressure, blood oxygen saturation, and respiratory rate from patients undergoing PCI for coronary heart disease to obtain the patient's physiological sign data, and the patient's physiological sign data is subjected to real-time noise filtering and data smoothing to obtain smoothed physiological sign data; Acquiring meridian information of the patient through a multimodal physiological data acquisition system to obtain original meridian data of the patient, and performing acupoint positioning and feature extraction on the original meridian data of the patient to obtain meridian feature data of the patient; Multi-source data fusion and information association analysis are performed based on the smoothed physiological sign data and the patient meridian characteristic data to obtain multi-dimensional patient physiological state data.

4. The virtual reality rehabilitation training method for integrated traditional Chinese and western medicine rehabilitation nursing for coronary heart disease after PCI surgery according to claim 2 is characterized in that: The patient's TCM syndrome type identification and Western medicine index quantitative analysis based on the multi-dimensional patient physiological status data are performed to obtain the TCM and Western medicine combined patient health status assessment results, including: Performing wavelet decomposition processing on the multi-dimensional patient physiological state data to obtain patient physiological characteristic basic data, and performing time-frequency feature extraction on the patient physiological characteristic basic data to obtain a patient physiological characteristic sequence; Performing TCM tongue and pulse feature mapping on the patient's physiological feature sequence to obtain basic syndrome identification data, and performing multi-level syndrome classification on the basic syndrome identification data to obtain a TCM syndrome feature index group; The TCM syndrome characteristic index group is converted into corresponding Western medicine indicators through the physiological-syndrome association analysis method to obtain a multi-dimensional evaluation feature set, and the multi-dimensional evaluation feature set is subjected to hierarchical quantitative processing to obtain a TCM and Western medicine integration parameter matrix; Based on the TCM and Western medicine integration parameter matrix, the patient's multi-dimensional health status is quantitatively evaluated to obtain an initial evaluation data set, and the initial evaluation data set is verified for syndrome-sign association to obtain a TCM and Western medicine integration patient health status evaluation result.

5. The virtual reality rehabilitation training method for integrated traditional Chinese and western medicine rehabilitation nursing for coronary heart disease after PCI surgery according to claim 2 is characterized in that: The method of performing personalized scene element configuration and interactive logic design on a preset virtual reality scene based on the health status assessment results of the integrated Chinese and Western medicine patient to obtain a customized virtual rehabilitation training scene includes: Performing rehabilitation load grading processing on the health status assessment results of the integrated Chinese and Western medicine patient to obtain patient rehabilitation ability grading data, and performing scene element mapping on a preset virtual reality scene based on the patient rehabilitation ability grading data to obtain a scene basic configuration parameter set; Performing interactive element layout design on the scene basic configuration parameter set to obtain a scene interaction layout scheme, and performing dynamic difficulty adjustment rule configuration on the scene interaction layout scheme to obtain a scene interaction rule; Performing spatial rendering processing on the scene interaction rules through scene rendering engine technology to obtain a scene rendering data stream, and performing real-time physical property calculation based on the scene rendering data stream to obtain a scene physical parameter set; Planning the motion trajectory of a virtual object in a virtual reality scene based on the scene physical parameter set to obtain object motion control data, and performing interactive logic design and human-computer interaction mapping on the object motion control data to obtain an interactive response configuration scheme; The interactive response configuration scheme is subjected to scene integration processing to obtain scene combination configuration data, and the scene combination configuration data is subjected to traditional Chinese medicine meridian fusion optimization to obtain a customized virtual rehabilitation training scene.

6. The virtual reality rehabilitation training method for integrated traditional Chinese and western medicine rehabilitation nursing for coronary heart disease after PCI surgery according to claim 5 is characterized in that: The scene element mapping is performed on the preset virtual reality scene based on the patient rehabilitation ability classification data to obtain a scene basic configuration parameter set, including: Performing physiological load threshold analysis on the patient's rehabilitation ability grading data to obtain a rehabilitation training intensity grading index, and performing hierarchical progressive conversion on the rehabilitation training intensity grading index to obtain a scenario difficulty gradient matrix; Performing virtual scene space coordinate division based on the scene difficulty gradient matrix to obtain scene space layout parameters, and performing dynamic threshold setting on the scene space layout parameters to obtain scene environment control parameters; Performing spatial mapping analysis on the scene environment control parameters through a meridian acupoint locator to obtain an acupoint activation area distribution map, and performing three-dimensional projection conversion on the acupoint activation area distribution map to obtain a scene interaction node matrix; Performing physical property configuration on the virtual object based on the scene interaction node matrix to obtain an object attribute parameter set, and performing spatial correlation processing on the object attribute parameter set to obtain scene element configuration data; The scene element configuration data is mapped to light and shadow effects using a preset scene rendering algorithm to obtain a scene rendering parameter group, and the scene rendering parameter group is optimized as a whole to obtain a scene basic configuration parameter set.

7. The virtual reality rehabilitation training method for integrated traditional Chinese and western medicine rehabilitation nursing for coronary heart disease after PCI surgery according to claim 6 is characterized in that: The light and shadow effect mapping is performed on the scene element configuration data by a preset scene rendering algorithm to obtain a scene rendering parameter group, including: Performing spatial illumination distribution calculation on the scene element configuration data to obtain scene basic illumination parameters, and performing TCM element mapping on the scene basic illumination parameters to obtain a scene atmosphere configuration matrix; Analyzing the material reflection characteristics of the scene atmosphere configuration matrix using a preset scene rendering algorithm to obtain surface material rendering parameters, and performing multi-level texture mapping on the surface material rendering parameters to obtain a scene texture feature set; Performing shadow casting calculation on the virtual object based on the scene texture feature set to obtain dynamic shadow mapping data, and performing spatial depth fusion on the dynamic shadow mapping data to obtain a stereoscopic perception parameter group; The stereoscopic perception parameter group is subjected to post-processing for special effects to obtain a visual optimization parameter set, and an overall effect synthesis is performed based on the visual optimization parameter set to obtain a scene rendering parameter group.

8. The virtual reality rehabilitation training method for integrated traditional Chinese and western medicine rehabilitation nursing for coronary heart disease after PCI surgery according to claim 1 is characterized in that: The step of performing immersive virtual reality rehabilitation training on the patient through the customized virtual rehabilitation training scene to obtain training interaction data includes: Performing multi-channel physiological sensing acquisition configuration on the customized virtual rehabilitation training scene to obtain a training scene physiological monitoring parameter set, and performing dynamic threshold setting on the training scene physiological monitoring parameter set to obtain a physiological parameter monitoring threshold matrix; Performing real-time pulse waveform acquisition on the patient by a photoplethysmography sensor to obtain a pulse waveform feature data stream, and performing traditional Chinese medicine pulse feature extraction on the pulse waveform feature data stream to obtain a real-time pulse dynamic feature set; Based on the physiological parameter monitoring threshold matrix and the real-time pulse dynamic feature set, the patient's exercise load is monitored in real time to obtain training process monitoring data, and the training process monitoring data is subjected to multi-dimensional feature correlation analysis to obtain a training status evaluation index group; A training interaction response analysis is performed on the training state evaluation indicator group to obtain a training interaction feature sequence, and a training effect quantification process is performed based on the training interaction feature sequence to obtain training interaction data.

9. A computer device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 2 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 2 to 8 are implemented.

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