Lung cancer patient home exercise rehabilitation training system and method based on severe games

Abstract

The invention discloses a lung cancer patient home exercise rehabilitation training system based on a severe game, and the system comprises a patient terminal device which is used for operating a severe game application and collecting exercise behavior data and physiological signals; the medical care terminal management interface is used for medical care personnel to log in and check patient information and training execution conditions; and the server / cloud platform comprises an exercise prescription engine module which is used for generating an individualized exercise prescription based on the baseline evaluation data of the patient. Through a virtual game scene and a hierarchical breakthrough and reward mechanism, the originally boring respiratory training, resistance training and walking training are integrated into a severe game with the sense of sexuality and goals, the participation interest and the sense of achievement of a patient are stimulated, and the possibility of long-term persistence is remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of medical rehabilitation and digital health, and particularly relates to a lung cancer patient home exercise rehabilitation training system and method based on serious games. BACKGROUND

[0002] Lung cancer is one of the malignant tumors with high morbidity and mortality worldwide. Surgical resection, radiotherapy and chemotherapy are the current main treatment methods. During the perioperative period and comprehensive treatment, lung cancer patients often have problems such as decreased lung function, weakened respiratory muscle strength, reduced exercise tolerance, fatigue and anxiety and depression. Clinical studies have shown that scientific and continuous lung rehabilitation exercise training (including respiratory training, resistance training and aerobic walking) can help improve lung function, increase exercise tolerance, reduce symptoms and improve quality of life.

[0003] The existing lung cancer patient home exercise rehabilitation guidance mainly adopts the forms of paper or electronic "booklets", propaganda leaflets, video teaching, etc., and has the following shortcomings: Poor compliance: this type of intervention mainly relies on the patient's self-conscious execution, lacks real-time feedback and incentive mechanism; the patient needs to remember the training content and frequency by himself, and the long-term execution willingness is low, and it is easy to give up halfway.

[0004] Uncontrollable training quality: it is difficult for medical staff to know the action quality, completion time, training intensity and physiological response of patients at home during training, and it is impossible to dynamically adjust the exercise prescription according to the actual execution situation.

[0005] Limited individualization: traditional paper guidance scheme is mostly a standardized fixed template, which is difficult to adjust the training content and intensity in time according to the patient's lung function basis, postoperative recovery stage, fatigue degree and comorbidity.

[0006] Lack of interest and immersion: the process of lung rehabilitation training is often repetitive and boring, and combined with the long-term treatment cycle of lung cancer patients, it is easy to cause psychological fatigue and boredom, and it is difficult to stimulate the motivation for sustained participation.

[0007] In recent years, some mobile medical applications have tried to introduce simple game elements such as point check-in and ranking list to improve patient participation. However, such applications mostly stay at the level of light gamification, and their core functions are still information display or passive check-in, lacking the design of serious games based on virtual scenes, task-driven and hierarchical clearance mechanisms, and failing to closely bind specific respiratory training, resistance training and aerobic walking actions to game tasks.

[0008] In addition, the existing applications generally lack monitoring of physiological signals during exercise, and do not fully consider the characteristics of lung cancer patients with relatively low cardiopulmonary reserve and high exercise risk, making it difficult to achieve a dynamic balance between training safety and effectiveness.

[0009] Therefore, there is an urgent need for a home exercise rehabilitation training system and method that deeply integrates lung rehabilitation training actions with virtual game scenes, can implement individualized prescriptions, real-time monitoring, and safety warnings, to improve the compliance and effectiveness of home exercise rehabilitation for lung cancer patients. SUMMARY

[0010] The present application aims to provide a lung cancer patient home exercise rehabilitation training system and method based on serious games to solve the technical problems raised in the background art.

[0011] To achieve the above-mentioned purpose, the specific technical solutions of the present application are as follows: a lung cancer patient home exercise rehabilitation training system based on serious games, comprising: A patient terminal device for running a serious game application and collecting exercise behavior data and physiological signals; A medical staff terminal management interface for medical staff to log in and view patient information and training execution; A server / cloud platform, the server / cloud platform comprising: A motion prescription engine module for generating individualized exercise prescriptions based on patient baseline assessment data; A game level management module for constructing virtual game scenes and hierarchical challenge tasks according to exercise prescriptions, and mapping respiratory training, resistance training, and aerobic walking training into corresponding game tasks; A data analysis and adaptive adjustment module for statistical analysis of patient uploaded exercise behavior data and physiological data, and adjustment of subsequent exercise prescription parameters according to preset rules or algorithms; A safety monitoring and warning module for comparing real-time physiological parameters with safety thresholds, and triggering a warning and training suspension prompt when the safety range is exceeded; A patient information and training record storage module for storing patient basic information, exercise prescriptions, training records, and evaluation results.

[0012] Preferably, the patient terminal device comprises a smartphone, a tablet computer, or a virtual reality headset.

[0013] Preferably, the patient terminal device is built-in or externally connected with an acceleration sensor, a gyroscope, a microphone or a respiratory sensor, and a wearable device; wherein, The acceleration sensor and the gyroscope are used to detect walking, aerobic activity, and upper and lower limb resistance training actions; The microphone or respiratory sensor is used to collect patient breathing rhythm and breathing duration parameters; The wearable device is used to collect physiological parameters such as heart rate and blood oxygen saturation.

[0014] Preferably, the medical staff terminal management interface comprises: A patient list and detailed information page for displaying basic information and condition data of each patient; A training compliance and effect visualization page for displaying patient training frequency, completion rate, heart rate and blood oxygen trend chart, game level progress; A prescription adjustment interface for medical staff to manually adjust exercise prescription or modify system adaptive parameters according to patient performance and follow-up results.

[0015] The application also relates to a lung cancer patient home exercise rehabilitation training method based on serious games, comprising the following steps: S1, baseline evaluation and individualized exercise prescription generation, medical staff enter patient basic information and baseline evaluation data through the medical staff end management interface; S2, virtual game scene and hierarchical level task construction, the game level management module constructs a virtual game scene according to the combination and intensity of various training tasks in the exercise prescription, and maps different training modules into different types of game levels; S3, data collection and real-time feedback during training, patients enter corresponding game levels through patient end devices in a home environment, and complete breathing training, resistance training and walking training according to screen or voice prompts; S4, level passing judgment and game feedback, after a single training ends or reaches a preset time, the patient end uploads the collected training data to the server, the data analysis and adaptive adjustment module processes the training data, judges, if the passing conditions are met, the level is determined to be passed and the patient's points, level and virtual scene progress in the game are updated, if not up to standard, appropriate prompts are given and recorded as incomplete or partially completed; S5, adaptive exercise prescription adjustment and safety control, the data analysis and adaptive adjustment module automatically adjusts the parameters of the subsequent exercise prescription based on the training completion rate, heart rate load, subjective fatigue score and discomfort event record in a period of time; S6, visualization display and follow-up support of compliance and rehabilitation effect, patient training data, game level passing records and physiological parameter statistical results are stored in the server for a long time, the medical staff end management interface displays patient training frequency, completion rate, continuous participation days, completion of different training modules, heart rate and blood oxygen trends during and after exercise, safety warning events, and the correlation trend with follow-up lung function test results and exercise tolerance evaluation results in the form of charts and reports, medical staff can comprehensively evaluate the rehabilitation effect of patients in reexamination or remote follow-up based on the above information, and further optimize the exercise prescription.

[0016] Preferably, the patient basic information and baseline evaluation data in the step S1 include age, gender, lung cancer stage, treatment method and stage, lung function indicators, 6-minute walk distance, Borg exertion score, comorbidity, and the exercise prescription engine module automatically generates an individualized lung rehabilitation exercise prescription for the patient based on a preset rule base and threshold, the exercise prescription including frequency, duration and rhythm parameters of respiratory training, action type, group number, number of times and resistance level of resistance training, target time, step number and intensity range of aerobic walking training.

[0017] Preferably, the game level in the step S2 includes: a respiratory training level, which corresponds the processes of inhaling, holding breath and slowly exhaling to the lifting, rotating or fluctuation of virtual objects through virtual balloons, windmills and wave elements; a resistance training level, which maps the upper limb and lower limb resistance training actions to the role energy value promotion or construction progress through the virtual role "lifting heavy objects" and "building bridges" animations; an aerobic walking level, which maps the patient's walking step number or time to the role travel distance and scene advancement through the virtual role moving on the city, forest or planet surface.

[0018] Preferably, the judgment basis in the step S4 is whether each training action reaches a preset completion number and quality threshold, and whether the physiological parameters remain within a safe range.

[0019] Preferably, the parameters in the step S5 include the acceleration or deceleration of respiratory training rhythm, the promotion or reduction of resistance level of resistance training, and the increase or reduction of aerobic walking time or target step number.

[0020] The lung cancer patient home exercise rehabilitation training system and method based on serious games has the following advantages: 1. The virtual game scene, graded level and reward mechanism of the present application integrate the originally dull respiratory training, resistance training and walking training into a serious game with a plot and a sense of target, stimulate the patient's interest in participation and sense of achievement, and significantly improve the possibility of long-term adherence.

[0021] 2. The exercise prescription engine and adaptive adjustment module of the present application individually set and dynamically adjust the training content and intensity according to the baseline evaluation results of the patient and the data feedback in the training process, so that the lung cancer patients gradually increase the exercise load within a safe range.

[0022] 3. The present application uses patient terminal devices and wearable devices to collect action data and physiological signals such as heart rate and blood oxygen in real time, and through action quality determination and safety warning mechanism, ensures that the patient carries out lung rehabilitation training in the home environment while reducing the risk of exercise.

[0023] 4. This invention allows medical staff to remotely monitor and adjust the patient's rehabilitation progress through a management interface after uploading home training data to a server, thus overcoming the problems of information opacity and management gaps in the traditional paper-based guidance model.

[0024] 5. The serious game architecture and modular design of this invention are not only applicable to lung cancer patients, but can also be extended to other chronic respiratory diseases and cardiopulmonary rehabilitation populations, which is conducive to its widespread promotion in the context of "Internet + healthcare". Attached Figure Description

[0025] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained from these drawings without creative effort.

[0026] Figure 1 This is a schematic diagram of the overall structure of the present invention; Figure 2 This is a schematic diagram of the patient-side device in this invention; Figure 3 This is a schematic diagram of the server / cloud platform structure in this invention; Figure 4 This is a schematic diagram of the TCM patient management interface of the present invention; Figure 5 This is a schematic diagram of the structure of a game level in this invention. Detailed Implementation

[0027] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the embodiments of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0028] In the description of the embodiments of the present invention, it should be understood that the terms "length", "vertical", "horizontal", "top", "bottom", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings. They are only for the convenience of describing the embodiments of the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the embodiments of the present invention.

[0029] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of embodiments of the present invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0030] In this embodiment of the invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection, an electrical connection, or a communication connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this embodiment of the invention according to the specific circumstances.

[0031] The following disclosure provides many different implementations or examples for carrying out different structures of the embodiments of the present invention. To simplify the disclosure of the embodiments of the present invention, specific examples of components and arrangements are described below. Of course, these are merely examples and are not intended to limit the embodiments of the present invention. Furthermore, reference numerals and / or reference letters may be repeated in different examples of the embodiments of the present invention; such repetition is for simplification and clarity and does not in itself indicate a relationship between the various implementations and / or arrangements discussed.

[0032] To better understand the purpose, structure, and function of this invention, the following detailed description, in conjunction with the accompanying drawings, provides an overview of a home-based exercise rehabilitation training system and method for lung cancer patients based on serious games.

[0033] like Figures 1-5 As shown, the present invention provides a home-based exercise rehabilitation training system for lung cancer patients based on serious games, comprising: The patient-side device is used to run serious gaming applications and collect motion behavior data and physiological signals. The healthcare management interface is used by healthcare staff to log in and view patient information and training progress. Server / cloud platform, wherein the server / cloud platform includes: The exercise prescription engine module is used to generate individualized exercise prescriptions based on patient baseline assessment data; The game level management module is used to construct virtual game scenes and graded challenge tasks based on exercise prescriptions, and to map breathing training, resistance training and aerobic walking training into corresponding game tasks. The data analysis and adaptive adjustment module is used to perform statistical analysis on the exercise behavior data and physiological data uploaded by patients, and adjust the parameters of subsequent exercise prescriptions according to preset rules or algorithms. The safety monitoring and early warning module is used to compare real-time physiological parameters with safety thresholds and trigger early warnings and training stop prompts when they exceed the safety range. The patient information and training record storage module is used to store basic patient information, exercise prescriptions, training records, and evaluation results.

[0034] The patient-side devices include, but are not limited to, smartphones, tablets, or virtual reality headsets.

[0035] The patient-side device is equipped with or connected to an accelerometer, gyroscope, microphone or respiratory sensor, and wearable device, either internally or externally. The accelerometer and gyroscope are used to detect walking, aerobic activity, and resistance training movements of the upper and lower limbs. The microphone or breathing sensor is used to collect parameters such as the patient's breathing rhythm and breathing duration. The wearable devices (such as heart rate wristbands and finger-clip pulse oximeters) are used to collect physiological parameters such as heart rate and blood oxygen saturation.

[0036] The healthcare management interface includes: The patient list and details page is used to display the basic information and condition data of each patient; The training compliance and effectiveness visualization page is used to display patients' training frequency, completion rate, heart rate and blood oxygen trend graphs, and game progress. The prescription adjustment interface allows medical staff to manually adjust exercise prescriptions or modify system adaptive parameters based on patient compliance and follow-up results.

[0037] This invention also relates to a method for home-based exercise rehabilitation training for lung cancer patients based on serious games, comprising the following steps: S1. Baseline assessment and individualized exercise prescription generation: Medical staff enter basic patient information and baseline assessment data through the medical staff management interface. S2. Virtual game scene and graded challenge task construction: The game level management module constructs virtual game scenes based on the combination and intensity of various training tasks in the exercise prescription, and maps different training modules to different types of game levels. S3. Data collection and real-time feedback during training: Patients access corresponding game levels in their home environment via their patient-end device and complete breathing training, resistance training, and walking training according to on-screen or voice prompts. The patient-end device collects data in real time through built-in / external sensors. Motor behavior data: including steps, cadence, acceleration changes, upper / lower limb range of motion and rhythm, etc. Respiratory data: including inspiratory and expiratory duration, respiratory rate, and rhythm characteristics; Physiological signal data: including heart rate, blood oxygen saturation, and patient subjective discomfort reports (via in-app ratings or button feedback); The patient-side device makes a preliminary judgment on the completion of the action based on a preset algorithm, and provides positive feedback or corrective prompts through animation effects, sound effects and text prompts in the game; S4. Level completion judgment and game feedback: After a single training session ends or a preset time is reached, the patient uploads the collected training data to the server. The data analysis and adaptive adjustment module processes the training data and makes a judgment. If the level completion conditions are met, the level is determined to be completed and the patient's score, level and virtual scene progress in the game are updated. If the conditions are not met, a corresponding prompt is given and it is recorded as incomplete or partially completed. S5. Adaptive exercise prescription adjustment and safety control: The data analysis and adaptive adjustment module automatically adjusts the parameters of subsequent exercise prescriptions based on training completion rate, heart rate load, subjective fatigue score and discomfort event records over a period of time (e.g., 1 week). S6. Visualization and follow-up support for compliance and rehabilitation effects: Patient training data, game completion records, and physiological parameter statistics are stored on the server. The medical staff management interface displays patient training frequency, completion rate, number of consecutive days of participation, completion status of different training modules, heart rate and blood oxygen trends during and after exercise, safety warning events, and correlation trends with lung function test results and exercise tolerance assessment results during follow-up visits based on the above information. Medical staff can comprehensively evaluate the patient's rehabilitation effect during follow-up visits or remote follow-ups and further optimize exercise prescriptions.

[0038] In step S1, the patient's basic information and baseline assessment data include age, gender, lung cancer stage, treatment method and stage, pulmonary function indicators, 6-minute walking distance, Borg fatigue score, and comorbidities. The exercise prescription engine module automatically generates an individualized pulmonary rehabilitation exercise prescription for the patient based on a preset rule base and thresholds. The exercise prescription includes the frequency, duration, and rhythm parameters of breathing training, the type of movement, number of sets, number of repetitions, and resistance level of resistance training, and the target time, number of steps, and intensity range (such as the target heart rate zone) of aerobic walking training.

[0039] The game levels in step S2 include: The breathing training challenge uses virtual balloons, windmills, and waves to correspond the processes of inhalation, breath-holding, and slow exhalation with the rising, falling, rotating, or undulating of virtual objects. Resistance training levels use animations of virtual characters "lifting heavy objects" and "building bridges" to map upper and lower limb resistance training movements to character energy increases or construction progress. The aerobic walking challenge involves a virtual character moving through a city, forest, or planetary surface. The number of steps or time taken by the patient is mapped to the distance the character travels and the progression of the scene. Each challenge has set conditions for completion, including minimum training time, number of times the movement can be completed, quality judgment threshold, and physiological safety range. A reward mechanism is also established by combining elements such as points, badges, virtual props, and story unlocks.

[0040] The criteria for judgment in step S4 are whether each training action has reached the preset number of completions and quality thresholds, and whether physiological parameters are kept within a safe range.

[0041] The parameters in step S5 include accelerating or slowing down the breathing training rhythm, increasing or decreasing the resistance level of resistance training, and increasing or decreasing the aerobic walking time or target number of steps. The safety monitoring and early warning module compares real-time physiological data with preset safety thresholds. When the heart rate exceeds the upper limit, the blood oxygen saturation is lower than the lower limit, or the patient actively reports obvious discomfort, it is automatically triggered. A safety prompt pops up on the patient's end and pauses or terminates the current level, and sends an early warning message to the medical staff management interface to prompt medical staff to conduct assessment and intervention.

[0042] Upon entering the game, the game screen will load and you will be directed to the game homepage. You can choose to log in via WeChat or as a guest. To log in via WeChat, you can scan a QR code and then link your account to enter the main game menu. You will then see breathing training, resistance training, and walking training. Select a training method to start the game. After the game ends, your score will be displayed.

[0043] It is understood that the present invention has been described through some embodiments, and those skilled in the art will recognize that various changes or equivalent substitutions can be made to these features and embodiments without departing from the spirit and scope of the invention. Furthermore, under the teachings of the present invention, these features and embodiments can be modified to adapt to specific situations and materials without departing from the spirit and scope of the invention. Therefore, the present invention is not limited to the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are within the protection scope of the present invention.

Claims

1. A home-based exercise rehabilitation training system for lung cancer patients based on serious games, characterized in that: include: The patient-side device is used to run serious gaming applications and collect motion behavior data and physiological signals. The healthcare management interface is used by healthcare staff to log in and view patient information and training progress. Server / cloud platform, wherein the server / cloud platform includes: The exercise prescription engine module is used to generate individualized exercise prescriptions based on patient baseline assessment data; The game level management module is used to construct virtual game scenes and graded challenge tasks based on exercise prescriptions, and to map breathing training, resistance training and aerobic walking training into corresponding game tasks. The data analysis and adaptive adjustment module is used to perform statistical analysis on the exercise behavior data and physiological data uploaded by patients, and adjust the parameters of subsequent exercise prescriptions according to preset rules or algorithms. The safety monitoring and early warning module is used to compare real-time physiological parameters with safety thresholds and trigger early warnings and training stop prompts when they exceed the safety range. The patient information and training record storage module is used to store basic patient information, exercise prescriptions, training records, and evaluation results.

2. The home-based exercise rehabilitation training system for lung cancer patients based on serious games according to claim 1, characterized in that: The patient-side device includes a smartphone, tablet, or virtual reality headset.

3. The home-based exercise rehabilitation training system for lung cancer patients based on serious games according to claim 1, characterized in that: The patient-side device is equipped with or connected to an accelerometer, gyroscope, microphone or respiratory sensor, and wearable device, either internally or externally. The accelerometer and gyroscope are used to detect walking, aerobic activity, and resistance training movements of the upper and lower limbs. The microphone or breathing sensor is used to collect parameters such as the patient's breathing rhythm and breathing duration. The wearable device is used to collect physiological parameters such as heart rate and blood oxygen saturation.

4. The home-based exercise rehabilitation training system for lung cancer patients based on serious games according to claim 1, characterized in that: The healthcare management interface includes: The patient list and details page is used to display the basic information and condition data of each patient; The training compliance and effectiveness visualization page is used to display patients' training frequency, completion rate, heart rate and blood oxygen trend graphs, and game progress. The prescription adjustment interface allows medical staff to manually adjust exercise prescriptions or modify system adaptive parameters based on patient compliance and follow-up results.

5. A method for home-based exercise rehabilitation training for lung cancer patients based on serious games, characterized in that: Includes the following steps: S1. Baseline assessment and individualized exercise prescription generation: Medical staff enter basic patient information and baseline assessment data through the medical staff management interface. S2. Virtual game scene and graded challenge task construction: The game level management module constructs virtual game scenes based on the combination and intensity of various training tasks in the exercise prescription, and maps different training modules to different types of game levels. S3. Data collection and real-time feedback during training: Patients can enter the corresponding game level through the patient terminal device in their home environment and complete breathing training, resistance training and walking training according to the screen or voice prompts. S4. Level completion judgment and game feedback: After a single training session ends or a preset time is reached, the patient uploads the collected training data to the server. The data analysis and adaptive adjustment module processes the training data and makes a judgment. If the level completion conditions are met, the level is determined to be completed and the patient's score, level and virtual scene progress in the game are updated. If the conditions are not met, a corresponding prompt is given and it is recorded as incomplete or partially completed. S5. Adaptive exercise prescription adjustment and safety control: The data analysis and adaptive adjustment module automatically adjusts the parameters of subsequent exercise prescriptions based on training completion rate, heart rate load, subjective fatigue score and discomfort event records over a period of time. S6. Visualization and follow-up support for compliance and rehabilitation effects: Patient training data, game completion records, and physiological parameter statistics are stored on the server. The medical staff management interface displays patient training frequency, completion rate, number of consecutive days of participation, completion status of different training modules, heart rate and blood oxygen trends during and after exercise, safety warning events, and correlation trends with lung function test results and exercise tolerance assessment results during follow-up visits based on the above information. Medical staff can comprehensively evaluate the patient's rehabilitation effect during follow-up visits or remote follow-ups and further optimize exercise prescriptions.

6. The method for home-based exercise rehabilitation training for lung cancer patients based on serious games according to claim 5, characterized in that: In step S1, the patient's basic information and baseline assessment data include age, gender, lung cancer stage, treatment method and stage, lung function indicators, 6-minute walking distance, Borg fatigue score, and comorbidities. The exercise prescription engine module automatically generates an individualized pulmonary rehabilitation exercise prescription for the patient based on a preset rule base and thresholds. The exercise prescription includes the frequency, duration, and rhythm parameters of breathing training, the type of movement, number of sets, number of repetitions, and resistance level of resistance training, and the target time, number of steps, and intensity range of aerobic walking training.

7. A method for home-based exercise rehabilitation training for lung cancer patients based on serious games, as described in claim 5, characterized in that: The game levels in step S2 include: The breathing training challenge uses virtual balloons, windmills, and waves to correspond the processes of inhalation, breath-holding, and slow exhalation with the rising, falling, rotating, or undulating of virtual objects. Resistance training levels use animations of virtual characters "lifting heavy objects" and "building bridges" to map upper and lower limb resistance training movements to character energy increases or construction progress. Aerobic walking challenges allow users to move through cities, forests, or planetary surfaces using virtual characters, mapping the number of steps or time taken by the user to the distance the character travels and the progression of the scene.

8. A method for home-based exercise rehabilitation training for lung cancer patients based on serious games, as described in claim 5, characterized in that: The criteria for judgment in step S4 are whether each training action has reached the preset number of completions and quality thresholds, and whether physiological parameters are kept within a safe range.

9. A method for home-based exercise rehabilitation training for lung cancer patients based on serious games, as described in claim 5, characterized in that: The parameters in step S5 include accelerating or slowing down the breathing training rhythm, increasing or decreasing the resistance level of resistance training, and increasing or decreasing the aerobic walking time or target number of steps.

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