Human body use state dynamic evaluation method and system based on artificial intelligence

Abstract

The invention discloses a human body use state dynamic evaluation method based on artificial intelligence. The method comprises the steps that state information used for reflecting the overall human body use state is acquired; analyzing the state information based on an artificial intelligence model to judge whether the human body use state is suitable for continuing or not; outputting a judgment conclusion according to an analysis result, wherein the judgment conclusion is used for indicating whether the human body use state is allowed to continue; in the continuous use process of the human body, the steps are periodically repeated to keep the consistency and stability of judgment. The invention further discloses a human body use state dynamic evaluation system based on artificial intelligence. By using the method or the system, the overall state in the continuous use process of the human body can be dynamically tracked and evaluated, the long-term consistency and stability of judgment are ensured, and running state judgment parameters of the human body use state lacked in an existing diagnosis system are complemented; the judgment result has a blocking type control characteristic; and the judgment layer and the execution scheme are structurally decoupled.

Description

A method and system for dynamic assessment of human usage status based on artificial intelligence Technical Field

[0001] This invention relates to the fields of artificial intelligence and human condition assessment technology, and in particular to an artificial intelligence method and system for dynamically assessing, judging and controlling the overall usage status of the human body, independent of specific diagnostic conclusions or implementation plans. Background Technology

[0002] During prolonged work, exercise, or daily activities, the human body often experiences a state of use disorder characterized by pain, discomfort, or functional limitations. Current medical systems typically rely on imaging examinations, biochemical indicators, or local tissue damage for diagnosis. Their core advantage lies in static diagnosis and short-term treatment. However, for discomfort conditions that are persistent and recurring without a clear organic lesion, they often lack effective means of continuous assessment and control.

[0003] Meanwhile, various training, rehabilitation, physiotherapy, and health management systems typically jump directly to the implementation or intervention phase, relying on individual experience or single-point assessment results, lacking a systematic judgment mechanism to determine whether the overall state of human use is still suitable for continued use. Without a unified judgment layer, the human body may be continuously used in unsuitable structures or states, leading to the repeated amplification of problems. However, the aforementioned solutions generally assume that the human system is in a state of sustainable use, lacking an independent judgment and intervention mechanism to determine whether the overall state of human use is still suitable for continued use.

[0004] Therefore, there is an urgent need for a technological means that is independent of specific training, treatment or implementation plans, to dynamically assess and judge the overall use status of the human body, and to control and guide it in a timely manner when an unsuitable state occurs, so as to avoid the human body being used continuously in an unsuitable state. Summary of the Invention

[0005] To overcome the shortcomings of existing technologies, this invention provides a method and system for dynamic evaluation of human body usage status based on artificial intelligence. This system can dynamically evaluate and judge the overall usage status of the human body, and promptly control and guide the body when unsuitable conditions occur, thereby preventing continuous use of the human body in an unsuitable state. This invention provides a judgment and control layer independent of specific training, treatment, diagnosis, or correction schemes. This judgment and control layer is used to make system-level judgments on whether continued use is permitted during continuous human use, enabling the human body usage process to have, for the first time, an operational permission mechanism that can be blocked, reverted, and verified, thereby preventing the continuous amplification of human body system use in unsuitable states.

[0006] The technical solution adopted by this invention to solve its technical problem is: a dynamic evaluation method for human body usage status based on artificial intelligence, comprising: acquiring status information to reflect the overall human body usage status; analyzing the status information based on an artificial intelligence model to determine whether the human body usage status is suitable to continue; outputting a judgment conclusion based on the analysis results to indicate whether the human body usage status is allowed to continue; and periodically repeating the above steps during continuous human body use to maintain the consistency and stability of the judgment.

[0007] Furthermore, the status information includes information related to human usage behavior, subjective feedback information related to human discomfort or pain, and information related to human posture, movement, or usage status.

[0008] Furthermore, the judgment conclusion includes allowing continuation and pointing back to a safe state.

[0009] Furthermore, the "return to a safe state" refers to prompting the human body to return to a usage state range that the system judges to be relatively safe or more sustainable. This includes, but is not limited to, prompting that the current state is not suitable to continue, prompting that the current usage mode needs to be restricted, adjusted or suspended, and prompting to return to the usage state that was previously judged to be relatively safe.

[0010] Furthermore, the status information includes image information, structured query information, or a combination of both.

[0011] Furthermore, the image information includes multi-angle image information, and the multi-angle image information can be acquired synchronously or nearly synchronously by one or more camera devices at different viewpoints.

[0012] Furthermore, the evaluation results obtained based on artificial intelligence analysis are not used to generate, replace, or automatically execute specific medical diagnosis, treatment, training, or intervention plans, but only to determine whether the human body's usage status is qualified to continue operating, continue using, or enter the next usage stage under the current system conditions.

[0013] Furthermore, the artificial intelligence model includes rule-based models, statistical models, machine learning models, deep learning models, or any combination thereof, and changes in the algorithm structure, training method, or model form of the artificial intelligence model do not affect the operational qualification determination structure corresponding to the dynamic assessment of the human body's usage status.

[0014] Furthermore, the periodic or multi-time-point assessment of the human body's usage status is used to perform system-level stability verification on the consistency of the assessment results before and after, rather than to perform numerical optimization, result correction, or probability superposition on the results of a single assessment.

[0015] Furthermore, the status information includes execution status information formed by basic actions or functional actions.

[0016] Furthermore, the basic or functional actions are used to induce, expose, or confirm the current use state of the human body under uniform execution conditions, so as to support the artificial intelligence model in judging whether the use state of the human body is appropriate to continue.

[0017] Furthermore, the periodic assessment is triggered based on at least one of time, changes in usage status, or system policy.

[0018] This invention also discloses an artificial intelligence-based dynamic evaluation system for human body usage status, comprising: a status information acquisition module for acquiring status information reflecting the overall human body usage status; a status analysis module for analyzing the status information based on an artificial intelligence model; a judgment output module for generating a judgment conclusion on whether the human body usage status is suitable to continue; and a stability control module for maintaining consistency in judgment during long-term operation; wherein, the judgment output module includes a control and feedback unit, which is used to execute control and prompt a return to a safe state when the status is not suitable to continue.

[0019] The beneficial effects of this invention are as follows: By using the above method, an artificial intelligence model can be used to analyze state information reflecting the overall usage state of the human body, thereby determining whether the current or intended usage state is suitable to continue. If the determination result is negative, the user is prompted to impose restrictions and return to a safe usage state. Periodically performing this test allows for dynamic tracking and evaluation of the overall state of the human body during continuous use, ensuring long-term consistency and stability of the judgment, avoiding the randomness of a single evaluation, and providing continuous and reliable state assurance for continuous use. Furthermore, using an artificial intelligence model for analysis and judgment can replace individual experience or single-point evaluation, improving the objectivity and accuracy of the judgment. Moreover, this method only generates… The system provides a prompt indicating whether the current or proposed usage status is suitable to continue, without offering medical improvement suggestions. This aims to prevent the amplification of existing problems and guide the body back to a safe state for sustainable use. It only determines whether the status is suitable to continue and is independent of the execution plan (specific rehabilitation training, treatment procedures, etc.). Its clear boundaries and lack of dependency ensure consistent and stable judgment standards, preventing the execution plan from negatively impacting these standards. Furthermore, the independent judgment result can be adapted to the most suitable execution plan based on the user's individual circumstances, remaining unaffected when the execution plan can be independently optimized, resulting in higher iteration efficiency. It also enables blocking-style risk control. The judgment layer focuses on the core safety judgment of "whether it is suitable to continue," unaffected by the execution plan, allowing for faster intervention when risks arise. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. The accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0022] Figure 1 is a flowchart of the algorithm of the method of the present invention; Figure 2 is a flowchart of the subdivision algorithm of step S100 of the method of the present invention; Figure 3 is a flowchart of the subdivision algorithm of step S400 of the method of the present invention; Figure 4 is a schematic diagram of the modules of the system of the present invention. Detailed Implementation

[0023] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, the specific embodiments of this application are described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of this application. However, this application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of this application. Therefore, this application is not limited to the specific embodiments disclosed below.

[0024] In the description of this specification, the references to "certain embodiments," "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples" refer to specific features, structures, materials, or characteristics described in connection with the described embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0025] Referring to Figures 1 to 3, an artificial intelligence-based dynamic evaluation method for human body usage status includes: S100, acquiring status information reflecting the overall human body usage status; S200, analyzing the status information based on an artificial intelligence model to determine whether the human body usage status is suitable to continue; S300, outputting a judgment conclusion based on the analysis results to indicate whether the human body usage status is allowed to continue; S400, periodically repeating the above steps S100-S300 during continuous human body usage to maintain the consistency and stability of the judgment.

[0026] By using the above method, an artificial intelligence model can be used to analyze state information reflecting the overall usage status of the human body, thereby determining whether the current or intended usage status is suitable to continue. If the judgment is negative, the user is prompted to impose restrictions and return to a safe usage state. Periodically conducting this test allows for dynamic tracking and evaluation of the overall status of the human body during continuous use, ensuring long-term consistency and stability of judgments, avoiding the randomness of single assessments, and providing continuous and reliable status assurance for ongoing use. Furthermore, using an artificial intelligence model for analysis and judgment can replace individual experience or single-point assessments, improving the objectivity and accuracy of the judgment. This method only generates prompts. Whether the current or proposed usage state is suitable to continue does not involve medical improvement suggestions, avoiding further amplification of existing problems and guiding the body back to a safe state for sustainable use. It only judges whether the state is suitable to continue, and is independent of the execution plan (specific rehabilitation training, treatment procedures, etc.), with clear boundaries of responsibility and no binding or dependency. This ensures the uniformity and stability of the judgment criteria, avoids the execution plan from negatively impacting the judgment criteria, and allows the independent judgment result to adapt to the most suitable execution plan based on the user's own situation. It remains unaffected when the execution plan can be independently optimized, resulting in higher iteration efficiency and enabling blocking-type risk control. The judgment layer focuses on the core safety judgment of "whether it is suitable to continue," unaffected by the execution plan, and can more quickly block risks when they occur. From a systems engineering perspective, the judgment and control layer of this invention constitutes a human system operation permission judgment mechanism, used to determine whether the human body in the current state has the system conditions to continue to be used, trained, or loaded.

[0027] The specific execution process of S100 includes the following: S101-S104.

[0028] S101, The person being assessed performs basic and functional actions, and the basic or functional actions form execution status information; S102, Image information is acquired; S103, Structured inquiry information is acquired; S104, Execution status information, image information and structured inquiry information are abstracted and mapped to form structured semantic information.

[0029] The status information includes information related to human usage behavior (such as stepping in place, squatting against a wall, etc.), subjective feedback information related to human discomfort or pain (such as soreness when raising the arm, inability to bend the knee, etc.), and information related to human posture, movement, or usage status (such as raising the thigh, bending the knee to 90 degrees, and swinging the arm to 45 degrees, etc.). This status information can more accurately reflect the overall usage status of the human body, providing sufficient material for subsequent artificial intelligence model analysis, and making the analysis and judgment results more accurate.

[0030] Among them, information related to human use behavior and information related to human posture, movement or use status can be image information, which can be obtained by one or more camera devices simultaneously or nearly simultaneously from different perspectives. Subjective feedback information related to human discomfort or pain can be obtained by structured question information to collect human use-related state descriptions in a standardized form, such as obtaining and filling out standard questionnaires through structured question and answer methods.

[0031] The evaluation process involves obtaining execution status information reflecting the overall usage state of the subject when performing basic or functional actions. This execution status information describes the body's control methods, coordination patterns, tension distribution, compensatory characteristics, or stability under uniform execution conditions. It supports judgments on whether the overall usage state is suitable for continued use. It's important to note that the focus of execution status information is not on evaluating whether specific actions are correct, completed, or have achieved training goals. Rather, it supplements and enhances the consistency and stability of judgments during continuous use. Under uniform execution conditions, it more easily induces, exposes, or confirms the body's current overall usage state, making the functional responses exhibited when performing the action comparable, allowing the AI ​​model to analyze and judge the execution status information. Furthermore, longitudinal analysis of execution status information collected during repetitive execution can identify the stability or deviation trends of the body's state, without relying on subjective judgment. This status information may include, but is not limited to, user subjective experience information, behavior-related information, and execution status information obtained through structured questioning. This status information describes the body's overall usage state at a specific point in time, rather than determining specific physiological structures, disease categories, or treatment paths.

[0032] Among them, structured semantic information is used to constrain the semantic representation of the consistency of artificial intelligence judgment, so that execution state information, image information and structured query information have a consistent expression form, which facilitates the analysis and judgment of state information by artificial intelligence models and enables data from different sources to obtain a consistent expression.

[0033] In step S300, the output judgment conclusion includes allowing continuation and reverting to a safe state. Reverting to a safe state includes, but is not limited to, prompting that the current state is unsuitable for continuation, prompting the need for restriction, adjustment, or suspension of the current usage mode, and prompting a return to a previously determined relatively safe usage state. When it is determined that the human body usage state is unsuitable for continuation, the state is controlled, and the system is reverted to a safe state. This invention, by introducing an independent system-level judgment layer, enables the human body usage process to possess, for the first time, an operational permission mechanism that can be blocked, reverted, and verified, thereby avoiding the continuous amplification of human body system use in unsuitable states.

[0034] In step S400, "periodicity" can be triggered by a time cycle, such as assessing the human body's usage status every three days and repeating steps S100-S300. Alternatively, it can be triggered by a set diagnostic time cycle, with more repetitions in the early stages and gradually decreasing in the later stages. "Periodicity" can also be triggered by a system strategy, where system strategy triggering refers to the periodic assessment being triggered by a preset or adaptive judgment strategy of the system. For example: ① when the judgment result changes significantly; ② when the usage status remains within the boundary range for a long period; ③ when the system identifies an unstable trend in the judgment; ④ or when a review is performed based on a historical judgment consistency strategy. If any of the above conditions ① to ④ are met, the condition will be triggered, and the next repetition will be performed to assess the human body's usage status again.

[0035] For example, the specific execution process of S400 includes the following: S401-S406; S401, during continuous use by the human body, determine whether the system's preset time period has been reached. If the result is yes, execute step S100; if the result is no, execute step S402; S402, during continuous use by the human body, determine whether the judgment result has changed significantly. If the result is yes, execute step S100; if the result is no, execute step S403; S403, during continuous use by the human body, determine whether the usage state has been in the boundary range for a long time. If the result is yes, execute step S100; if the result is no, execute step S404; S404, during continuous use by the human body... During the process, the system determines whether an unstable trend has been detected. If the result is yes, step S100 is executed; if the result is no, step S402 is executed. In step S405, during continuous use of the human body, the current judgment conclusion is compared with historical judgments within a preset time period to determine whether it conforms to the consistent judgment pattern. If the result is no, step S100 is executed; if the result is yes, step S406 is executed. In step S406, during continuous use of the human body, it determines whether an instruction to end the evaluation has been received. If the result is yes, step S407 is executed; if the result is no, step S401 is executed. In step S407, all judgment conclusions during continuous use of the human body are integrated to generate an overall evaluation result.

[0036] In this embodiment, the evaluation results obtained based on artificial intelligence analysis are not used to generate, replace, or automatically execute specific medical diagnosis, treatment, training, or intervention plans, but are only used to determine whether the human body's usage status is qualified to continue operating, continue using, or enter the next usage stage under the current system conditions.

[0037] In this embodiment, the artificial intelligence model includes a rule model, a statistical model, a machine learning model, a deep learning model, or any combination thereof, and changes in the algorithm structure, training method, or model form of the artificial intelligence model do not affect the operational qualification determination structure corresponding to the dynamic assessment of human usage status.

[0038] In this embodiment, the periodic or multi-time-point evaluation of the human body's usage status is used to perform system-level stability verification on the consistency of the evaluation results before and after, rather than to perform numerical optimization, result correction or probability superposition on the results of a single evaluation.

[0039] Referring to Figure 4, the present invention also discloses an artificial intelligence-based dynamic evaluation system for human body usage status, comprising: a status information acquisition module for acquiring status information reflecting the overall human body usage status; a status analysis module for analyzing the status information based on an artificial intelligence model; a judgment output module for generating a judgment conclusion on whether the human body usage status is suitable to continue; and a stability control module for maintaining consistency of judgment during long-term operation; wherein, the judgment output module includes a control and feedback unit, the control and feedback unit being used to execute control and prompt a return to a safe state when the status is not suitable to continue.

[0040] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application. The above embodiments are merely illustrative examples of the present invention and do not constitute a limitation on the scope of protection of the present invention. Equivalent modifications or substitutions made by those skilled in the art without departing from the concept of the present invention should all fall within the scope of protection of the present invention.

Claims

1. A method for dynamically evaluating human usage status based on artificial intelligence, characterized in that, include: Obtain status information that reflects the overall human body usage status; The state information is analyzed based on an artificial intelligence model; a judgment conclusion is output based on the analysis results to indicate whether the human body is allowed to continue using the system; during continuous human use, the above steps are repeated periodically to maintain the consistency and stability of the judgment.

2. The method for dynamic evaluation of human usage status based on artificial intelligence according to claim 1, characterized in that, The status information includes information related to human usage behavior, subjective feedback information related to human discomfort or pain, and information related to human posture, movement, or usage status.

3. The method for dynamic evaluation of human usage status based on artificial intelligence according to claim 1, characterized in that, The judgment conclusion includes allowing continuation and reverting to a safe state.

4. The method for dynamic evaluation of human usage status based on artificial intelligence according to claim 3, characterized in that, The "return to safe state" refers to prompting the user to return to a usage state range that the system judges to be relatively safe or more sustainable. This includes, but is not limited to, prompting that the current state is not suitable to continue, prompting that the current usage mode needs to be restricted, adjusted or suspended, and prompting to return to the usage state that was previously judged to be relatively safe.

5. The method for dynamic evaluation of human usage status based on artificial intelligence according to claim 1, characterized in that, The status information includes image information, structured query information, or a combination of both.

6. The method for dynamic evaluation of human usage status based on artificial intelligence according to claim 5, characterized in that, The image information includes multi-angle image information, and the multi-angle image information can be acquired synchronously or nearly synchronously by one or more camera devices at different viewpoints.

7. The method for dynamic evaluation of human usage status based on artificial intelligence according to claim 1, characterized in that, The evaluation results obtained based on artificial intelligence analysis are not used to generate, replace, or automatically execute specific medical diagnosis, treatment, training, or intervention plans, but only to determine whether the human body's usage status is qualified to continue operating, continue using, or enter the next usage stage under the current system conditions.

8. The method for dynamic evaluation of human usage status based on artificial intelligence according to claim 1, characterized in that, The artificial intelligence model includes rule-based models, statistical models, machine learning models, deep learning models, or any combination thereof, and changes in the algorithm structure, training method, or model form of the artificial intelligence model do not affect the operational qualification determination structure corresponding to the dynamic assessment of human usage status.

9. The method for dynamic evaluation of human usage status based on artificial intelligence according to claim 1, characterized in that, The periodic or multi-time-point assessments of human usage status are used to perform system-level stability verification on the consistency of assessment results before and after, rather than to perform numerical optimization, result correction, or probability superposition on single assessment results.

10. The method for dynamic evaluation of human usage status based on artificial intelligence according to claim 1, characterized in that, The status information includes execution status information formed by basic actions or functional actions.

11. The method for dynamic evaluation of human usage status based on artificial intelligence according to claim 10, characterized in that, The basic or functional actions are used to induce, expose, or confirm the current state of human use under uniform execution conditions, so as to support the artificial intelligence model in judging whether the human use state is appropriate to continue.

12. The method for dynamic evaluation of human usage status based on artificial intelligence according to claim 5, characterized in that, The periodic assessment is triggered based on at least one of time, changes in usage status, or system policy.

13. A dynamic assessment system for human body usage status based on artificial intelligence, characterized in that, include: The status information acquisition module is used to acquire status information that reflects the overall human body usage status; The state analysis module is used to analyze the state information based on an artificial intelligence model; the judgment output module is used to generate a judgment conclusion on whether the human body's usage state is suitable to continue. A stability control module is used to maintain consistency in judgments during long-term operation; wherein, the judgment output module includes a control and feedback unit, which is used to execute control and prompt a return to a safe state when the state is not suitable to continue.

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