A lung cancer postoperative rehabilitation method and system

Abstract

The present invention relates to a lung cancer postoperative rehabilitation method and system, and relates to the field of medical technology, including: a target patient obtains a test video and performs exercise; real-time monitoring of the motion position information and physical sign information during the exercise; after the exercise is completed, a motion video is generated; the preoperative motion data of the target patient is obtained; according to the physical sign information, the tolerance value of the target patient is obtained; according to the motion video and the preoperative motion data, the emotional value of the target patient is obtained; according to the motion position information, the mastery value of the target patient is obtained; according to the tolerance value, the emotional value and the mastery value, the postoperative rehabilitation plan of the target patient for lung cancer is determined. Thus, a personalized rehabilitation plan is formulated according to the patient's condition, and the rehabilitation effect is improved through real-time monitoring and comprehensive evaluation indicators.

Description

Technical Field

[0001] The present invention relates to the field of medical technology, and in particular to a method, system, electronic device and non-transitory computer-readable storage medium for lung cancer post-operative rehabilitation. Background Art

[0002] Lung cancer is a common malignant tumor, and surgical resection is a common treatment method. However, postoperative rehabilitation is crucial for the patient's recovery and quality of life. Currently, there is a lack of a comprehensive postoperative rehabilitation method for lung cancer that can effectively promote the patient's recovery and improve their quality of life. Summary of the invention

[0003] In view of the technical problems existing in the prior art, the present invention provides a lung cancer postoperative rehabilitation method, system, electronic device and non-transitory computer-readable storage medium.

[0004] The technical solution of the present invention to solve the above technical problems is as follows:

[0005] The present invention provides a method for postoperative rehabilitation of lung cancer, the method comprising:

[0006] The target patient obtains the test video and performs the exercise;

[0007] Real-time monitoring of movement position information and vital sign information during the movement;

[0008] After the exercise is completed, a motion video is generated;

[0009] Acquiring preoperative movement data of the target patient;

[0010] Obtaining the tolerance value of the target patient according to the physical sign information;

[0011] Obtaining an emotion value of the target patient according to the motion video and the preoperative motion data;

[0012] obtaining a grasp value of the target patient according to the motion position information;

[0013] A postoperative rehabilitation program for lung cancer of the target patient is determined according to the tolerance value, the emotion value and the mastery value.

[0014] Optionally, before the target patient obtains the test video and performs exercise, the method further includes:

[0015] The doctor sends the test video to the target patient.

[0016] Optionally, obtaining the tolerance value of the target patient according to the physical sign information includes:

[0017] The vital signs information includes heart rate and respiratory rate;

[0018] Obtaining an average heart rate and an average respiratory rate of the target patient during exercise;

[0019] The tolerance value of the target patient is calculated according to the average heart rate and the average respiratory rate.

[0020] Optionally, calculating the tolerance value of the target patient according to the average heart rate and the average respiratory rate includes:

[0021] Tolerance value = (average heart rate - baseline heart rate) / baseline heart rate + (average respiratory rate - baseline respiratory rate) / baseline respiratory rate.

[0022] Optionally, obtaining the emotion value of the target patient according to the motion video and the preoperative motion data includes:

[0023] calculating the preoperative emotion of the target patient according to the preoperative movement data;

[0024] Calculating the sports emotion of the target patient according to the sports video;

[0025] Based on the preoperative emotion and the exercise emotion, an emotion value of the target patient is obtained.

[0026] Optionally, calculating the preoperative emotion of the target patient according to the preoperative movement data includes:

[0027] The preoperative exercise data includes preoperative exercise duration and preoperative exercise type;

[0028] If the preoperative exercise duration is less than the time threshold, the preoperative emotion is 0;

[0029] If the duration of the preoperative exercise is greater than the time threshold, determining whether the preoperative exercise type belongs to high-intensity exercise;

[0030] If the preoperative exercise type is high-intensity exercise, the preoperative mood is 2; if the preoperative exercise type is not high-intensity exercise, the preoperative mood is 1.

[0031] Optionally, calculating the sports emotion of the target patient according to the sports video includes:

[0032] Input the motion video into an expression recognition model to obtain an expression emotion type; the expression emotion type includes positive, neutral, and negative;

[0033] Obtaining the occurrence period of negative expressions and neutral expressions in the sports video;

[0034] In the sports video, obtaining the sound information of the occurrence period;

[0035] extracting semantic information from the sound information;

[0036] Inputting the semantic information into a semantic recognition model to obtain a semantic emotion type; the semantic emotion type includes positive, neutral, and negative;

[0037] If the facial expression type is negative and the semantic emotion type is negative, the motion emotion is 0; if the facial expression type is positive and the semantic emotion type is positive, the motion emotion is 2; otherwise, the motion emotion is 1.

[0038] Optionally, obtaining the grasping value of the target patient according to the motion position information includes:

[0039] Determining the standard degree of the action according to the motion position information;

[0040] The action standard degree is used as the mastery value of the target patient.

[0041] Optionally, determining a postoperative rehabilitation program for lung cancer of the target patient according to the tolerance value, the emotion value, and the mastery value includes:

[0042] Calculating the suitability of the test video according to the tolerance value, the emotion value, and the mastery value;

[0043] Based on the suitability, a postoperative rehabilitation program for lung cancer is determined for the target patient.

[0044] The present invention also provides a lung cancer postoperative rehabilitation system, the system comprising:

[0045] A motion module is used for the target patient to obtain a test video and perform exercise; after the exercise is completed, a motion video is generated;

[0046] A first data acquisition module, used for real-time monitoring of movement position information and vital sign information during the movement;

[0047] A second data acquisition module, used to acquire preoperative movement data of the target patient;

[0048] A first data calculation module, used for obtaining the tolerance value of the target patient according to the physical sign information;

[0049] A second data calculation module, used for obtaining the emotion value of the target patient according to the motion video and the preoperative motion data;

[0050] A third data calculation module, used for obtaining the grasp value of the target patient according to the motion position information;

[0051] A program determination module is used to determine the target patient's lung cancer postoperative rehabilitation program based on the tolerance value, the emotion value and the mastery value.

[0052] Optionally, before the target patient obtains the test video and performs exercise, the method further includes:

[0053] The doctor sends the test video to the target patient.

[0054] Optionally, the first data calculation module is further used to:

[0055] The vital signs information includes heart rate and respiratory rate;

[0056] Obtaining an average heart rate and an average respiratory rate of the target patient during exercise;

[0057] The tolerance value of the target patient is calculated according to the average heart rate and the average respiratory rate.

[0058] Optionally, calculating the tolerance value of the target patient according to the average heart rate and the average respiratory rate includes:

[0059] Tolerance value = (average heart rate - baseline heart rate) / baseline heart rate + (average respiratory rate - baseline respiratory rate) / baseline respiratory rate.

[0060] Optionally, the second data calculation module is further used to:

[0061] calculating the preoperative emotion of the target patient according to the preoperative movement data;

[0062] Calculating the sports emotion of the target patient according to the sports video;

[0063] Based on the preoperative emotion and the exercise emotion, an emotion value of the target patient is obtained.

[0064] Optionally, calculating the preoperative emotion of the target patient according to the preoperative movement data includes:

[0065] The preoperative exercise data includes preoperative exercise duration and preoperative exercise type;

[0066] If the preoperative exercise duration is less than the time threshold, the preoperative emotion is 0;

[0067] If the duration of the preoperative exercise is greater than the time threshold, determining whether the preoperative exercise type belongs to high-intensity exercise;

[0068] If the preoperative exercise type is high-intensity exercise, the preoperative mood is 2; if the preoperative exercise type is not high-intensity exercise, the preoperative mood is 1.

[0069] Optionally, calculating the sports emotion of the target patient according to the sports video includes:

[0070] Input the motion video into an expression recognition model to obtain an expression emotion type; the expression emotion type includes positive, neutral, and negative;

[0071] Obtaining the occurrence period of negative expressions and neutral expressions in the sports video;

[0072] In the sports video, obtaining the sound information of the occurrence period;

[0073] extracting semantic information from the sound information;

[0074] Inputting the semantic information into a semantic recognition model to obtain a semantic emotion type; the semantic emotion type includes positive, neutral, and negative;

[0075] If the facial expression type is negative and the semantic emotion type is negative, the motion emotion is 0; if the facial expression type is positive and the semantic emotion type is positive, the motion emotion is 2; otherwise, the motion emotion is 1.

[0076] Optionally, the third data calculation module is further used to:

[0077] Determining the standard degree of the action according to the motion position information;

[0078] The action standard degree is used as the mastery value of the target patient.

[0079] Optionally, the solution determination module is further used to:

[0080] Calculating the suitability of the test video according to the tolerance value, the emotion value, and the mastery value;

[0081] Based on the suitability, a postoperative rehabilitation program for lung cancer is determined for the target patient.

[0082] In addition, to achieve the above-mentioned purpose, the present invention also proposes an electronic device, comprising: a memory for storing a computer software program; a processor for reading and executing the computer software program, thereby realizing a lung cancer postoperative rehabilitation method as described above.

[0083] In addition, to achieve the above-mentioned purpose, the present invention also proposes a non-transitory computer-readable storage medium, in which a computer software program is stored. When the computer software program is executed by a processor, a lung cancer postoperative rehabilitation method as described above is implemented.

[0084] The beneficial effects of the present invention are:

[0085] (1) The target patient of the present invention obtains a test video and performs exercise; monitors the movement position information and physical sign information during the exercise in real time; generates a movement video after the exercise is completed; obtains the preoperative movement data of the target patient; obtains the tolerance value of the target patient based on the physical sign information; obtains the emotional value of the target patient based on the movement video and the preoperative movement data; obtains the mastery value of the target patient based on the movement position information; calculates the suitability of the test video based on the tolerance value, the emotional value, and the mastery value, and determines the postoperative rehabilitation plan for lung cancer of the target patient. In this way, a personalized rehabilitation plan is formulated according to the patient's condition, and the rehabilitation effect is improved through real-time monitoring and comprehensive evaluation indicators.

[0086] (2) The present invention takes into account the influence of the patient's exercise habits before lung cancer surgery and the possible psychological changes of the patient after surgery on the postoperative rehabilitation exercise, and calculates the preoperative emotion of the target patient based on the preoperative exercise data; calculates the exercise emotion of the target patient based on the exercise video; and obtains the emotion value of the target patient based on the preoperative emotion and the exercise emotion. In this way, more accurate emotion recognition is achieved.

[0087] (3) At the same time, the semantics of facial expressions and speech at the same time are combined to determine the sports emotions, further improving the accuracy of emotion recognition.

[0088] (4) The present invention also determines the standard degree of movement based on the movement position information, and uses the standard degree of movement as the mastery value of the target patient. Thus, the patient's ability and progress are adapted to improve the rehabilitation effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0089] Figure 1 A scene diagram of a lung cancer postoperative rehabilitation method provided by the present invention;

[0090] Figure 2 A flowchart of a lung cancer postoperative rehabilitation method provided by the present invention;

[0091] Figure 3 A flow chart for determining the emotion value of a target patient provided by the present invention;

[0092] Figure 4 A schematic diagram of the structure of a lung cancer postoperative rehabilitation system provided by the present invention;

[0093] Figure 5 A schematic diagram of the hardware structure of a possible electronic device provided by the present invention;

[0094] Figure 6 A schematic diagram of the hardware structure of a possible computer-readable storage medium provided by the present invention. DETAILED DESCRIPTION

[0095] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0096] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0097] In the description of the present invention, the term "for example" is used to mean "used as an example, illustration or explanation". Any embodiment described as "for example" in the present invention is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any technician in the field to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in the present invention.

[0098] See also Figure 1 , Figure 1 This is a scene diagram of a lung cancer postoperative rehabilitation method provided by the present invention. Figure 1 As shown, the terminal and the server are connected via a network, such as a wired or wireless network connection. The terminal may include but is not limited to portable terminals such as mobile phones and tablets installed with various network platform applications, as well as fixed terminals such as computers, query machines, and advertising machines. The server provides users with various business services, including service push servers, user recommendation servers, etc.

[0099] It should be noted that Figure 1The scenario diagram of a lung cancer postoperative rehabilitation method shown is only an example. The terminal, server, and application scenario described in the embodiment of the present invention are intended to more clearly illustrate the technical solution of the embodiment of the present invention, and do not generate limitations on the technical solution provided by the embodiment of the present invention. Ordinary technicians in this field can know that with the evolution of the system and the emergence of new business scenarios, the technical solution provided by the embodiment of the present invention is also applicable to similar technical problems.

[0100] Among them, the terminal can be used for:

[0101] The target patient obtains the test video and performs the exercise;

[0102] Real-time monitoring of movement position information and vital sign information during the movement;

[0103] After the exercise is completed, a motion video is generated;

[0104] Acquiring preoperative movement data of the target patient;

[0105] Obtaining the tolerance value of the target patient according to the physical sign information;

[0106] Obtaining an emotion value of the target patient according to the motion video and the preoperative motion data;

[0107] obtaining a grasp value of the target patient according to the motion position information;

[0108] A postoperative rehabilitation program for lung cancer of the target patient is determined according to the tolerance value, the emotion value and the mastery value.

[0109] See also Figure 2 , provides a flow chart of a lung cancer postoperative rehabilitation method of the present invention, comprising the following steps:

[0110] Step 201: The target patient obtains a test video and performs exercise.

[0111] Optionally, the target patient logs in to the patient terminal, wears a gyroscope device, an optical heart rate sensor device, and an acceleration sensor device, then turns on the test video and camera, and starts exercising following the test video. The gyroscope device, the optical heart rate sensor device, and the acceleration sensor device can be integrated into the same device or dispersed in different devices, which is not specifically limited here.

[0112] Before step 201, the method further includes: a doctor logs in to a doctor's terminal to view and send the test video to the target patient.

[0113] The test video can be automatically generated by the system or edited by the doctor based on the actual situation of the patient.

[0114] Step 202: monitor the movement position information and vital sign information during the movement in real time.

[0115] Among them, the motion position information of the target patient is collected by a gyroscope device, and the motion position information includes joint angles and body part positions; the vital sign information of the target patient is collected by an optical heart rate sensor device and an acceleration sensor device, and the vital sign information includes heart rate and respiratory rate.

[0116] Step 203: After the exercise is completed, a motion video is generated.

[0117] Step 204: Acquire preoperative movement data of the target patient.

[0118] The preoperative movement data may be filled in manually by the target patient, or may be obtained from the target patient's movement recording device, such as a sports bracelet.

[0119] Step 205: Obtain the tolerance value of the target patient according to the physical sign information.

[0120] Specifically, the average heart rate and average respiratory rate of the target patient during exercise are obtained; based on the average heart rate and average respiratory rate, the tolerance value of the target patient is calculated according to the formula: tolerance value = (average heart rate - baseline heart rate) / baseline heart rate + (average respiratory rate - baseline respiratory rate) / baseline respiratory rate.

[0121] It should be noted that the baseline heart rate and baseline respiratory rate can be set according to the individual differences and rehabilitation goals of the patient.

[0122] Step 206: Obtain the emotion value of the target patient according to the motion video and the preoperative motion data.

[0123] In one implementation, step 206 may include the following steps:

[0124] Step 2061: Calculate the preoperative emotion of the target patient based on the preoperative movement data.

[0125] The preoperative exercise data includes preoperative exercise duration and preoperative exercise type. The preoperative exercise type may include high-intensity exercise (such as weightlifting, sprinting) and general exercise.

[0126] Specifically, if the preoperative exercise duration is less than the time threshold, the preoperative emotion is 0; if the preoperative exercise duration is greater than the time threshold, it is determined whether the preoperative exercise type belongs to high-intensity exercise; if so, the preoperative emotion is 2; otherwise, the preoperative emotion is 1. It can be seen that the higher the preoperative emotion, the higher the target patient's willingness to exercise.

[0127] Step 2062: Calculate the target patient's sports emotion based on the sports video.

[0128] Specifically, the motion video is input into a trained expression recognition model, and the expression recognition model includes an input layer, a convolution layer, a nonlinear sampling layer, a smoothing layer, a fully connected layer, and an output layer; the expression features of the motion video are extracted through the convolution layer, and the convolution result sequence is combined and input into the nonlinear sampling layer and the smoothing layer for processing, and then enters the fully connected layer to obtain the expression information, and finally the expression emotion type of the motion video is output through the output layer; the expression emotion type includes positive, neutral, and negative; then, the occurrence period of negative expression and neutral expression in the motion video is obtained; in the motion video, the sound information of the occurrence period is obtained; the semantic information in the sound information is extracted; the semantic information is input into the semantic recognition model to obtain the semantic emotion type; the semantic emotion type includes positive, neutral, and negative; if the expression emotion type is negative and the semantic emotion type is negative, the motion emotion is 0; if the expression emotion type is positive and the semantic emotion type is positive, the motion emotion is 2; in other cases, the motion emotion is 1. That is, when both the expression and the semantics are positive, the target patient has a higher willingness to exercise.

[0129] Therefore, the sports emotions determined by combining facial expressions and semantics of the same period are more accurate.

[0130] Step 2063: Obtain the emotion value of the target patient based on the preoperative emotion and the exercise emotion.

[0131] Specifically, the sentiment value is calculated according to the following formula:

[0132] ;

[0133] in, Expressing preoperative emotions, It represents the exercise mood. The values ​​of α and β can be set according to the severity of lung cancer, α+β=1.

[0134] In the above-mentioned way, more accurate emotion recognition is achieved by taking into account the exercise habits of patients before lung cancer surgery and the impact of possible psychological changes of patients after surgery on postoperative rehabilitation exercises.

[0135] Step 207: Obtain the grasp value of the target patient according to the motion position information.

[0136] Specifically, the average difference between the joint angles and the corresponding joint angles in the standard movements is calculated, and the average difference between the body part positions and the corresponding positions in the standard movements is calculated. The sum of these two average difference degrees is equal to the standard movement degree; the standard movement degree is used as the mastery value of the target patient.

[0137] Among them, indicators such as Euclidean distance, angle difference or position deviation can be used to measure the degree of difference, and no specific limitation is made here.

[0138] Thus, the patient's abilities and progress are adapted to improve the rehabilitation effect.

[0139] Step 208: Determine a postoperative rehabilitation plan for lung cancer for the target patient according to the tolerance value, the emotion value, and the mastery value.

[0140] Specifically, the suitability of the test video is calculated according to the tolerance value, the emotion value and the mastery value; and the postoperative rehabilitation program for lung cancer of the target patient is determined according to the suitability.

[0141] Optionally, calculate fitness according to the following formula:

[0142] ;

[0143] Among them, c represents the tolerance value, s represents the emotion value, and z represents the mastery value. They represent parameter weights respectively.

[0144] Optionally, when the suitability is greater than a preset threshold, the current test video is determined as the lung cancer postoperative rehabilitation plan for the target patient; when the suitability is less than or equal to the preset threshold, the lung cancer postoperative rehabilitation plan for the target patient is adjusted.

[0145] Therefore, a personalized rehabilitation plan is formulated according to the patient's condition, and the rehabilitation effect is improved through real-time monitoring and comprehensive evaluation indicators.

[0146] See also Figure 4 , Figure 4 This is a schematic structural diagram of a lung cancer postoperative rehabilitation system provided by the present invention.

[0147] like Figure 4 As shown, a lung cancer postoperative rehabilitation system proposed in an embodiment of the present invention includes:

[0148] A motion module is used for the target patient to obtain a test video and perform exercise; after the exercise is completed, a motion video is generated;

[0149] A first data acquisition module, used for real-time monitoring of movement position information and vital sign information during the movement;

[0150] A second data acquisition module, used to acquire preoperative movement data of the target patient;

[0151] A first data calculation module, used for obtaining the tolerance value of the target patient according to the physical sign information;

[0152] A second data calculation module, used for obtaining the emotion value of the target patient according to the motion video and the preoperative motion data;

[0153] A third data calculation module, used for obtaining the grasp value of the target patient according to the motion position information;

[0154] A program determination module is used to determine the target patient's lung cancer postoperative rehabilitation program based on the tolerance value, the emotion value and the mastery value.

[0155] See also Figure 5 , Figure 5 Schematic diagram of an electronic device provided by an embodiment of the present invention. Figure 5 As shown, an embodiment of the present invention provides an electronic device 400, including a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and executable on the processor 420. When the processor 420 executes the computer program 411, the following steps are implemented:

[0156] The target patient obtains the test video and performs the exercise;

[0157] Real-time monitoring of movement position information and vital sign information during the movement;

[0158] After the exercise is completed, a motion video is generated;

[0159] Acquiring preoperative movement data of the target patient;

[0160] Obtaining the tolerance value of the target patient according to the physical sign information;

[0161] Obtaining an emotion value of the target patient according to the motion video and the preoperative motion data;

[0162] obtaining a grasp value of the target patient according to the motion position information;

[0163] A postoperative rehabilitation program for lung cancer of the target patient is determined according to the tolerance value, the emotion value and the mastery value.

[0164] See also Figure 6 , Figure 6 A schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present invention. Figure 6 As shown, this embodiment provides a computer-readable storage medium 500, on which a computer program 411 is stored. When the computer program 411 is executed by a processor, the following steps are implemented:

[0165] The target patient obtains the test video and performs the exercise;

[0166] Real-time monitoring of movement position information and vital sign information during the movement;

[0167] After the exercise is completed, a motion video is generated;

[0168] Acquiring preoperative movement data of the target patient;

[0169] Obtaining the tolerance value of the target patient according to the physical sign information;

[0170] Obtaining an emotion value of the target patient according to the motion video and the preoperative motion data;

[0171] obtaining a grasp value of the target patient according to the motion position information;

[0172] A postoperative rehabilitation program for lung cancer of the target patient is determined according to the tolerance value, the emotion value and the mastery value.

[0173] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0174] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0175] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A system that specifies the functions of a box or multiple boxes.

[0176] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction system, which is implemented in the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0177] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0178] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0179] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for postoperative rehabilitation of lung cancer, characterized in that: include: The target patient obtains the test video and performs the exercise; Real-time monitoring of movement position information and vital sign information during the movement; After the movement is completed, a movement video is generated; acquiring preoperative movement data of the target patient; Obtaining the tolerance value of the target patient according to the physical sign information; Obtaining the emotion value of the target patient according to the motion video and the preoperative motion data; including: Calculating the preoperative emotion of the target patient according to the preoperative exercise data, including: the preoperative exercise data includes preoperative exercise duration and preoperative exercise type; if the preoperative exercise duration is less than the time threshold, the preoperative emotion is 0; if the preoperative exercise duration is greater than the time threshold, determining whether the preoperative exercise type belongs to high-intensity exercise; if the preoperative exercise type belongs to high-intensity exercise, the preoperative emotion is 2; if the preoperative exercise type does not belong to high-intensity exercise, the preoperative emotion is 1; According to the motion video, the motion emotion of the target patient is calculated, including: inputting the motion video into an expression recognition model to obtain an expression emotion type; the expression emotion type includes positive, neutral, and negative; obtaining the occurrence time period of negative expressions and neutral expressions in the motion video; in the motion video, obtaining the sound information of the occurrence time period; extracting the semantic information in the sound information; inputting the semantic information into a semantic recognition model to obtain a semantic emotion type; the semantic emotion type includes positive, neutral, and negative; if the expression emotion type is negative and the semantic emotion type is negative, the motion emotion is 0; if the expression emotion type is positive and the semantic emotion type is positive, the motion emotion is 2; in other cases, the motion emotion is 1; Based on the preoperative emotion and the exercise emotion, obtaining an emotion value of the target patient; The sentiment value is calculated according to the following formula: ； in, Expressing preoperative emotions, represents sports emotion, α+β=1; obtaining a grasp value of the target patient according to the motion position information; A postoperative rehabilitation program for lung cancer of the target patient is determined according to the tolerance value, the emotion value and the mastery value.

2. The lung cancer postoperative rehabilitation method according to claim 1, characterized in that: Before the target patient obtains the test video and performs exercise, the method further includes: The doctor sends the test video to the target patient.

3. The lung cancer postoperative rehabilitation method according to claim 1, characterized in that: The step of obtaining the tolerance value of the target patient according to the physical sign information includes: The vital signs information includes heart rate and respiratory rate; Obtaining an average heart rate and an average respiratory rate of the target patient during exercise; The tolerance value of the target patient is calculated according to the average heart rate and the average respiratory rate.

4. The lung cancer postoperative rehabilitation method according to claim 3, wherein the calculation of the tolerance value of the target patient according to the average heart rate and the average respiratory rate comprises: Tolerance value = (average heart rate - baseline heart rate) / baseline heart rate + (average respiratory rate - baseline respiratory rate) / baseline respiratory rate.

5. The lung cancer postoperative rehabilitation method according to claim 1, characterized in that: The step of obtaining the grasp value of the target patient according to the motion position information includes: Determining the standard degree of the action according to the motion position information; The action standard degree is used as the mastery value of the target patient.

6. The lung cancer postoperative rehabilitation method according to claim 1, characterized in that: Determining a postoperative rehabilitation program for lung cancer of the target patient according to the tolerance value, the emotion value, and the mastery value includes: Calculating the suitability of the test video according to the tolerance value, the emotion value, and the mastery value; Based on the suitability, a postoperative rehabilitation program for lung cancer is determined for the target patient.

7. A postoperative rehabilitation system for lung cancer, characterized in that: The system comprises: A motion module is used for the target patient to obtain a test video and perform exercise; after the exercise is completed, a motion video is generated; A first data acquisition module, used for real-time monitoring of movement position information and vital sign information during the movement; A second data acquisition module, used to acquire preoperative movement data of the target patient; A first data calculation module, used for obtaining the tolerance value of the target patient according to the physical sign information; A second data calculation module, used for obtaining the emotion value of the target patient according to the motion video and the preoperative motion data; The second data calculation module is further used to: Calculating the preoperative emotion of the target patient according to the preoperative exercise data is also used for: the preoperative exercise data includes preoperative exercise duration and preoperative exercise type; if the preoperative exercise duration is less than the time threshold, the preoperative emotion is 0; if the preoperative exercise duration is greater than the time threshold, determining whether the preoperative exercise type belongs to high-intensity exercise; if the preoperative exercise type belongs to high-intensity exercise, the preoperative emotion is 2; if the preoperative exercise type does not belong to high-intensity exercise, the preoperative emotion is 1; According to the motion video, the motion emotion of the target patient is calculated, and it is also used to: input the motion video into an expression recognition model to obtain an expression emotion type; the expression emotion type includes positive, neutral, and negative; obtain the occurrence time period of negative expressions and neutral expressions in the motion video; in the motion video, obtain the sound information of the occurrence time period; extract the semantic information in the sound information; input the semantic information into a semantic recognition model to obtain a semantic emotion type; the semantic emotion type includes positive, neutral, and negative; if the expression emotion type is negative and the semantic emotion type is negative, the motion emotion is 0; if the expression emotion type is positive and the semantic emotion type is positive, the motion emotion is 2; in other cases, the motion emotion is 1; Based on the preoperative emotion and the exercise emotion, obtaining an emotion value of the target patient; The sentiment value is calculated according to the following formula: ； in, Expressing preoperative emotions, represents sports emotion, α+β=1; A third data calculation module, used for obtaining the grasp value of the target patient according to the motion position information; A program determination module is used to determine the target patient's lung cancer postoperative rehabilitation program based on the tolerance value, the emotion value and the mastery value.

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