CN114333435A - Training system and training method - Google Patents
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Abstract
The application discloses a training system and a training method, wherein the training system comprises: a processor for selecting a training task from a training task database for execution by a user; and the excitation feedback device selects individualized excitation feedback stimulation and parameters thereof from the excitation feedback stimulation tool library according to historical existing data of the user and/or real-time data of the training task executed by the user, and displays the individualized excitation feedback stimulation and the parameters to the user.
Description
Technical Field
The present application relates to a training system and a training method.
Background
In daily life, the training activities can be summarized into a training behavior regardless of learning of knowledge and training of physical activities. As another example, in recent years, with intensive research on brain science, neuropsychology, and the like, people have begun to try to train human cognitive functions by using technical intervention means.
This process is often tedious for the user, and thus often difficult to sustain, especially for users who are short of patience, as the user or subject is always challenged with cognitive functions when performing a training task for cognitive functions.
Moreover, in some cases, some cognitive function training tasks need to be performed repeatedly in a large number, or the training difficulty gradually increases with the increase of cognitive functions, which increases the boring feeling and difficulty of the user or trainer, and is not favorable for the user to insist on performing cognitive function training for a long time. However, in order to improve cognitive function well, a relatively long period of time is often required for cognitive function training.
To this end, technical ideas have been proposed in the art to add motivational feedback to training programs to urge users to adhere to training tasks that accomplish their cognitive functions. However, in practice it has been found that this motivational feedback, while in some cases it may be a good feedback incentive, in some cases it may be ineffective or even negative. The problem is not solved in the industry.
In view of the above, how to provide a training scheme for keeping a good feedback effect is a technical problem to be solved in the art.
Disclosure of Invention
The research and development team of the application finds that: the effect of the motivational feedback mechanism is closely related to various factors such as age, sex, task completion, motivational content and time. Motivational feedback content can affect the motivation of the user to train and learn. Even if the same motivational feedback is given, different effects may be expected if the user's age is different, sex is different, intelligence level, education level, etc. Therefore, the motivational feedback mechanism for the user or the trainee must be associated with various factors such as age, sex, form of task, and task completion, so as to achieve better effects.
The traditional training scheme does not always provide Good motivational effects, because the traditional motivational feedback is mostly the demonstration of "Good! "," excelent! "," very excellent! "etc., are consistent and do not take personalized consideration for the user. Thus, in actual operation, it may be effective, it may be ineffective, or it may even have adverse effects in the opposite direction.
Based on the above-mentioned research and development results and technical analysis, the present application provides a training system, which includes: a processor for selecting a training task from a training task database for execution by a user; and the excitation feedback device selects individualized excitation feedback stimulation and parameters thereof from the excitation feedback stimulation tool library according to historical existing data of the user and/or real-time data of the training task executed by the user, and displays the individualized excitation feedback stimulation and the parameters to the user.
Preferably, the personalized stimulus feedback stimulus corresponds to the training task or a training target for which it is intended; preferably, the personalized stimulus feedback stimulus has information directly corresponding to the training task or the training target for which it is directed.
Preferably, the motivational feedback stimuli include at least one of motivational feedback stimuli, flagging feedback stimuli, neutral feedback stimuli, negative feedback stimuli, criticizing feedback stimuli.
Preferably, the training system comprises: the training task interaction terminal is communicated with the processor and is used for receiving the training task from the processor and providing the training task for at least one user to interactively execute; and/or the data acquisition module is used for acquiring real-time data of the training task executed by the user and sending the real-time data to the excitation feedback device, and the training task interaction terminal and the data acquisition module are integrally arranged or are mutually independent.
Preferably, the training task is a knowledge learning training task, a motor action training task or a cognitive function training task.
Preferably, the training system comprises a database for storing historical existing data of the user, the database being in communication with the motivational feedback device and the data collection module, respectively.
Preferably, the user history existing data includes at least one of the following data:
the background data of the user, the background data comprises identity information, age, gender, native language, education condition and family condition;
physiological or clinical data of the user, the physiological or clinical data including height, weight, body fat rate, heart rate, body shape, medical history, physical examination information;
historical training data of the user performing a training task;
the brain scan or monitoring data of the user, the brain scan or monitoring data being static and/or dynamic data about the user's brain obtained in an invasive and/or non-invasive manner.
Preferably, the type of stimulus feedback stimulus comprises at least one of a visual stimulus, an auditory stimulus, an audio-visual stimulus, a tactile stimulus, a gustatory stimulus, an olfactory stimulus, a skin stimulus, a temperature stimulus, a fluid stimulus, a vibration stimulus, a blurring stimulus; and/or the parameters of the stimulus feedback stimulus comprise type, display sequence, display position, display time, display shape, display size, display color, display incidental information, display frequency, display times, display number, display intensity and display proportion; and/or the content form of the stimulus feedback stimulus comprises: at least one of text, graphics, sound, animation, virtual currency; and/or storing each stimulus feedback stimulus in the stimulus feedback stimulus tool library after classification processing.
Preferably, the data acquisition module includes: physiological monitoring means for detecting real-time physiological parameters of the user performing the training task, the physiological parameters including heart rate, blood pressure, respiratory rate, brain waves, cortisol; and/or a camera or microphone for detecting external features of the user while performing the training task, the external features including facial expressions, limb movements, sounds, eye movements of the user.
Preferably, the excitation feedback means comprises: the excitation triggering module is used for judging whether a triggering condition for sending an instruction for providing the excitation feedback stimulation is reached or not according to the real-time data of the training task executed by the user; the excitation feedback analysis module is used for selecting individualized excitation feedback stimulation and parameters thereof from the excitation feedback stimulation tool library after receiving the instruction sent by the trigger module; and the incentive feedback display module is used for receiving the information of the personalized incentive feedback stimulation and the parameters thereof selected by the incentive feedback analysis module and displaying the information to the user.
Preferably, the stimulation trigger module determines whether a trigger condition for issuing an instruction to provide the stimulation feedback stimulus is reached according to at least one of the following ways:
comparing the real-time data of the user performing the training task with historical training data thereof;
dividing the real-time data of the user executing the training task into a plurality of time periods, and comparing the real-time data of a certain later time period with the real-time data of a certain earlier time period;
comparing the real-time data of the user performing the training task to a norm;
comparing the real-time physiological parameters of the user performing the training task with their historical physiological parameters;
dividing the real-time physiological parameters of the user executing the training task into a plurality of time periods, wherein the real-time physiological parameters of a certain time period are compared with the real-time physiological parameters of a certain time period;
comparing the real-time physiological parameters of the user performing the training task to a norm;
comparing the real-time appearance of the user performing the training task to historical appearance in historical training data thereof;
comparing the external features of the user performing the training task to a norm;
the real-time external features of the user performing the training task are divided into a plurality of time periods, and the real-time external features of a certain time period are compared with the real-time external features of a certain time period.
Preferably, the basis of said determination is at least one parameter of real-time data of said user performing said training task, said parameter comprising average or local execution speed, average or local execution accuracy, average or local reaction time; and/or the determination is based on at least one parameter of real-time physiological parameters or real-time external characteristics of the user performing the training task, the parameter comprising expression, heart rate, respiratory rate, limb movement, eye movement, sound, brain waves, cortisol.
Preferably, the incentive feedback analysis module includes an incentive matching module, and the incentive matching module is configured to select a personalized incentive feedback stimulus and parameters thereof matching the user from an incentive feedback stimulus tool library according to at least one of the following factors after receiving the instruction sent by the trigger module:
real-time data of the user performing the training task;
preset parameters of the training task;
real-time physiological parameters of the user performing the training task;
historical existing data of the user; and
the user's predictable lifting space.
Preferably, the working mode of the same user by the incentive feedback device is a self-adaptive iterative working mode, and the incentive feedback device selects an updated personalized incentive feedback stimulus and parameters thereof from the incentive feedback stimulus tool library according to updated historical existing data of the user and/or updated real-time data of the training task executed by the user, and displays the selected incentive feedback stimulus and parameters to the user.
The application also provides a training method, which comprises the following steps: selecting a training task from a training task database for execution by a user; and selecting individualized stimulus feedback and parameters thereof from a stimulus feedback stimulus tool library according to historical existing data of the user and/or real-time data of the training task executed by the user, and displaying the individualized stimulus feedback and the parameters to the user.
Preferably, the personalized stimulus feedback stimulus corresponds to the training task or a training target for which it is intended; preferably, the personalized stimulus feedback stimulus has information directly corresponding to a training task or a training target for which it is directed; preferably, the motivational feedback stimuli include at least one of motivational feedback stimuli, flagging feedback stimuli, neutral feedback stimuli, negative feedback stimuli, criticizing feedback stimuli; preferably, the training task is a knowledge learning training task, a motor action training task or a cognitive function training task; preferably, the type of stimulus feedback stimulus comprises at least one of a visual stimulus, an auditory stimulus, an audio-visual stimulus, a tactile stimulus, a gustatory stimulus, an olfactory stimulus, a skin stimulus, a temperature stimulus, a fluid stimulus, a vibration stimulus, a blurring stimulus; preferably, the parameters of the excitation feedback stimulation include type, display sequence, display position, display time, display shape, display size, display color, display incidental information, display frequency, display times, display number, display intensity and display proportion; preferably, the content form of the stimulus feedback stimulus comprises: at least one of text, graphics, sound, animation, virtual currency; preferably, each stimulus feedback stimulus in the stimulus feedback stimulus tool library is stored after being classified.
Preferably, the training method comprises: and collecting real-time data of the user executing the training task, and sending the real-time data to the excitation feedback device. Preferably, real-time physiological parameters of the user performing the training task are detected, and the physiological parameters comprise heart rate, blood pressure, respiratory rate, brain waves and cortisol; preferably, external features of the user during the training task are detected, wherein the external features comprise facial expressions, body movements, sounds and eyeball movements of the user.
Preferably, the training method comprises: judging whether a trigger condition for sending an instruction for providing the excitation feedback stimulation is reached or not according to real-time data of the user for executing the training task; after receiving the instruction sent by the trigger module, selecting individualized stimulus feedback stimulation and parameters thereof from a stimulus feedback stimulation tool library; and receiving the information of the personalized incentive feedback stimulation and the parameters thereof selected by the incentive feedback analysis module, and displaying the information to the user.
Preferably, whether the trigger condition for issuing the instruction to provide the stimulus feedback stimulus is reached is determined according to at least one of the following ways:
comparing the real-time data of the user performing the training task with historical training data thereof;
dividing the real-time data of the user executing the training task into a plurality of time periods, and comparing the real-time data of a certain later time period with the real-time data of a certain earlier time period;
comparing the real-time data of the user performing the training task to a norm;
comparing the real-time physiological parameters of the user performing the training task with their historical physiological parameters;
dividing the real-time physiological parameters of the user executing the training task into a plurality of time periods, wherein the real-time physiological parameters of a certain time period are compared with the real-time physiological parameters of a certain time period;
comparing the real-time physiological parameters of the user performing the training task to a norm;
comparing the real-time appearance of the user performing the training task to historical appearance in historical training data thereof;
comparing the external features of the user performing the training task to a norm;
the real-time external features of the user performing the training task are divided into a plurality of time periods, and the real-time external features of a certain time period are compared with the real-time external features of a certain time period.
Preferably, the basis of said determination is at least one parameter of real-time data of said user performing said training task, said parameter comprising average or local execution speed, average or local execution accuracy, average or local reaction time; and/or the determination is based on at least one parameter of real-time physiological parameters or real-time external characteristics of the user performing the training task, the parameter comprising expression, heart rate, respiratory rate, limb movement, eye movement, sound, brain waves, cortisol.
Preferably, after receiving the instruction, the apparatus is configured to select a personalized stimulus feedback and parameters thereof matching the user from a library of stimulus feedback stimuli based on at least one of the following factors:
real-time data of the user performing the training task;
preset parameters of the training task;
real-time physiological parameters of the user performing the training task;
historical existing data of the user; and
the user's predictable lifting space.
Preferably, the training method is an adaptive iterative working mode for the working mode of the same user, wherein an updated personalized stimulus feedback and parameters thereof are selected from the stimulus feedback stimulus tool library according to updated historical existing data of the user and/or updated real-time data of the training task executed by the user, and are displayed to the user.
In the technical scheme of the application, according to historical existing data of the user and/or real-time data of the training task executed by the user, personalized stimulus feedback and parameters thereof are selected from a stimulus feedback stimulus tool library and displayed to the user. Therefore, in the training process, the incentive feedback mechanism can be associated with the personal condition of the user, so that a good incentive effect can be always obtained, the persistence and the enthusiasm of the user are improved, and the training task which encourages the user to have higher difficulty or longer time is obtained.
Additional features and advantages of the present application will be described in detail in the detailed description which follows.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate an embodiment of the invention and, together with the description, serve to explain the invention. In the drawings:
FIGS. 1 and 2 are schematic diagrams of a training system according to various embodiments of the present application, respectively;
fig. 3 is a schematic flow chart of a training method according to a preferred embodiment of the present application.
Detailed Description
The technical solutions of the present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments. The descriptions or explanations of the technical solutions and the technical features thereof in the present application are exemplary or explanatory, and are not intended to limit the scope of the present application. It will be appreciated by those skilled in the art that aspects of the present invention may be practiced in the same or similar manner as that described herein, and is not limited to the embodiments specifically described herein.
In the present application, the definition of the related terms is as follows.
"training" includes the process of learning unconsciously or consciously by a human or animal, including learning of knowledge, learning of movement, regulation of cognitive function, and the like. Training is usually performed in connection with training tasks, which are performed by requiring the user or the person to be trained to perform the relevant training task. In the present application, the training task may be a knowledge learning training task, a motor action training task, or a cognitive function training task.
"motivational feedback" refers to information that is fed back to a person or animal in order to urge him to perform more difficult or longer follow-up tasks, depending on the situation in which the person or animal performs the task, usually in the form of various motivational feedback stimulation signals. In the present application, the stimulus feedback stimulus includes at least one of an incentive feedback stimulus, a whiplash feedback stimulus, a neutral feedback stimulus, a negative feedback stimulus, a criticality feedback stimulus.
As shown in fig. 1, the present application proposes a training system comprising: a processor for selecting a training task from a training task database for execution by a user; and the excitation feedback device selects individualized excitation feedback stimulation and parameters thereof from the excitation feedback stimulation tool library according to historical existing data of the user and/or real-time data of the training task executed by the user, and displays the individualized excitation feedback stimulation and the parameters to the user.
Compared with the traditional training scheme which is uniform and lacks of personalized incentive modes, in the training system, the personalized incentive feedback stimulation and the parameters thereof can be selected by utilizing the incentive feedback device according to the historical existing data of the user and/or the real-time data during the execution of the training task, so that the defects of the traditional training scheme which is uniform and lacks of personalization are overcome, and the purpose of the training system is further realized.
The processor can be in various physical forms, such as a desktop computer, a notebook computer, a server, a workstation, a smart phone, a tablet computer and the like; or as an alternative, the regulating device may be a cloud server. The excitation feedback means may be arranged integrally with the processor or independently.
The user history existing data comprises at least one of the following data: the background data of the user, the background data comprises identity information, age, gender, native language, education condition and family condition; physiological or clinical data of the user, the physiological or clinical data including height, weight, body fat rate, heart rate, body shape, medical history, physical examination information; historical training data of the user performing a training task; the brain scan or monitoring data of the user, the brain scan or monitoring data being static and/or dynamic data about the user's brain obtained in an invasive and/or non-invasive manner. Preferably, the training system comprises a database for storing historical existing data of the user, the database being in communication with the motivational feedback device and the data collection module, respectively. Thus, the database can update the historical existing data and the real-time data of the user when the user is training. Real-time data of the user performing the training task may be collected by a data collection module, which will be described in detail below.
The training system can be applied to different working situations, for example, in the situation that a user learns knowledge, such as learning English words, the user or the person to be trained can be shown words needing pronunciation by using a mobile phone or an ipad, and then a proper excitation feedback stimulus is selected according to the pronunciation situation; in the field of sports training, the action required for training can be shown to the person to be trained, and then the appropriate stimulation feedback stimulation is selected according to the condition of the simulated action made by the person to be trained; in the cognitive function training field, for example, when the cognitive function object remembering the cognitive function object is subjected to N-back paradigm training, a training task is displayed to a user by a mobile phone or an ipad, and then appropriate excitation feedback stimulation is selected according to the training task execution condition of the user.
Preferably, as shown in fig. 1, the training system comprises: and the training task interaction terminal is communicated with the processor and is used for receiving the training task from the processor for interactive execution of at least one user. Training task interaction terminals are in various forms, including but not limited to smart phones, tablet computers, notebook computers, desktop computers, earphones with interactive functions, displays, glasses, augmented reality devices, virtual reality devices, and the like. In some cases, the training task interaction terminal may be omitted, such as in the case of the action training field described above. In addition, preferably, the training system includes a data acquisition module, and the data acquisition module is configured to acquire real-time data of the user performing the training task and send the real-time data to the motivation feedback device. The data acquisition terminal can be in various forms, including but not limited to a gyroscope, an accelerometer, a velocimeter, a motion sensor, a pressure sensor, an optical sensor, an audio acquisition device, a video acquisition device, an auditory sensor, a vibration sensor, a brain scanning or monitoring instrument. According to various embodiments, the data acquisition module may include: physiological monitoring means for detecting real-time physiological parameters of the user performing the training task, including heart rate, blood pressure, respiratory rate, brain waves, cortisol (level); and/or a camera or microphone for detecting external features of the user while performing the training task, the external features including facial expressions, limb movements, sounds, eye movements of the user.
The training task interaction terminal and the data acquisition module can be in integrated arrangement or mutually independent. According to different embodiments, at least two of the training task interaction terminal, the data acquisition module and the processor are in an integrated arrangement. For example, the training task interaction terminal and the data acquisition module can be integrally arranged and realized by using the data acquisition function of the training interaction terminal. For example, when a tablet computer is used as the training interactive terminal, the tablet computer can be used as a data acquisition module, and the data of the user during the cognitive function training task can be acquired by acquiring the operation information of the user on the tablet computer. For another example, the training task interaction terminal and the processor can be integrally arranged, and the function of the processor can be given to the tablet personal computer by setting a corresponding application program for the tablet personal computer. Or as another alternative implementation mode, the training task interaction terminal, the data acquisition module and the processor are respectively and independently arranged. For example, the training task interaction terminal is a smart phone, the data acquisition module is a camera for monitoring a user when the user uses the training task interaction terminal, the processor is a cloud server, and the training task interaction terminal, the data acquisition module and the processor are in communication with each other through a network.
Depending on the application scenario, a "terminal" or a "module" may be understood as various embodiments. For example, the training task interaction terminal may be a physical terminal, such as a smart phone, a computer, etc., as described above; or may also be understood as a software terminal, such as an APP installed on the smart phone or the tablet computer, or an application installed on the desktop computer; or a combination of physical and software terminals.
The stimulus feedback stimulus tool library may be in the form of a database comprising a plurality of stimulus feedback stimuli evaluated in different dimensions. Depending on the application scenario, the type of stimulus feedback stimulus may include at least one of a visual stimulus, an auditory stimulus, an audio-visual stimulus, a tactile stimulus, a gustatory stimulus, an olfactory stimulus, a skin stimulus, a temperature stimulus, a fluid stimulus, a vibration stimulus, a blur stimulus. For different stimulus feedback stimuli, the parameters of the stimulus feedback stimuli may include type, presentation sequence, presentation location (e.g., location in a display screen), presentation time, presentation shape, presentation size, presentation color, presentation collateral information, presentation frequency, number of presentations, intensity of presentations, and presentation ratio. Thus, in this preferred case, there may be a personalized selection of not only the stimulus feedback stimulus, but also individual parameters for the stimulus feedback stimulus, thereby providing a more personalized stimulus feedback to the user. The content presentation of the stimulus feedback stimulus may include: at least one of text, graphics, sound, animation, virtual currency.
Preferably, each stimulus feedback stimulus in the stimulus feedback stimulus tool library is stored after being classified, so as to provide personalized stimulus feedback stimuli for users in a targeted manner. For example, the following table shows one way of categorizing each stimulus feedback stimulus. As can be seen from the table, different content of motivational stimulus content can be selected for users of different genders, ages and training targets.
Preferably, the personalized stimulus feedback stimulus corresponds to the training task or a training target for which it is intended. That is, when a user or a person to be trained is training for the training target, the stimulus feedback stimulus provided to the user is related to the trainingThe corresponding target practice is carried out. For example, when a trainer is performing a rapid-calculation training, the motivational feedback stimulus given to the user corresponds to the rapid-calculation training task or the calculation speed targeted (training target). Therefore, the stimulation feedback stimulation can create psychological hint for the user, thereby playing a better stimulation role. As indicated in the above table, preferably the personalized stimulus feedback stimulus has information directly corresponding to the training task or the training target for which it is intended. For example, if the user's training task or training target is concentration, the stimulus feedback stimulus has information related to concentration, such as "your" for exampleSpecial attention for strengthening the spleenAlso at the lift we are more difficult a bit ". Through a psychological cued technical mode, on one hand, a better excitation effect can be obtained, and the user can be excited to carry out a training task with greater difficulty or longer time; on the other hand, the overall training effect can be significantly improved.
For example, a group of 10-14 year old adolescents are memory trained using more difficult working memory training software. Without any stimulus for motivational feedback, the user or trainee can insist on an average for 5 minutes. In the case of traditional discordant stimuli of motivational feedback (e.g. "like", "true"), there is no statistical increase in the time the user or person adheres to the training. In the case of using individualized and training-targeted stimuli, the duration of the adherence to training of the user or person to be trained is significantly increased, with an average adherence to training of up to 8 minutes and up to 12 minutes.
As shown in fig. 2 and 3, the excitation feedback device of the present application preferably includes: the excitation triggering module is used for judging whether a triggering condition for sending an instruction for providing the excitation feedback stimulation is reached or not according to the real-time data of the training task executed by the user; the excitation feedback analysis module is used for selecting individualized excitation feedback stimulation and parameters thereof from the excitation feedback stimulation tool library after receiving the instruction sent by the trigger module; and the incentive feedback display module is used for receiving the information of the personalized incentive feedback stimulation and the parameters thereof selected by the incentive feedback analysis module and displaying the information to the user.
The excitation triggering module is used for judging whether excitation feedback stimulation needs to be sent out. In order to determine whether a triggering condition for issuing an instruction to provide an excitation feedback stimulus is reached, the excitation triggering module may preferably determine according to at least one of the following ways.
1) Comparing the real-time data of the user performing the training task with historical training data thereof. If the user's real-time data is found to be better than their historical training data and reaches a predetermined threshold, a pragmatic or encouraging motivational feedback stimulus may be issued; and if the user's real-time data is found to be worse than his historical training data and reaches a predetermined threshold, a criticizing motivational feedback stimulus may be issued.
2) Dividing the real-time data of the user executing the training task into a plurality of time periods, and comparing the real-time data of a certain later time period with the real-time data of a certain earlier time period. If the real-time data for the user at a later time period is found to be better than the real-time data for a previous time period and reaches a predetermined threshold, a pragmatic or encouraging motivational feedback stimulus may be issued; and if the real-time data of the user in a later time period is found to be worse than the real-time data in a previous time period and reaches a predetermined threshold, a criticizing stimulus feedback stimulus may be issued.
3) The real-time data of the user performing the training task is compared to the norm (normal criteria for the training task, such as reaching a passing level). If the user's real-time data is found to be better than normal and reaches a predetermined threshold, a pragmatic or encouraging motivational feedback stimulus may be issued; and if the user's real-time data is found to be worse than normal and reaches a predetermined threshold, a criticizing motivational feedback stimulus may be issued.
4) Comparing the real-time physiological parameters of the user performing the training task to their historical physiological parameters. If the user's real-time physiological parameters are found to be better than their historical physiological parameters (a lower heart rate indicates a decrease in stress) and a predetermined threshold is reached, a pragmatic or encouraging motivational feedback stimulus may be issued; and if the user's real-time physiological parameters are found to be worse (e.g., more cardiac or less experienced in operation) than their historical physiological parameters and reach a predetermined threshold, criticizing motivational feedback stimuli may be issued.
5) Dividing the real-time physiological parameters of the user executing the training task into a plurality of time periods, and comparing the real-time physiological parameters of a certain later time period with the real-time physiological parameters of a certain earlier time period. If the real-time physiological data of the user in a later time period is found to be better than the real-time physiological data in a previous time period and reaches a predetermined threshold, a pragmatic or encouraging motivational feedback stimulus may be issued; and if the real-time physiological data of the user in a later time period is found to be worse than the real-time physiological data in a previous time period and reaches a predetermined threshold, a criticizing incentive feedback stimulus may be issued.
6) Comparing the real-time physiological parameters of the user performing the training task to normals. If the user's real-time physiological data is found to be better than normal (e.g., normal heart rate range) and reaches a predetermined threshold, a pragmatic or encouraging motivational feedback stimulus may be issued; and if the real-time physiological data of the user is found to be worse than normal and reaches a predetermined threshold, criticizing motivation feedback stimuli may be issued.
7) Comparing the real-time appearance of the user performing the training task to historical appearance in historical training data thereof; or comparing the external features of the user performing the training task to a norm; or dividing the real-time external features of the user executing the training task into a plurality of time periods, and comparing the real-time external features of a certain later time period with the real-time external features of a certain earlier time period.
In performing the comparative analysis described above, a variety of parameters may be considered. Preferably, the determination is based on at least one parameter of real-time data of the user performing the training task, the parameter including an average or local execution speed, an average or local execution accuracy, an average or local reaction time; and/or the determination is based on at least one parameter of real-time physiological parameters or real-time external characteristics of the user performing the training task, the parameter comprising expression, heart rate, respiratory rate, limb movement, eye movement, sound, brain waves, cortisol. Thus, the threshold may be a threshold of a selected suitable parameter.
Preferably, the incentive feedback analysis module comprises an incentive matching module (not shown) for selecting the personalized incentive feedback stimulation and parameters thereof matched with the user from an incentive feedback stimulation tool library according to at least one of the following factors after receiving the instruction sent by the trigger module:
1) real-time data of the user performing the training task;
2) the preset parameters of the training task, such as the preset time length, the repetition times and the like of the training task;
3) real-time physiological parameters of the user performing the training task, such as heart rate, blood pressure, etc.;
4) historical existing data of the user, such as the last training time period is parameters of the morning or afternoon, accuracy rate and the like;
5) a predictable lifting space for the user, the intensity of the stimulus provided may be increased if the user is predicted to have a relatively large lifting space; the intensity of the stimulation stimulus may be maintained or reduced if the user is predicted to have a relatively small lifting volume.
The matching module can be selected according to different indexing information of the stimulation feedback stimulation, and can also be selected from a tool library of the stimulation feedback stimulation by utilizing a one-to-one rule; or the selection of the personalized incentive stimulus information can also be realized based on a machine learning mode.
In the technical solution of the present application, preferably, as shown in fig. 2 and 3, the operation mode of the incentive feedback device for the same user is an adaptive iterative operation mode, wherein the incentive feedback device selects an updated personalized incentive feedback stimulus and parameters thereof from the incentive feedback stimulus tool library according to updated historical existing data of the user and/or updated real-time data of the user executing the training task, and displays the selected incentive feedback stimulus and parameters to the user. During the training process, or after multiple training sessions, the training level of the user is generally increased. Through an iterative working mode, the individual stimulation feedback stimulation is selected for the user according to the self condition of the user in a self-adaptive mode.
As shown in fig. 3, the present application further provides a training method, including: selecting a training task from a training task database for execution by a user; and selecting individualized stimulus feedback and parameters thereof from a stimulus feedback stimulus tool library according to historical existing data of the user and/or real-time data of the training task executed by the user, and displaying the individualized stimulus feedback and the parameters to the user. Although the training method is not described in detail individually above, it is natural that the training method is also explained fully indirectly by the above detailed description of the training system. The technical solution of the present application is exemplarily presented below in connection with three training schemes.
According to one embodiment, the user or person to be trained repeatedly performs focused training and continuously completes a series of repetitive training sessions. In this case, the corresponding stimulus feedback stimulus may be extracted from the stimulus feedback stimulus tool library or database according to the training real-time data and the existing data of the user, for example, the text contents are: "you keep concentrating on the ability to strengthen, the achievement will be better. "the stimulus feedback stimulation information is displayed on the screen in the cognitive training process in the form of characters.
According to another embodiment, the user or trainee repeats the challenging memory training, but the training performance is worse than what was achieved with the easier training in the past. In this case, according to the training real-time data and the existing data of the user, the corresponding stimulus feedback stimulus is extracted from the stimulus feedback stimulus tool library or database, for example, the text contents are: "harder training works better for memory improvement". The stimulus feedback stimulus is presented on a screen for cognitive training by text during the training process.
According to yet another embodiment, the user or person to be trained repeats the mathematical computational capability training. The real-time data collected by the training system shows that the training performance of the person to be trained is the same as the historical data. Meanwhile, the data acquisition module collects the eye movement data of the person to be trained and displays that the person to be trained is not concentrated on the training task. In this case, the corresponding stimulus feedback stimulus can be extracted from the stimulus feedback stimulus tool library or database according to the training real-time data and the existing data of the user, and the text content is: "your arithmetic ability is improving and more challenging training can be done". The text is played through a microphone during the training process.
The technical solutions provided in the present application are described in detail above. The descriptions or explanations of the technical solutions and the technical features thereof in the present application are exemplary or explanatory, and are not intended to limit the scope of the present application. It will be appreciated by those skilled in the art that aspects of the present invention may be practiced in the same or similar manner as that described herein, and is not limited to the embodiments specifically described herein.
The preferred embodiments of the present application have been described in detail above, but the present application is not limited to the specific details of the above embodiments, and various simple modifications can be made to the technical solution of the present application within the technical idea of the present application, and these simple modifications all belong to the protection scope of the present application.
It should be noted that, in the foregoing embodiments, various features described in the above embodiments may be combined in any suitable manner, and in order to avoid unnecessary repetition, various possible combinations are not described in the present application.
In addition, any combination of the various embodiments of the present application can be made, and the same should be considered as the disclosure of the present invention as long as the combination does not depart from the spirit of the present application.
Claims (22)
1. A training system, the training system comprising:
a processor for selecting a training task from a training task database for execution by a user;
and the excitation feedback device selects individualized excitation feedback stimulation and parameters thereof from the excitation feedback stimulation tool library according to historical existing data of the user and/or real-time data of the training task executed by the user, and displays the individualized excitation feedback stimulation and the parameters to the user.
2. The training system of claim 1, wherein the personalized motivational feedback stimulus corresponds to the training task or a training target for which it is directed;
preferably, the personalized stimulus feedback stimulus has information directly corresponding to the training task or the training target for which it is directed.
3. The training system of claim 1, wherein the motivational feedback stimuli comprises at least one of motivational feedback stimuli, flagging feedback stimuli, neutral feedback stimuli, negative feedback stimuli, criticizing feedback stimuli.
4. Training system according to claim 1, wherein the training system comprises:
the training task interaction terminal is communicated with the processor and is used for receiving the training task from the processor and providing the training task for at least one user to interactively execute; and/or
A data acquisition module for acquiring real-time data of the user performing the training task and sending the real-time data to the motivation feedback device,
the training task interaction terminal and the data acquisition module are in integrated arrangement or are mutually independent.
5. The training system of claim 1, wherein the training task is a knowledge learning training task, a motor action training task, or a cognitive function training task.
6. The training system of claim 2, wherein the training system comprises a database for storing historical data of the user, the database being in communication with the motivational feedback device and the data collection module, respectively.
7. The training system of claim 1, wherein the user historical prior data comprises at least one of:
the background data of the user, the background data comprises identity information, age, gender, native language, education condition and family condition;
physiological or clinical data of the user, the physiological or clinical data including height, weight, body fat rate, heart rate, body shape, medical history, physical examination information;
historical training data of the user performing a training task;
the brain scan or monitoring data of the user, the brain scan or monitoring data being static and/or dynamic data about the user's brain obtained in an invasive and/or non-invasive manner.
8. The training system of claim 1,
the type of the stimulus feedback stimulus comprises at least one of a visual stimulus, an auditory stimulus, an audio-visual stimulus, a tactile stimulus, a gustatory stimulus, an olfactory stimulus, a skin stimulus, a temperature stimulus, a fluid stimulus, a vibration stimulus, a blur stimulus; and/or
The parameters of the excitation feedback stimulation comprise type, display sequence, display position, display time, display shape, display size, display color, display incidental information, display frequency, display times, display number, display intensity and display proportion; and/or
The content form of the incentive feedback stimulation comprises: at least one of text, graphics, sound, animation, virtual currency; and/or
And each excitation feedback stimulus in the excitation feedback stimulus tool library is stored after being classified.
9. The training system of claim 2, wherein the data acquisition module comprises:
physiological monitoring means for detecting real-time physiological parameters of the user performing the training task, the physiological parameters including heart rate, blood pressure, respiratory rate, brain waves, cortisol; and/or
A camera or microphone for detecting external features of the user while performing the training task, the external features including facial expressions, limb movements, sounds, eye movements of the user.
10. Training system according to any of the claims 1-9, wherein the stimulus feedback means comprise:
the excitation triggering module is used for judging whether a triggering condition for sending an instruction for providing the excitation feedback stimulation is reached or not according to the real-time data of the training task executed by the user;
the excitation feedback analysis module is used for selecting individualized excitation feedback stimulation and parameters thereof from the excitation feedback stimulation tool library after receiving the instruction sent by the trigger module;
and the incentive feedback display module is used for receiving the information of the personalized incentive feedback stimulation and the parameters thereof selected by the incentive feedback analysis module and displaying the information to the user.
11. The training system of claim 10, wherein the motivational trigger module determines whether a trigger condition for issuing instructions to provide motivational feedback stimulation has been reached based on at least one of:
comparing the real-time data of the user performing the training task with historical training data thereof;
dividing the real-time data of the user executing the training task into a plurality of time periods, and comparing the real-time data of a certain later time period with the real-time data of a certain earlier time period;
comparing the real-time data of the user performing the training task to a norm;
comparing the real-time physiological parameters of the user performing the training task with their historical physiological parameters;
dividing the real-time physiological parameters of the user executing the training task into a plurality of time periods, wherein the real-time physiological parameters of a certain time period are compared with the real-time physiological parameters of a certain time period;
comparing the real-time physiological parameters of the user performing the training task to a norm;
comparing the real-time appearance of the user performing the training task to historical appearance in historical training data thereof;
comparing the external features of the user performing the training task to a norm;
the real-time external features of the user performing the training task are divided into a plurality of time periods, and the real-time external features of a certain time period are compared with the real-time external features of a certain time period.
12. The training system of claim 11,
the basis of the judgment is at least one parameter of real-time data of the training task executed by the user, and the parameter comprises average or local execution speed, average or local execution accuracy rate and average or local reaction time; and/or
The basis of the determination is at least one parameter of real-time physiological parameters or real-time external characteristics of the user performing the training task, the parameter including expression, heart rate, respiratory rate, limb movement, eyeball movement, sound, brain waves, and cortisol.
13. The training system of claim 10, wherein the motivational feedback analysis module comprises a motivational matching module configured to select a personalized motivational feedback stimulus and parameters thereof from a motivational feedback stimulus tool library that match the user based on at least one of the following factors, upon receipt of an instruction from the trigger module:
real-time data of the user performing the training task;
preset parameters of the training task;
real-time physiological parameters of the user performing the training task;
historical existing data of the user; and
the user's predictable lifting space.
14. Training system according to claim 1, wherein the mode of operation of the motivational feedback means for the same user is an adaptive iterative mode of operation,
and the incentive feedback device selects updated personalized incentive feedback stimulation and parameters thereof from the incentive feedback stimulation tool library according to the updated historical existing data of the user and/or the updated real-time data of the training task executed by the user, and displays the updated personalized incentive feedback stimulation and parameters thereof to the user.
15. A training method, the training method comprising:
selecting a training task from a training task database for execution by a user;
and selecting individualized stimulus feedback and parameters thereof from a stimulus feedback stimulus tool library according to historical existing data of the user and/or real-time data of the training task executed by the user, and displaying the individualized stimulus feedback and the parameters to the user.
16. The training method of claim 15,
the personalized stimulus feedback stimulus corresponds to the training task or a training target for which it is intended;
preferably, the personalized stimulus feedback stimulus has information directly corresponding to a training task or a training target for which it is directed;
preferably, the motivational feedback stimuli include at least one of motivational feedback stimuli, flagging feedback stimuli, neutral feedback stimuli, negative feedback stimuli, criticizing feedback stimuli;
preferably, the training task is a knowledge learning training task, a motor action training task or a cognitive function training task;
preferably, the type of stimulus feedback stimulus comprises at least one of a visual stimulus, an auditory stimulus, an audio-visual stimulus, a tactile stimulus, a gustatory stimulus, an olfactory stimulus, a skin stimulus, a temperature stimulus, a fluid stimulus, a vibration stimulus, a blurring stimulus;
preferably, the parameters of the excitation feedback stimulation include type, display sequence, display position, display time, display shape, display size, display color, display incidental information, display frequency, display times, display number, display intensity and display proportion;
preferably, the content form of the stimulus feedback stimulus comprises: at least one of text, graphics, sound, animation, virtual currency;
preferably, each stimulus feedback stimulus in the stimulus feedback stimulus tool library is stored after being classified.
17. The training method of claim 15, wherein the training method comprises: collecting real-time data of the user performing the training task and sending the real-time data to the motivation feedback device, wherein:
preferably, real-time physiological parameters of the user performing the training task are detected, and the physiological parameters comprise heart rate, blood pressure, respiratory rate, brain waves and cortisol;
preferably, external features of the user during the training task are detected, wherein the external features comprise facial expressions, body movements, sounds and eyeball movements of the user.
18. Training method according to any of the claims 15-17, wherein the training method comprises:
judging whether a trigger condition for sending an instruction for providing the excitation feedback stimulation is reached or not according to real-time data of the user for executing the training task;
after receiving the instruction sent by the trigger module, selecting individualized stimulus feedback stimulation and parameters thereof from a stimulus feedback stimulation tool library;
and receiving the information of the personalized incentive feedback stimulation and the parameters thereof selected by the incentive feedback analysis module, and displaying the information to the user.
19. The training method of claim 18, wherein determining whether a triggering condition for issuing an instruction to provide an incentive feedback stimulus is reached is based on at least one of:
comparing the real-time data of the user performing the training task with historical training data thereof;
dividing the real-time data of the user executing the training task into a plurality of time periods, and comparing the real-time data of a certain later time period with the real-time data of a certain earlier time period;
comparing the real-time data of the user performing the training task to a norm;
comparing the real-time physiological parameters of the user performing the training task with their historical physiological parameters;
dividing the real-time physiological parameters of the user executing the training task into a plurality of time periods, wherein the real-time physiological parameters of a certain time period are compared with the real-time physiological parameters of a certain time period;
comparing the real-time physiological parameters of the user performing the training task to a norm;
comparing the real-time appearance of the user performing the training task to historical appearance in historical training data thereof;
comparing the external features of the user performing the training task to a norm;
the real-time external features of the user performing the training task are divided into a plurality of time periods, and the real-time external features of a certain time period are compared with the real-time external features of a certain time period.
20. The training method of claim 19,
the basis of the judgment is at least one parameter of real-time data of the training task executed by the user, and the parameter comprises average or local execution speed, average or local execution accuracy rate and average or local reaction time; and/or
The basis of the determination is at least one parameter of real-time physiological parameters or real-time external characteristics of the user performing the training task, the parameter including expression, heart rate, respiratory rate, limb movement, eyeball movement, sound, brain waves, and cortisol.
21. Training method according to claim 18, wherein, upon receipt of said instruction, the user is adapted to select a personalized stimulus for feedback and its parameters matching said user from a library of stimulus feedback stimuli depending on at least one of the following factors:
real-time data of the user performing the training task;
preset parameters of the training task;
real-time physiological parameters of the user performing the training task;
historical existing data of the user; and
the user's predictable lifting space.
22. Training method according to claim 15, wherein the training method is an adaptive iterative working method for the working method of the same user,
and selecting updated personalized stimulus feedback and parameters thereof from the stimulus feedback stimulus tool library according to the updated historical existing data of the user and/or the updated real-time data of the training task executed by the user, and displaying the selected personalized stimulus feedback and parameters to the user.
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