CN114758486A

CN114758486A - Behavior habit training method, device, equipment and storage medium

Info

Publication number: CN114758486A
Application number: CN202210664413.4A
Authority: CN
Inventors: 孙克龙; 杜军红; 葛振纲; 路广
Original assignee: Shanghai Haocheng Information Technology Co ltd
Current assignee: Shanghai Haocheng Information Technology Co ltd
Priority date: 2022-06-14
Filing date: 2022-06-14
Publication date: 2022-07-15

Abstract

The application provides a behavior habit training method, a behavior habit training device, behavior habit training equipment and a behavior habit storage medium, wherein a wearable device receives a target task and a reminding task which are sent by a central device, the reminding task is used for reminding and guiding a wearer of the wearable device to finish the target task at preset time, and the target task corresponds to a target behavior preset by a user; in a detection period before the preset time, the wearable device detects the behavior state of at least one corresponding wearer in real time, and judges whether to execute a pre-guiding task according to the behavior state, wherein the pre-guiding task is used for guiding the wearer to change the behavior state so that the difficulty of the wearer responding to a reminding task and executing a target task meets the preset requirement; if yes, the wearable device executes a pre-guiding task and executes a reminding task after reaching the preset time. The training of good and accurate behavior habits of the target training object through the cooperation of the central equipment and the wearable equipment is realized.

Description

Behavior habit training method, device, equipment and storage medium

Technical Field

The present application relates to the field of intelligent electronic products, and in particular, to a method, an apparatus, a device, and a storage medium for training a behavior habit.

Background

With the development of science and technology and the improvement of the living standard of people, various intelligent electronic products have been integrated into the work and daily life of people.

At present, many intelligent functions of intelligent electronic products mainly depend on collection, statistics and analysis of behavior habits of users. However, there are many needs in real life to establish good behavior habits with certain meanings for some training subjects, such as insisting on exercise, early sleep, no lingering, and so on, and besides human behavior training, there is also a need for behavior habit training for animals, such as pets, functional animals (e.g., guide dogs, dog killers), and livestock, poultry, etc., which are raised for obtaining meat.

Therefore, how to use intelligent electronic products to assist the training of behavior habits of target training subjects becomes a technical problem which needs to be solved urgently.

Disclosure of Invention

The application provides a behavior habit training method, a behavior habit training device and a storage medium, and aims to solve the technical problem of how to assist in training the behavior habit of a target training object by using an intelligent electronic product.

In a first aspect, the present application provides a method for training behavioral habits, comprising:

the wearable device receives a target task and a reminding task sent by the central device, wherein the reminding task is used for reminding and guiding a wearer of the wearable device to finish the target task at preset time, and the target task corresponds to a target behavior preset by a user;

in a detection period before preset time, the wearable device detects the behavior state of at least one corresponding wearer in real time, and the behavior state is used for representing the physiological state and behavior action information of the wearer;

the wearable device judges whether to execute a pre-guiding task according to the behavior state, wherein the pre-guiding task is used for guiding the wearer to change the behavior state so that the difficulty of the wearer responding to the reminding task and executing the target task meets the preset requirement;

if yes, the wearable device and/or the central device executes a pre-guiding task, and executes a reminding task after the preset time is reached; if not, the wearable device executes a reminding task after reaching the preset time.

In one possible design, the wearable device and/or the central device performs pre-boot tasks, including:

the wearable device and/or the central device determines an output mode of the guiding information according to the physiological state and the behavior action information;

The wearable device and/or the central device outputs the guiding information in a preset mode;

the preset mode comprises one or more of the following modes: the method includes continuously or intermittently outputting the guidance information of uniform intensity, continuously or intermittently increasing or decreasing the intensity of the guidance information, and continuously or intermittently changing the kind or kind combination of the guidance information.

Optionally, the types of the guidance information include: sound or alarm, light, flashing, vibration, acupuncture, heat, shock, pressure, itch, blowing.

In one possible design, the difficulty level includes a response difficulty level of the wearer responding to the reminding task, and the wearable device judges whether to execute the pre-guiding task according to the behavior state, including:

the wearable device judges the response difficulty of the wearer in responding to the reminding task according to the behavior state;

and the wearable equipment judges whether to execute a pre-guiding task according to the response difficulty, so that the response difficulty reaches a preset requirement.

Optionally, the difficulty level further includes a difficulty level of performing the target task, and after the wearable device detects the behavior state of at least one wearer corresponding to the wearable device, the method further includes:

the wearable device or the central device determines the ending condition of the reminding task according to the execution difficulty, and monitors whether the behavior state meets the ending condition in real time through the wearable device;

If yes, the wearable device or the central device finishes the reminding task;

if not, the wearable device or the central device outputs corresponding prompt information and continues to execute the reminding task so as to guide the wearer to continue to complete the target task.

In one possible design, the method further includes:

before the preset time is reached, if the central equipment and any one or any plurality of the wearable equipment receive the early ending instruction, the central equipment and the wearable equipment receive the early ending instruction

Each wearable device detects the behavior state of a corresponding wearer and judges whether the behavior state meets a condition of ending in advance, and an instruction of ending in advance is used for closing a reminding task;

if not, the central equipment or the wearable equipment outputs prompt information to guide the wearer to change the behavior state, so that the behavior state meets the early ending condition.

In one possible design, outputting the cue information to guide the wearer to change the behavioral state includes:

the visual information is displayed on the display screen, the wearer is guided to complete the operation task corresponding to the visual information, and meanwhile various operations of the wearer when the operation task is completed are received, so that whether the wearer completes the operation task or not is judged according to the operations.

In one possible design, the operational task includes a combination of one or more of the following: indicating the location of a particular word or symbol in a piece of textual information, reading the textual information, drawing a specified shape on a display screen, and performing a specified action or actions.

In one possible design, the central device executes the task synchronization instruction, and further includes:

and closing the central equipment and other reminding tasks irrelevant to the target behaviors in each wearable equipment so as to ensure the compulsory and unique reminding tasks.

In one possible design, the wearable device is worn in at least one of the following ways: the method includes the steps of wearing the same or one or more wearable devices on each wearer that are complementary to each other, wearing the same wearable device on at least two wearers, and wearing complementary wearable devices on multiple wearers.

In one possible design, before the wearable device receives the target task and the reminding task sent by the central device, the method further includes:

the method comprises the steps that central equipment receives target behaviors set by a user, and determines task synchronization instructions through a preset behavior habit training model, wherein the task synchronization instructions comprise at least one target task and at least one reminding task;

The central device executes the task synchronization instruction to send each target task and each reminding task to at least one wearable device.

In a second aspect, the present application provides a behavior habit training device, comprising:

the acquisition module is used for receiving a target behavior set by a user;

the first processing module is used for determining a task synchronization instruction through a preset behavior habit training model, wherein the task synchronization instruction comprises at least one target task and at least one reminding task, the reminding task is used for reminding and guiding at least one target training object to complete the target task at preset time, and the target task corresponds to a target behavior;

the first processing module is also used for executing the task synchronization instruction so as to send each target task and each reminding task to the second processing module, and the second processing module is worn on the target training object;

the second processing module is used for detecting the behavior state of at least one corresponding target training object in real time within a detection time period, wherein the detection time period is before preset time;

a second processing module further configured to:

judging whether to execute a pre-boot task according to the behavior state, wherein the pre-boot task is used for guiding the target training object to change the behavior state so that the difficulty of the target training object responding to the reminding task and executing the target task meets the preset requirement;

If yes, the first processing module and/or the second processing module executes a pre-boot task, and executes a reminding task after a preset time is reached; and if not, the first processing module and/or the second processing module execute the reminding task after the preset time is reached.

In a third aspect, the present application provides an electronic device, comprising:

a memory for storing program instructions;

and the processor is used for calling and executing the program instructions in the memory, and executing each step corresponding to the central device or the wearable device in any one possible behavior habit training method provided by the first aspect.

In a fourth aspect, the present application provides a storage medium, in which a computer program is stored, wherein the computer program is configured to execute any one of the possible behavior habit training methods provided in the first aspect.

In a fifth aspect, the present application further provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the computer program implements any one of the possible behavior habit training system methods provided by the first aspect.

The application provides a behavior habit training method, a behavior habit training device, behavior habit training media and a behavior habit training program product, wherein a wearable device receives a target task and a reminding task which are sent by a central device, the reminding task is used for reminding and guiding a wearer of the wearable device to finish the target task at a preset time, and the target task corresponds to a target behavior preset by a user; in a detection period before the preset time, the wearable device detects the behavior state of at least one corresponding wearer in real time, and judges whether to execute a pre-guiding task according to the behavior state, wherein the pre-guiding task is used for guiding the wearer to change the behavior state so that the difficulty of the wearer responding to a reminding task and executing a target task meets the preset requirement; if yes, the wearable device executes a pre-boot task and executes a reminding task after reaching the preset time. The training of good and accurate behavior habits of the target training object through the cooperation of the central equipment and the wearable equipment is realized.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and, together with the description, serve to explain the principles of the application.

Fig. 1 is a schematic view of an application scenario of a behavior habit training method provided in the present application;

fig. 2 is a schematic flowchart of a method for training a behavior habit according to an embodiment of the present disclosure;

FIG. 3 is a schematic flow chart of another behavior habit training method provided in the present application;

fig. 4 is a schematic structural diagram of a behavior habit training device according to an embodiment of the present application;

fig. 5 is a schematic structural diagram of an electronic device provided in the present application.

With the above figures, there are shown specific embodiments of the present application, which will be described in more detail below. These drawings and written description are not intended to limit the scope of the inventive concepts in any manner, but rather to illustrate the inventive concepts to those skilled in the art by reference to specific embodiments.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. All other embodiments, including but not limited to combinations of embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any inventive step are within the scope of the present application.

The terms "first," "second," "third," "fourth," and the like in the description and claims of this application and in the above-described drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged under appropriate circumstances such that the embodiments of the application described herein may be implemented, for example, in sequences other than those illustrated or described herein. Moreover, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

The inventor finds that the realization of multiple functions of artificial intelligence depends on the collection, big data statistics and analysis of behavior habits of users, so that a corresponding intelligent control strategy is formulated for electronic products. However, many times, a certain behavior habit does not have a good influence on the user, for example, the user often stays up night, cannot get up to work in the morning, or influences the working state of a new day due to entertainment in the night. At this time, if the intelligent electronic product still works according to the bad habit, the user may be guided by mistake, so that the degree of the bad habit is increased, and even the physical and mental health and the normal life of the user are affected. However, the development or training of good behavior habits, such as insisting on exercise, early sleep, early waking, no delay, etc., can only be changed by the conscious of people, or specialized training can be performed by engaging professionals, such as a fitness coach, participating in training on related topics, setting a reminding alarm clock on a mobile phone, etc., but the expense of engaging the professionals is high, which is not bearable by people, and the effect of setting the reminding alarm clock on people with weak self-control is not obvious.

In addition, the inventor of the present application also finds that, in addition to the training requirement of human beings having behavior habits, there are training requirements of behavior habits for many animals, such as pets at home need to train excretion behaviors, and further, for example, the targeted training of some special-purpose animals, such as guide dogs, enforcement dogs, police dogs, shepherdspeams and sled dogs, and the exercise training of livestock and poultry raised for obtaining high-quality meat, so as to improve the fat-thin ratio or meat quality, and there is no special equipment for animal training.

The above requirements give rise to the thinking of the inventor of the present application about the design of a training method of behavior habits, and the inventive concept of the present application is as follows:

the method comprises the steps that one or more wearable devices are equipped for each target training object, target behaviors are set through a central device, a corresponding series of target tasks are set for each target behavior to train the target behaviors, each target task can be reminded and/or guided through the wearable devices to be executed, and certain compulsory is provided, so that a user is guided to complete a series of target tasks, good behavior habits are formed finally, the target training objects master preset training targets, or the meat quality of livestock or poultry meets preset quality requirements.

The wearable device starts to detect physiological information and behavior information of the target training object within a period of time before the target task is executed, and judges whether the wearable device needs to intervene in advance for intervention guidance, so that the target training object can reduce rejection feeling of the target task to be executed or reduce difficulty of the target training object in responding to reminding or executing the target task. And whether the target training object enters the target task in advance or not is intelligently judged, so that the phenomenon that the target training object closes the corresponding reminding in advance without executing the target task or intentionally or unintentionally forgets to execute the target task after independently closing the corresponding reminding is prevented.

The inventive concept can be applied to training of single individuals and team participating in training of multiple individuals, and at least comprises the following steps: military training of students, training of new soldiers, daily training of firefighters, training of behaviors of special workers, training of personal living habits, training alone or in groups for police dogs, training alone or in groups for shepherd dogs, training alone or in groups for domestic pets, training alone or in groups for livestock or poultry, and the like.

Fig. 1 is a schematic view of an application scenario of a behavior habit training method provided in the present application. As shown in fig. 1, the target training subject 101 wears at least one wearable device 102, and the user may set a training task of the target behavior on the wearable device 102 or the central device 103, so that the target training subject 101 forms a behavior habit meeting the preset requirement after being trained.

Fig. 2 is a flowchart illustrating a method for training a behavior habit according to an embodiment of the present disclosure. As shown in fig. 2, the method for training the behavioral habits is applied to a behavioral habits training system, the behavioral habits training system comprises a central device and one or more wearable devices, and the method comprises the following specific steps:

s201, the wearable device receives the target task and the reminding task sent by the central device.

In this step, the reminding task is used for reminding and guiding a wearer of the wearable device to complete a target task at a preset time, and the target task corresponds to a target behavior preset by a user.

Specifically, the method comprises the following steps:

(1) the central equipment receives a target behavior set by a user, and determines a task synchronization instruction through a preset behavior habit training model.

In this step, the task synchronization instruction includes at least one target task and at least one reminder task.

Specifically, the user may be the target exercise subject itself or one of the plurality of target exercise subjects, or another person other than the target exercise subject, such as a trainer or other professional. The center device includes: desktop computers, notebook computers, tablet computers, cell phones, local servers, cloud servers, and the like.

It is noted that the target training object comprises a wearer of the wearable device.

In one possible design, when the central device is: when any one of a desktop computer, a notebook computer, a tablet computer and a mobile phone is used, a user directly sets various basic information of a target behavior on an operation interface of the central device through a special application program, and the basic information comprises the following steps: setting the times of the target behaviors, setting execution judgment conditions (such as exercise amount conditions, physiological index conditions, positions or action conditions and the like) of the target behaviors, and setting reminding information corresponding to a reminding mode of the target behaviors or guiding information corresponding to a guiding mode.

Further, the target behavior includes: the single-time behavior and the multiple-time behavior can be set as periodic behavior or aperiodic behavior, the corresponding period can be set for the periodic behavior, and the interval time or trigger condition of each behavior can be set for the aperiodic behavior.

Generally, the development of a behavior habit requires the construction of multiple behaviors for training, and a single behavior can be used for testing, behavior habit effect enhancement, detection and the like.

In another possible design, when the central device is any one of the local server or the cloud server, the user directly sets each item of basic information of the target behavior on an operation interface of the mobile user side through the mobile user side such as a mobile phone, and then uploads each item of basic information of the target behavior to the central device through the wireless network.

It should be noted that, when training the target training object, the central device and the target training object may be located in the same spatial environment (for example, the central device is a mobile phone), or the central device may remotely monitor the target training object through a monitoring device in the spatial environment.

(2) The central device executes the task synchronization instruction to send each target task and each reminding task to at least one wearable device.

In the step, the central device sends the task synchronization instruction to each wearable device in a wireless transmission mode or a wireless network (such as the internet of things and 5G/4G/3G/2G) to issue and arrange the target task and the reminding task.

The wearing mode of the wearable device by the wearer comprises at least one of the following modes: the method includes the steps of wearing the same or one or more wearable devices on each wearer that are complementary to each other, wearing the same wearable device on at least two wearers, and wearing complementary wearable devices on multiple wearers.

The wearing modes correspond to different training modes of different target behaviors respectively, or different target tasks can correspond to different wearing modes.

Specifically, a. wear one or more identical or mutually supporting wearable devices on each wearer, including: a wearable equipment is worn on one wearer, a plurality of same wearable equipments are worn on one wearer, and a plurality of wearable equipments that match each other are worn on one wearer.

For example, in a single individual training, there is only one target training object on which a wearable device may be worn, such as a smart watch or smart bracelet worn on either hand of the user. The target training object can be worn by a plurality of same wearable devices, for example, a smart watch and a smart bracelet are worn on two hands of a user respectively, further, the user can also wear a smart helmet, and the smart watch, the smart bracelet and the smart helmet are mutually matched, and can be matched functionally or matched structurally, so that the functional matching means that two or more wearable devices are matched to complete one function, for example, the smart watch on the left hand and the smart bracelet on the right hand vibrate alternately to guide the user to make corresponding actions or change a plurality of action combinations, for example, the guiding effect of physical exercise is achieved.

For a target training object that is an animal, the wearable device may comprise: one or more of a collar, a bracelet/foot ring, a saddle-worn device, and the like.

Similarly, in team training, each wearer may also wear the wearable device in the manner described above and assign the same or different target tasks to each wearer depending on the target behavior.

B. Wearing the same wearable device on at least two wearers:

refers to the use of the same wearable device to restrain two wearers, such as: when police dog training, horse training, sled dog training, in order to let a plurality of target training objects accomplish the target action in coordination, like many horses draw same carriage in acrobatic ball, just can get up many horses with a wearable equipment. At present, the intelligent rope pulling device can also be used for training people, two or more people needing to cooperatively execute a certain target behavior, for example, the training target behavior is tug-of-war, and a plurality of people in the tug-of-war can be sleeved together through a plurality of branch ends of an intelligent rope, so that the cooperation of a plurality of people in the tug-of-war can be trained.

C. Wearing the wearable equipment of mutually supporting on a plurality of wearers:

The wearable equipment is characterized in that a plurality of wearable equipment form an equipment group with a preset integral function, and the structure and the function of each wearable equipment are mutually matched. For example, when military training, in order to make all the trainees when just walking, the shank height, the contained angle of two legs, the position of two legs possess uniformity and uniformity, all dresses wearable equipment on two legs of every trainee object, through mechanical structure or electromagnetic form, interconnect or restraint between the wearable equipment of the trainee object of adjacent arrangement to the uniformity when guaranteeing just walking.

S202, in the detection period, the wearable device detects the behavior state of at least one corresponding wearer in real time.

In this step, the behavior state is used to characterize the physiological state of the wearer and the behavior action information, and the detection period is before the preset time.

Specifically, the wearable device detects physiological indexes of the target training object such as heartbeat, body temperature, respiratory rate and blood pressure in real time to acquire the physiological state of the target training object. Meanwhile, the acceleration sensor and the positioning device on the wearable device detect the action and the change condition of the position of the target training object in real time so as to determine the action information of the target training object.

For example, during military training, the wearable device detects the physiological status and behavior and action information of each trained object in real time, and can monitor the behavior and status of each trained object before the army posture, left/right/forward/backward rotation, step walking, forward walking and the transition of the training action are carried out, so as to find out whether the trained object is uncomfortable or has wrong action or is predicted to have wrong tendency.

For another example, in a horsemanship training, a horse and a rider wear wearable devices which are matched with each other, for example, a saddle on the horse, boots on the rider, an intelligent cushion on the hip of trousers, and a vest can form the wearable devices which are sleeved with each other, and whether the horse and the rider are in a good physiological state before training, whether the walking posture of the horse is normal, whether the warm-up action of the rider shows stiffness of the action, and the like are detected.

For another example, for the training of the behavior habit of regularly and regularly excreting pets, the excretion time is set once in the morning and once in the evening, and before the excretion time is reached, the physiological state of the pet and the behavior action of the pet are detected, so that the tendency and possibility that the pet excretes outside the excretion time and the excretion place are detected.

And S203, the wearable device judges whether to execute a pre-boot task according to the behavior state.

In this step, the pre-boot task is used to guide the wearer to change the behavior state, so that the difficulty of the wearer responding to the reminding task and executing the target task meets the preset requirement. If so, step S204 is executed, otherwise, step S205 is executed.

Specifically, the wearable device judges the response difficulty of the wearer in responding to the reminding task and the execution difficulty of the target task according to the behavior state;

the wearable device judges whether to execute a pre-guiding task according to the response difficulty, wherein the pre-guiding task is used for guiding the wearer to change the behavior state so as to enable the response difficulty to reach a preset requirement;

if yes, the wearable device executes a pre-boot task and executes a reminding task after a preset time is reached; if not, the wearable device executes a reminding task after reaching the preset time.

It should be noted that, in this embodiment, the difficulty determining manner includes: judging whether various physiological indexes of the physiological state in the behavior state fall into respective preset index ranges; if so, determining the value of the prediction operator corresponding to the physiological index as a first value, if the value is 1; if not, determining the value of the prediction operator as a second value, if the value is 2; then, the products of each predictor and the preset weight of the corresponding physiological index are obtained, and the products are summed to obtain the value of the physiological measurement and calculation factor corresponding to the physiological state; similarly, for the behavior measurement factor corresponding to the behavior action information, any two items of the current position, the motion amount, the calorie consumption and the current posture of the target training object can be compared with the corresponding preset threshold range, if the two items are within the preset threshold range, the value of the corresponding predictor is determined as a third value, such as any value in 0-3, if the two items are not within the preset threshold range, the value of the corresponding predictor is determined as a fourth value, such as any value in 2-5, then the products of the technical predictors and the corresponding preset weights are multiplied, and the products are summed to obtain the behavior measurement factor; and finally, summing the victory measurement factor and the behavior measurement factor or calculating the weighted average of the victory measurement factor and the behavior measurement factor to obtain the response difficulty.

The difficulty comprehensively judges whether the current state of the target training object can respond to the reminding task in time from two aspects of physiology and behavior.

It should be noted that the difficulties include: the response difficulty and the execution difficulty are calculated in a similar manner, but the corresponding threshold parameters and weight values are different.

It should be further noted that the above thresholds or threshold ranges may be determined by big data modeling analysis, such as calculation using neural network algorithm.

And S204, the wearable device and/or the central device execute a pre-guiding task and execute a reminding task after the preset time is reached.

In this step, the wearable device and/or the central device determines an output mode of the guidance information according to the behavior state, i.e., the physiological state and the behavior and action information of the wearer, and then the wearable device outputs the guidance information in a preset mode.

For example, during military training, before military posture training is about to be finished, or before the military posture training is about to be performed, the wearable device detects whether various physiological indexes of the trained object, such as heartbeat, body temperature, respiratory frequency, blood pressure and the like, are normal, and if one or more physiological indexes are smaller than a preset difference value with an index threshold value, the wearable device detects behavior actions of the trained object, such as whether the trained object falls down, swings, and involuntary leg shaking occur during military posture training, and if so, a guidance task, such as sending an alarm to the central device, and guiding the trained object to stop training in a voice or vibration mode needs to be performed.

For another example, in equestrian training, although the physiological indexes of the horse or the rider are normal, the abnormal oscillation frequency of the walking motion of the horse is detected, at this time, the wearable device on the rider can guide the rider to make adjustment or guide the rider to perform a confirmatory motion instruction on the horse, such as an intelligent waistcoat on the rider, left side vibration, guide the rider to pull a halter on the left side, control the horse to perform in-situ circling, so that the wearable device on the horse, such as a foot ring, confirms whether abnormal motion exists on the legs or the hoofs of the horse, if so, a cushion on the trousers of the rider or an intelligent saddle on the horse sends an alarm, or vibrates, and the rider performs checking or stops training on the horse.

S205, the wearable device executes a reminding task after the preset time is reached.

In this step, before the preset time of the target task is reached, if no abnormality is found in the detection stage, or the target training object meets the execution requirement of the target task, the wearable device sends out a reminder when the preset time is reached.

For example, during military training, when the training of standing military posture or walking is about to be completed, a continuous voice prompt is sent, or a vibration prompt from weak to strong or from strong to weak is sent.

In a possible design, if the reminding task is performed, the wearable device detects that the behavior of the target training object does not meet a preset ending condition, for example, the military training station has no time to stand for a military posture, a stepping action occurs, or the personal exercise has no running time, or the calorie consumption of exercise has not reached, the training is stopped, so that the reminding task can be automatically extended until the target training object completes the preset target task, and the reminding task can be ended.

Overall the whole process of this embodiment can be summarized as follows:

the method comprises the steps that central equipment receives target behaviors set by a user, and determines task synchronization instructions through a preset behavior habit training model, wherein the task synchronization instructions comprise at least one target task and at least one reminding task, the reminding task is used for reminding and guiding at least one target training object to complete the target task in preset time, the target task corresponds to the target behaviors, and the target tasks comprise that the movement amount of the target training object reaches a preset standard;

The central equipment executes the task synchronization instruction to send each target task and each reminding task to at least one piece of wearable equipment, wherein the wearing mode of the wearable equipment by a wearer comprises at least one of the following modes: wearing the same or one or more wearable devices on each wearer, wearing the same wearable device on at least two wearers, and wearing the wearable devices on multiple wearers in coordination with each other;

in the detection interval before the preset time arrives, the wearable device detects the behavior state of at least one wearer corresponding to the wearable device, and the behavior state includes: the current physiological state of the wearer and the current behavior information of the wearer;

the wearable device judges the response difficulty of the wearer in responding to the reminding task and the execution difficulty of the target task according to the behavior state;

if yes, the wearable device executes a pre-boot task and executes a reminding task after reaching preset time; if not, the wearable device executes a reminding task after reaching the preset time;

Meanwhile, the wearable device or the central device determines the ending condition of the reminding task according to the execution difficulty, monitors whether the behavior state meets the ending condition in real time through the wearable device, and if yes, the wearable device or the central device ends the reminding task.

The embodiment provides a behavior habit training system method, which includes that wearable equipment receives a target task and a reminding task sent by central equipment, wherein the reminding task is used for reminding and guiding a wearer of the wearable equipment to finish the target task at preset time, and the target task corresponds to a target behavior preset by a user; in a detection period before preset time, the wearable device detects the behavior state of at least one corresponding wearer in real time and judges whether to execute a pre-guiding task according to the behavior state, wherein the pre-guiding task is used for guiding the wearer to change the behavior state so that the difficulty of the wearer responding to a reminding task and executing a target task meets a preset requirement; if yes, the wearable device executes a pre-boot task and executes a reminding task after reaching the preset time. The training of good, accurate behavior habits is carried out on the target training object through the cooperation of the central equipment and the wearable equipment.

For easy understanding, the training method of the behavior habits provided by the present application is further explained below by taking a training scenario of the individual sleeping and getting up behavior habits, i.e. good work and rest habits, as an example.

Fig. 3 is a schematic flow chart of another behavior habit training method provided in the present application. The behavior habit training method is applied to a training scene with good work and rest habits, namely, work and rest on time and getting up on time, and finally the good work and rest habits can be naturally waken at specific time in the morning, such as 7 o' clock.

As shown in fig. 3, the method for training the behavior habit includes the following specific steps:

s301, the central equipment receives a target behavior set by a user, and determines a task synchronization instruction through a preset behavior habit training model.

In this step, the task synchronization instruction includes at least one target task and at least one reminding task, the reminding task is used for reminding and guiding a wearer of the wearable device to complete the target task at a preset time, and the target task corresponds to a target behavior preset by a user.

In this embodiment, the central device includes a cell phone and the wearable device includes a smart watch. The user himself serves as a target training object, the user sets a target behavior of a quantified work and rest habit on the mobile phone, for example, if the user sets that the user starts sleeping at 10 o 'clock in the evening, gets up at 6 o' clock in the morning and gets up for half an hour totally, and sets a sleep reminding task and a get-up reminding task on the mobile phone and start time Tr of each reminding task correspondingly, for example, the reminding task is activated half an hour or 15 minutes in advance, and the user starts to monitor the behavior state of the user.

For a target task of sleep, for example, 10 pm is the execution time of the sleep task, the reminding task may be set to start monitoring various physiological and motion conditions of the user at 9 pm and 30 pm, such as the number of steps taken, the total amount of calories consumed, and so on.

For the waking task, for example, six o ' clock and half a time in the morning are the execution time of the waking task, the user may set the 6 o ' clock or 5 o ' clock 45 minutes to activate the reminding task, and start to monitor various physiological and motion conditions of the user. In one possible design, the central device or the wearable device may adjust the timing of the execution of the wake up task and/or the timing of the activation of the reminder task according to the sleep cycle of the user for N consecutive days (N is greater than or equal to 2). A sleep cycle may be divided into a shallow sleep period and a deep sleep period, and the user may be reminded to get up in the shallow sleep period as much as possible, or a task of getting up or reminding may be performed after a period of time, such as 5 minutes, after the deep sleep period ends, so as to reduce the response difficulty or the execution difficulty of the user, or reduce the physiological disorder of the user in the process of sleeping to waking.

It should be noted that, when setting the reminding task, besides setting the activation time, an ending condition may also be set, for example, for the reminding task of the sleep task, the ending condition may be set as: (1) the heartbeat of the user is below a preset threshold, (2) the breathing rate is below a preset breathing threshold, (3) the number of steps or the accumulated amount of calorie consumption of the user within 5 minutes is less than a preset movement threshold, and (4) all electronic devices are in an inactive state.

For the reminding task of the getting-up task, the ending condition can be set as follows: the number of steps is greater than or equal to a preset number of steps, such as 200/300/400 steps, or the calorie consumption is greater than or equal to a preset calorie threshold, such as 20/25/30 kcal.

In a possible design, prompt information is synchronously displayed on an interface for setting a reminding task to prompt a user, after the behavior habit training mode is started, if other reminding tasks conflict with the reminding task of the training, other reminding tasks can be automatically and forcibly closed or cancelled, when the user sets the reminding task of the behavior habit training, the prompt information can be popped up when a storage button is clicked, and the user needs to click a confirmation button to enter a generation stage of the synchronous task.

In a possible design, the setting of the target behavior may also be performed on the wearable device, and after the setting is completed, the wearable device performs data synchronization with the central device.

After the user finishes the setting of the sleep task and the getting-up task, a task synchronization instruction is automatically generated through a preset behavior habit training model, and the next execution process is carried out.

S302, the central device sends each target task and each reminding task to at least one wearable device by executing the task synchronization instruction.

In this step, the central device performs data synchronization with the wearable device by executing the task synchronization instruction, so as to form a set of complete training auxiliary devices for behavior habits.

In this embodiment, the mobile phone synchronizes the sleep task and the get-up task to the smart watch, and the corresponding reminding task.

In one possible design, the execution of the task synchronization command by the smart watch is data synchronized with the handset if the user is initially a training target for good work and rest set on the smart watch.

And S303, the central equipment closes the central equipment and other reminding tasks irrelevant to the target behaviors in each wearable equipment by executing the task synchronization instruction.

In this step, other reminding tasks unrelated to the target behavior in the central device and the wearable devices are turned off, so as to ensure the compulsory and unique reminding tasks.

In this embodiment, after the task synchronization, the mobile phone and the smart watch will forcibly close or cancel other reminding tasks that conflict with the reminding task of the training.

S304, in a detection period before the preset time, the wearable device detects the behavior state of at least one corresponding wearer in real time.

In this step, the behavioral state is used to characterize the wearer's physiological state as well as behavioral action information.

In this embodiment, the physiological state includes: at least one of respiratory rate, heartbeat, may further include: blood pressure, brain waves, etc., and the behavioral action information includes: the number of steps or calorie consumption may further include: current motion and position.

Specifically, for the sleep task, the reminding task is activated 15-30 minutes before the sleep time arrives, at this time, the wearable device, namely the smart watch, starts to monitor the heartbeat and the breathing frequency of the user, and simultaneously monitors the behavior action of the user, namely the number of moving steps or calories, because the movement of the user is reduced before the sleep, the heartbeat and the breathing frequency are both reduced, and the phenomenon that the user is excited excessively and cannot fall asleep is avoided. Optionally, it may be monitored whether the user is using the mobile phone 3 to 5 minutes before the sleep time is reached.

For the getting-up task, the reminding task is activated 15-30 minutes before the preset getting-up time is reached, or the reminding task is activated when the user is in a shallow sleep stage closest to the getting-up time after statistics of a period of time, and the heartbeat or the respiratory frequency of the user is monitored to judge whether the user is in the shallow sleep stage or the deep sleep stage, or the user is already awake in advance.

S305, the wearable device judges whether to execute a pre-boot task according to the behavior state.

In this step, the pre-boot task is used to guide the wearer to change the behavior state, so that the difficulty of the wearer responding to the reminding task and executing the target task meets the preset requirement.

In this embodiment, the difficulty level includes: the difficulty of the wearer's response to the reminder task, and the difficulty of performing the target task.

S3051, the wearable device judges the response difficulty of the wearer in responding to the reminding task according to the behavior state;

s3052, the wearable device judges whether to execute a pre-boot task according to the response difficulty, so that the response difficulty meets a preset requirement.

If yes, go to step S306, otherwise go to step S307.

Specifically, for the sleep task, the response difficulty = first physiological measurand factor + first behavior weight.

If the heartbeat or the respiratory frequency is higher than a first preset threshold value, the first physiological measurement and calculation factor takes a first value, such as 2, otherwise, the first physiological measurement and calculation factor takes a second value, such as 1.

If the number of steps or the calorie consumption is larger than a second preset threshold value within a first preset time period, such as 5 minutes, the first behavior measurement factor takes a third value, such as 4, otherwise, the first behavior measurement factor takes a fourth value, such as 1.

For the sleep task, considering that the behavior of the user has a greater influence on sleep, the first behavior weight is greater than the first physiological weight, e.g., the first behavior weight is 70% and the first physiological weight is 30%.

For the wake task, the response difficulty = a second physiological metric, a second physiological weight + a second behavior metric, a second behavior weight.

And if the heartbeat or the respiratory frequency is lower than or equal to a third preset threshold, at the moment, the user is proved to be in a deep sleep stage, the fifth value, if 3, is taken as the second physiological measurement factor, and otherwise, the sixth value, if 2, is taken as the second physiological measurement factor.

If the step number or calorie consumption or turnover number is smaller than a fourth preset threshold value within a second preset time period, such as 15 minutes, at the moment, the user is proved to be in a deep sleep period, the second behavior measurement factor takes a seventh value, such as 2, or else takes an eighth value, such as 1.

For the getting-up task, the second physiological weight is larger than the second behavior weight, such as the second physiological weight is 80% and the second behavior weight is 20%, considering that the different stages of the sleep cycle the user is in have a greater influence on getting-up. Of course, if it is detected that the user is awake, for example, the number of steps is continuously increased to a certain threshold, the response difficulty level may be set to 0, or the response difficulty level may not be calculated.

For the execution difficulty, in one possible design, the execution difficulty may be determined according to whether the user responds or not and the value of the response difficulty. For example, if the user responds to the reminding task, recalculating in the manner of the above-mentioned response difficulty after responding to obtain the execution difficulty, and if the user does not respond to the reminding task, directly multiplying the current value of the response difficulty by a preset coefficient to obtain the execution difficulty.

It should be noted that, responding to the reminding task includes: the physiological state of the user is monitored to be changed, such as the change of heartbeat or respiratory frequency, or the movement amount such as the step number, the calorie consumption or the movement of turning over.

Further, in this step, the method further includes:

s3053, the wearable device or the central device determines the end condition of the reminding task according to the execution difficulty.

S3054, monitoring whether the behavior state meets an end condition in real time through the wearable device.

If yes, go to S308; if not, go to S309.

It should be noted that the end condition is set mainly to prevent fraudulent actions of the user or the case where the user does not actually perform the task after responding to the reminder.

And S306, if yes, the wearable device and/or the central device execute a pre-guiding task, and execute a reminding task after the preset time is reached.

In the step, the wearable device and/or the central device determines an output mode of the guiding information according to the physiological state and the behavior and action information;

the preset mode comprises one or more of the following modes: continuously or intermittently outputting the guidance information of uniform intensity, continuously or intermittently increasing or decreasing the intensity of the guidance information, and continuously or intermittently changing the kind or kind combination of the guidance information.

In this embodiment, for the sleep task, when the response difficulty is greater than or equal to the preset guidance threshold, the pre-guidance task is started, if the user is in a motion state, the wearable device emits continuous vibration, the frequency or intensity of the vibration changes along with the amount of change of the amount of motion in the unit time, for example, the intensity of the continuous vibration of the smart watch weakens along with the decrease of the amount of motion in the unit time, and the vibration stops until the user stops moving. This may guide the user to reduce the amount of exercise to rest in bed.

For the waking task, if the user is in the deep sleep period, the value of the response difficulty is greater than the preset guidance threshold, at this time, the guidance task is executed, and the wearable device executes continuous vibration for 5-10 seconds at preset intervals, such as 1 minute, so that the user gradually transitions from the deep sleep state to the shallow sleep state.

And S307, if not, the wearable device executes a reminding task after reaching the preset time.

In this embodiment, for the sleep task, if the user is in bed but the mobile phone is still in working state, when the sleep time arrives, a reminder pops up, or vibrates, and is forced to turn off.

For the waking task, if the user is in a shallow sleep period, the value of the response difficulty is lower than a preset guidance threshold, the guidance task does not need to be executed at this time, and the mobile phone or the smart watch directly executes ringing or vibration at the waking time.

And S308, the wearable device or the central device finishes the reminding task.

In this embodiment, for the sleep task, if it is monitored that the user enters the sleep state and the mobile phone is not turned on again, the reminding may be ended to confirm that the sleep task is executed. For the get-up task, if the user's quantity of motion, such as the number of steps, reaches a preset number of steps, or the calorie consumption amount reaches a preset consumption threshold, it is determined that the user is awake, and the get-up task is completed.

S309, the wearable device or the central device outputs corresponding prompt information and continues to execute the reminding task so as to guide the wearer to continue to complete the target task.

In this step, outputting a prompt message to guide the wearer to change the behavior state includes: visual information is displayed on the display screen, the wearer is guided to complete the operation task corresponding to the visual information, and meanwhile various operations of the wearer when the operation task is completed are received, so that whether the wearer completes the operation task or not is judged according to the operations.

In this embodiment, for the sleep task, if it is detected that the user turns on the mobile phone again, or gets up to move again after that, the mobile phone end pops up the reminding information, and after a preset time, for example, after 2 minutes, the mobile phone is turned off again, and the smart watch vibrates again until the user returns to the bed to stop moving.

For the getting-up task, after the user is reminded by a reminding task, such as vibration and/or alarm, the user is wakeful for a short time and may get up to walk for several steps, the smart watch judges that the user responds to the reminding, but the user returns to the bed to continuously sleep, at the moment, the execution difficulty is confirmed according to the behavior state of the user after the user responds to the reminding,

And S310, before the preset time is reached, if the central device and any one or more of the wearable devices receive the early ending instruction, each wearable device detects the behavior state of the corresponding wearer.

In this step, if the user starts to detect the user state before the reminding task is activated or the reminding task is activated, but does not start to execute the reminding task, the user actively cancels the reminding task through the central device or the wearable device, and the behavior state of the user needs to be monitored to confirm whether the user can complete the target task under the condition of no reminding, so as to avoid the situation that the user cancels the reminding task but does not execute the target task at last.

In this embodiment, for a sleep task, a user gets to bed for rest in advance, and in order not to be disturbed by a reminding task, the user manually clicks on a mobile phone or a smart watch to cancel reminding, and then the smart watch starts to detect a behavior state of the user, that is, a physiological state and behavior action information, to confirm whether the user has fallen asleep, and continues to detect until a preset sleep time.

For the getting-up task, if the user wakes up in advance and clicks a button for canceling the reminding on the mobile phone or the smart watch, the smart watch also starts to detect the behavior state of the user.

It should be noted that, at this time, if the user does not wear the wearable device, that is, the smart watch, the central device, that is, the mobile phone, pops up prompt information that requires the user to wear the wearable device in the cancel interface.

S311, judging whether the behavior state meets the early ending condition.

In this step, the early ending condition may be preset or automatically set by the behavior habit training model.

In this embodiment, for the sleep task, the early termination condition may be set as: the heartbeat or respiratory rate of the user reaches a preset threshold value, and meanwhile, the user does not generate new step numbers or newly increased calorie consumption.

For the getting-up task, the early end condition may be set as: the user's quantity of exercise, i.e., the number of steps or the calorie consumption amount, reaches a preset exercise threshold. This is because the user is physiologically awake after performing a certain amount of exercise.

And S312, if not, the central equipment or the wearable equipment outputs prompt information.

In this step, the prompt is used to guide the wearer to change the behavior state so that the behavior state satisfies the early termination condition.

In this embodiment, for the sleep task, after the user clicks to cancel the reminder, the user does not directly cancel the reminder but suspends the execution of the reminder task, but the smart watch still continuously detects the behavior state of the user, and if it is detected that the behavior state of the user does not meet the condition of ending in advance, the reminder is still executed when the reminding time is reached.

For the task of getting up, if the user wakes up in advance, a button for canceling the reminding is clicked on the mobile phone or the smart watch, or the electronic equipment such as the mobile phone and the computer is opened, the current display picture of the electronic equipment is combined, if the user watches the text data through the mobile phone, the mobile phone or the smart watch sends out guide information such as broadcast voice, the user clicks the position of a specific text on the mobile phone or the computer, or reads a specific text paragraph aloud, or the user draws a specific shape such as a star or a hexagon on the display screen of the mobile phone or the computer, or the user executes the in-situ stepping action to further confirm that the user is awake and avoid the occurrence of the condition that the user falls asleep again.

It should be noted that if the user takes off the wearable device before the detection phase arrives, the execution of the reminder task is taken on the part of the main device.

Fig. 4 is a schematic structural diagram of a training apparatus for behavior habits according to an embodiment of the present application. The behavior habit training device 400 can be implemented by software, hardware or a combination of both.

As shown in fig. 4, the apparatus 400 for training a habit of a user is applied to a wearable device, the wearable device is provided with one or more contact arrays, contact elements in the contact arrays are arranged in a predetermined arrangement to form a predetermined pattern, and the apparatus 400 for training a habit of a user comprises:

an obtaining module 401, configured to receive a target behavior set by a user;

the first processing module 402 is configured to determine a task synchronization instruction through a preset behavior habit training model, where the task synchronization instruction includes at least one target task and at least one reminding task, and the reminding task is used to remind and guide at least one target training object to complete the target task at a preset time, where the target task corresponds to a target behavior;

the first processing module 402 is further configured to execute a task synchronization instruction, so as to send each target task and each reminder task to the second processing module 403, where the second processing module 403 is worn on the target training object;

the second processing module 403 is configured to detect a behavior state of at least one target training object corresponding to the second processing module in real time within a detection time period, where the detection time period is before preset time;

A second processing module 403, further configured to:

if yes, the first processing module 402 and/or the second processing module 403 execute a pre-boot task, and execute a reminding task after a preset time is reached; if not, the first processing module 402 and/or the second processing module 403 execute the reminding task after the preset time is reached.

In one possible design, the first processing module 402 and/or the second processing module 403 perform pre-boot tasks, including:

the first processing module 402 and/or the second processing module 403 determine an output mode of the guidance information according to the physiological state and the behavior and action information;

the first processing module 402 and/or the second processing module 403 outputs the guiding information in a preset manner;

Optionally, the types of the guidance information include: sound or alarm, light, flash, vibration, acupuncture, heat, shock, press, itch, blow.

In one possible design, the difficulty level includes a difficulty level of response of the wearer to the reminder task, and the second processing module 403 is configured to:

judging the response difficulty of the wearer in responding to the reminding task according to the behavior state;

and judging whether to execute the pre-boot task according to the response difficulty, so that the response difficulty reaches a preset requirement.

Optionally, the difficulty level further includes an execution difficulty level of the target task, and the second processing module 403 is further configured to:

determining the end condition of the reminding task according to the execution difficulty, and monitoring whether the behavior state meets the end condition in real time through wearable equipment;

if yes, the first processing module 402 and/or the second processing module 403 ends the reminding task;

if not, the first processing module 402 and/or the second processing module 403 are further configured to: and outputting corresponding prompt information, and continuously executing the reminding task to guide the wearer to continuously complete the target task.

In a possible design, before the preset time is reached, if any one or any more of the first processing module 402 and/or the second processing module 403 receives the early-ending instruction, the second processing module 403 is further configured to: detecting the behavior state of a corresponding wearer, judging whether the behavior state meets an early ending condition or not, wherein an early ending instruction is used for closing a reminding task;

If not, the first processing module 402 or the second processing module 403 is further configured to:

and outputting prompt information to guide the wearer to change the behavior state so that the behavior state meets the early ending condition.

visual information is displayed on the display screen, the wearer is guided to complete the operation task corresponding to the visual information, and meanwhile various operations of the wearer when the operation task is completed are received, so that whether the wearer completes the operation task or not is judged according to the operations.

In one possible design, the first processing module 402 is further configured to:

and closing other reminding tasks irrelevant to the target behaviors so as to ensure the obligatory and unique properties of the reminding tasks.

It should be noted that the apparatus provided in the embodiment shown in fig. 4 may execute the method provided in any of the above method embodiments, and the specific implementation principle, technical features, term explanations and technical effects thereof are similar and will not be described herein again.

Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 5, the electronic device 500 may include: at least one processor 501 and memory 502. Fig. 5 shows an electronic device as an example of a processor.

The memory 502 stores programs. In particular, the program may include program code comprising computer operating instructions.

Memory 502 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.

Processor 501 is configured to execute computer-executable instructions stored in memory 502 to implement the methods described in the method embodiments above.

The processor 501 may be a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

Alternatively, the memory 502 may be separate or integrated with the processor 501. When the memory 502 is a device independent from the processor 501, the electronic device 500 may further include:

A bus 503 for connecting the processor 501 and the memory 502. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. Buses may be divided into address buses, data buses, control buses, etc., but do not represent only one bus or type of bus.

Alternatively, in a specific implementation, if the memory 502 and the processor 501 are integrated into a chip, the memory 502 and the processor 501 may complete communication through an internal interface.

Embodiments of the present application further provide a computer-readable storage medium, where the computer-readable storage medium may include: various media that can store program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and in particular, the computer-readable storage medium stores program instructions for the methods in the above method embodiments.

Embodiments of the present application further provide a computer program product, which includes a computer program, and when the computer program is executed by a processor, the computer program implements the method in the foregoing method embodiments.

Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.

It will be understood that the present application is not limited to the precise arrangements that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.

Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method of training behavioral habits, comprising:

the method comprises the steps that wearable equipment receives a target task and a reminding task sent by central equipment, wherein the reminding task is used for reminding and guiding a wearer of the wearable equipment to finish the target task at preset time, and the target task corresponds to a target behavior preset by a user;

in a detection period before the preset time, the wearable device detects the behavior state of at least one corresponding wearer in real time, wherein the behavior state is used for representing the physiological state and behavior action information of the wearer;

the wearable device judges whether to execute a pre-guiding task according to the behavior state, wherein the pre-guiding task is used for guiding the wearer to change the behavior state so that the difficulty of the wearer responding to the reminding task and executing the target task meets a preset requirement;

if yes, the wearable device and/or the central device execute the pre-guiding task, and execute the reminding task after the preset time is reached; if not, the wearable device executes the reminding task after the preset time is reached.

2. The method for training behavioral habits according to claim 1, wherein the wearable device performs a pre-boot task comprising:

the wearable equipment and/or the central equipment determine an output mode of guiding information according to the physiological state and the behavior and action information;

wherein the preset mode comprises one or more of the following modes: continuously or intermittently outputting the guidance information of uniform intensity, continuously or intermittently increasing or decreasing the intensity of the guidance information, continuously or intermittently changing the kind or kind combination of the guidance information.

3. The method for training behavioral habits according to claim 2, wherein the categories of the guidance information include: sound or alarm, light, flashing, vibration, acupuncture, heat, shock, pressure, itch, blowing.

4. The method for training behavioral habits according to any one of claims 1-3, wherein the difficulty level includes a response difficulty level of the wearer in responding to the reminder task, and the wearable device determines whether to perform a pre-boot task according to the behavioral state, including:

and the wearable equipment judges whether to execute the pre-guiding task according to the response difficulty degree so as to enable the response difficulty degree to reach a preset requirement.

5. The method of training behavioral habits according to claim 4, wherein the difficulty level further includes a difficulty level of performing the target task, further comprising, after the wearable device detects a behavioral state of its corresponding at least one of the wearers in real-time:

the wearable device or the central device determines an ending condition of the reminding task according to the execution difficulty level, and monitors whether the behavior state meets the ending condition in real time through the wearable device;

if yes, the wearable device or the central device ends the reminding task;

6. A method for training behavioral habits according to any one of claims 1-3, further comprising:

Before the preset time is reached, if the central equipment and any one or any plurality of the wearable equipment receive an early ending instruction, the central equipment and any one or any plurality of the wearable equipment receive the early ending instruction

Each wearable device detects the behavior state of the corresponding wearer and judges whether the behavior state meets a condition of ending in advance, wherein the instruction of ending in advance is used for closing the reminding task;

7. The method of claim 6, wherein the outputting a prompt directing the wearer to change the behavioral state comprises:

displaying visual information on a display screen, guiding the wearer to complete an operation task corresponding to the visual information, and receiving various operations of the wearer when the operation task is completed so as to judge whether the wearer completes the operation task according to the operations.

8. The method for training behavioral habits according to claim 7, wherein the operational task comprises one or more of the following combinations: indicating a location of a particular word or symbol in a piece of textual information, reading the textual information, drawing a specified shape on the display screen, and performing a specified action or actions.

9. A method for training behavioral habits according to any one of claims 1-3, wherein the central apparatus executes the task synchronization instruction, further comprising:

10. A method for training behavioral habits according to any one of claims 1-3, wherein the wearable device is worn in a manner including at least one of: wearing the same or one or more of said wearable devices on each of said wearers, wearing the same wearable device on at least two of said wearers, and wearing said wearable devices on a plurality of said wearers in coordination with each other.

11. The method for training behavioral habits according to any one of claims 1 to 3, wherein before the wearable device receives the target task and the reminding task transmitted by the central device, the method further comprises:

the central equipment receives the target behaviors set by the user, and determines a task synchronization instruction through a preset behavior habit training model, wherein the task synchronization instruction comprises at least one target task and at least one reminding task;

And the central equipment executes the task synchronization instruction so as to send each target task and each reminding task to at least one piece of wearable equipment.

12. A device for training behavioral habits, comprising:

the acquisition module is used for receiving a target behavior set by a user;

the first processing module is used for determining a task synchronization instruction through a preset behavior habit training model, wherein the task synchronization instruction comprises at least one target task and at least one reminding task, the reminding task is used for reminding and guiding at least one target training object to complete the target task at preset time, and the target task corresponds to the target behavior;

the first processing module is further configured to execute the task synchronization instruction to send each target task and each reminding task to a second processing module, and the second processing module is worn on the target training object;

the second processing module is used for detecting the behavior state of at least one corresponding target training object in real time within a detection time period, wherein the detection time period is before the preset time;

The second processing module is further configured to:

judging whether a pre-boot task is executed or not according to the behavior state, wherein the pre-boot task is used for guiding the target training object to change the behavior state so that the difficulty of the target training object responding to the reminding task and executing the target task meets a preset requirement;

if so, the first processing module and/or the second processing module executes the pre-boot task, and executes the reminding task after the preset time is reached; and if not, the first processing module and/or the second processing module execute the reminding task after the preset time is reached.

13. An electronic device, comprising:

a processor; and the number of the first and second groups,

a memory for storing a computer program for the processor;

wherein the processor is configured to execute, via execution of the computer program, the respective steps corresponding to the central device or the wearable device in the method for training a behavioral habit according to any one of claims 1 to 11.

14. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out a method for training a behavioral habit according to any one of claims 1 to 11.