CN114492541A - Meditation training scheme making method, device, equipment and storage terminal - Google Patents
Meditation training scheme making method, device, equipment and storage terminal Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/02—Preprocessing
- G06F2218/04—Denoising
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/369—Electroencephalography [EEG]
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M21/00—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
- A61M21/02—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis for inducing sleep or relaxation, e.g. by direct nerve stimulation, hypnosis, analgesia
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/70—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mental therapies, e.g. psychological therapy or autogenous training
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M21/00—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
- A61M2021/0005—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M2230/00—Measuring parameters of the user
- A61M2230/08—Other bio-electrical signals
- A61M2230/10—Electroencephalographic signals
Abstract
The invention relates to the technical field of electroencephalogram signal processing, in particular to a meditation training scheme making method, a meditation training device, meditation training equipment and a storage terminal. The invention collects various meditation training real-time curves corresponding to the electroencephalogram signals according to various time periods which are sequentially performed by the meditation training, and compares the meditation training real-time curves of the various time periods with meditation training reference curves corresponding to the various time periods. If the real-time curve of the meditation training in a certain time period is not matched with the reference curve of the meditation training corresponding to the certain time period, the meditation effect in the certain time period is not good, and a targeted training scheme needs to be formulated for the certain time period to carry out intensive training. The invention carries out strengthening training aiming at the time period with poor meditation effect, and can quickly improve the meditation effect of the whole meditation process.
Description
Technical Field
The invention relates to the technical field of electroencephalogram signal processing, in particular to a meditation training scheme making method, a meditation training device, meditation training equipment and a storage terminal.
Background
The meditation training enables the person to be in a relatively relaxed state, and the meditation state should be gradually improved as the meditation progress time advances. In order to enable the user to gradually improve the meditation state along with the advancement of the meditation progress time, a corresponding training scheme is formulated according to the meditation training result of each time of the user, so that the user can better perform meditation training under the guidance of the training scheme when performing the next meditation training, and the meditation effect is improved. However, the existing training schemes are all directed to the whole meditation process, and corresponding training schemes are not formulated for local time periods in the meditation process, so that the formulated training schemes are difficult to improve the meditation training of the local time periods with weak meditation effect.
In summary, it is difficult to improve the meditation training in the local time zone where the meditation effect is weak in the training scheme established in the prior art.
Thus, there is a need for improvements and enhancements in the art.
Disclosure of Invention
In order to solve the technical problems, the invention provides a meditation training scheme making method, a device, equipment and a storage terminal, and solves the problem that the meditation training in local time periods with weak meditation effect is difficult to improve by the training scheme made in the prior art.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, the present invention provides a meditation training plan formulation method in which meditation training real-time curves composed of electroencephalogram signals of respective time periods of a user are acquired;
comparing the real-time meditation training curves of the time periods with meditation training reference curves of the corresponding time periods to obtain comparison results of the time periods;
and formulating a training scheme aiming at each time period according to the comparison result of each time period.
In one implementation, the acquiring a meditation training real-time curve composed of electroencephalogram signals of respective time periods of a user includes:
acquiring training time duration corresponding to meditation training of the user;
dividing the training time into time periods according to the distance from the training starting time, wherein the time period close to the training starting time corresponds to a time period longer than the time period far away from the training starting time;
collecting electroencephalogram signals of each time period of the user;
and drawing the electroencephalogram signals of the time periods into meditation training real-time curves.
In one implementation, the comparing the meditation training real-time curves of the respective time periods with the meditation training reference curves of the corresponding respective time periods to obtain the comparison result for each of the time periods includes:
obtaining a first reference curve and a second reference curve of each time period according to the meditation training reference curve of each time period, wherein the electroencephalogram signal on the first reference curve is larger than the electroencephalogram signal on the second reference curve;
constructing a reference interval consisting of the first reference curve and the second reference curve;
comparing the meditation training real-time curves of the respective time periods with the reference intervals of the respective time periods to obtain comparison results for the respective time periods.
In one implementation, the comparing the meditation training real-time curve for each of the time periods with the reference interval for each of the time periods to obtain a comparison result for each of the time periods includes:
acquiring meditation training historical curves of the users in various time periods;
obtaining a history curve section of each time period corresponding to the meditation training history curve of each time period through the meditation training history curve of each time period, wherein the meditation training history curve is positioned in the history curve section;
comparing the meditation training real-time curve of each time period with the reference interval and the historical curve interval of each time period to obtain a comparison result for each time period.
In one implementation, the obtaining of the meditation training history curves for the respective time periods of the user includes:
acquiring a real-time date corresponding to the meditation training real-time curve;
according to the real-time date, obtaining a historical date which is different from the real-time date by a set date;
calculating the average value of the meditation training curves corresponding to the historical dates to obtain the meditation training historical curve of the user;
and dividing the meditation training historical curve into time periods to obtain the meditation training historical curve of each time period.
In one implementation, the formulating a training scheme for each of the time periods according to the comparison result of each of the time periods includes:
according to the comparison result, obtaining a weak real-time curve segment on the meditation training real-time curve in the comparison result, wherein the weak real-time curve segment is a curve segment which is positioned outside the reference interval and outside the historical curve interval;
according to the weak real-time curve segments, weak time segments corresponding to the weak real-time curve segments in the time segments are obtained;
and formulating a training scheme aiming at the weak time period.
In one implementation, the comparing the meditation training real-time curves of the respective time periods with the meditation training reference curves of the corresponding respective time periods to obtain the comparison result for each of the time periods includes:
obtaining a first reference curve and a second reference curve of each time period according to the meditation training reference curve of each time period, wherein the electroencephalogram signal on the first reference curve is larger than the electroencephalogram signal on the second reference curve;
constructing a reference interval consisting of the first reference curve and the second reference curve;
acquiring meditation training historical curves of the users in various time periods;
obtaining a history curve section of each time period corresponding to the meditation training history curve of each time period through the meditation training history curve of each time period, wherein the meditation training history curve is positioned in the history curve section;
counting the lengths of weak curves corresponding to the meditation training real-time curves of the time periods, wherein the weak curves are located outside the reference interval and outside the historical curve interval;
and obtaining weak time periods in the time periods according to the weak curve lengths corresponding to the time periods.
In a second aspect, the embodiment of the present invention further provides a device for making a meditation training scheme, wherein the device includes the following components:
the curve acquisition module is used for acquiring a meditation training real-time curve formed by the electroencephalogram signals of the user in each time period;
the calculation module is used for comparing the meditation training real-time curve of each time period with the meditation training reference curve of each corresponding time period to obtain a comparison result aiming at each time period;
a scheme making module for making a scheme for each station according to the comparison result of each time period
A training scheme for the time period.
In a third aspect, the embodiment of the present invention further provides a terminal device, where the terminal device includes a memory, a processor, and a meditation training scenario making program stored in the memory and operable on the processor, and when the processor executes the meditation training scenario making program, the method for making the meditation training scenario is implemented.
In a fourth aspect, the embodiment of the present invention further provides a computer-readable storage medium, on which a meditation training plan making program is stored, and when the meditation training plan making program is executed by a processor, the meditation training plan making program implements the steps of the meditation training plan making method.
Has the advantages that: the invention collects various meditation training real-time curves corresponding to the electroencephalogram signals according to various time periods which are sequentially carried out by the meditation training, compares the meditation training real-time curves of the various time periods with meditation training reference curves corresponding to the various time periods, and if the meditation training real-time curves of a certain time period are matched with the meditation training reference curves corresponding to a certain time period, the meditation effect of the certain time period is good, and a special training scheme does not need to be made aiming at the certain time period. If the real-time curve of the meditation training in a certain time period is not matched with the reference curve of the meditation training corresponding to the certain time period, the meditation effect in the certain time period is not good, and a targeted training scheme needs to be formulated for the certain time period to carry out intensive training. The invention carries out strengthening training aiming at the time periods (weak time periods) with poor meditation effect, and can quickly improve the meditation effect of the whole meditation process.
Drawings
FIG. 1 is an overall flow chart of the present invention;
FIG. 2 is a schematic view of various curves of the present invention;
fig. 3 is a schematic block diagram of an internal structure of a terminal device according to an embodiment of the present invention.
Detailed Description
The technical scheme of the invention is clearly and completely described below by combining the embodiment and the attached drawings of the specification. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It has been found that meditation training enables a person to be in a relatively relaxed state, which is gradually improved as the meditation progresses over time. In order to enable the user to gradually improve the meditation state along with the advancement of the meditation progress time, a corresponding training scheme is formulated according to the meditation training result of each time of the user, so that the user can better perform meditation training under the guidance of the training scheme when performing the next meditation training, and the meditation effect is improved. However, the existing training schemes are all directed to the whole meditation process, and corresponding training schemes are not formulated for local time periods in the meditation process, so that the formulated training schemes are difficult to improve the meditation training of the local time periods with weak meditation effect.
In order to solve the technical problems, the invention provides a meditation training scheme making method, a device, equipment and a storage terminal, and solves the problem that the meditation training in local time periods with weak meditation effect is difficult to improve by the training scheme made in the prior art. When the specific implementation is carried out, firstly, a meditation training real-time curve formed by the electroencephalogram signals of each time period of the user is collected; then comparing the real-time meditation training curves of all time periods with the corresponding meditation training reference curves of all time periods to obtain comparison results aiming at all the time periods; and finally, according to the comparison result of each time period, making a training scheme aiming at each time period.
For example, the meditation training comprises a first time period, a second time period and a third time period which are sequentially arranged from beginning to end, the electroencephalogram signals of the user in the first time period are drawn into a first meditation training real-time curve, the electroencephalogram signals in the second time period are drawn into a second meditation training real-time curve, and the electroencephalogram signals in the third time period are drawn into a third meditation training real-time curve. The meditation training reference curve is also formed by drawing corresponding electroencephalogram signals in corresponding three time periods, namely the meditation training reference curve also comprises a first meditation training reference curve, a second meditation training reference curve and a third meditation training reference curve. If the difference between the first meditation training real-time curve and the first meditation training reference curve is large, corresponding guiding sound effects (training schemes) can be played in the first time period when the meditation training is started at the next meditation training, so that the user can be helped to perform meditation training in the first time period to enable the first meditation training real-time curve to be close to the first meditation training reference curve, the same processing is performed on the meditation training real-time curves in the second time period and the third time period, so that the meditation training effect in which one or more of the three time periods of the user is poor can be known, and the corresponding training schemes can be made for the time periods with poor meditation training effects at the next meditation training to improve the meditation training effect of the time periods.
Exemplary method
The meditation training scheme making method of the embodiment can be applied to terminal equipment, and the terminal equipment can be terminal products with an audio and video playing function, such as televisions, computers, mobile phones and the like. In this embodiment, as shown in fig. 1, the meditation training plan making method specifically includes the following steps:
and S100, acquiring a meditation training real-time curve formed by the electroencephalogram signals of the user in each time period.
The electroencephalogram signals of the embodiment are sequentially generated by the user along with the time of meditation training, the time of the generation of the electroencephalogram signals is used as an abscissa, the intensity of the electroencephalogram signals is used as an ordinate, a meditation training real-time curve is drawn, then the total time formed by the time of the generation of the electroencephalogram signals is divided into time periods, and the meditation training real-time curves of the time periods are obtained. In the embodiment, the electroencephalogram signal is acquired by the electroencephalogram ring, and the electroencephalogram ring generates noise in the use process, so that the electroencephalogram signal acquired by the electroencephalogram cannot represent the real electroencephalogram signal of a user, and therefore the acquired electroencephalogram signal needs to be filtered to obtain the real electroencephalogram signal of the user.
Step S100 includes steps S101, S102, S103, S104 as follows:
s101, acquiring training time duration corresponding to the meditation training of the user.
S102, dividing the training time into time periods according to the distance from the training starting time, wherein the time period close to the training starting time corresponds to a time period longer than the time period far away from the training starting time.
As shown in fig. 2, the training duration is T, and the training duration is divided into time periods, wherein the first time period (T1) is greater than the second time period (T2), and the second time period (T2) is greater than the third time period (T3). The reason why the time lengths corresponding to the time periods are sequentially reduced along with the meditation training is that the more difficult the user controls the electroencephalogram signal along with the meditation training, the more likely the meditation training real-time curve deviates from the meditation training reference curve, so that the time length of the later time period can be more accurately positioned to the time period where the meditation training real-time curve deviating from the meditation training reference curve is located, and a training scheme for the time period can be specifically formulated.
S103, collecting the electroencephalogram signals of the user in each time period.
And S104, drawing the electroencephalogram signals of the time periods into meditation training real-time curves.
When the meditation training real-time curve is drawn according to the electroencephalogram signals, the electroencephalogram signals which are obviously deviated from the meditation training reference curve are deleted, the electroencephalogram signals are caused by interference of the acquisition equipment and are not the real electroencephalogram signals of the user, and the authenticity of the drawn meditation training real-time curve can be influenced by the existence of the signals.
And S200, comparing the real-time meditation training curves of the time periods with meditation training reference curves of the corresponding time periods to obtain comparison results of the time periods.
The step S200 is to select weak time periods (the meditation training real-time curved meditation of the weak time periods) from all the time periods, and specifically includes the following steps S201, S202, S203, S204, S205, S206, S207, S208:
s201, obtaining a first reference curve and a second reference curve of each time period according to the meditation training reference curve of each time period, wherein the electroencephalogram signal on the first reference curve is larger than the electroencephalogram signal on the second reference curve.
The first reference curve and the second reference curve are shown in fig. 2, the brain electrical signals are allowed to fluctuate during the meditation training process, and the meditation training effect of the user is good as long as the fluctuation degree of the brain electrical signals of the user is between the first reference curve and the second reference curve.
S202, constructing a reference interval consisting of the first reference curve and the second reference curve.
S203, acquiring the real-time date corresponding to the meditation training real-time curve.
And S204, obtaining a historical date which is different from the real-time date by a set date according to the real-time date.
And S205, calculating the average value of the meditation training curves corresponding to the historical dates to obtain the meditation training historical curve of the user.
The real-time date is the date of the day when the user performs the meditation training, and the history date of the present embodiment is a date one week away from the real-time date. For example, the real-time date is today (thirty-five), the history date is as same as the current date (february to thirty-four), electroencephalograms during meditation training of the user in seven days of february to thirty-four are collected, the historical electroencephalograms at the same moment are averaged, and the average value at all the moments forms a meditation training history curve. For example, the average value of the electroencephalogram signals from February to March fourteen at the first moment when the meditation starts is obtained, the average value of the historical electroencephalogram signals at the first moment when the meditation starts is obtained, the average value of the electroencephalogram signals from February to March fourteen at the second moment when the meditation starts is similarly obtained, the average value of the historical electroencephalogram signals at the second moment when the meditation starts is obtained, and the historical electroencephalogram signals at all the moments are drawn into curves to obtain a meditation training historical curve.
And S206, dividing the meditation training history curve into time periods to obtain the meditation training history curves of each time period.
As shown in fig. 2, the time period division of the meditation training history curve is the same as the time period division of the meditation training real-time curve.
And S207, obtaining a history curve section of each time slot corresponding to the meditation training history curve of each time slot according to the meditation training history curve of each time slot, wherein the meditation training history curve is positioned in the history curve section.
And S208, comparing the meditation training real-time curve of each time period with the reference interval and the historical curve interval of each time period to obtain a comparison result for each time period.
The reason why the real-time curve of the meditation training is compared with the reference interval and the historical curve interval to obtain the final comparison result is that the comparison with the historical curve interval can know whether the current meditation training improves on the basis of the past meditation training of the user, if so, how much difference exists between the improved meditation training and the reference meditation training, and a specific subsequent training scheme can be made according to the difference. If there is no improvement in the current meditation training, it is shown that the previous training scheme has no recognizability, and the subsequent training scheme can be completely separated from the existing training scheme and the training scheme can be re-established.
S300, according to the comparison result of each time period, a training scheme aiming at each time period is formulated.
The present embodiment finds the time period in which the meditation effect is poor among the respective time periods, through the comparison result of the respective time periods. Step S300 includes the following steps:
and S301, obtaining a weak real-time curve segment on the meditation training real-time curve in the comparison result according to the comparison result, wherein the weak real-time curve segment is a curve segment which is positioned outside the reference interval and outside the historical curve interval.
And S302, according to the weak real-time curve segments, obtaining weak time segments corresponding to the weak real-time curve segments in the time segments.
As shown in fig. 2, the period T2 and the period T3 are weak periods.
And S303, formulating a training scheme aiming at the weak time period.
The training scheme which can be made for the weak time period is that when the next meditation training is carried out to the weak time period, the corresponding guide sound effect is played to strengthen the meditation training of the user in the weak time period, so that the meditation training effect in the weak time period is improved.
In summary, the present invention collects the respective meditation training real-time curves corresponding to the electroencephalogram signals according to the respective time periods in which the meditation training is sequentially performed, compares the meditation training real-time curves of the respective time periods with the meditation training reference curves corresponding to the respective time periods, and if the meditation training real-time curves of a certain time period are matched with the meditation training reference curves corresponding to a certain time period, it indicates that the meditation effect of a certain time period is good, and it is not necessary to make a special training scheme for the certain time period. If the real-time curve of the meditation training in a certain time period is not matched with the reference curve of the meditation training corresponding to the certain time period, the meditation effect in the certain time period is not good, and a targeted training scheme needs to be formulated for the certain time period to carry out intensive training. The invention carries out strengthening training aiming at the time periods (weak time periods) with poor meditation effect, and can quickly improve the meditation effect of the whole meditation process.
Exemplary devices
The embodiment also provides a meditation training scheme making device, which comprises the following components:
the curve acquisition module is used for acquiring a meditation training real-time curve formed by the electroencephalogram signals of the user in each time period;
the calculation module is used for comparing the meditation training real-time curve of each time period with the meditation training reference curve of each corresponding time period to obtain a comparison result aiming at each time period;
a scheme making module for making a scheme for each station according to the comparison result of each time period
A training scheme for the time period.
Based on the above embodiments, the present invention further provides a terminal device, and a schematic block diagram thereof may be as shown in fig. 3. The terminal equipment comprises a processor, a memory, a network interface, a display screen and a temperature sensor which are connected through a system bus. Wherein the processor of the terminal device is configured to provide computing and control capabilities. The memory of the terminal equipment comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the terminal device is used for connecting and communicating with an external terminal through a network. The computer program is executed by a processor to implement a meditation training regimen preparation method. The display screen of the terminal equipment can be a liquid crystal display screen or an electronic ink display screen, and the temperature sensor of the terminal equipment is arranged in the terminal equipment in advance and used for detecting the operating temperature of the internal equipment.
It will be understood by those skilled in the art that the block diagram shown in fig. 3 is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation to the terminal device to which the solution of the present invention is applied, and a specific terminal device may include more or less components than those shown in the figure, or may combine some components, or have different arrangements of components.
In one embodiment, a terminal device is provided, the terminal device comprises a memory, a processor and a meditation training scheme making program stored in the memory and operable on the processor, and the processor implements the following operation instructions when executing the meditation training scheme making program:
collecting a meditation training real-time curve formed by electroencephalogram signals of each time period of a user;
comparing the real-time meditation training curves of the time periods with meditation training reference curves of the corresponding time periods to obtain comparison results of the time periods;
and formulating a training scheme aiming at each time period according to the comparison result of each time period.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, databases, or other media used in embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
In summary, the invention discloses a meditation training scheme making method, a meditation training scheme making device, a meditation training device and a storage terminal, wherein the method comprises the following steps: collecting a meditation training real-time curve formed by electroencephalogram signals of each time period of a user; comparing the real-time meditation training curves of the time periods with meditation training reference curves of the corresponding time periods to obtain comparison results of the time periods; and formulating a training scheme aiming at each time period according to the comparison result of each time period. The invention carries out strengthening training aiming at the time periods (weak time periods) with poor meditation effect, and can quickly improve the meditation effect of the whole meditation process.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will 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 technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A meditation training scheme making method is characterized by comprising the following steps:
collecting a meditation training real-time curve formed by electroencephalogram signals of each time period of a user;
comparing the real-time meditation training curves of the time periods with meditation training reference curves of the corresponding time periods to obtain comparison results of the time periods;
and formulating a training scheme aiming at each time period according to the comparison result of each time period.
2. The meditation training protocol making method according to claim 1, wherein the acquiring meditation training real-time curves composed of the electroencephalogram signals of the respective time periods of the user includes:
acquiring training time duration corresponding to meditation training of the user;
dividing the training time into time periods according to the distance from the training starting time, wherein the time period close to the training starting time corresponds to a time period longer than the time period far away from the training starting time;
collecting electroencephalogram signals of each time period of the user;
and drawing the EEG signals of the time periods into a meditation training real-time curve.
3. The meditation training scenario formulation method of claim 2, wherein comparing the meditation training real-time curves for each time period with meditation training reference curves for corresponding respective time periods to obtain comparison results for each of the time periods comprises:
obtaining a first reference curve and a second reference curve of each time period according to the meditation training reference curve of each time period, wherein the electroencephalogram signal on the first reference curve is larger than the electroencephalogram signal on the second reference curve;
constructing a reference interval consisting of the first reference curve and the second reference curve;
comparing the meditation training real-time curves of the respective time periods with the reference intervals of the respective time periods to obtain comparison results for the respective time periods.
4. The meditation training protocol making method according to claim 3, wherein the comparing the meditation training real-time curves of the respective time periods with the reference intervals of the respective time periods to obtain the comparison result for the respective time periods comprises:
acquiring meditation training historical curves of the users in various time periods;
obtaining a history curve section of each time period corresponding to the meditation training history curve of each time period through the meditation training history curve of each time period, wherein the meditation training history curve is positioned in the history curve section;
comparing the meditation training real-time curve of each time period with the reference interval and the historical curve interval of each time period to obtain a comparison result for each time period.
5. The meditation training scenario formulation method of claim 4, wherein the obtaining of meditation training history curves for respective time periods of the user comprises:
acquiring a real-time date corresponding to the meditation training real-time curve;
according to the real-time date, obtaining a historical date which is different from the real-time date by a set date;
calculating the average value of the meditation training curves corresponding to the historical dates to obtain the meditation training historical curve of the user;
and dividing the meditation training historical curve into time periods to obtain the meditation training historical curve of each time period.
6. The meditation training plan making method according to claim 4, wherein the making of the training plan for each of the time periods according to the comparison result of each of the time periods includes:
according to the comparison result, obtaining a weak real-time curve segment on the meditation training real-time curve in the comparison result, wherein the weak real-time curve segment is a curve segment which is positioned outside the reference interval and outside the historical curve interval;
according to the weak real-time curve segments, weak time segments corresponding to the weak real-time curve segments in the time segments are obtained;
and formulating a training scheme aiming at the weak time period.
7. The meditation training plan making method according to claim 1, wherein the comparing the meditation training real-time curve of each time zone with the meditation training reference curve of the corresponding each time zone to obtain the comparison result for each time zone comprises:
obtaining a first reference curve and a second reference curve of each time period according to the meditation training reference curve of each time period, wherein the electroencephalogram signal on the first reference curve is larger than the electroencephalogram signal on the second reference curve;
constructing a reference interval consisting of the first reference curve and the second reference curve;
acquiring meditation training historical curves of the users in various time periods;
obtaining a history curve section of each time period corresponding to the meditation training history curve of each time period through the meditation training history curve of each time period, wherein the meditation training history curve is positioned in the history curve section;
counting the lengths of weak curves corresponding to the meditation training real-time curves of the time periods, wherein the weak curves are located outside the reference interval and outside the historical curve interval;
and obtaining weak time periods in the time periods according to the weak curve lengths corresponding to the time periods.
8. A meditation training plan making device is characterized in that the device comprises the following components:
the curve acquisition module is used for acquiring a meditation training real-time curve formed by the electroencephalogram signals of the user in each time period;
the calculation module is used for comparing the meditation training real-time curve of each time period with the meditation training reference curve of each corresponding time period to obtain a comparison result aiming at each time period;
a scheme making module for making a scheme for each station according to the comparison result of each time period
A training scheme for the time period.
9. A terminal device, characterized in that the terminal device comprises a memory, a processor and a meditation training scenario formulation program stored in the memory and executable on the processor, when executing the meditation training scenario formulation program, implementing the steps of the meditation training scenario formulation method according to any one of claims 1-7.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a meditation training scenario formulation program, which when executed by a processor, carries out the steps of the meditation training scenario formulation method as claimed in any one of claims 1 to 7.
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