CN114916942A - Method, device and equipment for evaluating in-place training effect based on electroencephalogram signals - Google Patents
Method, device and equipment for evaluating in-place training effect based on electroencephalogram signals Download PDFInfo
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- 238000011156 evaluation Methods 0.000 claims abstract description 65
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- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 17
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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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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/1116—Determining posture transitions
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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
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/1455—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters
- A61B5/14551—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters for measuring blood gases
Abstract
The invention relates to the technical field of electroencephalogram signal processing, in particular to an electroencephalogram signal-based method, device and equipment for evaluating an entrance training effect. Acquiring electroencephalogram data of a user to be evaluated; according to the electroencephalogram signal data, obtaining an entry electroencephalogram signal corresponding to an entry state; counting the coincidence duration corresponding to the coincidence of the entrance electroencephalogram signal and the entrance electroencephalogram reference signal; and obtaining an evaluation result of the entrance training according to the matching duration, wherein the evaluation result is used for representing the training effect of the meditation training based on the entrance training. According to the evaluation method, the electroencephalogram signals in the determined state are mainly considered, and the accuracy of evaluating the meditation training effect can be improved.
Description
Technical Field
The invention relates to the technical field of electroencephalogram signal processing, in particular to an electroencephalogram signal-based method, device and equipment for evaluating an admission training effect.
Background
The meditation can change the tension of people and relieve the stress so as to obtain tranquilization of mind. When people just start to learn the meditation training, the actions and breathing frequency do not meet the requirement of the meditation training, so that the meditation training does not meet the standard. The meditation training state is an active state, a calm state, a relax state and an entrance state in sequence according to the time sequence, and the best or bad effect of the entrance state can best indicate the best or bad effect of the meditation training. In the prior art, the importance of the entrance state on the whole meditation training is often ignored when evaluating the meditation training effect, so that the accuracy of the evaluation result is poor.
In conclusion, the evaluation result of the meditation training in the prior art is poor in accuracy.
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 an electroencephalogram signal-based method, a device and equipment for evaluating the entropic training effect, and solves the problem that the evaluation result of meditation training in the prior art is poor in accuracy.
In order to realize the purpose, the invention adopts the following technical scheme:
in a first aspect, the present invention provides a method for evaluating an effect of an entering-fixed training based on an electroencephalogram signal, wherein the method comprises:
acquiring electroencephalogram data of a user to be evaluated;
according to the electroencephalogram signal data, obtaining an entrance-fixed electroencephalogram signal corresponding to an entrance-fixed state;
counting the coincidence duration corresponding to the coincidence of the entrance electroencephalogram signal and the entrance electroencephalogram reference signal;
acquiring head posture data of a user to be evaluated through a posture sensor, wherein the head posture data is the head posture data of the user to be evaluated in a fixed state;
and obtaining an evaluation result of the entering training according to the matching duration and the head posture data, wherein the evaluation result is used for representing the training effect of the meditation training based on the entering training.
In one implementation, the obtaining, according to the electroencephalogram signal data, an entry-fixed electroencephalogram signal corresponding to an entry-fixed state includes;
according to the entering fixed state, obtaining a preset starting time and a preset ending time corresponding to the entering fixed state;
and taking the signal corresponding to the electroencephalogram signal data with the occurrence time between the preset starting time and the preset ending time as the determined electroencephalogram signal.
In one implementation, the counting an anastomosis duration that the determined electroencephalogram signal is anastomosed to the determined electroencephalogram reference signal includes:
acquiring a set time length corresponding to the entering state;
dividing the set time into a plurality of time periods;
calculating the average value of the determined electroencephalogram signals in each time period;
obtaining an anastomosis time period in a plurality of time periods according to the average value and the determined electroencephalogram reference signal;
and obtaining the anastomosis duration according to the anastomosis time interval.
In one implementation, the counting an anastomosis duration that the determined electroencephalogram signal is anastomosed to the determined electroencephalogram reference signal includes:
dividing the input electroencephalogram signal into a plurality of signal sections;
drawing a signal curve corresponding to each signal section;
drawing a reference curve corresponding to the determined electroencephalogram reference signal according to the determined electroencephalogram reference signal;
recording the signal curve superposed with the reference curve as a coincidence curve;
obtaining the duration corresponding to the inosculating curve according to the inosculating curve;
and obtaining the duration of the fit of the determined electroencephalogram signal to the determined electroencephalogram reference signal according to the duration corresponding to the fit curve.
In one implementation, the obtaining, according to a duration corresponding to the fit curve, an fit duration corresponding to the fit electroencephalogram signal being fit to the fit electroencephalogram reference signal includes:
obtaining the anastomosis length corresponding to each anastomosis curve according to each anastomosis curve;
counting the anastomosis curve corresponding to the anastomosis length being greater than the set length, and recording as an anastomosis standard curve;
obtaining the duration corresponding to the standard curve according to the standard curve;
and obtaining the duration of the fit of the determined electroencephalogram signal to the determined electroencephalogram reference signal according to the duration corresponding to the fit standard curve.
In one implementation, the obtaining, according to the length of the fit-in period, an evaluation result of the entrance training, the evaluation result being used for characterizing a training effect of a meditation training based on the entrance training, includes:
acquiring a set time length corresponding to the entering state;
calculating the ratio of the matching time length to a set time length;
according to the head posture data, head pitching motion data and horizontal rotation data in the head posture data are obtained;
and obtaining an evaluation result of the entering-set training according to the ratio, the head pitching motion data and the horizontal rotation data.
In one implementation, the method further comprises:
calculating the difference value between the electroencephalogram signal data of the user to be evaluated and the electroencephalogram reference signal data, wherein the electroencephalogram signal data are electroencephalogram signals corresponding to the user to be evaluated for completing the whole meditation training process;
obtaining a primary evaluation result aiming at the whole meditation training process according to the difference value, wherein the primary evaluation result is used for reflecting the whole effect of the whole meditation training process;
and adding the difference value to the anastomosis duration to obtain a final evaluation result.
In one implementation, the method further comprises:
arranging an infrared instrument in front of a user to be evaluated;
continuously acquiring the blood oxygen concentration of the blood of a user to be evaluated through the infrared ray meter;
when the blood oxygen concentration is maintained within a set concentration range, counting the blood oxygen concentration value at the moment, and recording as a blood oxygen concentration fixed value;
calculating the maximum value and the minimum value of all the blood oxygen concentration input fixed values;
and obtaining the evaluation result of the entering-definite training according to the maximum value and the minimum value.
In a second aspect, an embodiment of the present invention further provides a device for evaluating an admission training effect based on an electroencephalogram signal, where the device includes the following components:
the signal acquisition module is used for acquiring electroencephalogram data of a user to be evaluated;
the signal dividing module is used for obtaining an entrance-fixed electroencephalogram signal corresponding to an entrance-fixed state according to the electroencephalogram signal data;
the time length calculating module is used for counting the fit time length of the fit electroencephalogram signal matched with the fit electroencephalogram reference signal;
and the evaluation module is used for obtaining an evaluation result of the entering training according to the matching duration, and the evaluation result is used for representing the training effect of the meditation training based on the entering training.
In a third aspect, an embodiment of the present invention further provides a terminal device, where the terminal device includes a memory, a processor, and an admission training effect evaluation program based on an electroencephalogram signal, where the admission training effect evaluation program based on an electroencephalogram signal is stored in the memory and is executable on the processor, and when the processor executes the admission training effect evaluation program based on an electroencephalogram signal, the step of implementing the above described admission training effect evaluation method based on an electroencephalogram signal is implemented.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, where an admission training effect evaluation program based on an electroencephalogram signal is stored on the computer-readable storage medium, and when the admission training effect evaluation program based on the electroencephalogram signal is executed by a processor, the steps of the admission training effect evaluation method based on the electroencephalogram signal are implemented.
Has the beneficial effects that: the strength of the electroencephalogram signals can reflect the activity degree of the brain of the user, and the quality of the final effect of the meditation training is reflected on the activity degree of the brain, so that the method adopts the strength of the electroencephalogram signals to reflect the effect of the meditation training, and the accuracy of the evaluation result for the meditation training effect is improved. In addition, on the basis of adopting the brain electric signal to evaluate the meditation training effect, the invention also realizes the brain electric signal when the user enters the entering state (one state in the meditation training), because the effect of the entering state can best reflect the quality of the whole meditation training process in all states of the meditation training. Therefore, the electroencephalogram signals in the determined state are mainly considered, and the accuracy of evaluating the meditation training effect can be improved. In addition, the method also collects the head posture data of the user to be evaluated, and the stable head posture data and the great fitting training effect of the fitting time length of the fit electroencephalogram signal to the fit electroencephalogram reference signal are better than the stable head posture data but the small fitting training effect of the fit electroencephalogram signal to the fit electroencephalogram reference signal. Therefore, the method integrates the anastomosis duration and the head posture data, and can improve the evaluation accuracy of the enrollment training effect.
Drawings
FIG. 1 is an overall flow chart of the present invention;
FIG. 2 is a schematic diagram of an electroencephalogram signal according to 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.
Researches show that the meditation can change the tension of people and relieve the stress so as to obtain a tranquilization of mind. When people just start to learn the meditation training, the actions and breathing frequency do not meet the requirements of the meditation training, so that the meditation training does not reach the standard. The states of the meditation training are an active state, a calm state, a relax state and an entrance state in sequence according to time sequence, and the quality of the effect of the entrance state can best indicate the quality of the meditation training effect. In the prior art, the importance of the entrance status on the whole meditation training is often ignored when evaluating the meditation training effect, so that the accuracy of the evaluation result is poor.
In order to solve the technical problems, the invention provides a method, a device and equipment for evaluating the entrypoint training effect based on electroencephalogram signals, and solves the problem that the evaluation result of meditation training in the prior art is poor in accuracy. In specific implementation, firstly, an entry electroencephalogram signal corresponding to an entry state is obtained, and then the duration of the coincidence of the entry electroencephalogram signal and an entry electroencephalogram reference signal is counted; and finally, obtaining the evaluation result of the entering-set training according to the matching duration. According to the evaluation method, the electroencephalogram signals in the determined state are mainly considered, and the accuracy of evaluating the meditation training effect can be improved.
For example, as shown in fig. 2, first, electroencephalogram data of the user is acquired from 0 to t4 times when the user starts performing meditation training, and the whole process of the meditation training includes four processes corresponding to an active state, a calm state, a relaxed state, and an entrance state. In fig. 2, time 0 to time t1 is a preset active state, time t1 to time t2 is a preset calm state, time t2 to time t3 is a preset relaxed state, and time t3 to time t4 is a preset entering state. In the embodiment, the matching degree between the determined electroencephalogram signal and the determined electroencephalogram reference signal of the user to be evaluated in the determination state from the time t3 to the time t4 is mainly considered, the matching degree is represented by the matching duration, and when the determined electroencephalogram signal in most of time is very close to the determined electroencephalogram reference signal in the time from the time t3 to the time t4, the effect of the whole meditation training is good, otherwise, the meditation training effect is not good. The determination state plays an important role in the evaluation of the whole meditation training effect, so the invention mainly considers the matching duration corresponding to the determination state and can improve the accuracy of the meditation training evaluation.
Exemplary method
The method for evaluating the training effect based on the electroencephalogram signal can be applied to terminal equipment, and the terminal equipment can be terminal products with an audio playing function, such as televisions, computers, mobile phones and the like. In this embodiment, as shown in fig. 1, the method for evaluating an admission training effect based on an electroencephalogram signal specifically includes the following steps:
s100, acquiring electroencephalogram data of a user to be evaluated.
The electroencephalogram data of the embodiment is an electroencephalogram generated by the user to be evaluated in the whole meditation training process. Firstly, a large number of electroencephalogram data sets of a user to be evaluated are collected for multiple times, and electroencephalogram data with the difference value between the maximum value of the signal intensity and the maximum value of the electroencephalogram reference signal (namely, the electroencephalogram signal generated by the user when meditation training meets the requirements) intensity smaller than a set value are selected from the electroencephalogram data sets. The electroencephalogram signal data in this embodiment is a signal in which the difference between the maximum value of the signal intensity and the maximum value of the electroencephalogram reference signal intensity is smaller than a set value. The selection of these electroencephalograph signals for evaluating the meditation training effect of the user to be evaluated means that these signals indicate that the user has substantially met the requirements of the meditation training when performing the meditation training, and it is valuable to evaluate the meditation training effect of the user to be evaluated with respect to these signals.
And S200, obtaining an entry-fixed electroencephalogram signal corresponding to an entry-fixed state according to the electroencephalogram signal data.
The electroencephalogram data comprise signals of meditation training in an active state stage, a calm state stage, a relax state stage and an entering state stage, and the present embodiment mainly considers the entering electroencephalogram signal in the entering state stage (electroencephalogram signals in the time period from t3 to t4 in fig. 2), so as to improve the accuracy of the evaluation result of the meditation training effect.
S300, counting the duration of the fit when the fit electroencephalogram signal fits the fit electroencephalogram reference signal.
Step S300 includes two ways, the first way: obtaining the duration of the fit according to the duration corresponding to the fit of the electroencephalogram signal in the fit state to the fit electroencephalogram reference signal; the second mode is as follows: and obtaining the length of the anastomotic time by adopting the corresponding length of the anastomotic curve, wherein the anastomotic curve is the curve of the coincident part of the curve of the determined electroencephalogram signal and the curve of the determined electroencephalogram reference signal. Adopt the first mode, convenient and fast. The second method can be used to accurately obtain the anastomosis time.
When the first mode is adopted in step S300, the method includes the following steps:
s301, acquiring a set time length corresponding to the entering state.
As shown in fig. 2, the time period from the time t1 to the time t2 is a preset time period corresponding to a preset calm state, the time period from the time t2 to the time t3 is a preset time period corresponding to a preset relax state, and the time period from the time t3 to the time t4 is a preset time period corresponding to a preset enter-set state. What this embodiment needs to use is the set time period from time t3 to time t 4.
S302, dividing the set duration into a plurality of time periods.
For example, the set time period from time t3 to time t4 is divided into five time periods, which may be equally divided time periods or unequally divided time periods. In this embodiment, the time duration corresponding to the third time period is the largest, the third time period is located in the middle of the five time periods, and the signal corresponding to the middle time period can reflect the best state.
S303, calculating the average value of the determined electroencephalogram signals in each time period.
For example, the average value of the determined electroencephalogram signals in the first time period and the average value of the determined electroencephalogram signals in the second time period are calculated until the average values of the determined electroencephalogram signals in the five time periods are calculated.
And S304, obtaining an inosculating time period in a plurality of time periods according to the average value and the determined electroencephalogram reference signal.
Since the imputed electroencephalogram reference signal is a signal generated by the meditation training up to the standard, the imputed electroencephalogram reference signal in the stage of the imputed state is basically kept unchanged, and the average value of the imputed electroencephalogram reference signal does not need to be calculated.
For example, when the average value of the second time segment and the third time segment of the five time segments is equal to the determined electroencephalogram reference signal, the second time segment and the third time segment are the matching time segment.
S305, obtaining the matching duration according to the matching time interval.
And adding the corresponding time lengths of the anastomosis time periods to obtain the anastomosis time length. For example, the sum of the durations corresponding to the second time period and the third time period in step S304 is the matching duration.
When the second mode is adopted in step S300, the following steps S306, S307, S308, S309, S3010, S3011, S3012, S3013, and S3014 are included:
s306, dividing the determined electroencephalogram signal into a plurality of signal sections.
For example, the computer signals with the time length from t3 to t4 in fig. 2 are divided into three parts, namely a first section of incoming definite electroencephalogram signal, a second section of incoming definite electroencephalogram signal and a third section of incoming definite electroencephalogram signal.
And S307, drawing a signal curve corresponding to each signal section.
And drawing the signals on each signal segment into segment curves, such as a first segment signal curve corresponding to the first segment input electroencephalogram signal, a second segment signal curve corresponding to the second segment input electroencephalogram signal, and a third segment signal curve corresponding to the third segment input electroencephalogram signal.
And S308, drawing a reference curve corresponding to the determined electroencephalogram reference signal according to the determined electroencephalogram reference signal.
The reference curve in this embodiment is a curve of the determined electroencephalogram signal over the period of time t3 to t4 as shown in fig. 2.
And S309, marking the signal curve superposed with the reference curve as a coincidence curve.
The first section of signal curve, the second section of signal curve and the third section of signal curve of the user to be evaluated, which section of the three sections of curves is superposed with the reference curve, and which section of curves is a coincident curve.
S3010, obtaining duration corresponding to the inosculating curve according to the inosculating curve.
S3011, obtaining the anastomosis length corresponding to each anastomosis curve according to each anastomosis curve.
S3012, counting the anastomosis curve corresponding to the anastomosis length greater than the set length, and marking as the anastomosis standard curve.
And S3013, obtaining the duration corresponding to the standard curve according to the standard curve.
And S3014, obtaining an anastomosis time length corresponding to the fact that the input electroencephalogram signal is anastomosed to the input electroencephalogram reference signal according to the time length corresponding to the anastomosis standard curve.
S400, head posture data of the user to be evaluated is obtained through the posture sensor, and the head posture data are the head posture data of the user to be evaluated in a fixed state.
S500, obtaining an evaluation result of the entering training according to the matching duration, wherein the evaluation result is used for representing the training effect of the meditation training based on the entering training.
The embodiment is to take the matching duration corresponding to the determined electroencephalogram signal matched with the determined electroencephalogram reference signal as the basis for evaluating the meditation training effect. Step S500 includes steps S501, S502, S503 as follows:
s501, acquiring the set time length corresponding to the entering state.
The set time period in this embodiment is the preset time period from t3 to t4 in fig. 2.
S502, calculating the ratio of the matching time length to the set time length.
And S503, according to the head posture data, obtaining head pitching motion data and horizontal rotation data in the head posture data.
S503, obtaining an evaluation result of the entering-definite training according to the ratio, the head pitching motion data and the horizontal rotation data.
In this embodiment, the larger the ratio is, the better the evaluation result of the training is.
In addition, the present embodiment may also collect the head posture data of the user to be evaluated from the head posture data at the beginning of the meditation training to the head posture data at the end of the meditation training, and find the head posture data (referred to as head posture entering data) corresponding to the entering state from all the head posture data. And comprehensively considering the head posture input data and the specific value to obtain an accurate evaluation result aiming at the input training effect. The head posture data of the user to be evaluated is collected in the embodiment, but not the posture data of other parts of the user to be evaluated, because the head movement is most easily associated with the meditation training effect when the user to be evaluated performs meditation training, for example, the head of the user to be evaluated is most likely to move up and down as long as the user to be evaluated is out of the meditation state, and the leg data of other parts such as the legs are not changed as long as the user to be evaluated does not stand up and move in the meditation training process, so that the quality of the meditation training can be accurately reflected through the head posture data.
The embodiment sends out different evaluation prompt tones according to different ratio values so as to inform the user to be evaluated of the quality of the training.
The embodiment not only evaluates the quality of the training of the user to be evaluated in the total entrance state stage of the meditation training process, but also evaluates the quality of the training of the whole process of the meditation training process including the entrance state, and specifically comprises the following steps S601, S602, and S603:
s601, calculating a difference value between the electroencephalogram data of the user to be evaluated and the electroencephalogram reference signal data, wherein the electroencephalogram data are electroencephalograms corresponding to the user to be evaluated for completing the whole meditation training process.
S602, obtaining a primary evaluation result for the whole meditation training process according to the difference, wherein the primary evaluation result is used for reflecting the whole effect of the whole meditation training process.
And S603, adding the difference value to the anastomosis duration to obtain a final evaluation result.
The embodiment not only obtains the in-line training effect of the user to be evaluated according to the head posture data and the electroencephalogram signal, but also can obtain the quality of the in-line training effect according to the blood oxygen concentration of the user. The method specifically comprises the following steps of S701, S702, S703, S704 and S705:
s701, an infrared instrument is arranged in front of a user to be evaluated.
S702, continuously collecting the blood oxygen concentration of the user to be evaluated through the infrared ray meter;
s703, when the blood oxygen concentration is maintained within a set concentration range, counting the blood oxygen concentration value at the moment, and recording as a blood oxygen concentration fixed value;
s704, calculating the maximum value and the minimum value of all the blood oxygen concentration setting values;
s705, obtaining the evaluation result of the entering-definite training according to the maximum value and the minimum value.
The present embodiment is to arrange the infrared ray instrument in front of the user to be evaluated, but on the body of the user to be evaluated, so that it is possible to prevent the meditation training of the user from being disturbed by additionally adding the instrument on the body of the user to be evaluated.
In this embodiment, when the difference between the maximum value and the minimum value of the blood oxygen concentration entering-setting value is greater than the predetermined threshold value, it indicates that the entering-setting training effect is not good, otherwise, the entering-setting training effect is good.
In conclusion, the strength of the electroencephalogram signals can reflect the activity degree of the brain of the user, and the quality of the final effect of the meditation training is reflected on the activity degree of the brain, so that the strength of the electroencephalogram signals is adopted to reflect the effect of the meditation training, and the accuracy of the evaluation result for the meditation training effect is improved. In addition, on the basis of evaluating the meditation training effect by using the brain electric signals, the invention also realizes the brain electric signals when the user enters into the state of settlement (one state in the meditation training), because the good and bad effect of the state of settlement can best reflect the good and bad of the whole meditation training process in all states of the meditation training. Therefore, the electroencephalogram signals in the determined state are mainly considered, and the accuracy of evaluating the meditation training effect can be improved.
Exemplary devices
The embodiment also provides a device of the method for evaluating the training effect based on the electroencephalogram signal, which comprises the following components:
the signal acquisition module is used for acquiring electroencephalogram data of a user to be evaluated;
the signal dividing module is used for obtaining an entry-fixed electroencephalogram signal corresponding to an entry-fixed state according to the electroencephalogram signal data;
the time length calculating module is used for counting the anastomotic time length of the fit electroencephalogram signal anastomosed with the fit electroencephalogram reference signal;
the head posture data acquisition module is used for acquiring head posture data of a user to be evaluated through a posture sensor, wherein the head posture data is the head posture data of the user to be evaluated in a fixed state;
and the evaluation module is used for obtaining an evaluation result of the entering training according to the matching duration and the head posture data, and the evaluation result is used for representing the training effect of the meditation training based on the entering training.
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 realize a method for evaluating the training effect based on the electroencephalogram signal. 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, where the terminal device includes a memory, a processor, and a training effect evaluation program based on electroencephalogram signals, where the training effect evaluation program based on electroencephalogram signals is stored in the memory and is executable on the processor, and when the processor executes the training effect evaluation program based on electroencephalogram signals, the following operation instructions are implemented:
acquiring electroencephalogram data of a user to be evaluated;
according to the electroencephalogram signal data, obtaining an entry electroencephalogram signal corresponding to an entry state;
counting the length of the fit time corresponding to the fit of the fit electroencephalogram signal to the fit electroencephalogram reference signal;
acquiring head posture data of a user to be evaluated through a posture sensor, wherein the head posture data is the head posture data of the user to be evaluated in a fixed state;
and obtaining an evaluation result of the entering training according to the matching duration and the head posture data, wherein the evaluation result is used for representing the training effect of the meditation training based on the entering training.
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 the 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 method, a device and equipment for evaluating an admission training effect based on an electroencephalogram signal, wherein the method comprises the following steps: acquiring electroencephalogram data of a user to be evaluated; according to the electroencephalogram signal data, obtaining an entry electroencephalogram signal corresponding to an entry state; counting the coincidence duration corresponding to the coincidence of the entrance electroencephalogram signal and the entrance electroencephalogram reference signal; and obtaining an evaluation result of the entrance training according to the matching duration, wherein the evaluation result is used for representing the training effect of the meditation training based on the entrance training. According to the evaluation method, the electroencephalogram signals in the fixed state are mainly considered, and the accuracy of evaluation on the meditation training effect can be improved.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, and not to limit it; although the present invention 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 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 (11)
1. An electroencephalogram signal-based method for evaluating an on-duty training effect is characterized by comprising the following steps:
acquiring electroencephalogram data of a user to be evaluated;
according to the electroencephalogram signal data, obtaining an entry electroencephalogram signal corresponding to an entry state;
counting the coincidence duration corresponding to the coincidence of the entrance electroencephalogram signal and the entrance electroencephalogram reference signal;
acquiring head posture data of a user to be evaluated through a posture sensor, wherein the head posture data is the head posture data of the user to be evaluated in a fixed state;
obtaining an evaluation result of the admitted training according to the anastomosis duration and the head posture data, wherein the evaluation result is used for representing the training effect of meditation training based on the admitted training.
2. The method for evaluating an entrance training effect based on electroencephalogram signals according to claim 1, wherein obtaining the entrance electroencephalogram signal corresponding to an entrance state according to the electroencephalogram signal data comprises:
according to the entering fixed state, obtaining a preset starting time and a preset ending time corresponding to the entering fixed state;
and taking the signal corresponding to the electroencephalogram signal data with the occurrence time between the preset starting time and the preset ending time as the determined electroencephalogram signal.
3. The method for evaluating the effect of the electroencephalogram signal-based on the on-set training, according to claim 1, wherein the counting the length of the fit time when the on-set electroencephalogram signal fits the on-set electroencephalogram reference signal comprises:
acquiring a set time length corresponding to the entering state;
dividing the set time into a plurality of time periods;
calculating the average value of the determined electroencephalogram signals in each time period;
obtaining an anastomotic period in a plurality of time periods according to the average value and the determined electroencephalogram reference signal;
and obtaining the anastomosis duration according to the anastomosis time interval.
4. The method for evaluating the effect of the electroencephalogram signal-based on the on-set training, according to claim 1, wherein the counting the length of the fit time when the on-set electroencephalogram signal fits the on-set electroencephalogram reference signal comprises:
dividing the input electroencephalogram signal into a plurality of signal sections;
drawing a signal curve corresponding to each signal section;
drawing a reference curve corresponding to the determined electroencephalogram reference signal according to the determined electroencephalogram reference signal;
recording the signal curve superposed with the reference curve as a coincidence curve;
obtaining the duration corresponding to the inosculating curve according to the inosculating curve;
and obtaining the matching duration of the matching electroencephalogram signals to the matching electroencephalogram reference signals according to the duration corresponding to the matching curve.
5. The method for evaluating the effect of the electroencephalogram signal-based on the tentative training, according to the duration corresponding to the fit curve, wherein obtaining the fit duration corresponding to the fact that the tentative electroencephalogram signal fits the tentative electroencephalogram reference signal comprises:
obtaining the anastomotic length corresponding to each anastomotic curve according to each anastomotic curve;
counting the anastomosis curve corresponding to the anastomosis length being greater than the set length, and recording as an anastomosis standard curve;
obtaining the duration corresponding to the standard curve according to the standard curve;
and obtaining the matching time length of the matching electroencephalogram signal matched with the matching electroencephalogram reference signal according to the time length corresponding to the matching standard curve.
6. The method for evaluating the effect of the inbound training based on electroencephalogram signal according to claim 1, wherein the obtaining of the evaluation result of the inbound training based on the fitting duration and the head posture data, the evaluation result being used for characterizing the training effect of the meditation training based on the inbound training, comprises:
acquiring a set time length corresponding to the entering state;
calculating the ratio of the matching time length to a set time length;
according to the head posture data, head pitching motion data and horizontal rotation data in the head posture data are obtained;
and obtaining an evaluation result of the training according to the ratio, the head pitching motion data and the horizontal rotation data.
7. The method for evaluating the training effectiveness of entrance to a base on electroencephalogram signals of claim 1, further comprising:
calculating the difference value between the electroencephalogram signal data of the user to be evaluated and the electroencephalogram reference signal data, wherein the electroencephalogram signal data are electroencephalogram signals corresponding to the user to be evaluated for completing the whole meditation training process;
obtaining a primary evaluation result aiming at the whole meditation training process according to the difference value, wherein the primary evaluation result is used for reflecting the whole effect of the whole meditation training process;
and adding the difference value to the anastomosis duration to obtain a final evaluation result.
8. The method for evaluating the training effectiveness of entrance to a base on electroencephalogram signals of claim 1, further comprising:
arranging an infrared instrument in front of a user to be evaluated;
continuously acquiring the blood oxygen concentration of the blood of a user to be evaluated through the infrared ray meter;
when the blood oxygen concentration is maintained within a set concentration range, counting the blood oxygen concentration value at the moment, and recording as a blood oxygen concentration fixed value;
calculating the maximum value and the minimum value of all the blood oxygen concentration setting values;
and obtaining an evaluation result of the training according to the maximum value and the minimum value.
9. A device of an electroencephalogram signal-based on-duty training effect evaluation method is characterized by comprising the following components:
the signal acquisition module is used for acquiring electroencephalogram data of a user to be evaluated;
the signal dividing module is used for obtaining an entrance-fixed electroencephalogram signal corresponding to an entrance-fixed state according to the electroencephalogram signal data;
the time length calculating module is used for counting the fit time length of the fit electroencephalogram signal matched with the fit electroencephalogram reference signal;
the gesture acquisition module is used for acquiring head gesture data of a user to be evaluated through a gesture sensor, wherein the head gesture data is the head gesture data of the user to be evaluated in a fixed state;
an evaluation module for obtaining an evaluation result of the entering training according to the fitting duration and the head posture data, wherein the evaluation result is used for representing the training effect of the meditation training based on the entering training.
10. A terminal device, characterized in that the terminal device comprises a memory, a processor and a scheduled training effect evaluation program based on electroencephalogram signals, which is stored in the memory and can run on the processor, and when the processor executes the scheduled training effect evaluation program based on electroencephalogram signals, the steps of the scheduled training effect evaluation method based on electroencephalogram signals according to any one of claims 1 to 8 are implemented.
11. A computer-readable storage medium, wherein the computer-readable storage medium stores thereon an electroencephalogram signal-based on-training effect evaluation program, and when the electroencephalogram signal-based on-training effect evaluation program is executed by a processor, the steps of the electroencephalogram signal-based on-training effect evaluation method according to any one of claims 1 to 8 are implemented.
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