CN109549643B - Intelligence training instrument - Google Patents
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Abstract
The invention provides an intelligence training instrument: a gamma wave adjusting module: starting a preset gamma wave regulation mode, wherein the gamma wave regulation mode is used for regulating the electroencephalogram gamma wave characteristics of the trainee; the electroencephalogram parameter detection module: acquiring a current electroencephalogram preset parameter value of a trainee, wherein the electroencephalogram preset parameter is an electroencephalogram gamma wave characteristic parameter or an associated parameter of the electroencephalogram gamma wave characteristic parameter; the electroencephalogram parameter judging module: judging whether the current electroencephalogram preset parameter value meets a preset condition, if so, executing a feedback signal module, and if not, returning to an electroencephalogram parameter detection module; a feedback signal module: and judging whether a preset feedback signal is started or not, if so, adjusting the intensity of the preset feedback signal according to the current electroencephalogram preset parameter value, returning to the electroencephalogram parameter detection module, otherwise, starting the preset feedback signal, adjusting the intensity of the preset feedback signal according to the current electroencephalogram preset parameter value, and returning to the electroencephalogram parameter detection module. The intelligence training instrument based on the invention can improve the intelligence level of a trainee and delay the intelligence decline.
Description
Technical Field
The invention relates to the field of biomedical engineering, in particular to an intelligence training instrument.
Background
With the gradual progress of China into the aging society, the problem of intelligence health of the old has gradually become a major problem affecting the health condition and the quality of life of the old. For example, the problem of intelligence loss of the old people is the first problem affecting the intelligence health of the old people.
In various non-drug treatment and prevention methods of senile dementia, physical and mental intervention (/ interventional) training (/ therapy) is an attractive option for those who are predicted to be at high risk for senile dementia but do not yet exhibit significant clinical symptoms.
The physical and mental intervention (/ interventional) training comprises various trainings such as qigong, taiji, meditation (sitting), memorial thought, yoga, meditation, hypnosis, abdominal respiration and the like, is a physical and mental exercise method derived from the traditional eastern health preserving technology, and can train the mind, the physical strength and the psychology. The physical and mental intervention training method not only continuously pays attention to and is applied to the oriental nationality, but also arouses more and more intense interest in the western world. However, until now, there have been many difficulties and obstacles to the use of such training to prevent dementia in the elderly. Firstly, many physical and mental intervention training methods do not have indexes which are easy to be sensed by trainees, and the difficulty in practicing is large. For example, some trainees who practice qigong often feel "quiet" and "get qi" difficult, and do not get much time and do not need to be. Even if it seems that a certain state can be entered in holidays, there is still a natural loam between the state that can be entered and the state that a high hand is in for many years of refining. Secondly, various physical and mental intervention training methods have respective characteristics, the training methods are also very different, physical and mental states of trainees are very different during training, and health problems suitable for solving are also very different. For example, some physical and mental intervention training methods may be particularly suitable for the prevention and treatment of digestive system diseases in some people, but are not necessarily most suitable for intelligence training and are not necessarily most effective for the prevention of senile dementia. In addition, individual differences of people are everywhere, and the same physical and mental intervention training is effective for the intelligence training of one person but not necessarily suitable for the other person. How to select a physical and mental intervention mode which is most suitable for the intelligence training of an individual and how to carry out effective intelligence training is more lack of effective methods at present. Finally, how to avoid mental disorders (so-called fire-fighting) induced by some physical and mental intervention training (such as training of some qigong) is also a problem to be faced by the physical and mental intervention training.
Disclosure of Invention
In view of the above, the present invention provides an intelligence training method and an intelligence training apparatus, so as to solve the problem of how to perform effective intelligence training.
The invention provides a method for intelligence training, which comprises the following steps
Step 11: starting a preset gamma wave regulation mode, wherein the gamma wave regulation mode is used for regulating the electroencephalogram gamma wave characteristics of the trainee;
step 12: acquiring a current electroencephalogram preset parameter value of a trainee, wherein the electroencephalogram preset parameter is an electroencephalogram gamma wave characteristic parameter or an associated parameter of the electroencephalogram gamma wave characteristic parameter;
step 13: judging whether the current electroencephalogram preset parameter value meets the preset condition, if so, executing the step 14, and if not, returning to the step 12;
step 14: and judging whether the preset feedback signal is started or not, if so, adjusting the intensity of the preset feedback signal according to the current electroencephalogram preset parameter value, returning to the step 12, otherwise, starting the preset feedback signal, adjusting the intensity of the preset feedback signal according to the current electroencephalogram preset parameter value, and returning to the step 12.
The invention also provides an intelligence training instrument, comprising:
a gamma wave adjusting module: starting a preset gamma wave regulation mode, wherein the gamma wave regulation mode is used for regulating the electroencephalogram gamma wave characteristics of the trainee;
the electroencephalogram parameter detection module: acquiring a current electroencephalogram preset parameter value of a trainee, wherein the electroencephalogram preset parameter is an electroencephalogram gamma wave characteristic parameter or an associated parameter of the electroencephalogram gamma wave characteristic parameter;
the electroencephalogram parameter judging module: judging whether the current electroencephalogram preset parameter value meets the preset condition, if so, executing a feedback signal module, and if not, returning to an electroencephalogram parameter detection module;
a feedback signal module: and judging whether the preset feedback signal is started or not, if so, adjusting the intensity of the preset feedback signal according to the current electroencephalogram preset parameter value, returning to the electroencephalogram parameter detection module, otherwise, starting the preset feedback signal, adjusting the intensity of the preset feedback signal according to the current electroencephalogram preset parameter value, and returning to the electroencephalogram parameter detection module.
The brain wave gamma wave parameter or the associated parameter is adopted to guide the intelligence training, the key index of the change of the brain wave gamma wave parameter or the associated parameter is fed back to a user (a trainee or a coach) in an easily-perceived form during the training, the user is helped to select a physical and mental intervention intelligence training mode which is most suitable for the user condition and prevents or improves the senile dementia, the walking is avoided, the wrong way is prevented from entering a wrong way, and the training skill is further improved and the training result is optimized through the brain wave gamma wave parameter or the associated parameter, so that the better intelligence training and senile dementia preventing effects are obtained. That is, the intellectual training method and the intellectual training apparatus of the present invention enable a user (trainee or coach) to easily select and grasp a physical and mental intervention intellectual training manner, method and technique suitable for the user, so as to achieve the purpose of training and improving the intellectual training of the trainee most effectively.
The intelligence training method and the intelligence training instrument can also be used for the auxiliary treatment and rehabilitation of neuropathy, and the intelligence training, the relaxing and the recovery of other people.
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FIG. 1 is a flow chart of a method of intellectual training of the present invention;
fig. 2 is a structural diagram of the intelligence training instrument of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in detail with reference to the accompanying drawings and specific embodiments.
The brain wave is spontaneous rhythmic nerve electrical activity, the frequency variation range of the brain wave is 1-30 times per second, and the brain wave can be divided into four wave bands, namely delta (1-3 Hz), theta (4-7 Hz), alpha (8-13 Hz) and beta (14-30 Hz). In addition, upon waking up and focusing on a certain event, a gamma wave with a higher frequency than beta wave is often seen, with a frequency >30Hz and an amplitude <30 μ V; while other normal brain waves with special waveforms, such as hump wave, sigma wave, lambda wave, kappa-complex wave, mu wave, etc., can appear during sleep.
Recent research shows that the electroencephalogram gamma wave of the patients with the dementia is abnormal compared with normal people or wild animals are abnormal compared with the animals with the dementia, and the abnormality is mainly manifested in that the gamma wave is weakened, namely the relative power of the electroencephalogram gamma wave (namely the ratio of the gamma wave power in the total brain wave power) of the patients with the dementia or the model animals is lower than that of the normal people or wild control animals of the same age.
Based on this, the present invention provides a method for intelligence training, as shown in fig. 1, comprising:
step 11 (S11): starting a preset gamma wave regulation mode, wherein the gamma wave regulation mode is used for regulating the electroencephalogram gamma wave characteristics of the trainee;
step 12 (S12): acquiring a current electroencephalogram preset parameter value of a trainee, wherein the electroencephalogram preset parameter is an electroencephalogram gamma wave characteristic parameter or an associated parameter of the electroencephalogram gamma wave characteristic parameter;
step 13 (S13): judging whether the current electroencephalogram preset parameter value meets the preset condition, if so, executing the step 14, and if not, returning to the step 12;
the execution main body for judging whether the current electroencephalogram preset parameter value meets the preset condition can be a trainee or a coach, or can be equipment or a program, and when a new trainee is used in the initial stage, in view of large individual difference, the gamma wave regulation mode and the feedback signal which are suitable for each person are different, the coach intervention step 13 is suggested to help the new user to find the gamma wave regulation mode and the feedback signal which are suitable for the user at the fastest. Once the user determines the appropriate gamma wave modulation pattern and feedback signals for the trainee, the execution of step 13 can be automated using "equipment or programs".
Step 14 (S14): and judging whether the preset feedback signal is started or not, if so, adjusting the intensity of the preset feedback signal according to the current electroencephalogram preset parameter value, returning to the step 12, otherwise, starting the preset feedback signal, adjusting the intensity of the preset feedback signal according to the current electroencephalogram preset parameter value, and returning to the step 12.
The electroencephalogram gamma wave characteristic parameters can be the power of electroencephalogram gamma waves, the average peak value of the electroencephalogram gamma waves or the power of the electroencephalogram gamma waves in a preset frequency band, and the like, and the correlation parameters of the electroencephalogram gamma wave characteristic parameters can be the ratio of the gamma wave to the theta wave power, the ratio of the gamma wave to the delta wave power, the ratio of the gamma wave to the alpha wave power, the ratio of the gamma wave to the beta wave power or the ratio of the gamma wave power to the total electroencephalogram power.
The preset condition is that the difference value between the current electroencephalogram preset parameter and the electroencephalogram preset parameter in a calm state is larger than a preset value, and the value of the preset value can be flexibly set according to the personal condition of each user. The preset parameters of the electroencephalogram in the calm state can be acquired before the method is implemented, for example, when a user is in the calm state, 3 times of electroencephalograms are acquired, the preset parameters are calculated from each electroencephalogram record, the average value of the preset parameters is used as the baseline value of the preset parameters of the electroencephalogram in the calm state, and then the preset value is determined according to the baseline value and the fluctuation range (error range) of the preset parameters of the electroencephalogram in the calm state.
The gamma wave modulation mode includes: qigong, taiji, sit-up or meditation, Buddhist stillness, yoga, meditation, hypnosis, self-massage, abdominal respiration, sound signals, light signals (including picture signals and video signals), smell signals, force signals, electric signals (including electric needle signals), magnetic signals and ultrasonic signals. The gamma wave modulation mode may be one of the above modes alone, or may be a combination of any two or more of the above modes.
The feedback signal includes: sound signals, light signals (including picture signals, video signals), smell signals, and/or force signals, etc. The feedback signal may be a single signal or a combination of any two or more signals.
The invention integrates the feedback of the brain wave gamma wave characteristic parameters or the associated parameters into a non-drug intelligence training method, and during training, the key index of the change of the brain wave gamma wave parameters is presented to a trainee or a caregiver in a form easy to sense so as to stimulate and guide the trainee to carry out proper gamma wave regulation mode training, and further, the training process for promoting the positive and positive change of the gamma wave is constructed by optimizing the training method and skill through the feedback of the brain wave gamma wave characteristic parameters or the associated parameters, so that the trainee is helped to obtain better intelligence training effect, and the potential patients with senile dementia or the patients with the dementia are helped to delay the intelligence deterioration and accelerate the intelligence rehabilitation.
Optionally, to further improve the efficiency of the method of fig. 1, the preset gamma wave regulation mode is verified through testing: when a user is in a preset gamma wave regulation mode, electroencephalogram preset parameters meet preset requirements; the preset feedback signal is tested and verified: the preset feedback signal does not conflict (or interfere with) the preset gamma wave adjustment mode. Namely, the preset gamma wave regulation mode and the preset feedback signal are screened and are effective to the user, and the training time of the user is prevented from being wasted by the ineffective gamma wave regulation mode and the ineffective feedback signal.
The preset requirement is set firstly to ensure that the value of the electroencephalogram preset parameter measured during training is larger than that of the electroencephalogram preset parameter in a calm state, and secondly, the preset requirement is set according to a training target of a user.
Considering the condition that the result of intelligence training is not ideal due to improper selection of a certain gamma wave regulation mode or electroencephalogram preset parameters or feedback signals, the step 13 further comprises:
and if the electroencephalogram preset parameters in the first preset time of continuous monitoring do not accord with preset conditions and replaceable electroencephalogram preset parameters exist, replacing the electroencephalogram preset parameters, and returning to the step 12.
Further, step 13 further comprises:
and if the electroencephalogram preset parameters in the second preset time are continuously monitored, the electroencephalogram preset parameters do not accord with the preset conditions, and a replaceable preset gamma wave regulation mode exists, replacing the preset gamma wave regulation mode or replacing the preset gamma wave regulation mode and the preset feedback signal, and returning to the step 11.
In the step 13, the content is added, and the execution logic is as follows: adjusting the electroencephalogram preset parameters, and then adjusting the preset gamma wave regulation mode or the preset gamma wave regulation mode and the preset feedback signal, or adjusting the preset gamma wave regulation mode or the preset gamma wave regulation mode and the preset feedback signal, and then adjusting the electroencephalogram preset parameters. Because there are some gamma wave adjustment modes and some feedback signals, there is an optimal solution so that the feedback signal can follow the gamma wave adjustment modes together.
The first preset time and the second preset time are set according to the personal condition and the expected target of the user. For example, the first preset time may be set to 30 minutes or more; the second preset time may be set to 30 minutes or more. If the first preset time is longer than the second preset time, the electroencephalogram preset parameters are adjusted firstly, and if the second preset time is longer than the first preset time, the electroencephalogram preset parameters are adjusted afterwards.
It has been found that a physical signal stimulus of a certain frequency can enhance brain waves of the same frequency, that is, gamma waves can be enhanced by a physical signal stimulus of the same frequency as gamma waves.
In order to further enhance the training effect, in the gamma wave regulation mode or the preset feedback signal, the optical signal further comprises a flickering optical signal with adjustable flickering frequency, a sound signal with adjustable binaural frequency difference, the main frequency and/or amplitude of the force signal, the electric signal (including the electric needle signal), the magnetic signal and the ultrasonic signal are adjustable, and the frequency of amplitude modulation of the ultrasonic signal is also adjustable.
The adjustable flashing signal is a flashing light signal which is superimposed (i.e. simultaneously presented) on a certain picture signal and a certain video signal and can be set or adjusted (by a user) by parameters such as intensity (illumination intensity), duration, flashing frequency, frequency range (color) and the like. The scintillation frequency adjustment range of the scintillation light signal preferably corresponds to the frequency range of gamma waves.
The binaural frequency difference of the sound signal is adjustable: the same sound signal that is synchronously fed to both ears remains at a fixed frequency difference throughout a training session, and this frequency difference is preferably set or adjusted (by the user) within the frequency range of the corresponding gamma waves.
The main frequency and/or amplitude of the force signal, the electric signal (electric needle signal), the magnetic signal and the ultrasonic signal can be adjusted, the frequency of the ultrasonic signal amplitude modulation can be adjusted, and the frequency adjusting range of the ultrasonic signal also preferably corresponds to the frequency range of the gamma wave.
As shown in fig. 2, the present invention also includes a mental training apparatus comprising:
a gamma wave adjusting module: starting a preset gamma wave regulation mode, wherein the gamma wave regulation mode is used for regulating the electroencephalogram gamma wave characteristics of the trainee;
the electroencephalogram parameter detection module: acquiring a current electroencephalogram preset parameter value of a trainee, wherein the electroencephalogram preset parameter is an electroencephalogram gamma wave characteristic parameter or an associated parameter of the electroencephalogram gamma wave characteristic parameter;
the electroencephalogram parameter judging module: judging whether the current electroencephalogram preset parameter value meets the preset condition, if so, executing a feedback signal module, and if not, returning to an electroencephalogram parameter detection module;
a feedback signal module: and judging whether the preset feedback signal is started or not, if so, adjusting the intensity of the preset feedback signal according to the current electroencephalogram preset parameter value, returning to the electroencephalogram parameter detection module, otherwise, starting the preset feedback signal, adjusting the intensity of the preset feedback signal according to the current electroencephalogram preset parameter value, and returning to the electroencephalogram parameter detection module.
Optionally, the preset gamma wave regulation mode is verified by tests: when a user is in a preset gamma wave regulation mode, electroencephalogram preset parameters meet preset requirements; the preset feedback signal is tested and verified: the preset feedback signal does not conflict with the preset gamma wave regulation mode.
Optionally, the electroencephalogram parameter judging module further includes:
if the electroencephalogram preset parameters in the first preset time of continuous monitoring do not accord with preset conditions and replaceable electroencephalogram preset parameters exist, the electroencephalogram preset parameters are replaced, and the electroencephalogram parameter detection module is returned.
Optionally, the electroencephalogram parameter judging module further includes:
and if the electroencephalogram preset parameters in the second preset time are continuously monitored, the electroencephalogram preset parameters do not accord with the preset conditions, and a replaceable preset gamma wave adjusting mode exists, the preset gamma wave adjusting mode is replaced, or the preset gamma wave adjusting mode and the preset feedback signal are replaced, and the signals are returned to the gamma wave adjusting module.
Optionally, the associated parameters of the brain wave gamma wave characteristic parameters include a ratio of gamma wave to theta wave power, a ratio of gamma wave to delta wave power, a ratio of gamma wave to alpha wave power, a ratio of gamma wave to beta wave power, or a ratio of gamma wave power to total brain wave power.
Optionally, the preset condition is that a difference value between the current electroencephalogram preset parameter and the electroencephalogram preset parameter in a calm state is larger than a preset value.
Optionally, the feedback signal comprises: a sound signal, a light signal (including a picture signal, a video signal), a scent signal, a force signal, and/or combinations thereof.
Optionally, the gamma wave modulation mode comprises: qigong, tai chi, sit-up or meditation, Buddhist stillness, yoga, meditation, hypnosis, self-massage, abdominal respiration, sound signals, light signals (including picture signals, video signals), smell signals, force signals, electrical signals (including electric needle signals), magnetic signals, ultrasonic signals and/or combinations thereof.
Optionally, in the gamma wave adjustment mode or the preset feedback signal, the optical signal further includes a flashing optical signal with adjustable flashing frequency, a sound signal with adjustable binaural frequency difference, a main frequency and/or amplitude of the force signal, the electric signal (including the electric needle signal), the magnetic signal and the ultrasonic signal is adjustable, and a frequency of the ultrasonic signal amplitude modulation is adjustable.
Before or during the training session, the trainee or trainer can select or change the appropriate EEG preset parameters related to the gamma wave parameters to "modulate" the preset feedback signal. Once the training generates positive change beneficial to the intelligence improvement of the trainee, the positive change is reflected from the electroencephalogram preset parameters, and the training instrument immediately presents feedback signals with the strength changing according to the training effect to the user. Therefore, the user can select a gamma wave regulation mode (such as a certain Qigong mode, Taiji mode, sitting and meditation mode, ideation mode, yoga mode, meditation mode, hypnosis mode, abdominal respiration mode and the like) which is most suitable for certain physical and mental intervention of the trainee under the guidance and excitation of the electroencephalogram preset parameters, is assisted by auxiliary signals (such as sound, light, electricity, magnetism, force, ultrasound and the like) of the certain gamma wave regulation mode, and searches for corresponding training skills to regulate the electroencephalogram preset parameters of the trainee so as to generate positive and positive changes and achieve the aim of intelligence training. The training instrument can also be used for the auxiliary treatment and rehabilitation of certain nerve diseases and the intelligence training, the relaxation and the recovery of other people.
It should be noted that the embodiments of the intelligence training apparatus of the present invention have the same principle as the embodiments of the intelligence training method, and the related points can be referred to each other.
Examples of applications of the intellectual training method and the intellectual training apparatus of the present invention are given below.
Application example 1
The intelligence training instrument consists of a set of wearable device and a PC. The functions of electroencephalogram amplification and analog-to-digital conversion in the electroencephalogram parameter detection module are realized by an EEG special data conversion chip, circuits such as an electroencephalogram data acquisition electrode, a protection circuit, a filter circuit and the EEG special data conversion chip in the electroencephalogram parameter detection module are assembled with a gamma wave regulation module, a feedback signal module and partial control function blocks of the electroencephalogram parameter judgment module to form a VR helmet, and the helmet is worn on the head of a trainee; the electroencephalogram data processing, electroencephalogram characteristic signal extraction and other parts in the electroencephalogram parameter judging module and the electroencephalogram parameter detecting module are combined in a PC. The helmet is connected with the PC through a cable, data exchange is achieved, the PC is further connected with the background and the cloud end through wireless data exchange, and trainees can control the training instrument through the PC. According to specific conditions, the training instrument can be controlled by a trainee through a mouse of a PC and a VR display; the trainee can also control the training instrument through the display and the mouse of the PC to guide the trainee to carry out the mental training of physical and mental intervention.
In this embodiment, the intellectual training apparatus is preset to a mode completely controlled by the trainee himself. The trainee generally adopts a sitting posture during training, and can also adopt a standing/lying posture or other postures according to the intention of the trainee.
The trainee needs to select different electroencephalogram gamma wave characteristic parameters (such as the power of gamma waves) or correlation parameters of the electroencephalogram gamma wave characteristic parameters (the combination of a certain gamma wave parameter and another certain electroencephalogram parameter, such as the ratio of the gamma wave power to the theta wave power or the ratio of the gamma wave power to the total electroencephalogram power) as electroencephalogram preset parameters according to specific conditions. In this embodiment, the trainee selects "ratio of gamma wave to theta wave power (mean value)" as the electroencephalogram preset parameter under the "electroencephalogram parameter" option of the VR display.
Before training, a trainee wears a VR helmet, turns on the helmet and a PC power supply, selects an electrode impedance test option on a VR display through a PC mouse (in the example, the trainee operates a training instrument in the mode), measures the impedance of each electroencephalogram electrode, turns to a gamma wave test option after the impedance of each electrode is lower than a specified value, records the electroencephalogram of the trainee in a certain time length (for example, two minutes), records the electroencephalogram for 3 times, and then calculates the mean value of the electroencephalogram preset parameters of the trainee in the three sampling data sections and the fluctuation range (error range) of the electroencephalogram preset parameters along with the time through an instrument, so as to obtain the baseline value of the electroencephalogram preset parameters in a calm state.
Before the wearable household intelligence training instrument is used for intelligence training, one of physical signals such as sound, light, electricity, electric acupuncture, magnetism, force, ultrasound and the like can be selected as an auxiliary signal of a gamma wave adjusting module for physical and mental intervention training according to the specific situation of a trainee, and the auxiliary signal can be selected not to be used. In this embodiment, the trainee does not have a basis of physical and mental intervention training, and by coaching of the trainer, the trainee successively tries a (default) praying method, a certain meditation method for yoga, an abdominal breathing method and other gamma wave regulation modes, takes buddhist music as a feedback signal, and takes the size of the played (pre-recorded) praying sound as a feedback signal of the electroencephalogram preset parameter. In training, the training instrument uses the feedback signal of 'the sound of Buddha' which is compared with the power (mean value) of gamma wave and theta wave as the pre-set parameters of the brain electricity of the trainee to perform 'modulation': if the ratio of the power (mean value) of the gamma wave to the power (mean value) of the theta wave increases by more than 5 times of the fluctuation range of the corresponding baseline value measured before training, the trainee hears the pre-stored praying sound from the helmet, and the size of the praying sound heard by the trainee positively correlates with the increment size of the ratio of the power (mean value) of the gamma wave to the power (mean value) of the theta wave in training. After the trainee selects the praying sound as the feedback signal, according to the requirement of the training step, the trainee selects the option of 'feedback signal experience' from the VR display before training, and experiences (audits) the condition that the size of the praying sound changes along with the correlation of the preset parameters for several times.
After training, the trainee tries to make his/her mind and body enter the state required by the training method by using the selected mind and body intervention training method (preset gamma wave regulation mode). The training instrument continuously records the electroencephalogram data of a trainee in training according to the time length of electroencephalogram measurement in a baseline measurement stage, and then calculates the magnitude of the power (mean value) ratio of gamma waves to theta waves and the difference value between the power (mean value) ratio of the gamma waves to the theta waves and the corresponding baseline value, once the difference between the power (mean value) ratio of the gamma waves to the theta waves obtained by calculating the recorded data at a certain time and the corresponding baseline value reaches or exceeds 5 times of the fluctuation range (error range) of the baseline value, the trainee can listen to the Buddha sound from the VR helmet, and the Buddha sound is increased along with the improvement of the training effect (the increment of the power (mean value) ratio of the gamma waves to the theta waves is increased). The trainee should make an effort to adjust the physical and mental state so that the heard sound is sustained and increased. The trainees should also try to remember the physical and mental intervention training method and physical and mental state adopted when listening to the praying sound and select to carry out the training at other times without the aid of a training instrument, and try to make the self body and mind in the state more often.
In training, the trainee may encounter the situation that no matter how to try to improve the training skill and no feedback signal is always obtained when a certain physical and mental intervention training method is adopted in training, that is, the user cannot feel the obvious effect of training. The user may then try to adopt another gamma wave regulation mode (in this embodiment, the trainee tries the gamma wave regulation mode of the praying method, the meditation method for yoga, the abdominal breathing method, etc. in succession), or to improve the training technique.
The selection of a gamma wave regulation mode in each training process of a trainee, the key points of training skills, the selection of electroencephalogram preset parameters, the selection of gamma wave regulation mode auxiliary signals, the selection of the types of the auxiliary signals, the types of auxiliary signal generation and presentation devices, the selection of the auxiliary signals during training, the selection of selection time, the baseline value of the trainee electroencephalogram preset parameters before training, the time length measured each time during training, the measurement result of main electroencephalogram parameters and other data can be transmitted and stored to the cloud end in a wireless and/or wired mode, and the data enter personal files of the trainee in a related medical health big database.
By comparing the difference of the feedback signals heard during the intelligence training by adopting the three gamma wave regulation modes, namely the existence and the size of the praying sound, the trainee finally selects the (silent) praying method as the intelligence training method for the physical and mental intervention of the trainee, gradually masters the training skill suitable for the trainee, gradually improves the lower electroencephalogram gamma wave power before the training and improves the learning and memory functions. Such training is increasingly becoming an integral part of the trainee's daily life.
Application example two
In this example, the trainee is an elderly person who is detected to be at high risk of future senile dementia and shows early symptoms of dementia such as significant deterioration of memory, but has a substantially normal cognitive function.
The same mental training apparatus as in example one was used. In this example, the training apparatus is preset to a mode in which the trainee's trainer is operated via a PC. During training, a trainee takes a standing posture, a coach wears the VR helmet of the wearable intelligence training instrument in the first example for the trainee, the helmet and the PC power supply are turned on, after the impedance of all the electroencephalogram electrodes is adjusted to be lower than a specified value, the option of gamma wave test is turned to, and the baseline value of each electroencephalogram parameter of the trainee is measured and calculated.
In this example, the trainer selects a certain qigong as the trainee's gamma wave regulation mode, selects the ratio of the trainee's gamma wave power to the total mean value of the electroencephalogram power as the electroencephalogram preset parameter, and selects the olfactory signal as the feedback signal. More specifically, in the example, a certain perfume flavor is selected as a feedback signal, the feedback signal, namely the perfume flavor, is 'modulated' by using the increment of the ratio of gamma wave power of a trainee to the mean value of total electroencephalogram power during training, if the ratio of the electroencephalogram gamma wave power of the trainee, namely an AD patient, to the mean value of the total electroencephalogram power is increased during training, and the increment is more than 5 times of the fluctuation range of the corresponding baseline value of the trainee, the VR helmet releases the perfume flavor to the front of the nostrils of the trainee, and a trainer also hears the name pronunciation of the perfume from the earphones of a PC. The larger the increment of the ratio of the gamma wave power to the total power mean value of the brain electricity in the training of the trainee is, the larger the perfume amount released by the helmet is, the stronger the perfume flavor is, and the larger the perfume name pronunciation heard by the trainer from the earphones of the PC is. Similarly to the first example, before the training begins, the trainee and the trainer experience the perfume smell (and the pronunciation of the perfume name heard by the trainer) along with the change of the ratio of the gamma wave power to the brain electricity total power mean value, and during the experience, the trainer should explain relevant rules to the trainee.
In this example, the trainer teaches the trainee the qigong method in advance according to the specific situation of the trainee, and during training, the trainer firstly adopts the qigong as a gamma wave regulation mode of the trainee and uses the image stimulation to present three-dimensional images of classic music of spring river, moon and night, river water and flower branches under the light of spring and night moon and moon to the trainee through a VR helmet, and the parameters such as the number of training rounds (times), the duration of each round (time) of training, the time interval between two rounds (times) of training, the time interval (for example, 10 seconds) recorded by each electroencephalogram in each round (time) of training, the recording time (for example, 2 seconds) and the like are set by the trainer. Before training, the preset electroencephalogram parameter recording data are collected and calculated to be used as an electroencephalogram baseline. In training, after electroencephalogram recording is finished each time, increment of electroencephalogram preset parameters is calculated immediately, once the increment calculated in recording at a certain time is larger than 5 times of a corresponding baseline value fluctuation range, feedback signals are respectively sent to a user, namely a trainee and a coach, namely perfume fragrance with fragrance strength positively correlated with the electroencephalogram preset parameter signal increment is released to the trainee, and perfume name pronunciation with sound size positively correlated with the electroencephalogram preset parameter signal increment of the trainee is sent to a coach earphone. In the training process, trainees can improve the work of the trainees according to whether the trainees can smell perfume, the duration of the fragrance and the strength of the fragrance under the guidance of the trainees, and enter the state required by the qigong as soon as possible, and the work of the trainees is continuously improved.
If the training effect is not ideal, besides instructing the trainee to improve the training method or adopting other gamma wave regulation modes, the trainer can also change the auxiliary signal of the gamma wave regulation mode for the trainee, for example, different images and different background music can be tried as the auxiliary signal in the qigong training. Further, it is also possible to superimpose a flare light having a flare frequency within the γ -wave frequency range on the video signal, or to present "binaural difference music" having a binaural difference of a certain value within the γ -wave frequency range to the trainee while presenting the video signal. The coach has a large space for adjusting parameters of the auxiliary image signal, for example, can try to adjust different background images, or adjust related parameters of the image signal such as brightness, hue, contrast, etc., or can try to adjust parameters such as intensity of the flickering light, width of the light pulse of the flickering light, or adjust the flickering frequency of the flickering light within the gamma wave frequency range. There is also a certain space for adjusting the background music, for example, the song of the frequency difference music can be switched, the volume and the tone color can be adjusted.
There is also a certain space for the selection of electroencephalogram preset parameters, and in this embodiment, the ratio of the trainee's gamma wave power to the average value of the total electroencephalogram power is selected as the electroencephalogram preset parameters. If the user is difficult to receive the feedback signal in the physical and mental intervention training of the trainee, the electroencephalogram preset parameter which is more sensitive than the power (mean value) of gamma waves and theta waves of the electroencephalogram of the trainee can be taken as a detection signal, and the intelligence of the trainee can be trained by retrying the method, so that the electroencephalogram preset parameter which is replaced by the trainee is enhanced. If the intelligence of the trainee is restored to a certain level after training, the less sensitive parameter of the ratio of the gamma wave power of the trainee to the total power mean value of the brain electricity can be adopted as the brain electricity preset parameter again.
As with the first example, the time and parameters of each selection, each adjustment, and each measurement made by the user when training the trainee using the intelligence trainer, and the pre-set electroencephalogram parameter measurement results before and after training are transmitted and stored to the cloud in a wireless and/or wired manner, and the data enters the personal file of the trainee in the relevant medical health big database for later use.
Application example three
In the example, the intelligence training instrument is still composed of a gamma wave adjusting module, an electroencephalogram parameter detecting module, an electroencephalogram parameter judging module and a feedback signal module. The electroencephalogram parameter detection module is used for acquiring, amplifying and processing electroencephalogram data of a trainee and extracting electroencephalogram characteristic parameters; the feedback signal module is used for generating and presenting a feedback signal to a user; the gamma wave regulating module is used for generating and presenting auxiliary alternating current stimulation to the trainee. The electroencephalogram parameter detection module consists of an electroencephalogram data acquisition electrode, a protection circuit, a filter circuit, an amplification circuit, analog-to-digital conversion, electroencephalogram data processing, electroencephalogram parameter extraction and the like, and is used for acquiring electroencephalogram gamma wave characteristic parameters of a trainee. The electroencephalogram parameter detection module is divided into an electrode cap and an electroencephalogram signal box. The electroencephalogram parameter judging module and the feedback signal module are composed of a PC and related software. The feedback signal is generated and "modulated" in the PC and presented to the user via the computer display and headphones. The gamma wave regulating module is a group of auxiliary AC feedback signal generating and presenting parts, and consists of an AC feedback signal generator and stimulating electrodes in the electrode caps.
In this example, the trainee is an elderly person who has shown a decline in clinical symptoms in the early stages of dementia, memory and cognitive abilities, and the training apparatus is operated by a hypnotic. The trainee takes a prone position during training. Before training, a hypnotic puts on an electrode cap for a trainee, installs an electroencephalogram data acquisition electrode and an alternating current stimulation electrode, switches on an instrument power supply, and sets a training instrument to be in a working mode controlled by a guardian; and then alternating current stimulation is selected as an auxiliary signal of a gamma wave regulation mode. After the impedance of all the electroencephalogram electrodes is adjusted to be lower than a specified value, the options of gamma wave test are switched to, and baseline values of electroencephalogram parameters such as the mean value of the electroencephalogram gamma wave power of the trainee are measured. In this embodiment, the hypnotizer performs physical and mental intervention on the trainee by using hypnosis (gamma wave regulation mode), selects the trainee gamma wave power as an electroencephalogram preset parameter, and selects "snore" in the auditory signal as a feedback signal. Before the training begins, the hypnotizer needs to set auxiliary (gamma wave regulation mode) alternating current stimulation parameters, such as stimulation current amplitude, frequency (adjustable in the gamma wave frequency range) and the like, and parameters such as time interval (e.g. 10 seconds) of electroencephalogram recording, recording duration (e.g. 2 seconds), interval time (e.g. 5 seconds) between two electroencephalogram recordings and the like, and then can start to perform hypnotic physical and mental intervention on the trainee, and apply auxiliary alternating current stimulation to the trainee while performing the hypnotic physical and mental intervention. 10 seconds after the start of the hypnosis intervention, the electroencephalogram of the trainee is recorded, then the power of the gamma wave of the electroencephalogram of the trainee is extracted from the electroencephalogram data, and the difference between the gamma wave power and the baseline value in the process of the hypnosis intervention, namely the increment of the gamma wave power, is calculated. Once the calculated gamma wave power increment in a certain record is more than 5 times of the gamma wave power fluctuation range in the baseline, a feedback signal, namely snore, is presented to the trainee, and the larger the gamma wave power increment is, the larger the snore is. The hypnotic can adjust the technique of hypnosis (gamma wave regulation mode) or further adjust the parameters of auxiliary alternating current stimulation according to whether the snore can be heard or not and the snore size, and if the snore is louder and can be continued, the hypnotic will strive to maintain the physical and mental intervention condition unchanged.
Similar to the first and second examples, if the adjustment of the hypnosis and auxiliary ac stimulation parameters does not achieve the perceptible effect, and the hypnotic does not receive the feedback signal, i.e. does not hear the snoring, the hypnotic can consider to change one electroencephalogram preset parameter, and use the ratio of other more sensitive electroencephalogram parameters, such as the gamma wave power and the theta wave power, as the electroencephalogram preset parameter.
Like the first and second examples, the hypnotic uses the intelligence trainer to train the trainee, and the time of each selection, each adjustment and each measurement, the related parameters and the main measurement results of the electroencephalogram parameters before and after training, which are all transmitted and stored to the cloud end in a wireless and/or wired mode, and enter the personal file of the trainee in the related medical health big database for later calling.
Application example four
In this example, the mental training apparatus is still composed of: the device comprises a gamma wave adjusting module, an electroencephalogram parameter detecting module, an electroencephalogram parameter judging module and a feedback signal module. The electroencephalogram parameter detection module is used for acquiring, amplifying and processing electroencephalogram data of a trainee and extracting electroencephalogram characteristic parameters; the feedback signal module is used for generating and presenting a feedback signal to a user; the gamma wave modulation module is used for generating and presenting magnetic stimulation to the trainee. The electroencephalogram parameter detection module consists of an electroencephalogram data acquisition electrode, a protection circuit, a filter circuit, an amplification circuit, analog-to-digital conversion, electroencephalogram data processing, electroencephalogram parameter extraction and the like, and is used for acquiring characteristic parameters of an electroencephalogram gamma wave and the like of a trainee. The electroencephalogram parameter detection module is divided into an electrode cap and an electroencephalogram signal box. The electroencephalogram parameter judging module and the feedback signal module are composed of a PC and related software. The feedback signal is generated and "modulated" in the PC and presented to the user via the computer display and headphones.
In this example, the gamma wave modulation module is a certain repetitive transcranial magnetic stimulation (rTMS) treatment device, which is composed of components such as a magnetic stimulation power supply, a magnetic stimulation coil, and a stimulation target location system. The training instrument is connected with the transcranial magnetic stimulation therapeutic instrument through respective data external interfaces and cables.
In this example, the trainee is an elderly person who has exhibited some early clinical symptoms of senile dementia, but still has some cognitive and self-control abilities. The trainer is operated by a trainer.
Before training begins, a trainer wears an electrode cap for a trainee, installs an electroencephalogram data acquisition electrode and a magnetic stimulation coil, turns on a power supply of an intelligent training instrument and a transcranial magnetic stimulation therapeutic instrument, and sets the training instrument to be in a working mode controlled by the trainer. And then abdominal respiration is selected as a gamma wave regulation mode of the trainee, repeated transcranial magnetic stimulation is selected as an auxiliary signal of the gamma wave regulation mode, the electroencephalogram gamma wave power of the trainee is used as an electroencephalogram preset parameter, and played prerecorded 'palmar sound' is used as a feedback signal. Before training, after the impedance of all the electroencephalogram electrodes is adjusted to be lower than a specified value, a gamma wave test option is switched to, and baseline values of electroencephalogram parameters such as the mean value of electroencephalogram gamma wave power of a trainee are measured. Before the training is started, relevant parameters of abdominal respiration physical and mental intervention training (gamma wave regulation mode) need to be set, such as the number of training rounds (times), the duration time of each round (time), the time interval between two rounds (time) of training and the like, and parameters of auxiliary signals, namely repeated transcranial magnetic stimulation, including stimulation intensity, stimulation target position, stimulation frequency and the like. The electroencephalogram recording mode and parameters are mainly determined according to the magnetic stimulation parameters, which are auxiliary signals of the set gamma wave adjusting mode. The electroencephalogram recording time needs to avoid the application time of magnetic stimulation so as to reduce the interference of the magnetic stimulation on the electroencephalogram signal recording. When a trainee carries out abdominal respiration training, 1 second after each round of (once) abdominal respiration physical and mental intervention training is finished, the electroencephalogram signal of the trainee is recorded, then an electroencephalogram preset parameter number of the trainee, namely an electroencephalogram gamma wave power mean value of gamma waves, is extracted from electroencephalogram data, the difference between the gamma wave power mean value after the round of (once) training and a corresponding baseline value is calculated, once the calculated gamma wave power mean value increment in certain recording is larger than 5 times of the fluctuation range of the corresponding baseline value, feedback signals are respectively presented to a user, namely the trainee and a coach, namely, palm sound is released, and the larger the gamma wave power mean value increment is, the larger the palm sound is. The trainer can assist the trainee to improve the abdominal breathing skill according to whether the palm sound and the size of the palm sound can be heard during training, and the parameter of repeated transcranial magnetic stimulation is optimized.
Similar to the first, second and third examples, if the repeated improvement of the abdominal breathing training skill and the adjustment of the repeated transcranial magnetic stimulation parameters are not effective, and the trainer and the trainee can not feel feedback signals, i.e. can not hear the palm sound, the trainer can consider changing to an electroencephalogram preset parameter, i.e. the ratio of other parameters of the trainee gamma wave, such as the gamma wave power of a more sensitive point and the theta wave power, is taken as the electroencephalogram preset parameter.
The same as the first, second and third examples, the main results of each selection, each parameter adjustment, each measurement time, parameters and electroencephalogram parameter measurement before and after training, which are made by the user when the user trains the trainee by using the training instrument, are transmitted and stored to the cloud end in a wireless and/or wired mode, and enter personal files of the trainee in the relevant medical health big database for later calling.
The present invention has been briefly described above with reference to 4 examples, but the present invention is not limited to the above examples, and various changes can be made in the specific application and application range according to the purpose, basic idea and technical principle of the present invention.
The above description is only exemplary of the present invention and should not be taken as limiting the scope of the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (8)
1. An intelligent training apparatus, characterized in that the training apparatus comprises:
a gamma wave adjusting module: starting a preset gamma wave regulation mode, wherein the gamma wave regulation mode is used for regulating the electroencephalogram gamma wave characteristics of the trainee;
the electroencephalogram parameter detection module: acquiring a current electroencephalogram preset parameter value of a trainee, wherein the electroencephalogram preset parameter is an electroencephalogram gamma wave characteristic parameter or an associated parameter of the electroencephalogram gamma wave characteristic parameter;
the electroencephalogram parameter judging module: judging whether the current electroencephalogram preset parameter value meets a preset condition, if so, executing a feedback signal module, and if not, returning to an electroencephalogram parameter detection module;
a feedback signal module: judging whether a preset feedback signal is started, if so, adjusting the intensity of the preset feedback signal according to the current electroencephalogram preset parameter value, returning to the electroencephalogram parameter detection module, and if not, starting the preset feedback signal, adjusting the intensity of the preset feedback signal according to the current electroencephalogram preset parameter value, and returning to the electroencephalogram parameter detection module;
the electroencephalogram parameter judging module further comprises:
if the electroencephalogram preset parameters in the first preset time of continuous monitoring do not meet the preset conditions and replaceable electroencephalogram preset parameters exist, replacing the electroencephalogram preset parameters and returning to the electroencephalogram parameter detection module; and if the electroencephalogram preset parameters in the second preset time are continuously monitored, the electroencephalogram preset parameters do not accord with preset conditions and a replaceable preset gamma wave regulation mode exists, the preset gamma wave regulation mode is replaced, or the preset gamma wave regulation mode and a preset feedback signal are replaced, and the signals are returned to the gamma wave regulation module.
2. The intelligence trainer of claim 1, wherein the preset gamma wave regulation pattern satisfies: when the user is in the preset gamma wave regulation mode, the electroencephalogram preset parameters meet preset requirements; the preset feedback signal satisfies: the preset feedback signal does not conflict with the preset gamma wave regulation mode.
3. The mental training apparatus of claim 1 wherein the associated parameters include a ratio of gamma to theta wave power, a ratio of gamma to delta wave power, a ratio of gamma to alpha wave power, a ratio of gamma to beta wave power, or a ratio of gamma to total brain wave power.
4. An intelligence training apparatus according to claim 1, 2 or 3 wherein the preset condition is that the difference between the current brain electrical preset parameter and the calm state brain electrical preset parameter is greater than a preset value.
5. A brain training instrument according to claim 1, 2 or 3 wherein the feedback signal comprises: a sound signal, a light signal, a scent signal, and/or a force signal; the optical signal includes a picture signal and a video signal.
6. A brain training aid according to claim 1, 2 or 3 wherein the gamma wave modulation mode comprises: qigong, tai chi, sit-up or meditation, Buddhist stillness, yoga, meditation, hypnosis, self-massage, abdominal respiration, sound signals, light signals, smell signals, force signals, electrical signals, magnetic signals and/or ultrasonic signals; the optical signal comprises a picture signal or a video signal, and the electrical signal comprises an electrical pin signal.
7. Mental training apparatus according to claim 5, wherein the light signals further comprise flashing light signals with a tunable flashing frequency, the binaural frequency difference of the sound signals is tunable, and the dominant frequency and/or amplitude of the force signals is tunable.
8. The intelligence trainer of claim 6, wherein the light signals further comprise flashing light signals with adjustable flashing frequency, the binaural frequency difference of the sound signals is adjustable, the main frequencies and/or amplitudes of the force signals, the electrical signals, the magnetic signals and the ultrasonic signals are adjustable, and the frequency of the amplitude modulation of the ultrasonic signals is adjustable.
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