CN108399004B - Brain wave analysis method and related product - Google Patents
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Abstract
The application provides a brain wave analysis method and a related product, wherein the method is applied to an electronic device and comprises the following steps: transmitting preset information, acquiring first electroencephalogram data, analyzing the first electroencephalogram data to obtain a first result, and generating a control command corresponding to the first result; and instructing the electronic device to execute the control command. The technical scheme provided by the application has the advantage of high user experience.
Description
Technical Field
The application relates to the technical field of terminal equipment, in particular to a brain wave analysis method and a related product.
Background
In the prior art, mobile terminals (such as mobile phones, tablet computers, etc.) have become electronic devices preferred and most frequently used by users. Along with the popularization of smart phones, the interaction between people and the smart phones is more and more diversified, such as voice, fingerprints, irises, human faces, images and the like, but the information sent by the engine brain of a human body is not related at present. Therefore, the mobile phone cannot analyze and process the brain wave data at present, so that a user cannot control the mobile phone through the brain wave, and the experience degree of the user is further influenced.
Content of application
The embodiment of the application provides a brain wave analysis method and a related product, which can be used for analyzing brain wave data, so that interaction with a user is realized, and the user experience is improved.
In a first aspect, an embodiment of the present application provides an electronic device, including: an application processor AP; the electronic device further includes: a brain wave part connected with the AP through at least one circuit;
the AP is used for controlling the electronic device to transmit preset information, controlling the brain wave component to acquire first brain wave data reflecting the preset information, and analyzing the first brain wave data to obtain a first result to generate a control command corresponding to the first result;
the AP is also used for instructing the electronic device to execute the control command.
In a second aspect, a brain wave analysis method is provided, which is applied to an electronic device, and includes the following steps:
acquiring electroencephalogram data;
transmitting preset information, acquiring first electroencephalogram data reflecting the preset information, analyzing the first electroencephalogram data to obtain a first result, and generating a control command corresponding to the first result;
and instructing the electronic device to execute the control command.
In a third aspect, an electronic device is provided, which includes: a processing unit, a brain wave component and a circuit,
the processing unit is used for controlling the electronic device to transmit preset information, controlling the brain wave component to acquire first brain wave data reflecting the preset information, and analyzing the first brain wave data to obtain a first result to generate a control command corresponding to the first result;
the processing unit is further used for instructing the electronic device to execute the control command.
In a fourth aspect, a computer-readable storage medium is provided, which stores a computer program for electronic data exchange, wherein the computer program causes a computer to perform the method provided in the second aspect.
In a fifth aspect, there is provided a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform the method provided by the second aspect.
The embodiment of the application has the following beneficial effects:
according to the technical scheme, the electroencephalogram data are acquired through the electroencephalogram component, after preset information is transmitted, the first electroencephalogram data are acquired, the first electroencephalogram data are processed to obtain the electroencephalogram response of the user to the preset information, the first electroencephalogram data are analyzed and processed to obtain a first result, and the control command corresponding to the first result is determined, so that the user can control the user through the electroencephalogram and the mobile phone, and the user experience degree is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure.
Fig. 1a is a waveform diagram of a delta wave.
Fig. 1b is a waveform diagram of a θ wave.
Fig. 1c is a waveform diagram of an α -wave.
Fig. 1d is a waveform diagram of a beta wave.
Fig. 2 is a schematic view of an electronic device disclosed in an embodiment of the present application.
Fig. 3 is a schematic flow chart of an analysis method of brain wave data according to an embodiment of the present application.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Fig. 5 is a schematic structural diagram of a mobile phone disclosed in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all, embodiments of the present application. 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 application.
The terms "first," "second," "third," and "fourth," etc. in the description and claims of this application and in the accompanying drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The electronic device in the present application may include a smart Phone (e.g., an Android Phone, an iOS Phone, a Windows Phone, etc.), a tablet computer, a palm computer, a notebook computer, a Mobile Internet device (MID, Mobile Internet Devices), or a wearable device, and the electronic Devices are merely examples, but not exhaustive, and include but are not limited to the electronic Devices, and for convenience of description, the electronic Devices are referred to as User Equipment (UE) in the following embodiments. Of course, in practical applications, the user equipment is not limited to the above presentation form, and may also include: intelligent vehicle-mounted terminal, computer equipment and the like.
In the electronic device provided in the first aspect, the AP is specifically configured to control the brain wave section to acquire the first brain wave data after a start time of transmitting the preset information, an end time of transmitting the preset information, or an average time of transmitting the preset information.
In the electronic device provided in the first aspect, the AP is further configured to control the brain wave component to obtain second brain wave data before transmitting preset information, compare the second brain wave data with the first brain wave data to obtain a comparison result, and determine the control command according to the comparison result.
In the electronic device provided in the first aspect, the AP is specifically configured to analyze the first electroencephalogram data to determine whether there is a β wave, for example, a β wave, and determine that the first result is to respond to the preset information and generate a control command corresponding to the preset information.
In the electronic device provided in the first aspect, the AP is specifically configured to analyze the second electroencephalogram data to determine whether the second electroencephalogram data has a beta wave, analyze the first electroencephalogram data to determine whether the first electroencephalogram data has a beta wave, and if the second electroencephalogram data does not have a beta wave and the first electroencephalogram data has a beta wave, determine a comparison result as a response to the preset information, and generate a control command corresponding to the preset information.
In the electronic device provided in the first aspect, the AP is further configured to analyze the second electroencephalogram data to determine whether the second electroencephalogram data has a beta wave, analyze the first electroencephalogram data to determine whether the first electroencephalogram data has a beta wave, and if the second electroencephalogram data does not have a beta wave and the first electroencephalogram data does not have a beta wave, determine that the comparison result does not respond to the preset information, and not generate a control command.
In a method provided in a second aspect, the acquiring first brain wave data includes:
and acquiring the first electroencephalogram data after the starting time of transmitting the preset information, the ending time of transmitting the preset information or the average time of transmitting the preset information.
In a second aspect, before transmitting a preset message, the method further includes:
and acquiring second electroencephalogram data, comparing the second electroencephalogram data with the first electroencephalogram data to obtain a comparison result, and determining the control command according to the comparison result.
In the method provided in the second aspect, the comparing the second electroencephalogram data with the first electroencephalogram data to obtain a comparison result, and determining the control command according to the comparison result includes:
and analyzing the second electroencephalogram data to determine whether the second electroencephalogram data has beta waves, analyzing the first electroencephalogram data to determine whether the first electroencephalogram data has the beta waves, and if the second electroencephalogram data does not have the beta waves and the first electroencephalogram data has the beta waves, determining a comparison result as a response to the preset information, and generating a control command corresponding to the preset information.
Referring to fig. 1, fig. 1 is a schematic view of an electronic device according to an embodiment of the present disclosure, fig. 1 is a schematic view of an electronic device 100 according to an embodiment of the present disclosure, where the electronic device 100 includes: the brain wave touch screen comprises a shell 110, a circuit board 120, a battery 130, a cover plate 140, a touch control display screen 150 and a brain wave part 170, wherein the circuit board 120, the battery 130 and the cover plate 140 are arranged on the shell 110, and a circuit connected with the touch control display screen 150 is further arranged on the circuit board 120; the circuit board 120 may further include: the application processor AP190, the brain wave section 170. The above-mentioned brain wave part 170 may be different devices according to different apparatuses for collecting brain waves, for example, if brain waves are collected by electronic devices, the brain wave part 170 may be a brain wave sensor or a brain wave collector. The brain wave part 170 may be a brain wave transceiver if brain waves are collected through peripheral devices. Of course, in practical applications, other brain wave devices may be used, and the embodiments of the present invention are not limited to the specific expression of the brain wave components.
The touch Display screen may be a Thin Film Transistor-Liquid Crystal Display (TFT-LCD), a Light Emitting Diode (LED) Display screen, an Organic Light Emitting Diode (OLED) Display screen, or the like.
Different neural activity produces different brain wave patterns and thus presents different brain states. Different brain wave patterns emit brain waves with different amplitudes and frequencies, and besides the brain waves, contraction of muscles also generates different patterns of fluctuation, which is called electromyography. The intelligent device can detect muscle movement such as blinking and the like, so that electric waves generated by the muscles can be filtered out when electroencephalogram is measured.
Brain wave (Brain wave) is data obtained by recording Brain activity using electrophysiological indicators, and is formed by summing the postsynaptic potentials generated synchronously by a large number of neurons during Brain activity. It records the electrical wave changes during brain activity, which is a general reflection of the electrophysiological activity of brain neurons on the surface of the cerebral cortex or scalp.
The brain waves are spontaneous rhythmic nerve electrical activities with frequency ranging from 1 to 30 times per second, and are generally divided into four bands by frequency, namely, delta (1-3 Hz), theta (4-7 Hz), alpha (8-13 Hz), and beta (14-30 Hz). In addition, when a certain event is focused, a gamma wave with a frequency higher than that of a beta wave is often seen, the frequency is 30-80 Hz, and the amplitude range is indefinite; other normal brain waves with special waveforms, such as hump wave, sigma wave, lambda wave, kappa-complex wave, mu wave, etc., can also appear during sleep.
FIG. 1a shows a waveform of a delta wave, with a frequency of 1 to 3Hz and an amplitude of 20 to 200 μ V. This band is recorded in the temporal and apical lobes when a person is immature during infancy or mental development, and an adult is under extreme fatigue, lethargy or anesthesia.
FIG. 1b shows a waveform of a θ wave, with a frequency of 4 to 7Hz and an amplitude of 5 to 20 μ V. This wave is extremely pronounced in adults who are willing to suffer from frustration or depression, as well as in psychiatric patients.
FIG. 1c shows the waveform of the alpha wave, with a frequency of 8 to 13Hz (average 10Hz) and an amplitude of 20 to 100 μ V. It is the basic rhythm of the normal human brain waves, whose frequency is fairly constant if there is no applied stimulus. This rhythm is most pronounced when a person is awake, quiet, and closed, and the alpha wave disappears immediately when the eyes are opened (subject to light stimulation) or subject to other stimulation.
FIG. 1d shows a waveform of beta wave, with a frequency of 14 to 30Hz and an amplitude of 100 to 150 μ V. This wave occurs when mental stress and emotional agitation or excitement, and when a person wakes up from shocking sleep, the original slow wave rhythm is immediately replaced by the rhythm.
Referring to fig. 2, fig. 2 is an electronic device provided in the present application, and as shown in fig. 2, the electronic device may include: a touch display screen, an application processor AP202, a brain wave component 203; the touch display screen and brain wave component 203 is connected with the AP202 through at least one circuit 204; optionally, other sensors may be disposed within the electronic device, including but not limited to: cameras, gravity sensors, distance sensors, speakers, etc.
The AP202 is used for controlling the electronic device to transmit preset information, controlling the brain wave component to acquire brain wave data, analyzing the brain wave data to obtain a first result, and generating a control command corresponding to the first result;
AP202, further configured to instruct the electronic device to execute the control command. A brain wave section 203 for acquiring brain wave data;
the AP202 is configured to control the electronic apparatus to transmit a preset message;
the preset information includes but is not limited to: picture information, numeric strings, voice information, video information, and the like, or any combination thereof.
The AP202 is configured to divide the brain wave data into first brain wave data and second brain wave data according to the time of the preset information, analyze the first brain wave data and the second brain wave data to obtain a first result, and generate a control command corresponding to the first result;
the first brain wave data may be brain wave data before a time when a preset information is transmitted, and the second brain wave data may be brain wave data after the time when a preset information is transmitted. The time of the preset information may be specifically a starting time of transmitting the preset information, certainly may also be an ending time of transmitting the preset information, certainly may also be an average time of transmitting the preset information, and the average time may be an average value of the starting time and the ending time.
AP202, further configured to instruct the electronic device to execute the control command.
The control commands include, but are not limited to: unlock commands, payment commands, photograph commands, interaction commands, screen capture commands, mute commands, flight mode, and the like.
According to the technical scheme, the brain wave data is acquired through the brain wave component, after the preset information is transmitted, the brain wave data is split into two parts, the two parts are processed to obtain the brain wave reaction of the user to the preset information, the two parts are analyzed and processed to obtain a first result, and therefore the control command corresponding to the first result is determined, the user can control the mobile phone through the brain waves, and the user experience is improved.
The AP202 is specifically configured to analyze the first electroencephalogram data to determine whether the first electroencephalogram data has a beta wave, analyze the second electroencephalogram data to determine whether the second electroencephalogram data has a beta wave, and if the first electroencephalogram data has no beta wave and the second electroencephalogram data has a beta wave, determine that the first result is a response to the preset information, and generate a control command corresponding to the preset information.
Specifically, if the preset information is a voice "turn on the flashlight", the control command corresponding to the preset information generated by the preset information may be a "flashlight turn-on command"; if the preset information is voice 'turn on navigation', the control command corresponding to the preset information generated by the preset information can be 'start first navigation'. Of course, the preset information may also be other types of information, and if the preset information is a numeric string, the generated control command corresponding to the preset information may be "password setting" or "encryption processing".
It should be noted that the control command corresponding to the preset information may also be set for a user, for example, the user sets the control command corresponding to different types of preset information in advance, for example, the setting of the type of the numeric string corresponds to encryption processing, the setting of the picture information as a sharing command (which may implement sharing of the picture information in a sharing application), and so on.
The above setting is based on the principle that, for the waveform analysis of the brain waves, the applicant analyzes the brain waves in combination with the medical institution and actually compares the information, and finds that the fluctuation frequency of the brain waves has a direct relationship with whether the user pays attention to the information, and the direct representation thereof can be specifically, whether the user has beta waves, through experimental findings, when the user hears the information concerned by the user, the brain waves have a relatively large response, for example, when the user watches a relatively favorite picture, the frequency of the brain waves increases, otherwise, if the user does not pay attention to some information, the frequency of the brain waves and the frequency of the brain waves do not change obviously before receiving the information, according to the finding, the applicant considers that when setting a specific scene, the user can determine whether the user responds to the preset information according to the response of the brain waves by transmitting the preset information, the specific scheme includes that the brain wave data is divided into 2 parts, one part is before preset information is played, the other part is after the preset information is played, if the first brain wave data has no beta wave, it is indicated that a user has no information of special interest before the preset information is transmitted, and if the second brain wave data acquired after the preset information is transmitted has the beta wave, it is indicated that the user has the special interest to the preset information, only the preset information needs to be analyzed, a control command corresponding to the preset information can be generated, if the preset information is voice information, the voice information can be recognized through a natural language recognition algorithm, the meaning of the voice information is obtained, and then the control command corresponding to the meaning is generated.
Specifically, the above scenario may be used in cooperation with a plurality of sensors, for example, the scenario may be used in cooperation with an ambient light sensor, for example, when the ambient light sensor detects that the current light is lower than the set light intensity, a voice message "whether to turn on the flashlight" may be played, and if it is determined that the user responds to the voice message through the electroencephalogram data, a command to turn on the flashlight is generated. The navigation method can be implemented by other sensors, for example, if the detection speed of the mobile phone exceeds a set threshold, a voice message "turn on navigation" can be played, and if the user is determined to respond to the voice message through brain wave data, a navigation application program is turned on. The technical scheme can realize the control and interaction of the user on the terminal according to the brain wave data, and improve the experience of the user.
The AP202 is further specifically configured to analyze the first electroencephalogram data to determine whether the first electroencephalogram data has a beta wave, analyze the second electroencephalogram data to determine whether the second electroencephalogram data has a beta wave, and if the first electroencephalogram data does not have a beta wave and the second electroencephalogram data does not have a beta wave, determine that the first result is not to respond to the preset information and not to generate a control command.
The AP202 is specifically configured to analyze the first electroencephalogram data to determine whether the first electroencephalogram data has a beta wave, analyze the second electroencephalogram data to determine whether the second electroencephalogram data has a beta wave, if the first electroencephalogram data has a beta 0 wave and the second electroencephalogram data has a beta 1 wave, extract a first beta wave corresponding to the first electroencephalogram data and a second beta wave of the second electroencephalogram data, perform fast fourier transform on the first beta wave and the second beta wave to obtain first beta wave frequency domain data and second beta wave frequency domain data, and extract a maximum beta 1 intensity value of the first beta wave frequency domain datamax(ii) a Extracting the maximum intensity value beta 2 of the second beta wave frequency domain datamax(ii) a Such as beta 2max＞β1maxAnd determining that the first result is a control command corresponding to the preset information in response to the preset information.
Alternatively, the maximum intensity value may be a voltage value of brain waves.
The principle of the technical scheme is that when the two pieces of electroencephalogram data have beta waves, if the voltage value of the beta wave of the second electroencephalogram data is larger than that of the beta wave of the first electroencephalogram data, attention of a user to the preset information can be obtained, namely the preset information is responded.
Referring to fig. 3, fig. 3 provides a brain wave analysis method applied to an electronic device, which may adopt the structure of the electronic device shown in fig. 2 or fig. 1. The method comprises the following steps:
s301, acquiring electroencephalogram data;
step S302, transmitting preset information, acquiring electroencephalogram data, analyzing the electroencephalogram data to determine a first result, generating a control command corresponding to the first result, and instructing the electronic device to execute the control command.
Specifically, the method may further include, before step S302:
dividing the brain wave data into first brain wave data and second brain wave data according to the time of the preset information, analyzing the first brain wave data and the second brain wave data to obtain a first result, and generating a control command corresponding to the first result;
the preset information includes but is not limited to: picture information, numeric strings, voice information, video information, and the like, or any combination thereof.
The first brain wave data may be brain wave data before a time when a preset information is transmitted, and the second brain wave data may be brain wave data after the time when a preset information is transmitted. The time of the preset information may be specifically a starting time of transmitting the preset information, certainly may also be an ending time of transmitting the preset information, certainly may also be an average time of transmitting the preset information, and the average time may be an average value of the starting time and the ending time.
Step S303, instructing the electronic apparatus to execute the control command.
According to the technical scheme, the brain wave data is acquired through the brain wave component, after the preset information is transmitted, the brain wave data is split into two parts, the two parts are processed to obtain the brain wave reaction of the user to the preset information, the two parts are analyzed and processed to obtain a first result, and therefore the control command corresponding to the first result is determined, the user can control the mobile phone through the brain waves, and the user experience is improved.
Optionally, analyzing the first electroencephalogram data and the second electroencephalogram data to obtain a first result, and generating a control command corresponding to the first result, including:
and analyzing the first electroencephalogram data to determine whether the first electroencephalogram data has beta waves, analyzing the second electroencephalogram data to determine whether the second electroencephalogram data has beta waves, and if the first electroencephalogram data does not have beta waves and the second electroencephalogram data has beta waves, determining a first result as responding to the preset information and generating a control command corresponding to the preset information.
Optionally, the analyzing the first electroencephalogram data and the second electroencephalogram data to obtain a first result, and generating a control command corresponding to the first result includes:
and analyzing the first electroencephalogram data to determine whether the first electroencephalogram data has beta waves, analyzing the second electroencephalogram data to determine whether the second electroencephalogram data has beta waves, and if the first electroencephalogram data does not have beta waves and the second electroencephalogram data does not have beta waves, determining that the first result does not respond to the preset information and does not generate a control command.
Optionally, the analyzing the first electroencephalogram data and the second electroencephalogram data to obtain a first result, and generating a control command corresponding to the first result includes:
analyzing the first brain wave data to determine whether the first brain wave data has beta waves, analyzing the second brain wave data to determine whether the second brain wave data has beta waves, if the first brain wave data has beta 0 waves and the second brain wave data has beta 1 waves, extracting first beta waves corresponding to the first brain wave data and second beta waves of the second brain wave data, respectively performing fast Fourier transform on the first beta waves and the second beta waves to obtain first beta wave frequency domain data and second beta wave frequency domain data, and extracting the maximum intensity value beta 1 of the first beta wave frequency domain datamax(ii) a Extracting the maximum intensity value beta 2 of the second beta wave frequency domain datamax(ii) a Such as beta 2max＞β1maxAnd determining that the first result is a control command corresponding to the preset information in response to the preset information.
Referring to fig. 4, fig. 4 provides an electronic device, which includes: a processing unit 401, a touch display screen 402, a brain wave component 403, and a circuit,
the processing unit 401 is configured to control the electronic apparatus to transmit preset information, control a plurality of brain wave components to obtain first brain wave data, analyze the first brain wave data to obtain a first result, and generate a control command corresponding to the first result;
the processing unit 401 is further configured to instruct the electronic apparatus to execute the control command.
Optionally, the processing unit 401 is specifically configured to analyze the second electroencephalogram data to determine whether the second electroencephalogram data has a beta wave, analyze the first electroencephalogram data to determine whether the first electroencephalogram data has a beta wave, and if the second electroencephalogram data does not have a beta wave and the first electroencephalogram data has a beta wave, determine a comparison result as a response to the preset information, and generate a control command corresponding to the preset information.
Optionally, the processing unit 401 is further configured to analyze the second electroencephalogram data to determine whether the second electroencephalogram data has a beta wave, analyze the first electroencephalogram data to determine whether the first electroencephalogram data has a beta wave, and if the second electroencephalogram data does not have a beta wave and the first electroencephalogram data does not have a beta wave, determine that the comparison result does not respond to the preset information, and not generate a control command.
Fig. 5 is a block diagram illustrating a partial structure of a mobile phone related to a mobile terminal provided in an embodiment of the present application. Referring to fig. 5, the handset includes: a Radio Frequency (RF) circuit 910, a memory 920, an input unit 930, a sensor 950, an audio circuit 960, a Wireless Fidelity (WiFi) module 970, an application processor AP980, and a power supply 990, a brain wave unit 999, and the like. Those skilled in the art will appreciate that the handset configuration shown in fig. 5 is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
The following describes each component of the mobile phone in detail with reference to fig. 5:
the input unit 930 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the cellular phone. Specifically, the input unit 930 may include a touch display screen 933, a fingerprint recognition apparatus 931, a face recognition apparatus 936, an iris recognition apparatus 937, and other input devices 932. The input unit 930 may also include other input devices 932. In particular, other input devices 932 may include, but are not limited to, one or more of physical keys, function keys (e.g., volume control keys, switch keys, etc.), a trackball, a mouse, a joystick, and the like. Wherein the content of the first and second substances,
the brain wave component 999 is used for acquiring brain wave data and transmitting the brain wave data to the AP 980.
The AP980 is used for controlling the electronic device to transmit preset information, dividing the brain wave data into first brain wave data and second brain wave data according to the time of the preset information, analyzing the first brain wave data and the second brain wave data to obtain a first result, and generating a control command corresponding to the first result; and instructing the electronic device to execute the control command.
Optionally, the AP980 is specifically configured to analyze the first electroencephalogram data to determine whether the first electroencephalogram data has a beta wave, analyze the second electroencephalogram data to determine whether the second electroencephalogram data has a beta wave, and if the first electroencephalogram data has no beta wave and the second electroencephalogram data has a beta wave, determine that the first result is a response to the preset information, and generate a control command corresponding to the preset information.
Optionally, the AP980 is further configured to analyze the first electroencephalogram data to determine whether the first electroencephalogram data has a beta wave, analyze the second electroencephalogram data to determine whether the second electroencephalogram data has a beta wave, and if the first electroencephalogram data does not have a beta wave and the second electroencephalogram data does not have a beta wave, determine that the first result does not respond to the preset information and does not generate a control command.
Optionally, the AP980 is further configured to analyze the first electroencephalogram data to determine whether the first electroencephalogram data has a beta wave, analyze the second electroencephalogram data to determine whether the second electroencephalogram data has a beta wave, if the first electroencephalogram data has a beta wave and the second electroencephalogram data has a beta wave, extract a first beta wave corresponding to the first electroencephalogram data and a second beta wave corresponding to the second electroencephalogram data, and perform fast fourier transform on the first beta wave and the second beta wave to obtain the first beta waveExtracting the maximum intensity value beta 1 of the first beta wave frequency domain data from the frequency domain data and the second beta wave frequency domain datamax(ii) a Extracting the maximum intensity value beta 2 of the second beta wave frequency domain datamax(ii) a Such as beta 2max＞β1maxAnd determining that the first result is a control command corresponding to the preset information in response to the preset information.
The AP980 is a control center of the mobile phone, connects various parts of the entire mobile phone by using various interfaces and lines, and performs various functions and processes of the mobile phone by operating or executing software programs and/or modules stored in the memory 920 and calling data stored in the memory 920, thereby integrally monitoring the mobile phone. Optionally, AP980 may include one or more processing units; alternatively, the AP980 may integrate an application processor that handles primarily the operating system, user interface, and applications, etc., and a modem processor that handles primarily wireless communications. It will be appreciated that the modem processor described above may not be integrated into the AP 980.
Further, the memory 920 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.
The handset may also include at least one sensor 950, such as a light sensor, motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor may adjust the brightness of the touch display screen according to the brightness of ambient light, and the proximity sensor may turn off the touch display screen and/or the backlight when the mobile phone moves to the ear. As one of the motion sensors, the accelerometer sensor can detect the magnitude of acceleration in each direction (generally, three axes), can detect the magnitude and direction of gravity when stationary, and can be used for applications of recognizing the posture of a mobile phone (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer and tapping), and the like; as for other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which can be configured on the mobile phone, further description is omitted here.
WiFi belongs to short-distance wireless transmission technology, and the mobile phone can help a user to receive and send e-mails, browse webpages, access streaming media and the like through the WiFi module 970, and provides wireless broadband Internet access for the user. Although fig. 5 shows the WiFi module 970, it is understood that it does not belong to the essential constitution of the handset, and can be omitted entirely as needed within the scope of not changing the essence of the application.
The handset also includes a power supply 990 (e.g., a battery) for supplying power to various components, and optionally, the power supply may be logically connected to the AP980 via a power management system, so that functions of managing charging, discharging, and power consumption are implemented via the power management system.
Although not shown, the mobile phone may further include a camera, a bluetooth module, a light supplement device, a light sensor, and the like, which are not described herein again.
It can be seen that, through this application embodiment, after the acceleration data is gathered, the state of electron device is confirmed according to the acceleration data, when confirming for falling the state, gather the first picture on ground through the camera, then obtain the distance on electron device's ground according to acceleration value and acquisition time, extract electron device's second picture (specifically can be the appearance picture), just so can generate and have electron device fall the 3D animation on ground, improved user's experience degree.
Embodiments also provide a computer storage medium storing a computer program for electronic data exchange, the computer program causing a computer to execute a part or all of the steps of any one of the brain wave analysis methods as set forth in the above method embodiments.
Embodiments of the present application also provide a computer program product including a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any one of the brain wave analysis methods as set forth in the above method embodiments.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are exemplary embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may be implemented in the form of a software program module.
The integrated units, if implemented in the form of software program modules and sold or used as stand-alone products, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (9)
1. An electronic device, the electronic device comprising: an application processor AP; characterized in that, the electronic device further comprises: a brain wave part connected with the AP through at least one circuit;
the AP is used for controlling the electronic device to transmit preset information, controlling the brain wave component to acquire first brain wave data reflecting the preset information, analyzing the first brain wave data to obtain a first result, and generating a control command corresponding to the first result, wherein the preset information comprises one or any combination of picture information, a digital string, voice information and video information;
the AP is further used for controlling the brain wave component to acquire second brain wave data before transmitting preset information, comparing the second brain wave data with the first brain wave data to obtain a comparison result, and determining the control command according to the comparison result, wherein the first brain wave data and the second brain wave data are brain wave data of the same user;
the AP is specifically configured to analyze the second electroencephalogram data to determine whether the second electroencephalogram data has a beta wave, analyze the first electroencephalogram data to determine whether the first electroencephalogram data has a beta wave, if the second electroencephalogram data has a beta wave and the first electroencephalogram data has a beta wave, extract a first maximum intensity value in first beta-wave frequency domain data based on the first electroencephalogram data, and extract a second maximum intensity value in second beta-wave frequency domain data based on the second electroencephalogram data;
when the first maximum intensity value is larger than the second maximum intensity value, determining a comparison result as a response to the preset information, and generating a control command corresponding to the preset information;
the AP is also used for instructing the electronic device to execute the control command.
2. The electronic device of claim 1,
the AP is specifically configured to control the brain wave component to acquire first brain wave data after a start time of transmitting the preset information, an end time of transmitting the preset information, or an average time of transmitting the preset information.
3. The electronic device of claim 1,
the AP is specifically configured to analyze the second electroencephalogram data to determine whether the second electroencephalogram data has a beta wave, analyze the first electroencephalogram data to determine whether the first electroencephalogram data has a beta wave, and if the second electroencephalogram data does not have a beta wave and the first electroencephalogram data has a beta wave, determine a comparison result as a response to the preset information, and generate a control command corresponding to the preset information.
4. The electronic device of claim 1,
the AP is further used for analyzing the second electroencephalogram data to determine whether the second electroencephalogram data has beta waves, analyzing the first electroencephalogram data to determine whether the first electroencephalogram data has beta waves, and if the second electroencephalogram data does not have beta waves and the first electroencephalogram data does not have beta waves, determining that the comparison result does not respond to the preset information and does not generate a control command.
5. A brain wave analysis method is applied to an electronic device, and comprises the following steps:
transmitting preset information, acquiring first electroencephalogram data reflecting the preset information, analyzing the first electroencephalogram data to obtain a first result, and generating a control command corresponding to the first result; before transmitting a preset message, the method further comprises:
acquiring second electroencephalogram data, comparing the second electroencephalogram data with the first electroencephalogram data to obtain a comparison result, and determining the control command according to the comparison result, wherein the first electroencephalogram data and the second electroencephalogram data are electroencephalogram data of the same user, and the method comprises the following steps of: analyzing the second brain wave data to determine whether the second brain wave data has beta waves, analyzing the first brain wave data to determine whether the first brain wave data has beta waves, if the second brain wave data has beta waves and the first brain wave data has beta waves, extracting a first maximum intensity value in first beta wave frequency domain data based on the first brain wave data, and extracting a second maximum intensity value in second beta wave frequency domain data based on the second brain wave data;
when the first maximum intensity value is larger than the second maximum intensity value, determining a comparison result as a response to the preset information, and generating a control command corresponding to the preset information;
and instructing the electronic device to execute the control command.
6. The method of claim 5, wherein the acquiring first brain wave data comprises:
and acquiring the first electroencephalogram data after the starting time of transmitting the preset information, the ending time of transmitting the preset information or the average time of transmitting the preset information.
7. The method of claim 5, wherein comparing the second electroencephalogram data with the first electroencephalogram data to obtain a comparison result, and determining the control command according to the comparison result comprises:
and analyzing the second electroencephalogram data to determine whether the second electroencephalogram data has beta waves, analyzing the first electroencephalogram data to determine whether the first electroencephalogram data has the beta waves, and if the second electroencephalogram data does not have the beta waves and the first electroencephalogram data has the beta waves, determining a comparison result as a response to the preset information, and generating a control command corresponding to the preset information.
8. An electronic device, the electronic device comprising: a processing unit, a brain wave component, and a circuit,
the processing unit is used for controlling the electronic device to transmit preset information, controlling the brain wave component to acquire first brain wave data reflecting the preset information, and analyzing the first brain wave data to obtain a first result to generate a control command corresponding to the first result; the processing unit is further configured to control the brain wave component to obtain second brain wave data before transmitting preset information, compare the second brain wave data with the first brain wave data to obtain a comparison result, and determine the control command according to the comparison result, where the first brain wave data and the second brain wave data are brain wave data of the same user;
the processing unit is specifically configured to analyze the second electroencephalogram data to determine whether the second electroencephalogram data has a beta wave, analyze the first electroencephalogram data to determine whether the first electroencephalogram data has a beta wave, if the second electroencephalogram data has a beta wave and the first electroencephalogram data has a beta wave, extract a first maximum intensity value in first beta-wave frequency domain data based on the first electroencephalogram data, and extract a second maximum intensity value in second beta-wave frequency domain data based on the second electroencephalogram data;
when the first maximum intensity value is larger than the second maximum intensity value, determining a comparison result as a response to the preset information, and generating a control command corresponding to the preset information;
the processing unit is further configured to instruct the electronic apparatus to execute the control command when the first maximum intensity value is greater than the second maximum intensity value.
9. A computer-readable storage medium, characterized in that it stores a computer program for electronic data exchange, wherein the computer program causes a computer to perform the method according to any one of claims 5-7.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106488024A (en) * | 2016-10-18 | 2017-03-08 | 珠海格力电器股份有限公司 | A kind of mobile terminal, mobile terminal Intelligent photographing method and system |
| CN106933247A (en) * | 2017-03-30 | 2017-07-07 | 歌尔科技有限公司 | The control method of unmanned plane, apparatus and system |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN101430600A (en) * | 2008-11-05 | 2009-05-13 | 江西蓝天学院 | Game auxiliary control method based on imagination electroencephalogram |
| CN103190902B (en) * | 2012-01-06 | 2017-08-04 | 无极技术公司 | Shown using frequency of brain wave data and interactive multimedia determining, monitor and analyzing personal response variable method and system |
| CN106339091A (en) * | 2016-08-31 | 2017-01-18 | 博睿康科技（常州）股份有限公司 | Augmented reality interaction method based on brain-computer interface wearing system |
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| CN106933247A (en) * | 2017-03-30 | 2017-07-07 | 歌尔科技有限公司 | The control method of unmanned plane, apparatus and system |
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