JP2009268826A - Device and method for modulating electroencephalogram discrimination method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To achieve high precision calibration without failure to recognize stimulation for calibration related to electroencephalogram, in a system provided with an interface which uses the electroencephalogram. <P>SOLUTION: The electroencephalogram interface system 1 comprises an interface part 100 to obtain electroencephalogram signals of a user, discriminate P3 components of visual phenomenon-related potentials included in the electroencephalogram signals after an operation menu is provided, and actuate the equipment based on the discriminated P3 components. The electroencephalogram discrimination method modulation device 10 is usable for modulation for a discrimination method of the interface part 100. The device 10 introduces characteristic quantity of the user related to the P3 components of the visual phenomenon-related potentials based on a database 13 prescribing correlation between the P3 components of the phenomenon-related potentials obtained by stimulation to modality other than visual sense and the P3 components of the visual phenomenon-related potential, and the P3 components of the phenomenon-related potentials after the stimulation is provided, and modulates the electroencephalogram discrimination method of the interface part 100 based on the characteristic quantity. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to an interface (electroencephalogram interface) system capable of operating a device using an electroencephalogram. More specifically, the present invention relates to an electroencephalogram interface system equipped with a device for measuring a user's electroencephalogram in real time and performing calibration for accurate analysis.

  In recent years, various types of information devices such as televisions, mobile phones, and PDAs (Personal Digital Assistants) have become widespread and have entered human life, so users operate information devices in many situations in their daily lives. There is a need. Usually, a user uses a hand to input an input command via an input means (interface unit) such as a button, thereby realizing operation of the device. However, for example, when both hands are blocked by tasks other than device operation, such as when doing housework, childcare or driving, it is difficult to input using the interface unit, and device operation cannot be realized. For this reason, there is an increasing need for users who want to operate information devices in all situations.

  In response to such needs, input means using a user's biological signal have been developed. For example, Non-Patent Document 1 discloses a technique for identifying an option that a user wants to select using an event-related potential of an electroencephalogram. The technique described in Non-Patent Document 1 will be described in detail. Using the P3 component of the event-related potential that appears after about 300 ms starting from the timing when the option is highlighted at random, It identifies the options that the user wants to select. With this technology, the user can specify the option he / she wants to select without using his / her hands.

  As used herein, “event-related potential” refers to a transient potential fluctuation in the brain that occurs in time relation to an external or internal event. The electroencephalogram interface unit 100 uses an event-related potential obtained by a stimulus for vision as an external event. For example, by using a so-called P3 component of the event-related potential for the visual stimulus, it is possible to perform processing such as channel switching, selection of a genre of a program desired to be viewed, and volume adjustment. The “P3 component” refers to a positive component that appears in a time period from 250 ms to 500 ms after presentation of a target stimulus, regardless of the types of sensory stimuli such as auditory sense, visual sense, and somatic sensation among event-related potentials.

  In order to apply an event-related potential to an interface, it is important to identify a target event-related potential (for example, a visual P3 component) with high accuracy. For this purpose, it is necessary to accurately measure the biological signal and to accurately identify the measured biological signal by an appropriate identification method.

  In order to accurately measure a biological signal, it is common to calibrate the measuring device and adjust the data measured by the measuring device so that it accurately represents the user's biological information. For example, Patent Document 1 discloses a technique for calibrating a measuring device before measuring a line of sight in order to accurately measure a user's line of sight and aligning a coordinate system between the measuring device and the user's line of sight. .

On the other hand, an appropriate identification method has been devised in consideration of individual differences that appear in the event-related potential components. For example, Patent Document 2 discloses a technique for improving the identification rate by changing the identification method for each user. This technology does not identify all users based on a single criterion, but creates a template for each individual in advance from the averaged waveform of event-related potentials for the situation to be examined, and uses that template to create event-related The potential component is identified. As for individual differences in event-related potentials, for example, Non-Patent Document 2 is detailed.
JP 2005-312605 A International Publication No. 05/001677 pamphlet Emanuel Donchin, two others, "The Mental Prosthesis: Assessing the Speed of a P300-Based Brain-Computer Interface", TRANSACTIONS ON REHABILITION ENG. 8. June 2000 Hiroshi Irino, “Event-related Potential Guidebook for Psychology”, Kitaoji Shobo, 2005, p. 32

  As a calibration method for accurately measuring an electroencephalogram, for example, a method of intentionally creating a situation to be identified and allowing a user to select a dummy menu when the electroencephalograph is attached can be considered. Since the electroencephalogram at the time of menu selection represents the user's biological information when the desired menu is presented, the electroencephalograph is calibrated, so measurement of the electrode mounting state, for example, the electrical resistance of the scalp, the electrode mounting site, etc. Differences in waveforms caused by variations in conditions can be adjusted.

  However, when an electroencephalogram is used for an interface, the electroencephalogram is measured over a long period of time (sometimes throughout the day), so it is assumed that the electrode mounting state such as electrode position shift due to sweating or exercise changes. Therefore, it is impossible to accurately measure a biological signal only by calibration when the electroencephalograph is attached. On the other hand, in order to measure the change in the mounting state of the electrodes, periodic calibration as described above is necessary. However, the calibration described above is troublesome for the user, and periodic calibration is performed by the user. Increase the burden.

  In addition, it is known that the component of the event-related potential changes according to the arousal level. However, in the situation where the brain wave is measured all day, it is considered that the awakening level of the user changes, for example, in the morning and at night. In particular, when the arousal level is low, the amplitude decreases and the difficulty level of the identification increases. Therefore, it is necessary to change the identification standard. Although the conventional calibration method is effective for correcting the error of the measuring device, the user condition such as the arousal level cannot be measured, and therefore the identification standard cannot be changed depending on the arousal level of the user.

  In addition, when a device is operated by an electroencephalogram interface, a visual stimulus is conventionally presented as a stimulus for calibration because a visual P3 component for a visually presented menu item is used. There is a problem that accurate calibration cannot be performed because it is not guaranteed that the user's attention is suitable for the calibration stimulus, such as when operating a television while eating.

  These are problems that were not envisaged from experiments under laboratory conditions, and were first recognized when brain waves were routinely measured and used as an interface.

  It is an object of the present invention to allow a user to overlook a calibration stimulus when performing calibration in consideration of a user state and an electrode mounting state for measuring an electroencephalogram in a system including an interface using an electroencephalogram. It is to make sure there is no. At the same time, based on the P3 component of the event-related potential with respect to the calibration stimulus, the identification method of the visual P3 component used in the electroencephalogram interface is adjusted to realize highly accurate identification.

  An apparatus for adjusting an electroencephalogram identification method according to the present invention uses an output unit that visually presents an operation menu of an apparatus, a biological signal measurement unit that obtains a user's electroencephalogram signal, and a parameter of a visual event-related potential held in advance. An electroencephalogram interface system comprising: an electroencephalogram interface unit that identifies a P3 component of a visual event-related potential included in the electroencephalogram signal after the operation menu is presented and operates the device based on the identified P3 component; It is used to adjust the interface identification method. The electroencephalogram identification method adjusting device includes a database that defines a correlation between a P3 component of an event-related potential obtained by a stimulus to a modality other than vision and a P3 component of a visual event-related potential, and the stimulus via the output unit. A stimulus presentation unit to be presented; an analysis unit for analyzing an event-related potential included in the electroencephalogram signal after the presentation of the stimulus; and P3 of a visual event-related potential based on the P3 component of the analyzed event-related potential and the database An identification method adjustment unit that derives a feature amount of the user related to a component and adjusts an electroencephalogram identification method in the electroencephalogram interface unit based on the feature amount;

  The stimulus presentation unit may present an auditory stimulus as the stimulus.

  The stimulus presentation unit may present a somatosensory stimulus as the stimulus.

  The electroencephalogram interface unit identifies the presence or absence of the P3 component of the visual event-related potential of the user based on a threshold set as the parameter, and the identification method adjustment unit determines the threshold based on the feature amount. You may adjust.

  The electroencephalogram interface unit identifies the presence / absence of the P3 component of the visual event-related potential of the user based on a waveform template of the visual event-related potential set as the parameter, and the identification method adjustment unit includes the feature The template may be adjusted based on the amount.

  The identification method adjustment unit may adjust the brain wave signal of the user based on the feature amount.

  The electroencephalogram interface unit identifies the presence or absence of the P3 component of the visual event-related potential based on a threshold value related to the amplitude of the visual event-related potential; the database defines a correlation related to the amplitude of the P3 component; The identification method adjustment unit may adjust the threshold based on the feature quantity related to amplitude.

  The database may define a correlation related to the amplitude of the P3 component, and the identification method adjustment unit may adjust the template based on the feature quantity related to the amplitude.

  The database may define a correlation related to the amplitude of the P3 component, and the identification method adjustment unit may adjust the electroencephalogram signal based on the feature quantity related to the amplitude.

  The stimulus presentation unit may present the stimulus at the start of use of the electroencephalogram interface system.

  The stimulus presentation unit may present the stimulus at a random time during a period in which the electroencephalogram interface system is used.

  A method for adjusting an electroencephalogram identification method according to the present invention includes an output unit that visually presents an operation menu of a device, a biological signal measurement unit that acquires a user's electroencephalogram signal, and a visual event-related potential held in advance. An electroencephalogram interface having an electroencephalogram interface section that identifies a P3 component of a visual event-related potential included in an electroencephalogram signal after presentation of the operation menu using the parameters of the operation menu and operates the device based on the identified P3 component In the system, it is used to adjust the identification method of the electroencephalogram interface unit. The method includes a step of preparing a database that defines a correlation between a P3 component of an event-related potential obtained by a stimulus to a modality other than vision and a P3 component of a visual event-related potential, and the stimulus via the output unit. Presenting, analyzing the event-related potential contained in the electroencephalogram signal after presentation of the stimulus, and analyzing the P3 component of the event-related potential analyzed and the P3 component of the visual event-related potential based on the database Deriving a feature amount of a user and adjusting an electroencephalogram identification method in the electroencephalogram interface unit based on the feature amount.

  According to the identification method adjusting device, the method, and the electroencephalogram interface system incorporating the identification method adjusting device of the present invention, the P3 component of the event-related potential obtained by stimulation to a modality other than vision is used. The identification method of the visual P3 component used for identification is adjusted. This eliminates the oversight of calibration stimuli, which is a problem in interfaces that constantly measure brain waves, and eliminates the effects of changes in the state of the user's individual physical condition and the wearing state of electrodes for detecting brain waves, EEG can be measured with high accuracy and the identification rate can be kept high. Therefore, since the device operation unintended by the user due to an electroencephalogram identification error is reduced, the operability improvement of the electroencephalogram interface can be realized.

  Hereinafter, embodiments of an electroencephalogram interface system according to the present invention and an identification method adjusting apparatus incorporated in the electroencephalogram interface system will be described with reference to the accompanying drawings.

  Below, an electroencephalogram interface system is demonstrated first, and the structure and operation | movement of an identification method adjustment apparatus are demonstrated after that.

  FIG. 1 shows a configuration and usage environment of an electroencephalogram interface system 1. This electroencephalogram interface system 1 is illustrated corresponding to the system configuration of Embodiment 1 described later.

  The electroencephalogram interface system 1 is a system for providing an interface for operating the TV 2 using the electroencephalogram signal of the user 5. The electroencephalogram signal of the user 5 is acquired by the biological signal measurement unit 50 worn on the head by the user and transmitted to the electroencephalogram interface unit 100 wirelessly or by wire. The electroencephalogram interface unit 100 built in the TV 2 recognizes the user's intention by using a component called event-related potential that constitutes a part of the electroencephalogram, and performs processing such as channel switching.

  FIG. 2 shows an example when the user operates the TV 2 in the electroencephalogram interface system 1 to watch a program of a genre that the user 5 wants to view.

  FIG. 2A is an example of menu items that the electroencephalogram interface unit 100 presents to the user via the screen 3 a of the TV 2. FIG. 2A shows a state in which the menu items “baseball”, “weather forecast”, “animation”, and “news” are sequentially or randomly highlighted on screens 3a-1 to 3a-4, respectively. ing. By highlighting the menu item, the event-related potential can be measured starting from the time when each menu item is highlighted. Note that menu items may be presented at points using auxiliary arrows instead of highlights or together with highlights.

  FIG. 2B schematically shows the event-related potential of the user's brain wave signal measured from the time when the menu item is highlighted. Now, assume that the user wants to see the “weather forecast”. Among the electroencephalogram signals 201 to 204 corresponding to the screens 3a-1 to 3a-4, when the user 5 looks at the screen 3a-2 on which “weather forecast” is highlighted, “weather forecast” is highlighted. A positive component characteristic of a latency of about 400 to 450 ms appears from the set time (Non-Patent Document 1).

  When the electroencephalogram interface unit 100 identifies the appearance of the visual P3 component, the menu item “weather forecast” that the user wanted to select can be selected. FIG. 2C shows the screen 3a-5 after the channel is switched to “weather forecast” as a result of identifying the visual P3 component.

  FIG. 3 shows a processing procedure of the electroencephalogram interface. In step S101, the electroencephalogram interface unit 100 presents menu items (FIG. 2A). In step S102, the electroencephalogram interface unit 100 selects one of the menu items. In step S103, the menu item selected in step S102 is highlighted.

  In step S104, the electroencephalogram interface unit 100 measures the event-related potential of the user for 500 ms, for example, starting from the time when the menu item was highlighted in step S103. Here, event-related potentials 201 to 204 of the electroencephalogram signal schematically shown in FIG. 2B are measured.

  In step S105, it is identified whether or not the visual P3 component is included in the event-related potential measured in step S104. The visual P3 component may be identified by simply thresholding the waveform, or as described in Patent Document 2, the correlation coefficient with the template created with the average addition waveform of the visual P3 component measured for each user in advance is described. It may be calculated. If Yes in step S105, the process proceeds to step S106. If No, the process returns to step S102 to select the next menu item.

  In step S106, the electroencephalogram interface unit 100 executes a process corresponding to the menu item selected in step S105. Thereby, the menu item is selected and executed, and a screen 3a-5 shown in FIG. 2C is displayed.

  According to such an electroencephalogram interface system 1, for example, even when both hands are closed due to housework or childcare, the user can operate devices such as the TV 2 without using hands. Therefore, the operability of the device is greatly improved.

  In step S105 described above, since the time and amplitude at which the visual P3 component appears in the electroencephalogram signal (event-related potential) may vary from user to user, the appearance of the visual P3 component is uniformly determined using a fixed threshold. It is inappropriate to identify. Therefore, in order to realize the processing based on the event-related potential, in the electroencephalogram interface system 1, it is necessary to adjust the operating reference according to the signal of the user 5. This operation is so-called calibration. The calibration is performed by the identification method adjusting device 10 shown in FIG.

  The identification method adjusting apparatus described in the following embodiments is a stimulus to a modality other than vision (five senses other than vision) in which a reaction always occurs with respect to an event-related potential, for example, an auditory stimulus using the speaker 3b or a vibrator. The stimulation to the somatic sensation using 3c is presented to the user 5, and the event-related potential of the electroencephalogram after the presentation is measured. The event-related potential of the electroencephalogram is transmitted to the identification method adjusting device 10 wirelessly or by wire.

  The reason for using a stimulus for a modality other than vision is to perform calibration reliably without overlooking the stimulus for calibration. This is based on the fact that the user may overlook a visual stimulus when calibration is performed only by vision.

  In Embodiments 1 and 2 to be described later, an example in which auditory stimulation is employed as a calibration stimulus will be described, and in Embodiment 3, an example in which somatosensory stimulation is employed will be described. However, the calibration stimulus to be presented is not limited to one type, and a plurality of types of stimuli may be presented at the same time. Alternatively, the stimulus type may be switched by providing an appropriate reference.

  The P3 component (for example, auditory P3 component, odor P3 component) of the event-related potential obtained by stimulation to a modality other than vision and the P3 component of the visual event-related potential have a positive correlation between amplitude and latency for each subject. It is known. In addition, some of the differences in event-related potential for each subject are derived from anatomical individual differences such as skull and brain shape, and the amplitude and latency of visual P3 component and somatosensory P3 component are also considered. There seems to be a correlation. In addition, according to the description of Kaga et al., “Event Related Potential (ERP) Manual-Focusing on P300-”, Shinohara Publishing Shinsha, 1995: pp. 255, even the same user can increase the user's arousal level. It is known that the amplitude and latency of P3 change accordingly.

  Normally, the P3 component of the event-related potential appears for a low-frequency stimulus when two types of stimuli having different frequencies are discriminated. However, as described in Kashiwagi et al., “New Physiological Psychology Vol. 2”, Kitaoji Shobo, 1997, p. 15, it is known that it also appears when one kind of stimulus of the same pitch is presented. ing.

  By utilizing the correlation between the P3 component of the event-related potential for the auditory or somatosensory stimulus and the P3 component of the visual event-related potential, the feature amount of the user 5 regarding the P3 component of the visual event-related potential can be derived. The identification method adjusting device 10 adjusts the electroencephalogram identification method in the electroencephalogram interface unit 100 based on the feature amount.

  The timing for performing calibration is when the use of the electroencephalogram interface system 1 starts, and when a predetermined time has elapsed since the start of use. Alternatively, calibration may be performed at random timing. Since the method for discriminating the electroencephalogram can be adjusted according to the user state and the wearing state of the electrode at that time, the discrimination rate of the electroencephalogram interface is improved.

(Embodiment 1)
FIG. 4 shows a functional block configuration of the electroencephalogram interface system 1 according to the present embodiment. The electroencephalogram interface system 1 includes an output unit 3, an identification method adjustment device 10, a biological signal measurement unit 50, and an electroencephalogram interface (IF) unit 100. FIG. 4 also shows detailed functional blocks of the adjusting device 10. The user 5 block is shown for convenience of explanation.

  The output unit 3 includes a screen 3a and a speaker 3b.

  In this embodiment, the auditory stimulus is presented from the speaker 3b simultaneously with the display of the menu item on the screen 3a as the calibration stimulus, and the visual at the electroencephalogram interface is displayed using the P3 component of the event-related potential with respect to the auditory stimulus for calibration. Adjust the P3 component identification method. As a result, discrimination according to the user state immediately before operating the electroencephalogram interface and the wearing state of the electrodes becomes possible, and the discrimination rate of visual P3 components used in the electroencephalogram interface is improved.

  The user 5 simply sees the menu items (options) related to the device operation presented on the screen 3 a by the electroencephalogram interface unit 100 and does not input the operation, but according to the menu item selected via the electroencephalogram interface unit 100. The equipment shall operate. In addition, display of menu items, that is, visual stimulation is not essential. The contents of the menu item may be output as audio from the speaker 3b.

  The identification method adjustment device 10 is connected to the biological signal detection unit 50 and the electroencephalogram interface unit 100 in a wired or wireless manner, and transmits and receives signals. In FIG. 4, the biological signal detection unit 50 and the electroencephalogram interface unit 100 are separate from the identification method adjustment device 10, but this is an example. A part or all of the biological signal detection unit 50 and the electroencephalogram interface unit may be provided in the identification method adjustment device 10.

  The biological signal detection unit 50 is an electroencephalograph that detects a biological signal of the user 5 and measures an electroencephalogram as a biological signal. The electroencephalograph may be a head-mounted electroencephalograph as shown in FIG. It is assumed that the user 5 is wearing an electroencephalograph in advance.

  When worn on the head of the user 5, electrodes are arranged on the biological signal measuring unit 50 so as to come into contact with a predetermined position of the head. The arrangement of the electrodes is, for example, Pz (midline parietal), A1 (earlobe), and the nasal root of the user 5. However, it is sufficient that there are at least two electrodes. For example, potential measurement is possible only with Pz and A1. This electrode position is determined from the reliability of signal measurement and the ease of mounting.

  As a result, the biological signal measuring unit 50 can measure the event-related potential of the user 5. The measured electroencephalogram of the user 5 is sampled so as to be processed by a computer, and is sent to the electroencephalogram interface unit 100 and the identification method adjustment device 10. In order to reduce the influence of noise mixed in the electroencephalogram, the electroencephalogram measured in the biological signal measurement unit 50 is subjected to a band-pass filter process of, for example, 0.05 to 20 Hz in advance, and menu items and auditory stimuli are presented. It is assumed that the baseline correction is performed with an average potential of, for example, 200 ms.

  The electroencephalogram interface unit 100 presents menu items related to device operation to the user, and cuts out and identifies the electroencephalogram measured by the biological signal measurement unit 50. The device operation is controlled according to the identification result. The basic operation in the electroencephalogram interface unit 100 is as described above.

  If the device controlled using the electroencephalogram interface unit 100 is, for example, the TV 2 shown in FIG. 1, the menu items are presented to the user 5 via the screen 3a. As shown in FIG. 2A, the menu items are highlighted one by one every predetermined time (for example, 350 ms). The predetermined interval at which the menu item is highlighted may be 200 ms, 500 ms, or 1000 ms.

  The electroencephalogram interface unit 100 cuts out the brain wave of the user 5 measured by the biological signal measurement unit 50 from the time when the menu item is highlighted, for example, 500 ms longer than the latency of the auditory P3 component and the visual P3 component. Identify the waveform. The time for cutting out the electroencephalogram may be 1000 ms. As a method for identifying the event-related potential, the waveform may be simply subjected to threshold processing, or as described in Patent Document 2, a correlation with a template created with an added average waveform of visual P3 components measured in advance for each user. A number may be calculated. The parameter for identification is adjusted by the identification method adjustment apparatus 10 by a method described later.

  Next, a detailed configuration of the identification method adjustment device 10 according to the present embodiment will be described. One of the main features of the present invention resides in the configuration and operation of the adjusting device 10.

  The identification method adjustment apparatus 10 includes a calibration stimulus presentation unit 11, a calibration electroencephalogram analysis unit 12, a modality conversion database 13, and an identification method adjustment unit 14.

  The calibration stimulus presenting unit 11 (hereinafter referred to as “stimulus presenting unit 11”) presents auditory stimuli for calibration via the speaker 3b simultaneously with the menu item presentation via the screen 3a.

  The calibration electroencephalogram analysis unit 12 (hereinafter referred to as “electroencephalogram analysis unit 12”) analyzes the event-related potential for the calibration auditory stimulus measured by the biological signal measurement unit 50.

  The modality conversion database (DB) 13 defines the correlation between the auditory P3 component and the visual P3 component. The modality conversion DB 13 only needs to be recorded and held in an arbitrary recording medium. For example, the modality conversion DB 13 is recorded in a semiconductor memory such as a hard disk, ROM, SRAM, or flash memory.

  The identification method adjustment unit 14 refers to the modality conversion DB 13 based on the result analyzed by the electroencephalogram analysis unit 12, specifically based on the P3 component of the event-related potential obtained by the auditory stimulation, and the visual event-related potential. The feature quantity of the user regarding the P3 component of is derived. Based on the feature amount, the electroencephalogram identification method in the electroencephalogram interface unit 100 is adjusted. The adjustment of the electroencephalogram identification method refers to a process of determining a parameter used for identifying the P3 component of the visual event-related potential held by the electroencephalogram interface unit 100 and sending the parameter to the electroencephalogram interface unit 100 to update the parameter.

  Hereinafter, each component of the identification method adjustment apparatus 10 is demonstrated more concretely.

  The stimulus presentation unit 11 presents the auditory stimulus for calibration to the user 5 simultaneously with the presentation of the menu item. The auditory stimulus may be a simple sound, for example, a tone burst sound of 1000 Hz, or a sound such as “pawn” that is imaged as a device operation sound. Further, the sound is not limited to one type but may be a plurality of types.

  The electroencephalogram analysis unit 12 analyzes the feature quantity using the electroencephalogram for 500 ms, for example, starting from the timing at which the stimulus presentation unit 11 presents the calibration stimulus among the electroencephalograms of the user 5 measured by the biological signal measurement unit 50. To do. The feature quantity to be analyzed is, for example, the amplitude and latency of the P3 component with respect to the auditory stimulus.

  As described above, since the event-related potential has a low S / N ratio, for example, a 2 Hz low-pass filter may be used for the event-related potential in order to analyze the amplitude and latency of the P3 component with respect to the auditory stimulus. Good.

  As a feature amount analysis section, for example, a time zone of approximately 100 ms after presentation of a stimulus, in which a P3 component with respect to an auditory stimulus generally appears, may be employed. What is necessary is just to obtain | require latency and an amplitude using the positive peak in the time slot | zone. In addition, if a large amount of noise such as electrooculogram is mixed in the electroencephalogram immediately after the auditory stimulus for calibration is presented and correct calibration cannot be performed, the identification method is adjusted using the previous calibration result. The identification method may not be adjusted.

  Next, the modality conversion DB 13 will be described. 5A and 5B show examples of the data structure of the modality conversion DB. The modality conversion DB 13 is used to convert an event-related potential (auditory event-related potential) obtained by an auditory stimulus into an event-related potential (visual event-related potential) obtained by a visual stimulus.

  The modality conversion DB 13 determines the visual P3 component identification method in the electroencephalogram interface unit 100 according to the amplitude and latency data of the P3 component with respect to the auditory stimulus obtained by the electroencephalogram analysis unit 12, such as amplitude, latency, and correction interval. Data for adjustment is saved.

  FIG. 5A shows a modality conversion DB 13 that defines conversion rules that are commonly applied to all users. According to this modality conversion DB 13, the amplitude and latency of the auditory event-related potential are 1.2 respectively in the auditory event-related potential zone (200-500 ms after stimulus presentation) specified in the “correction zone” field. Doubled and 1.5 times. A section of 200 to 500 ms after the presentation of the stimulus is a section including the P3 component of the event-related potential.

  This conversion rule is defined based on the correlation data between the P3 component for the auditory stimulus and the P3 component for the visual stimulus obtained in advance by experiments or the like. Therefore, by performing the above-described conversion, a highly reliable P3 component of the visual event-related potential can be obtained based on the auditory event-related potential. Using this P3 component, it is possible to adjust the visual P3 component identification method in the electroencephalogram interface unit 100 described later.

  On the other hand, FIG. 5B shows a modality conversion DB 13 that preliminarily measures conversion criteria for each user and defines conversion rules to be applied by switching for each user. For example, by separately inputting information for specifying a user such as a user name, the conversion rule to be applied is specified and switched. The conversion method is the same as the conversion method described with reference to FIG.

  By referring to the modality conversion DB 13, the amplitude and latency of the visual event-related potential can be obtained from the amplitude and latency of the auditory event-related potential. By specifying a section including the P3 component as the correction section, it is possible to specify the P3 component of the visual event-related potential that is the feature amount of the user.

  The discrimination method adjustment unit 14 adjusts the discrimination method of the visual P3 component from the amplitude and latency of the auditory P3 component with respect to the calibration stimulus analyzed by the electroencephalogram analysis unit 12 and the auditory P3 component stored in the modality conversion DB 13. With reference to DB, parameters for identifying event-related potentials in the electroencephalogram interface unit 100 are rewritten. Various parameters are conceivable. For example, when the electroencephalogram interface unit 100 thresholds the waveform to identify the visual P3 component, the threshold value as a parameter may be rewritten to adjust the identification method. In addition, when the visual P3 component is identified using a template created in advance using the addition average waveform of the visual P3 component, the identification method may be adjusted by rewriting the template set as a parameter. The visual P3 component template may be created in advance from the brain wave when the user has used the brain wave interface in the past, or the total addition average waveform of the visual P3 component of an unspecified number of users caused by the visual oddball task. It may be used.

  FIGS. 6A and 6B show examples of adjusting the identification method by rewriting the template. FIG. 6A shows a data group used for adjusting the identification method and a calculation formula for template adjustment. As the data group, the amplitude and latency characteristic amount of the auditory P3 component analyzed by the electroencephalogram analysis unit 12, the correlation data of the auditory P3 component and the visual P3 component stored in the modality conversion DB 13, and the previously stored visual P3 Ingredient templates are used. The adjusted template amplitude / latency is held in advance so as to be a value obtained by multiplying the characteristics of the auditory P3 component analyzed by the electroencephalogram analysis unit 12 and the correlation data stored in the modality conversion DB 13. Parameters for adjusting characteristics relating to the amplitude / latency of the template before adjustment are calculated. The adjustment parameter is, for example, a pre-adjustment template that holds in advance the division and amplitude calculated from the auditory P3 component and correlation data as shown in the template correction parameter calculation line in FIG. Divided by the amplitude and the latency). FIG. 6B shows a standard template waveform adjusted by the template correction parameter calculated according to FIG. It can be seen that the template waveform is adjusted so that the amplitude is 0.8 times and the latency is 0.98 times in the adjustment section 200-500 ms. The “waveform” here means the amplitude and latency of the template waveform.

  Further, the threshold value and the template are not changed, and the electroencephalogram interface unit 100 adjusts the electroencephalogram signal measured by the biological signal measurement unit 50 by a method such as multiplying the electroencephalogram signal based on the identification method adjustment unit 14 by a certain magnification. You may go.

  FIGS. 7A and 7B show examples of adjustment of the identification method by changing the magnification of the electroencephalogram signal. FIG. 7A shows a data group used for adjusting the identification method and a calculation formula for template adjustment. As the data group, the amplitude and latency characteristic amount of the auditory P3 component analyzed by the electroencephalogram analysis unit 12, the correlation data of the auditory P3 component and the visual P3 component stored in the modality conversion DB 13, and the electroencephalogram interface unit 100 The stored standard template amplitude and latency related features are used. Then, the biological signal measuring unit 50 divides the amplitude of the standard template and the feature value related to the latency by the value obtained by multiplying the feature value related to the amplitude and latency of the calibration auditory P3 component by the correlation data of auditory vision. A parameter for adjusting the measured electroencephalogram signal is calculated. FIG. 7B shows the waveform of the electroencephalogram signal adjusted by the electroencephalogram signal adjustment parameter calculated by FIG. 7A. It can be seen that the waveform of the electroencephalogram signal is adjusted in the adjustment section 200-500 ms. The “waveform” here means the amplitude of the electroencephalogram signal.

  With this configuration, auditory stimuli are presented when menu items are presented as calibration stimuli, and the visual P3 component identification method in the electroencephalogram interface is adjusted using the P3 component of the event-related potential for the auditory stimuli for calibration. This makes it possible to identify the electroencephalogram based on the user state immediately before using the electroencephalogram interface, thereby improving the identification rate.

  Next, an overall processing procedure performed in the electroencephalogram identification method adjustment system 1 of FIG. 3 will be described with reference to the flowchart of FIG.

  FIG. 8 shows a procedure for performing the calibration in the electroencephalogram interface system 1 and then using the electroencephalogram interface. One of the features of the processing procedure shown in FIG. 8 is a method for identifying a visual P3 component used in an electroencephalogram interface based on an auditory P3 component corresponding to an auditory stimulus by presenting an auditory stimulus for calibration simultaneously with the presentation of a menu item. The step of adjusting is provided.

  Note that steps S101 to S106 shown in FIG. 8 are the same as the processing procedure of the electroencephalogram interface shown in FIG. Therefore, description thereof will be omitted below.

  In step S10, the stimulus presentation unit 11 presents an auditory stimulus for calibration via the speaker 3b. In FIG. 8, step S10 is performed after step S101, but in reality, the electroencephalogram interface unit 100 presents the menu item on the screen 3a, and at the same time, the process of step S10 is performed to present the auditory stimulus. .

  In step S20, the biological signal measurement unit 50 measures the event-related potential of the brain wave of the user 5 for, for example, 500 ms from the time when the auditory stimulus is presented in step S10. The biological signal measurement unit 50 continuously measures the event-related potential, and the electroencephalogram analysis unit 12 cuts out the event-related potential for 500 ms starting from the time when the auditory stimulus is presented, thereby obtaining substantially the same data. May be.

  In step S30, the electroencephalogram analysis unit 12 analyzes the auditory P3 component of the event-related potential measured in step S20, and calculates the amplitude and latency of the auditory P3 component as a feature amount. When calculating the feature amount, for example, a 2 Hz low-pass filter may be applied to the event-related potential measured in step S20. Thereby, the influence of an electrooculogram and a background electroencephalogram can be reduced.

  In step S40, the discrimination method adjustment unit 14 adjusts the discrimination parameter of the visual P3 component based on the feature amount of the auditory P3 component analyzed in step S30 and the modality conversion DB 13. As described above, the modality conversion DB 13 defines the correlation between the auditory P3 component and the visual P3 component. Therefore, when the modality conversion DB 13 is referred to using the auditory P3 component as a key, it is used for electroencephalogram identification in the electroencephalogram interface unit 100. The visual P3 component is obtained.

  As to how to adjust the electroencephalogram identification method, as described with reference to FIGS. 6 and 7, the template for identifying the visual P3 component stored in the electroencephalogram interface unit 100 may be adjusted. Alternatively, the waveform of the event-related potential measured by the biological signal measuring unit 50 may be adjusted.

  When the adjustment is completed, step S102 to step S106 are executed thereafter.

  Next, the processing of steps S30 and S40 described above will be described in detail with reference to the flowcharts of FIGS.

  FIG. 9 shows a detailed procedure of the process of the electroencephalogram analysis unit 12 performed in step S30 of FIG. The electroencephalogram analysis unit 12 switches processing depending on whether or not large noise is mixed in the event-related potential after presentation of the auditory stimulus for calibration.

  That is, in FIG. 9, in step S <b> 31, the electroencephalogram analysis unit 12 calculates the maximum absolute value of the event-related potential measured by the biological signal measurement unit 50. In the next step S32, the electroencephalogram analysis unit 12 determines whether or not the value calculated in step S31 is smaller than 100 μV, which is an electrooculogram (EOG) noise mixing reference value. When the voltage is smaller than 100 μV, the process proceeds to step S33. The reason for the end of the process is that the influence of noise is considered to be very strong when the maximum absolute value of the event-related potential is 100 μV or more. In step S33, the electroencephalogram analysis unit 12 analyzes the feature quantity of the event-related potential.

  Next, FIG. 10 shows a processing procedure of the identification method adjustment unit 14 performed in step S40 of FIG.

  In step S <b> 41, the identification method adjustment unit 14 acquires the amplitude and latency as the feature amount of the auditory P3 component calculated by the electroencephalogram analysis unit 12. In step S42, the identification method adjustment unit 14 refers to, for example, amplitude, latency, and adjustment section information as correlation data between the auditory P3 component and the visual P3 component stored in the modality conversion DB 13.

  In step S43, the feature amount of the user is derived based on the information such as the amplitude, latency, and adjustment interval acquired in steps S41 and S42, and parameters for adjusting the identification criterion are calculated. The parameter can be calculated by multiplication as described with reference to FIG.

  In step S44, the identification method adjustment unit 14 transmits the identification reference adjustment parameter calculated in step S43 to the electroencephalogram interface unit 100, and instructs to update the existing parameter.

  Note that the identification method shown in FIG. 11 may be used instead of the identification method shown in FIG. FIG. 11 shows a processing procedure for adjusting an electroencephalogram signal acquired in advance in the biological signal measurement unit 50. 11, steps that perform the same processing as in FIG. 10 are given the same reference numerals, and descriptions thereof are omitted.

  In step S <b> 45, the identification method adjustment unit 14 refers to a standard identification method such as a template created from, for example, the addition average waveform for each user stored in the electroencephalogram interface unit 100. In step S46, the identification method adjustment unit 14 derives the feature amount of the user based on information such as amplitude, latency, and adjustment interval acquired in steps S41, S42, and S45, and performs identification reference adjustment. Calculate the parameters for. The parameter may be calculated by multiplication and division as described with reference to FIG.

  In step S47, the identification method adjustment unit 14 transmits the parameters for adjusting the electroencephalogram signal calculated in step S46 to the electroencephalogram interface unit 100. Then, the electroencephalogram interface unit 100 is instructed to adjust the electroencephalogram signal based on the parameter.

  By such processing, the identification method of the visual P3 component in the electroencephalogram interface is adjusted using the P3 component of the event-related potential for the auditory stimulus presented simultaneously with the menu item, and the user state immediately before operating the electroencephalogram interface and electrode mounting Identification according to the state can be realized. Therefore, the discrimination rate of the visual P3 component used in the electroencephalogram interface is improved.

  By providing the identification method adjustment apparatus 10 in the electroencephalogram interface system 1 of the present embodiment, the user state immediately before operating the electroencephalogram interface using the feature amount of the P3 component for the auditory stimulus for calibration presented simultaneously with the menu item, The visual P3 component can be identified according to the mounting state of the electrode. Since the identification rate can be improved, an easy-to-use electroencephalogram interface can be realized.

(Embodiment 2)
In the electroencephalogram interface system 1 according to the first embodiment, the electroencephalogram interface unit 100 presents menu items, and at the same time, the stimulus presentation unit 11 presents auditory stimuli for calibration. This makes it possible to adjust the identification method according to the user state immediately before using the electroencephalogram interface and the wearing state of the electrodes.

  However, as mentioned earlier, because the event-related potential has a low S / N, calibration stimulus may be presented at the same time, and if large noise such as electrooculosis is mixed, calibration may not be performed correctly. There is sex.

  In the electroencephalogram interface system according to the present embodiment, the auditory stimulation for calibration is presented not only immediately before the use of the electroencephalogram interface but also at random timing or at a predetermined timing. Then, using the feature amount of the auditory P3 component, the user state and the electrode wearing state that can be constantly changed are measured to adjust the visual P3 component identification method of the electroencephalogram interface. This makes it possible to provide an electroencephalogram interface system that maintains a high identification rate.

  FIG. 12 shows a functional block configuration of the electroencephalogram interface system 120 according to the present embodiment. FIG. 12 also shows detailed functional blocks of the identification method adjustment device 122. The user 5 block is shown for convenience of explanation.

  The electroencephalogram interface system 120 is different from the electroencephalogram interface system 1 (FIG. 4) in the configuration of the identification method adjustment device 122. More specifically, the identification method adjustment device 122 includes a calibration auditory stimulation random presentation unit 21 and a calibration having functions different from those of the stimulus presentation unit 11 and the electroencephalogram analysis unit 12 of the identification method adjustment device 10 (FIG. 4). The provision of the electroencephalogram analysis unit 22 and the addition of a storage unit 23.

  Hereinafter, the calibration stimulus random presentation unit 21 and the calibration electroencephalogram analysis unit 22 will be described. Hereinafter, they are described as “stimulus random presentation unit 21” and “electroencephalogram analysis unit 22”, respectively. Of the constituent elements of the electroencephalogram interface system 120, the same constituent elements as those in the electroencephalogram interface system 1 (FIG. 4) are designated by the same reference numerals, and the description thereof is omitted.

  The stimulus random presentation unit 21 presents the auditory stimulus for calibration to the user 5 at a random timing or a predetermined timing. The random timing may be a frequency that does not cause the user who watches the program using the TV 2 to be bothered more than necessary, and may be any time with an interval of 20 minutes or more, for example. Further, the predetermined timing may be, for example, an interval of about 10 minutes, or may be an interval of 5 minutes, 20 minutes, or 1 hour. The auditory stimulation may be the same as the example described in the first embodiment, and may be, for example, a tone burst sound of 1000 Hz or a device operation sound. It does not matter whether there is one type or multiple types.

  The electroencephalogram analysis unit 22 analyzes the feature quantity of the event-related potential of the user 5 measured by the biological signal measurement unit 50, starting from the timing when the stimulus random presentation unit 21 presents the auditory stimulus.

  The storage unit 23 is, for example, a semiconductor memory or a hard disk. The accumulating unit 23 receives and accumulates event-related potential waveforms obtained in the last n calibrations from the electroencephalogram analyzing unit 22. Note that the number of waveforms to be accumulated may be a waveform of an event-related potential obtained due to a calibration stimulus presented for 30 minutes before using the electroencephalogram interface. Note that the waveform of the event-related potential can be stored in the recording medium that holds the modality conversion DB 13 without providing the storage unit 23.

  The feature quantity of the event-related potential analyzed by the electroencephalogram analysis unit 22 is the same as that of the electroencephalogram analysis unit 12 (FIG. 4). However, the analysis method is different. The electroencephalogram analysis unit 22 determines whether or not noise is included in the event-related potential after the calibration auditory stimulus is presented. If no noise is included, the waveforms of the latest n times of event-related potentials accumulated in the accumulation unit 23 are added and averaged, and the amplitude and latency of the auditory P3 component are calculated from the added average waveform. The number of additions n may be, for example, 5 or the number of calibration stimuli presented for 30 minutes before using the electroencephalogram interface.

  By adopting the above analysis method, the amplitude and latency of the auditory P3 component can be calculated more accurately while reducing the influence of noise. As a result, the adjustment parameter of the identification method in the identification method adjustment unit 14 can be calculated more correctly, and the identification rate of the visual P3 component of the electroencephalogram interface unit 100 can be improved.

  Next, an overall processing procedure performed in the electroencephalogram interface system 120 will be described with reference to the flowchart of FIG.

  FIG. 13 shows a processing procedure of the electroencephalogram interface system 120 according to the present embodiment. Steps in which the same processing as that of the electroencephalogram interface system 1 (FIG. 8) is performed are denoted by the same reference numerals and description thereof is omitted. Specifically, the processes from step S20, step S40, and step S101 to step S106 are common to the electroencephalogram interface systems 1 and 120.

  In step S50, the stimulus random presentation unit 21 presents the auditory stimulus for calibration at random timing.

  In step S60, the electroencephalogram analysis unit 22 analyzes the feature quantity of the event-related potential measured by the biological signal measurement unit 50 from the timing when the auditory stimulus is presented in step S50. Detailed processing for analysis will be described later.

  In step S70, the electroencephalogram interface unit 100 determines whether the electroencephalogram interface is activated, for example, whether a menu item is displayed. If the electroencephalogram interface is activated, the process proceeds to step S101. If the electroencephalogram interface is not activated, the process returns to step S50. In the latter case, the stimulus random presentation unit 21 continues the process of presenting auditory stimuli at random timing.

  In step S80, the electroencephalogram interface unit 100 determines whether or not the electroencephalogram measurement is completed. If the user 5 removes the biological signal measurement unit 50, which is an electroencephalograph, and terminates the electroencephalogram measurement, the process ends. If the user 5 continues the electroencephalogram measurement, the process returns to step S50.

  As described above, it is possible to perform calibration even after the user starts using the electroencephalogram identification method adjustment system 120 by providing a process of returning to step S50 for presenting auditory stimuli for calibration. Become. Therefore, the event-related potential of the electroencephalogram signal can be obtained even when the wearing state changes due to the use of the electroencephalogram identification method adjustment system 120 and the wearing state of the biological signal measuring unit 50 shifts or the arousal level of the user 5 changes. Can be recognized accurately.

  Next, detailed processing of step S60 will be described with reference to the flowchart of FIG.

  FIG. 14 shows a processing procedure of the electroencephalogram analysis unit 22 performed in step S60 of FIG. Note that steps that perform the same processing as the processing of the electroencephalogram interface system 1 shown in FIG. 9 are denoted by the same reference numerals, and description thereof is omitted. Specifically, the processes up to steps S31, S32 and S33 are common to the electroencephalogram analysis units 12 and 22.

  In step S34 performed after step S32 and before step S33, the electroencephalogram analysis unit 22 adds the latest n event-related potentials after presentation of the calibration auditory stimulus measured by the biological signal measurement unit 50. To do. The effect of noise is reduced by this addition, and the amplitude and latency of the auditory P3 component can be calculated more correctly. Therefore, calibration that is resistant to noise can be realized. In addition, the electroencephalogram analysis unit 22 may perform addition calculation instead of the addition average of the event-related potentials of the latest n times.

  By presenting auditory stimuli at random timing or at predetermined timing and executing calibration, it is possible to identify the visual P3 component of the event-related potential by accurately following the user state and the electrode mounting state that can change constantly. Adjustment is possible. Thereby, the improvement of the identification rate of the electroencephalogram interface can be realized.

(Embodiment 3)
In the electroencephalogram interface system according to the first and second embodiments, it has been described that the calibration is performed using the auditory stimulus that the user does not overlook the calibration stimulus.

  However, the electroencephalogram interface system can be constructed using not only a stationary device such as the TV 2 shown in FIG. 1 but also a portable device as an operation target. When you go out with a portable device and try to operate it using an electroencephalogram interface system, for example, even if you present an auditory stimulus in a crowd or train, you might miss it. In addition, there are cases where auditory stimuli should not be presented due to manners. If so, there is a possibility that appropriate calibration cannot be performed using auditory stimulation.

  The electroencephalogram interface system 150 according to the present embodiment presents a somatosensory stimulus instead of an auditory stimulus as a calibration stimulus. Somatic sensory stimuli are very unlikely to be overlooked even when the user is in a hustle and bustle. Therefore, even when calibration by auditory stimulation is difficult, it becomes possible to adjust the method for identifying the visual P3 component of the electroencephalogram interface, and the identification rate can be improved.

  FIG. 15 shows a functional block configuration of the electroencephalogram interface system 150 according to the present embodiment. FIG. 15 also shows detailed functional blocks of the identification method adjustment device 152. The user 5 block is shown for convenience of explanation.

  The electroencephalogram interface system 150 is different from the electroencephalogram interface system 1 (FIG. 4) in the configuration of the identification method adjustment device 152. More specifically, the somatic sensory stimulus presentation unit 31 for calibration and the somatic sensory calibration unit having functions different from those of the stimulus presentation unit 11 and the modality conversion DB 13 of the discrimination method adjustment device 10 (FIG. 4) are included in the identification method adjustment device 152. The sensory visual conversion database (DB) 32 is provided. In FIG. 15, a vibrator 3 c is shown in the output unit 3 of the electroencephalogram interface system 150. This is used for presenting somatic sensory stimulation described later to the user 5. Note that the speaker 3b (FIG. 4) is not shown in the output unit 3, but this does not exclude the speaker 3b.

  Hereinafter, the somatosensory stimulus presentation unit 31 for calibration and the somatosensory-visual conversion DB 32 will be described. Hereinafter, they are described as “somatosensory stimulus presentation unit 31” and “conversion DB 32”, respectively. Of the constituent elements of the electroencephalogram interface system 150, the same constituent elements as those of the electroencephalogram interface system 1 (FIG. 4) are designated by the same reference numerals, and the description thereof is omitted.

  The somatosensory stimulus presentation unit 31 presents the somatosensory stimulus for calibration to the user 5 via the vibrator 3 c simultaneously with the presentation of the menu item in the electroencephalogram interface unit 100. The vibrator 3c operates in response to an instruction from the somatosensory stimulus presentation unit 31 in a wireless or wired manner. It is assumed that vibrator 3c is attached to the arm of user 5, for example, and has a function of giving vibration to the user, such as a vibrator function of a mobile phone, but this is an example. In addition, the skin such as hands and face may be simply stimulated. There may be one kind of somatic sensory stimulus, or two or more kinds.

  The conversion DB 32 defines the correlation between the somatosensory P3 component and the visual P3 component.

  The conversion DB 32 adjusts the visual P3 component identification method in the electroencephalogram interface unit 100 according to the amplitude and latency data of the P3 component with respect to the auditory stimulus obtained by the electroencephalogram analysis unit 12, such as the amplitude, latency, and correction interval. Data for saving is saved.

  FIGS. 16A and 16B show examples of the data structure of the conversion DB 32. FIG. 16A shows a conversion DB 32 that defines conversion rules that are commonly applied to all users. On the other hand, FIG. 16B shows a conversion DB 32 that preliminarily measures conversion standards for each user and defines conversion rules to be applied by switching for each user. With reference to the conversion DB 32 in FIGS. 16 (a) and 16 (b), how to obtain the P3 component of the visual event-related potential from the event-related potential caused by somatosensory stimulation will be described with reference to FIGS. According to the example of (b).

  By incorporating the identification method adjustment device 152 including the somatosensory stimulus presentation unit 31 and the conversion DB 32 described above into the electroencephalogram interface system 150, even if calibration by auditory stimulation is not possible, the user can use somatic sensory stimulation. The identification method can be adjusted based on the state and the mounting state of the electrodes. Thereby, the identification rate in the electroencephalogram interface unit 100 can be improved.

  FIG. 17 shows a processing procedure of the electroencephalogram interface system 150 according to the present embodiment. The flowchart of FIG. 17 is the same as the flowchart of FIG. 8 except that somatosensory stimulation is used for calibration and processing is performed using the somatosensory P3 component of the event-related potential based on the stimulus. It is. Therefore, the description about FIG. 8 is used and description is abbreviate | omitted.

  The processing shown in FIG. 17 enables adjustment of the identification method based on the user state and the electrode mounting state using somatic sensory stimulation even when calibration by auditory stimulation is not possible. Thereby, the improvement of the identification rate of the electroencephalogram interface can be realized.

  Even in a situation where calibration by auditory stimulation is possible, calibration may be performed using somatic sensory stimulation. Alternatively, calibration may be performed using auditory stimulation and somatic sensory stimulation in combination.

  According to the discriminating method adjusting device and the electroencephalogram interface system incorporating the discriminating method adjusting device of the present invention, in order to adjust the discriminating method of the visual P3 component used for discrimination in the electroencephalogram interface system, the interface that constantly measures the electroencephalogram It is possible to eliminate the influence of the state such as the physical condition of the individual user and the change in the wearing state of the electrodes for detecting the electroencephalogram, and maintain the electroencephalogram discrimination rate. Therefore, since the device operation unintended by the user due to an electroencephalogram identification error is reduced, the operability improvement of the electroencephalogram interface can be realized. Such a function of the identification method adjusting device can be realized by, for example, a computer program, and can be easily implemented without significant modification of the system.

It is a figure which shows the structure and utilization environment of the electroencephalogram interface system. (A)-(c) is a figure which shows the example when operating TV2 in the electroencephalogram interface system 1, and watching the program of the genre which the user 5 wants to view. It is a flowchart which shows the procedure of the process of an electroencephalogram interface. FIG. 2 is a diagram showing a functional block configuration of an electroencephalogram interface system 1 according to the first embodiment. (A) And (b) is a figure which shows the example of the data structure of both modality conversion DB. (A) And (b) is a figure which shows the example of adjustment of the identification method by rewriting a template. (A) And (b) is a figure which shows the adjustment example of the identification method by changing the magnification of an electroencephalogram signal. It is a flowchart which shows the procedure of the process which performs calibration in the electroencephalogram interface system 1, and uses an electroencephalogram interface after that. It is a flowchart which shows the procedure of the process of the electroencephalogram analysis part 12 performed in step S30 of FIG. It is a flowchart which shows the procedure of the process of the identification method adjustment part 14 performed in step S40 of FIG. It is a flowchart which shows the procedure of the process which adjusts the electroencephalogram signal previously acquired in the biosignal measurement part 50. FIG. FIG. 6 is a diagram showing a functional block configuration of an electroencephalogram interface system 120 according to Embodiment 2. 10 is a flowchart showing a processing procedure of an electroencephalogram interface system 120 according to Embodiment 2. It is a flowchart which shows the procedure of the process of the electroencephalogram analysis part 22 performed in step S60 of FIG. It is a figure which shows the structure of the functional block of the electroencephalogram interface system 150 by embodiment. (A) And (b) is a figure which shows the example of the data structure of conversion DB32. 10 is a flowchart showing a processing procedure of an electroencephalogram interface system 150 according to Embodiment 3.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 EEG interface system 3 Output part 3a Screen 3b Speaker 10 Identification method adjustment apparatus 11 Stimulation presentation part for calibration 12 Electroencephalogram analysis part for calibration 13 Modality conversion database 14 Identification method adjustment part 50 Biological signal measurement part 100 EEG interface part

Claims (12)

An output unit for visually presenting the operation menu of the device;
A biological signal measuring unit for acquiring a user's brain wave signal;
The P3 component of the visual event-related potential included in the electroencephalogram signal after the operation menu is presented is identified using the previously stored visual event-related potential parameter, and the device is operated based on the identified P3 component An electroencephalogram interface,
An electroencephalogram interface system comprising: an apparatus used for adjusting an identification method of the electroencephalogram interface section,
A database defining the correlation between the P3 component of the event-related potential and the P3 component of the visual event-related potential obtained by stimulation to a modality other than vision;
A stimulus presentation unit that presents the stimulus via the output unit;
An analysis unit for analyzing an event-related potential included in the electroencephalogram signal after the stimulus presentation;
Based on the analyzed P3 component of the event-related potential and the database, the feature quantity of the user regarding the P3 component of the visual event-related potential is derived, and an electroencephalogram identification method in the electroencephalogram interface unit is adjusted based on the feature quantity An identification method adjustment unit to
An apparatus for adjusting an electroencephalogram identification method, comprising:   The electroencephalogram identification method adjustment device according to claim 1, wherein the stimulus presentation unit presents an auditory stimulus as the stimulus.   The electroencephalogram identification method adjustment device according to claim 1, wherein the stimulus presentation unit presents a somatosensory stimulus as the stimulus. The electroencephalogram interface unit identifies the presence or absence of the P3 component of the visual event-related potential of the user based on a threshold set as the parameter,
The electroencephalogram identification method adjustment device according to claim 1, wherein the identification method adjustment unit adjusts the threshold based on the feature amount. The electroencephalogram interface unit identifies the presence or absence of the P3 component of the visual event-related potential of the user based on a waveform template of the visual event-related potential set as the parameter;
The electroencephalogram identification method adjustment device according to claim 1, wherein the identification method adjustment unit adjusts the template based on the feature amount.   The electroencephalogram identification method adjustment device according to claim 1, wherein the identification method adjustment unit adjusts an electroencephalogram signal of the user based on the feature amount. The electroencephalogram interface unit identifies the presence or absence of the P3 component of the visual event-related potential based on a threshold value related to the amplitude of the visual event-related potential;
The database defines a correlation related to the amplitude of the P3 component,
The electroencephalogram identification method adjustment device according to claim 4, wherein the identification method adjustment unit adjusts the threshold based on the feature quantity related to amplitude. The database defines a correlation related to the amplitude of the P3 component,
The electroencephalogram identification method adjustment device according to claim 5, wherein the identification method adjustment unit adjusts the template based on the feature quantity related to amplitude. The database defines a correlation related to the amplitude of the P3 component,
The identification method adjustment unit adjusts the electroencephalogram signal based on the feature quantity related to amplitude;
The electroencephalogram identification method adjustment device according to claim 6.   The electroencephalogram identification method adjustment device according to claim 1, wherein the stimulus presentation unit presents the stimulus at the start of use of the electroencephalogram interface system.   The electroencephalogram identification method adjustment device according to claim 1, wherein the stimulus presentation unit presents the stimulus at a random time during a period in which the electroencephalogram interface system is used. An output unit for visually presenting the operation menu of the device;
A biological signal measuring unit for acquiring a user's brain wave signal;
The P3 component of the visual event-related potential included in the electroencephalogram signal after the operation menu is presented is identified using the previously stored visual event-related potential parameter, and the device is operated based on the identified P3 component An electroencephalogram interface,
In an electroencephalogram interface system comprising: a method used for adjusting an identification method of the electroencephalogram interface section,
Providing a database defining a correlation between a P3 component of an event-related potential obtained by stimulation to a modality other than vision and a P3 component of a visual event-related potential;
Presenting the stimulus via the output unit;
Analyzing an event-related potential included in the electroencephalogram signal after the stimulus presentation;
Deriving the user's feature value for the P3 component of the visual event-related potential based on the analyzed P3 component of the event-related potential and the database;
Adjusting an electroencephalogram identification method in the electroencephalogram interface based on the feature amount;
A method for adjusting an electroencephalogram identification method.

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