WO2021070456A1 - イヤホン、情報処理装置、及び情報処理方法 - Google Patents

イヤホン、情報処理装置、及び情報処理方法 Download PDF

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Publication number
WO2021070456A1
WO2021070456A1 PCT/JP2020/029385 JP2020029385W WO2021070456A1 WO 2021070456 A1 WO2021070456 A1 WO 2021070456A1 JP 2020029385 W JP2020029385 W JP 2020029385W WO 2021070456 A1 WO2021070456 A1 WO 2021070456A1
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WIPO (PCT)
Prior art keywords
signal
wearer
brain wave
earphone
state
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Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
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PCT/JP2020/029385
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English (en)
French (fr)
Japanese (ja)
Inventor
泰彦 今村
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Vie Style
Vie Style Inc
Original Assignee
Vie Style
Vie Style Inc
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Filing date
Publication date
Application filed by Vie Style, Vie Style Inc filed Critical Vie Style
Priority to US17/767,359 priority Critical patent/US12414718B2/en
Priority to JP2021550383A priority patent/JP7573215B2/ja
Publication of WO2021070456A1 publication Critical patent/WO2021070456A1/ja
Anticipated expiration legal-status Critical
Priority to JP2024174014A priority patent/JP2024177370A/ja
Priority to US19/307,516 priority patent/US20250375137A1/en
Ceased legal-status Critical Current

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/25—Bioelectric electrodes therefor
    • A61B5/279—Bioelectric electrodes therefor specially adapted for particular uses
    • A61B5/291—Bioelectric electrodes therefor specially adapted for particular uses for electroencephalography [EEG]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/25—Bioelectric electrodes therefor
    • A61B5/251—Means for maintaining electrode contact with the body
    • A61B5/256—Wearable electrodes, e.g. having straps or bands
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/25—Bioelectric electrodes therefor
    • A61B5/279—Bioelectric electrodes therefor specially adapted for particular uses
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6813—Specially adapted to be attached to a specific body part
    • A61B5/6814—Head
    • A61B5/6815—Ear
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6887—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
    • A61B5/6898—Portable consumer electronic devices, e.g. music players, telephones, tablet computers
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; ELECTRIC HEARING AIDS; PUBLIC ADDRESS SYSTEMS
    • H04R1/00—Details of transducers, loudspeakers or microphones
    • H04R1/10—Earpieces; Attachments therefor ; Earphones; Monophonic headphones
    • H04R1/1016—Earpieces of the intra-aural type
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; ELECTRIC HEARING AIDS; PUBLIC ADDRESS SYSTEMS
    • H04R1/00—Details of transducers, loudspeakers or microphones
    • H04R1/10—Earpieces; Attachments therefor ; Earphones; Monophonic headphones
    • H04R1/105—Earpiece supports, e.g. ear hooks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; ELECTRIC HEARING AIDS; PUBLIC ADDRESS SYSTEMS
    • H04R1/00—Details of transducers, loudspeakers or microphones
    • H04R1/10—Earpieces; Attachments therefor ; Earphones; Monophonic headphones
    • H04R1/1091—Details not provided for in groups H04R1/1008 - H04R1/1083
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/369—Electroencephalography [EEG]
    • A61B5/372—Analysis of electroencephalograms

Definitions

  • the present invention relates to an earphone, an information processing device, and an information processing method.
  • the electrodes for the electroencephalogram When acquiring an electroencephalogram signal, it is important to bring the electrodes for the electroencephalogram into close contact with the user in order to acquire the electroencephalogram signal with high accuracy.
  • the positions of the electrodes are not determined according to the shape of the ear or ear canal that differs depending on the user. Therefore, the electrodes for brain waves are used for users having various shapes of ears or ear canals. It was not always in close contact with the sensing position.
  • one aspect of the present invention is to provide an earphone that makes it easier for the electroencephalogram electrodes to come into close contact with each other when worn.
  • Another aspect of the present invention is to appropriately estimate the wearer's condition from the electroencephalogram signal using a model customized and generated for the wearer.
  • the information processing device in another embodiment uses an acquisition unit that acquires an electroencephalogram signal, a model that learns a predetermined electroencephalogram signal of the wearer of the earphone, and a state of the wearer at the time of acquiring the predetermined electroencephalogram signal. It includes an estimation unit that estimates the state of the wearer from the acquired electroencephalogram signal, and a processing unit that performs processing based on the estimated state of the wearer.
  • the present invention it is possible to provide an earphone in which the electroencephalogram electrode is more easily adhered when worn. Further, according to another aspect of the present invention, the state of the wearer can be appropriately estimated from the electroencephalogram signal using the model generated for the wearer.
  • FIG. 1 is a diagram showing an overall example of the earphone set 10 according to the first embodiment.
  • FIG. 2 is a diagram showing an enlarged example of the earphone 100 portion in the first embodiment.
  • FIG. 3 is a diagram showing an example of the right portion of the earphone 100 in the first embodiment.
  • the earphone set may be simply called an earphone.
  • the earphone set 10 includes a pair of earphones 100R and 100L, a cable 102 connected to each of the pair of earphones 100R and 100L, a first storage case 104 provided at an arbitrary position of the cable 102, and a second. Includes containment case 106.
  • the first storage case 104 and the second storage case 106 include, for example, a communication circuit (communication interface) for communicating a sound signal with another device, an operation unit having a function of operating the earphone 10, a power supply (battery), and a microphone. Etc. can be included.
  • the cable 102 may include, for example, a plurality of signal lines connecting the first accommodating case 104, the second accommodating case 106, each circuit in the earphone 100R (L), and the like.
  • the first storage case 104 and the second storage case 106 may be combined into one. Further, as will be described later, the earphone 10 is configured as a wireless type in which the first accommodating case 104 and the circuit accommodated inside the second accommodating case 106 are accommodated in the housing 112 portion of the earphone 10, and the cable 102 is unnecessary. May be done. When the right (R) and the left (L) are not particularly distinguished for each configuration, the RL reference numerals are omitted.
  • the earphone 100 has an ear tip 110, a housing 112, a speaker 113 housed inside the housing 112, a joint mechanism 114, a connection portion 116, a cable 118, and a grip portion 120.
  • the ear tip 110 is attached to one end side of the housing 112. At this time, one end side of the housing 112 is formed of a flexible material such as an elastic material or a rubber material. This is to prevent the vibration of the housing 112 from being transmitted to the ear tip 110. Further, the ear tip 110 includes a sound guiding portion 115 through which sound from the speaker 113 housed inside the housing 112 passes, and an elastic electrode that senses the brain wave of the wearer. As the elastic electrode, for example, a rubber electrode composed of all or a part of the ear tip 110 and capable of acquiring a biological signal can be used. As a result, the ear tip 110 including the elastic electrode can acquire the electroencephalogram signal of the wearer by coming into close contact with the inner wall of the ear canal.
  • the ear tip 110 is detachably attached to a nozzle protruding from one end of the housing 112.
  • the sound guide portion 115 functions as a passage through which the sound from the speaker 113 passes.
  • the nozzle has a sound guiding portion inside which the sound output from the speaker 113 is passed, and the sound passes through the sound guiding portion 115 of the ear tip 110 which partially overlaps the sound guiding portion of the nozzle. It reaches the eardrum of the wearer.
  • the elastic electrode included in the ear tip 110 and the copper wire (first signal line described later) in the housing 112 are provided at a portion as far as possible from the sound guiding portion 115.
  • an elastic electrode is provided on the outer edge of the ear tip 110, and a copper wire is provided on the outer edge inside the housing 112.
  • the elastic electrode and the copper wire that transmits the brain wave signal are less likely to be affected by the vibration of sound.
  • the housing 112 has elasticity in at least one end side outer layer. A nozzle protrudes toward the end having elasticity, and the ear tip 110 is attached to this nozzle.
  • the elastic portions of the ear tip 110 and the housing 112 are elastically deformed and mounted according to the shape of the ear canal of the wearer, and the ear tip 110 and the housing are attached to the inner wall of the ear canal.
  • the elastic part of 112 is designed to fit. As a result, the elastic electrode of the ear tip 110 fitted to the inner wall of the ear canal can acquire an electroencephalogram signal with high accuracy.
  • the elastic end of the housing 112 first comes into contact with the outer ear when the earphone 10 is attached, and is deformed so as to be dented by receiving the contact pressure.
  • the ear tip 110 including the elastic electrode is positioned in the ear canal and is in close contact with the entire circumference of the ear canal.
  • the housing 112 has a storage space in the direction opposite to the nozzle, and the housing 112 has a substrate including a sound processing circuit and a speaker 113 in this storage space.
  • the speaker 113 may be arranged in the housing 112 in consideration of the position of the speaker 113 so that the directivity of the output sound is directed directly to the eardrum in the ear canal, for example.
  • the speaker 113 is arranged so that sound is output from the central portion of the housing 112.
  • the peripheral portion of the speaker 113 is covered with a cushioning material such as a foaming material, and the cushioning material prevents the housing 112 and the speaker 113 from coming into direct contact with each other.
  • the vibration when the sound is output from the speaker 113 is less likely to be transmitted to the housing 112, and the vibration is less likely to be transmitted to the sensor (elastic electrode) of the ear tip 110 via the housing 112. That is, when sensing an electroencephalogram signal, it is possible to reduce the influence of vibration caused by sound output.
  • the joint mechanism 114 is a mechanism for connecting the end portion of the housing 112 opposite to the nozzle and the connecting portion 116.
  • the joint mechanism 114 is at least a ball joint mechanism capable of rotating and adjusting the housing 112 in the horizontal direction (direction of the XY plane). Further, the joint mechanism 114 may allow the housing 112 to rotate 360 degrees so that the position of the housing 112 can be adjusted.
  • the grip portion 120 grips the wearer's earlobe and has electrodes in the peripheral region of each end portion.
  • the grip portion 120 has a second electrode 140 at one end and a third electrode 142 at the other end.
  • the second electrode 140 is an electrode connected to the ground
  • the third electrode 142 is an electrode that functions as a reference electrode.
  • the brain wave signal can be accurately acquired by calculating the difference between the signal sensed by the elastic electrode (first electrode) of the ear tip 110 and the signal sensed by the third electrode of the reference electrode. become able to. This is because the signal acquired from the earlobe portion contains almost no brain wave signal.
  • the processing circuit 144R includes a signal processing circuit that converts an electroencephalogram signal sensed by the elastic electrode of the ear tip 110 into a digital signal. Further, the grip portion 120L has the same configuration as the grip portion 120R.
  • the first storage case 104 includes a communication circuit 150 and an operation unit 152.
  • the communication circuit 150 includes an antenna for performing wireless communication.
  • the antenna is compatible with wireless communication standards such as Bluetooth®. Therefore, the earphone 10 is wirelessly connected to devices such as mobile terminals and laptops, and communicates sound data with these devices.
  • the operation unit 152 has an operation function for controlling the volume and reproduction of the sound processing circuit inside the housing 112.
  • FIG. 5 shows a wireless type earphone 10, and shows an example in which the configuration housed in the storage case shown in FIG. 4 is housed in the grip portion 120.
  • the grip portion 120R has a second electrode 140R, a third electrode 142R, a processing circuit 144R, a communication circuit 150, and a power supply 154.
  • the functions of each part are the same as those shown in FIG.
  • each part may be provided inside the housing 112.
  • the communication circuit 150 and the processing circuit 144 may be provided in the housing 112.
  • the configuration inside the housing 112 and the configuration inside the grip portion 120 may be determined in consideration of the load on the ears.
  • the elastic housing 112 can be deformed according to the size and shape of the ear canal, so that the ear tip has an elastic electrode.
  • the 110 enters along the ear canal, and the ear tip 110 comes into close contact with the entire circumference of the ear canal. As a result, it becomes possible to appropriately sense the electroencephalogram signal from the elastic electrode.
  • the earphone 10 may be made of a material having elasticity and flexibility not only for the ear tip 110 but also for all the exterior parts (housing 112) that come into contact with the skin. As a result, even if there are individual differences in the shape of the ear, it is possible to obtain a high wearing feeling, high sound insulation, and difficulty in falling off by fitting the earphone 10 to the ear, and appropriately obtain an electroencephalogram signal. It will be possible to obtain.
  • FIG. 6 is a diagram showing each configuration example of the electroencephalogram signal processing system 1 according to the second embodiment.
  • the earphones 10A, 10B, ... Used by each user, the information processing devices 20A, 20B, ..., And the server 30 that processes the electroencephalogram signal are connected via the network N. ..
  • alphabetic codes such as A and B are omitted.
  • the earphone 10 is the earphone 10 described in the first embodiment, but is not necessarily limited to this.
  • the earphone 10 acquires at least one electroencephalogram signal from each of the left and right earphones 10R and 10L, and acquires a total of two electroencephalogram signals.
  • the electroencephalogram signal does not have to be two points.
  • the earphone 10 is not limited to the earphone, and may be any device capable of sensing brain waves.
  • the information processing device 20 is, for example, a smartphone, a mobile phone (feature phone), a computer, a tablet terminal, a PDA (Personal Digital Assistant), or the like.
  • the information processing device 20 is also referred to as a user terminal 20.
  • the information processing device 30 is, for example, a server, and may be composed of one or a plurality of devices. Further, the information processing device 30 processes the electroencephalogram signal and analyzes the user's state from the electroencephalogram signal by using, for example, the learning function of artificial intelligence (AI).
  • AI artificial intelligence
  • the information processing device 30 is also referred to as a server 30.
  • a user (user A) who uses the user terminal 20A wears the earphone 10A, and the earphone 10A acquires the brain wave signal of the user A.
  • the earphone 10A transmits the brain wave signal of the user A to the user terminal 20, and processes the brain wave signal in the application of the user terminal 20.
  • the application may analyze the electroencephalogram signal using the edge AI, or may acquire the analysis result by the server 30 by transmitting the electroencephalogram signal to the server 30.
  • the application provides the user A with a state of the user A estimated using the electroencephalogram signal, training for transitioning from the current state based on the electroencephalogram signal to a predetermined state, and the like.
  • FIG. 7 is a block diagram showing an example of the user terminal 20 according to the second embodiment.
  • the user terminal 20 is one for interconnecting one or more processing devices (control unit: CPU) 210, one or more network communication interfaces 220, a memory 230, a user interface 250, and their components. Alternatively, it includes a plurality of communication buses 270.
  • the memory 230 is, for example, a high-speed random access memory such as a DRAM, SRAM, DDR RAM or other random access solid-state storage device, and one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or It may be a non-volatile memory such as another non-volatile solid-state storage device.
  • the memory 230 stores the following programs, modules and data structures, or a subset thereof.
  • One or more processing devices (CPUs) 210 read and execute a program from the memory 230 as needed.
  • one or more processing units (CPUs) 210 may configure the acquisition unit 212, the estimation unit 214, and the processing unit 216 by executing a program stored in the memory 230.
  • the acquisition unit 212 acquires the brain wave signal output from the earphone 10 via the network communication interface 220.
  • the processing unit 216 performs processing based on the state of the wearer estimated by the estimation unit 214. This enables processing according to the wearer's condition estimated from the wearer's brain wave signal using the model learned for the wearer, and outputs personally customized processing results. Etc. become possible.
  • the trained model is a predetermined model in which the brain wave signal of another person and the state of another person at the time of acquiring the brain wave signal are learned, and the brain wave signal of the wearer and the state of the wearer at the time of acquisition of the brain wave signal are used. May be a customized model that has been additionally trained. As a result, it is possible to have a certain degree of estimation performance even in the initial stage, and it becomes possible to customize it for personal use as it is used (learned).
  • the processing unit 216 is an induction process for inducing a transition from the wearer's state estimated based on the current electroencephalogram signal to the predetermined state of the wearer indicated by the first electroencephalogram signal, and is based on the current electroencephalogram signal.
  • the guidance process that feeds back to the wearer may be performed.
  • the processing unit 216 shows or listens to various contents to the wearer to instruct the wearer of a better condition.
  • the processing unit 216 asks the wearer to indicate good conditions such as favorable, focused, relaxed, and drowsy.
  • the content is, for example, music, video, games, and the like.
  • the processing unit 216 displays a UI component (icon, button, etc.) indicating a good state on the screen of the user terminal 20, and the user operates the UI component when the user is in a good state.
  • the content is given a label indicating a feature such as a genre. For example, if the content is video, the label includes kids, family, documentary, comedy, suspense, romance, action, etc., and if the content is music, the label includes rock, pop, ballad, classic, etc.
  • the label may also be the type or mood of the work. Types of work include intellectual, violent, entertaining, controversial, dark, happy, family-friendly, and witty.
  • the atmosphere of the work includes gentle works and intense works.
  • the processing unit 216 associates the waveforms and features of the electroencephalogram signal (first electroencephalogram signal) when the wearer is instructed to be in a good state with the features of the content, and uses these as teacher data as the learning unit 311 of the server 30 (FIG. 8) to learn.
  • the processing unit 216 uses the learning unit 311 of the server 30 as teacher data for the brain wave signals before and after transitioning to the first brain wave signal when the wearer is in a good state, the state at the time of each brain wave signal, and the characteristics of the contents. It is possible to learn what kind of video, listen to music, or play a game to make a transition to a good state, and to generate a trained model including an inference algorithm.
  • the processing unit 216 learns the brain wave signals, states, and contents before and after the transition to the good state, so that the current brain wave signal of the wearer can be changed to a good state for the wearer. Can be grasped to show to the wearer.
  • the processing unit 216 informs the wearer of the analysis result using the trained model as a feedback result.
  • FIG. 8 is a block diagram showing an example of the server 30 according to the second embodiment.
  • the server 30 includes one or more processing units (CPUs) 310, one or more network communication interfaces 320, memory 330, and one or more communication buses 370 for interconnecting these components. ..
  • the memory 330 is, for example, a high-speed random access memory such as a DRAM, SRAM, DDR RAM or other random access solid-state storage device, and one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or It may be a non-volatile memory such as another non-volatile solid-state storage device.
  • the memory 330 may be one or a plurality of storage devices installed remotely from the CPU 310.
  • the memory 330 stores the following programs, modules and data structures, or a subset thereof.
  • the learning unit 311 analyzes the wearer's state using the wearer's brain wave signal and generates a model (first model). For example, a model in which an arbitrary extraction method among a plurality of methods for extracting learning data from an electroencephalogram signal and an arbitrary classifier among a plurality of classifiers may be used may be used.
  • the extraction method includes a wavelet transform, a Fourier transform, and the like
  • the classifier includes, for example, a random forest (RandomForest), a support vector machine (SVM), a neural network, a decision tree, and the like.
  • ⁇ Feedback training> It is known that the tendency of the frequency band and potential of brain waves differs from individual to individual. Therefore, an individual user who is measuring an electroencephalogram is asked to annotate his / her own arbitrary state (for example, the first state) using a symbol, an emoticon, or the like displayed on the user terminal 20. As a result, the learning unit 311 learns the electroencephalogram signal and the annotation so that the first electroencephalogram signal corresponding to the first state and the transition from an arbitrary electroencephalogram signal to the first electroencephalogram signal can be predicted and visualized. become. In addition, we aim to enable the user to reproduce an arbitrary state by performing predetermined training so as to transition from an arbitrary electroencephalogram signal to the first electroencephalogram signal.
  • the processing unit 216 calculates a frequency band for performing electroencephalogram training for each individual wearer. For example, the processing unit 216 detects Individual Alpha frequency Peak (IAP) from the electroencephalogram signal. Next, the processing unit 216 is centered on the IAP, and for each individual, delta (delta: 0.5 to 3 Hz), theta (theta: 4 to 7 Hz), alpha (alpha: 8 to 13 Hz), beta (beta: 14). ⁇ 30Hz) and gamma (gamma: 30Hz or more) are set. The processing unit 216 obtains a ratio between the total potential of the electroencephalogram signal (for example, the average value of all frequency bands) and the potential of each frequency band (for example, the average value of each frequency band). Alpha waves are said to appear when resting, awakening, and closing eyes, and theta waves and delta waves are set based on these alpha waves.
  • IAP Individual Alpha frequency Peak
  • the processing unit 216 calculates a predetermined ratio (hereinafter, also referred to as "golden ratio”) for each individual wearer.
  • a brain wave signal in an arbitrary good state of the wearer is calculated based on the analysis result of artificial intelligence (AI) by the server 30, and a predetermined Hz and high frequency are calculated in the low frequency direction with the IAP as the axis. It is divided into each frequency band using a predetermined Hz or the like in the direction, and the ratio of the average value of all frequency bands to the average value or representative value of each frequency band is calculated.
  • the representative value of each frequency band may be, for example, the peak frequency having the highest value in each frequency band.
  • the golden ratio may be the ratio of the average value or the representative value of each frequency band.
  • the processing unit 216 converts the calculated electroencephalogram signal into a ratio of the average value or the representative value in each frequency band in a good state.
  • the processing unit 216 may calculate the standard deviation of the ratio of the electroencephalogram signals categorized by gender, age, and time using the electroencephalogram signals of various wearers, and the calculated standard deviation and the individual's standard deviation may be calculated.
  • the golden ratio it may be converted to the golden ratio of each band suitable for the individual.
  • ⁇ Training method> 1 The learning unit 311 analyzes the frequency characteristics of an individual based on the calculated IAP and records the tendency of the potential.
  • the learning unit 311 learns the feature amount of the individual brain wave signal in an arbitrary state (not only a good state but also various states such as concentrated and relaxed) by the annotation of the wearer. To do. 3: When the AI in the learning unit 311 sufficiently learns the feature amount of the brain wave signal, the individual state can be estimated from the brain wave signal.
  • 4 The processing unit 216 converts the feature amount of the electroencephalogram signal that can be guessed into a frequency or an electric potential. 5: The processing unit 216 trains the learned individual to approach some arbitrary state, for example, to approach the numerical value of the converted frequency or potential.
  • the processing unit 216 selects the content and the stimulus while giving feedback.
  • the processing unit 216 selects the optimum music / moving image that leads to the ideal potential state.
  • the processing unit 216 may generate a recommendation from the viewing history (individual / whole) of the music / moving image.
  • FIG. 11 is a diagram showing an example of a training screen according to the second embodiment. As shown in FIG. 11, the wearer can learn the state of the wearer by pressing the face mark indicating the mood at that time while listening to the music.
  • FIG. 12 is a flowchart showing an example of the guidance process according to the second embodiment.
  • a process of inducing a predetermined state is performed using the acquired electroencephalogram signal.
  • step S102 the acquisition unit 212 acquires an electroencephalogram signal output from a sensor (for example, an elastic electrode of the earphone 10).
  • a sensor for example, an elastic electrode of the earphone 10
  • step S104 the estimation unit 214 uses the acquired brain wave signal from the acquired brain wave signal using a model that learns the predetermined brain wave signal of the wearer wearing the sensor and the state of the wearer at the time of acquiring the predetermined brain wave signal. Estimate the wearer's condition.
  • FIG. 13 is a flowchart showing an example of the training process according to the second embodiment. In the example shown in FIG. 13, a process of training to transition to a predetermined state while sensing an electroencephalogram signal is shown.
  • step S202 the acquisition unit 212 acquires an electroencephalogram signal output from a sensor (for example, an elastic electrode of the earphone 10).
  • a sensor for example, an elastic electrode of the earphone 10
  • step S204 the processing unit 216 calculates IAP (Individual Alpha frequency Peak) from the brain wave signal.
  • step S206 the processing unit 216 provides feedback on whether to move the IAP to a high potential or a low potential based on the calculated IAP.
  • FIG. 14 is a diagram showing an enlarged example of the earphone according to the modified example 1.
  • the installation direction of the grip portion 120 is different from that of the earphone shown in FIG. 2, and other configurations are the same as those of the earphone shown in FIG.
  • the grip portions 120RA and 120LA are provided with their longitudinal directions along the Z direction in the vertical direction. Further, the longitudinal direction of the grip portion 120 is provided along the moving direction by the adjusting mechanism provided in the connecting portion 116.
  • the portion that sandwiches the earlobe faces upward (housing direction) on the Z axis. As a result, most of the grip portion 120 is hidden behind the face side of the connection portion 116, so that the design can be improved.
  • the size of the grip portion 120 can be reduced. This is because the earlobe generally has a width in the horizontal direction, so that by gripping the earlobe from below as shown in FIG. 14, the grip portion is more than gripping the earlobe from the horizontal direction as shown in FIG. This is because the length of the folded portion of 120 in the longitudinal direction can be shortened.
  • the neck hanging portion 160 has a central member along the back of the neck and rod-shaped members (arms) 182R and 182L having a curved shape along both sides of the neck. Electrodes 162 and 164 for sensing electroencephalogram signals are provided on the surface of the central member in contact with the neck on the back side. Each of the electrodes 162 and 164 is a ground-connected electrode and a reference electrode. As a result, the distance from the elastic electrode provided on the ear tip of the earphone can be increased, and the brain wave signal can be acquired with high accuracy.
  • the rod-shaped members 182R and 182L on both sides of the neck hanging portion 160 are heavier on the tip side than on the base side (center member side), whereby the electrodes 162 and 164 are appropriately attached to the wearer's neck. It will be crimped. For example, a weight is provided on the tip end side of the rod-shaped members 182R and 182L.
  • FIG. 16 is a diagram showing a schematic example of the cross section of the earphone 170 in the modified example 2.
  • the earphone 170 shown in FIG. 16 is basically the same as the earphone 100, but an elastic member (for example, urethane) 174 is provided between the speaker 113 and the nozzle 172.
  • an elastic member for example, urethane
  • the vibration of the speaker 113 is less likely to be transmitted to the elastic electrode of the ear tip 176, and it is possible to prevent the elastic electrode of the ear tip 176 and the speaker 113 from interfering with each other with respect to sound.
  • the ear tip 176 including the elastic electrode is located at the sound guide port, it is possible to prevent interference due to sound vibration due to the elasticity of the elastic electrode itself. Further, since an elastic member is used for the housing, it is difficult for the elastic member to transmit sound vibration to the elastic electrode of the ear tip 176, and it is possible to prevent interference due to sound vibration.
  • the earphone 170 includes an audio sound processor, and uses this audio sound processor to cut a sound signal having a predetermined frequency (for example, 50 Hz) or less corresponding to an electroencephalogram signal.
  • the audio sound processor cuts a sound signal of 30 Hz or less in a frequency band in which a feature is likely to appear as an electroencephalogram signal, but amplifies a sound signal having a frequency around 70 Hz in order not to impair the bass sound. This makes it possible to prevent the sound signal and the brain wave signal from interfering with each other.
  • the audio / sound processor may cut a predetermined frequency only when the brain wave signal is sensed.
  • the audio / sound processor described above can also be applied to the earphone 10 in the embodiment.
  • FIG. 17 is a diagram showing an example of the structure around the electrode of the neck hanging portion 160 in the modified example 2.
  • the elastic member 166 is provided on the neck hanging portion 160 side of each of the electrodes 162 and 164.
  • the elastic member 166 is, for example, urethane or the like, and the elasticity of the elastic member 166 allows the electrodes 162 and 164 to change their positions.
  • the shape of the electrode is hemispherical, and the elastic member 166 is adhered so as to cover the central portion of the hemisphere, so that the electrode changes the angle by 360 degrees by using the elasticity of the elastic member 166. Can be done. Further, the elastic member 166 is deformed according to the shape of the wearer's neck, and the electrodes 162 and 164 can be easily crimped to the wearer's neck.
  • FIG. 18 is a diagram showing an example of substantially disassembling the earphone set 50 in the modified example 2.
  • the rod-shaped member 182R has a bellows structure inside, for example, an aluminum plate located on the outside, and the rod-shaped member 182R can be deformed according to the shape, thickness, and the like of the wearer's neck. ..
  • an elastic member 184R such as rubber is provided inside the neck of the rod-shaped member 182R, and the elastic member 184R comes into contact with the neck to reduce the burden of contact with the neck and improve the wearing feeling. it can.
  • the rod-shaped members 182 located on both sides of the neck hanging portion 160 can be folded toward the electrode side.
  • the rod-shaped member 182R can be folded toward the electrode side or the central member side by the folding structure 186R.
  • the rod-shaped member 182L also has a folding structure (for example, a hinge) and can be folded toward the electrode side. As a result, the neck hanging portion 160 can be stored compactly.
  • rod-shaped members 182R and 182L may have a shape in which the rod-shaped members 182R and 182L are slightly curved downward in the vertical direction so as to easily follow the clavicle of the wearer.
  • the processing unit 216 controls a predetermined area of the display screen of the user terminal 20, for example, a background, to display a gradation using colors assigned in advance for each frequency band of the brain wave signal. For example, when the brain wave signal is transitioning to a good state (golden ratio state), the color of a predetermined area is displayed so as to gradually become brighter, and when the brain wave signal is not transitioning to a good state, it is gradually displayed. The color of the processing area is displayed so that it becomes a dark color. Since the good state of the electroencephalogram signal differs depending on the user, the gradation is determined with reference to the frequency band of the electroencephalogram signal in the good state of the user. As a result, it becomes possible to display a predetermined area using a gradation according to the change of the electroencephalogram signal, and it becomes possible to visually express the current state of the electroencephalogram signal to the user.
  • a good state golden ratio state
  • the color of a predetermined area is displayed so as to gradually become bright
  • FIG. 19A is a diagram showing an example of a display screen during intensive training.
  • the screen shown in FIG. 19A is a screen displayed during a task in time management, indicating that the current score value is “42”, and “25:00” indicates a timer for the task time.
  • the processing unit 216 uses a timer to manage the time of each use case.
  • the processing unit 216 may display the waveform of the frequency band of the electroencephalogram signal related to each use case.
  • the processing unit 216 may be controlled to output a sound preset in the frequency band of the electroencephalogram signal from the speaker.
  • the preset sound is, for example, a natural sound, a sound of wind, rain, waves, forest, etc., and may be a sound in which these are appropriately combined.
  • a good state golden ratio state
  • the sound is output from the speaker so that the sound gradually becomes gentle
  • the brain wave signal is not transitioning to a good state, it gradually becomes a gentle sound. Sound is output from the speaker so that it becomes a rough sound.
  • the transition of the brain wave signal to a good state means that the difference between the ratio of the average value or the representative value in each frequency band of the current brain wave signal and the golden ratio becomes small, and each frequency band is required to have a golden ratio. It is the same as the frequency band.
  • the preset sound may be voice.
  • the processing unit 216 may display pictograms on the screen, output sound, or display in the color of the screen. Good.
  • the application in the specific example can score and visualize concentration, relaxation, tension, fatigue, etc. determined from brain wave signals for a predetermined period, for example, monthly, weekly, daily, or session unit. ..
  • the estimation unit 214 sets the golden ratio learned using the brain wave signal of each user according to each use case, and the representative value of each frequency band when the current brain wave signal is divided into each frequency band. The score is created based on the distance from the ratio of the above, and the processing unit 216 displays the scored score value on the screen.
  • FIG. 19B is a diagram showing an example of a screen displaying measurement results related to relaxation (relax), concentration (Focus), and meditation (CALM) on a daily basis.
  • the screen shown in FIG. 19B is a so-called dashboard that aggregates and visualizes data, and the time determined to be relaxed based on the brain wave signal measured on the 15th (Wed) is "33 minutes”. It indicates that the time determined to be able to concentrate is "23 minutes” and the time determined to be calm (can meditate) is "42" minutes.
  • the estimation unit 214 may obtain each score value by the estimation process using the trained model in each use case.
  • the relaxation score value indicates "68" and the concentration score value indicates "72".
  • the processing unit 216 may determine that the user is relaxed, focused, or calm.
  • each time-managed use case will be described.
  • the processing unit 216 performs a meditation guide using audio and video.
  • the acquisition unit 212 acquires the electroencephalogram signal after the meditation guide, and the estimation unit 214 calculates the score value based on the acquired electroencephalogram signal and the golden ratio, and when the electroencephalogram signal calms down and the score value becomes high ( (When the frequency approaches the golden ratio), the processing unit 216 changes the background color and controls the wind in the background image to stop and / or the bird's cry.
  • the processing unit 216 changes the background color, the wind in the background image blows, and / or the background image. Control the landscape to be a storm. Further, the processing unit 216 may change the background (natural environment) and the contents of the guide depending on the time (morning, afternoon, etc.) and purpose of executing this application.
  • FIG. 20 is a diagram showing an example of frequency waveforms during meditation and at times other than meditation.
  • lower frequencies of the delta wave and theta wave appear during meditation (Focus) than during non-meditation (Tired).
  • the golden ratio of the individual user can be obtained by using the characteristics of these individual waveforms.
  • a meditation guide is performed using the audio and video as described above.
  • Tasks (concentration, fatigue) are performed after meditation in the time management technique in this application, and then alternate with breaks.
  • the estimation unit 214 estimates the user's concentration and fatigue level based on the frequency of the acquired electroencephalogram signal. For example, the estimation unit 214 estimates that fatigue is increasing as theta waves increase during the task. This is because it is generally said that delta waves and theta waves do not appear in the awake state.
  • the break (break, concentration) is performed after the task in the time management technique in this application, and is performed alternately with the task thereafter. Since it is said that the alpha wave appears when the eyes are closed, the estimation unit 214 can estimate that the eyes are closed when the value of the alpha wave becomes large. Further, the estimation unit 214 estimates that the values of the low frequencies of the delta wave and theta wave increase when the meditation state is entered, and that the values of these frequency bands become calm as the values increase. In addition, the processing unit 216 provides calming content for the user, which is presented by the trained model if the user is awake even during a break.
  • the application in the specific example can support the optimization of how to use the time by using each time zone divided by the time for each use case.
  • this application can create a playlist that can be concentrated according to individual tastes and characteristics during the concentrated time in time management. For example, by using a trained model that has learned the user's annotation results, it is possible to select songs for transitioning to a good state (golden ratio state), and an order is set for these songs according to a predetermined standard. A playlist is generated.
  • this application uses a trained model to recommend guides such as simple meditation / stretching, games and videos that prepare the brain, etc., according to the characteristics of the user's brain wave signal during breaks in time management. It is possible to do.
  • FIG. 22 is a diagram showing an example of the position of each portion of the neck hanging portion 160 in the modified example 3.
  • a cross-sectional view of the neck hanging portion 160 in the XY plane is shown, and the electrodes 162 and 164 are arranged so as to be located on both sides of the wearer's neck and are composed of elastic electrodes.
  • each electrode may be arranged at both ends of a rod-shaped member or a central member located on both sides of the neck, and a predetermined distance (for example, 3 to 7 cm) from the center of the neck hanging portion 160 to the left and right. )
  • Each electrode 162, 164 may be arranged at a distant position.
  • a battery BA and a substrate ST on which the processing unit is mounted are provided at a central position inside the neck hanging portion 160.
  • an elastic member that can be attached to the inside of the neck hanging portion 160 may be provided, and the electrodes 162 and 164 may be provided on the elastic member. As a result, even when there is movement such as during exercise, the elastic member comes into close contact with the wearer's neck, so that the reference signal can be acquired with high accuracy.
  • FIG. 23 is a diagram showing the positional relationship between the carotid artery and the left electrode 162.
  • the signal sensed by the electrode 162 includes a signal based on the pulse of the carotid artery.
  • FIG. 24 is a diagram showing an example of a reference signal mixed with the beating of the carotid artery.
  • the example shown in FIG. 24 is an example of raw data of data sensed from electrodes 162 or 164.
  • the vertical axis represents the value of the sensed signal
  • the horizontal axis represents time.
  • the electrocardiogram signal (ECG) mixed in the reference signal is measured in the opposite phase.
  • the downwardly convex peak circled in FIG. 24 is a signal indicating an electrocardiogram signal.
  • the signal indicating the normal pulse of the wearer is synonymous with the electrocardiogram signal.
  • the CPU 210 Utilizing the mixing of the pulse of the carotid artery, for example, the CPU 210 outputs the signal output from each electrode 162, 164 provided on the neck hanging portion according to the modification 3 as a reference signal from the elastic electrode of the ear tip 176. Acquires an electroencephalogram signal based on the signal to be performed. Next, the CPU 210 detects the pulse based on the peak that appears in the phase opposite to the peak of the acquired electroencephalogram signal.
  • FIG. 25A is a diagram showing an example of a signal during mouth breathing.
  • FIG. 25B is a diagram showing an example of a signal during nasal breathing.
  • the vertical axis represents the energy difference value after filtering and the horizontal axis represents time.
  • the downward convex portion appears when inhaling (inhalation)
  • the upward convex portion appears when exhaling (exhalation). It is considered that one of the reasons why these peaks and valleys are formed is that the change in the myoelectric potential of the face during respiration is mixed in each electrode of the ear tip 176.
  • the CPU 210 is output from the elastic electrode of the ear tip 176 using the signal output from the electrodes 162 and 164 provided on the neck hanging portion described in the modification 3 as a reference signal. Acquires an electroencephalogram signal based on the signal. Next, the CPU 210 processes the acquired electroencephalogram signal with a low bus filter and a median filter, frequency-converts the filtered signal, and time-differentiates the time-series power spectrum value after frequency conversion. Respiration is detected based on the periodicity of the difference value of this time differentiation.
  • the CPU 210 detects the peak value of the electrocardiogram that appears in the opposite phase to the peak of the brain wave signal, processes the detected signal with a low-pass filter and a median filter, and frequency-converts the filtered signal. Then, the power spectrum value of the time series after frequency conversion is time-differentiated, and the pulse is detected based on the periodicity of the time-differentiated difference value. This makes it possible to detect the heartbeat using the noise-free pulse.
  • the CPU 210 detects the heartbeat / respiration by obtaining the periodicity from the data values shown in FIGS. 24 or 25 using an autocorrelation function. Further, the above-described processing for detecting heartbeat and respiration may be implemented as a program including instructions for each processing and executed by being installed in an information processing apparatus.

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