KR101566788B1 - Brain computer interface based functional electrical stimulator - Google Patents

Abstract

The present invention detects an EEG of a patient and detects an EEG concentration indicator from the detected EEG, while observing a training image of a leg and a walking of a monitor, And a brain-computer interface-based functional electrical stimulation therapy apparatus for exercising the legs and the gait according to the patient's will.
The present invention is characterized in that an EEG electrode unit for detecting an EEG is mounted on a frontal part of a patient watching a foot, foot, and gait training image through a monitor, and the controller detects an EEG concentration indicator from the EEG, A method of driving a functional electrical stimulation therapy apparatus based on a brain-computer interface for a leg function and a gait function to drive a FES unit mounted on a leg when the legs are greater than or equal to a threshold, A video output step of outputting a video signal; An EEG detection step of receiving an EEG signal detected by the EEG electrode unit through a signal collecting unit and detecting EEG waves by frequency intervals of SMR beta waves, Mid beta waves, and seta waves through digital filtering of received EEG signals; Detecting the EEG concentration indicator by calculating a power spectrum of an EEG wave of each frequency interval of SMR beta, Mid beta wave, and Ceta wave, which is obtained in the EEG detection step for each frequency section; An EEG concentration indicator and a threshold value comparison step for determining whether the EEG concentration index obtained in the EEG concentration index detection step is greater than or equal to a predetermined threshold value; And an FES stimulation signal generation step of generating an FES stimulation signal and outputting the FES stimulation signal to the FES driving unit if the EEG concentration indicator is equal to or greater than a preset threshold value in the EEG concentration index and threshold comparison step.

Description

[0001] The present invention relates to a brain-computer interface based functional electrical stimulator for functional and gait functions,

The present invention detects an EEG of a patient and detects an EEG concentration indicator from the detected EEG, while observing a training image of a leg and a walking of a monitor, And a brain-computer interface-based functional electrical stimulation therapy apparatus for exercising the legs and the gait according to the patient's will.

Stroke is a cerebrovascular disorder in which the supply of blood to the brain is blocked or bleeding occurs in the brain tissue resulting in a disorder of the blood supply to the brain. The stroke disorder pattern varies depending on the injured area and degree, but generally, hemiplegia, , Cognitive disorders, speech disorders, visual disturbances, and swallowing disorders. In addition, patients with stroke have a balance problem due to the asymmetrical posture because they support only the load of less than 43% of body weight in unbalance of strength, The ability to do so is reduced, resulting in abnormal walking.

The foot drop, one of the gait features of a stroke patient, is caused by partial or complete loss of exercise in the dorsi flexor, (circumducting gait) or excessively lifting the legs to walk. This type of walking is energy-intensive, which makes it easily tired, slows walking, is unsafe, and causes falls. Functional electrical stimulation therapy can be applied as one of the clinical interventions of the ankle to recover the loss of walking ability of a stroke patient with foot-and-mouth disease.

Functional Electrical Stimulation (FES) is a technique that is used to induce muscle contraction by electrical stimulation to muscles that are not subject to normal neural control in patients with central nervous disorders such as stroke, multiple sclerosis, In this method, electrical stimulation is applied to the tibial muscle to improve coordination ability in the walking cycle and improve the walking quality such as walking speed and angle of the ankle joint to the patient having the foot. However, functional electrical stimulation therapy is a simple and repetitive form, which has the disadvantage that the effect of exercise re-learning, which is an important factor in the recovery of stroke patients, is not effective because the patient's active will is not intervened.

To this end, the present invention proposes a functional electrical stimulation therapy device based on a Brain-Computer Interface (BCI) for the function of the lower limbs and the gait function.

 Brain-Computer Interface (BCI) is a field of Human Computer Interaction (HCI) that studies human-computer interaction. It measures the EEG signal in a certain state through brain waves, Related technology that extracts features, classifies them, and converts them into general control signals to control computers and devices. In other words, it refers to the technique of controlling any arbitrary device by analyzing brain waves in the process of brain activity in real time.

At present, there is not yet a research on brain-computer interface that stimulates the movement of the ankle according to the will of the stroke patient to treat the lower limb function and gait function.

Electroencephalogram (EEG) is an electrical signal that is measured using an electrode attached to the surface of the brain. As shown in the following table, EEG is generally classified into two groups according to the frequency range of oscillation: delta wave (0.5 to 4.99 Hz), theta wave (5 to 7.99 Hz), alpha wave (8 to 11.99 Hz) And gamma waves (30 to 50 Hz).

EEG type Eyes amplitude State of the brain Delta
(0.5 to 4.99 Hz) Closed High Deep sleep (completely shut out sensation and awakening to the outside) Low It may lead to intuitive insights. Open High It is activated when there is brain damage, which interferes with normal accidents. Low Normal state Theta
(5-7.99 Hz) Closed High Sleep state (with no sense of external or awakening) Low Meditation (increased spiritual identity and increased creative inspiration) Open High Emotional memory, fancies, increased sleepiness, attention deficit, decreased concentration, etc. Low Normal state Alpha
(8-11.99 Hz) Closed High Very high levels of awakening to the outside Low Comfortable, bridging bridges between consciousness and subconscious Open High Loosening, lack of motivation, loss of concentration, and depression. Low Normal state

Alpha waves usually appear in relaxed states such as relaxation, but the amplitude increases with more stable and relaxed conditions. When stable alpha waves appear, they appear when you close your eyes and are in a true state. When you open your eyes and look at an object or become mentally excited, alpha waves are suppressed.

Theta wave is an EEG that appears when you are sleepy or unconscious. It is called "drowsy" or "slow wave". It is an EEG that appears when you fall asleep.

Beta waves are brain waves when consciousness is awake, stress waves, anxiety, tension, and other activity waves. As shown in the following table, the beta wave is divided into SMR beta wave, Mid beta wave and Hign beta wave.

EEG type Eyes amplitude State of the brain SMR Beta
(12-15 Hz) Closed - Normally, it appears low, and when it is high, Open Low Degradation of brain function such as developmental disorder Mid A state that concentrates comfortably on the outside without moving.
Controls impulsivity, hyperactivity, and suppresses unnecessary reactions. High Excessively high means over-awakening Mid Beta
(16-20 Hz) Closed - Usually, it appears low, and when it appears high, Open Low Degradation of brain function such as developmental disorder Mid The state actively focusing on the outside.
Activate cognitive processes, improve sleep status, improve concentration High Excessively high means over-awakening High Beta
(21-35 Hz) Closed - Usually, it appears low, and when it appears high, Open - It usually appears low or stable. High Tension, anxiety. The level of arousal is so high that it is easily excited,
Anxiety, high stress, and stiffness.
It is also active in all kinds of addiction symptoms.

The SMR beta (sensory motor rhythm, low beta) is 12 ~ 15Hz, and it is the brain wave which appears when the concentration of external information is strengthened in the state of attention.

Mid (mid) The beta wave is 16 ~ 20Hz. It is in a state of concentration, activity, awakening, and the state at the time of task execution.

 High Beta waves are 21-35 Hz, and are associated with inhibition, with tension, excitement, and stress.

It is necessary to quantitatively understand how much each vibration component occupies in measured EEG, and it is mainly analyzed by power spectrum. The power spectrum refers to pre-converting the autocorrelation function. Generally speaking, it refers to the power (unit: dB) of the log scale by performing an FFT (fast pre-transform) on an EEG signal.

Generally, the EEG concentration index is expressed by Equation (1).

In other words, the EEG concentration index is a value obtained by dividing the power spectrum of the SMR beta wave and the power spectrum of the mid beta wave by theta wave power spectrum.

According to the present invention, the EEG is detected, the EEG is detected from the detected EEG, and the FES is measured according to the EEG concentration indicator. The present invention is to provide a functional electrical stimulation therapy device based on a brain-computer interface for an underarm function and a gait function, which enables supplementary driving so as to perform training of the legs and the gait according to the patient's will.

SUMMARY OF THE INVENTION It is an object of the present invention to provide a method and apparatus for monitoring an EEG of a patient, It is intended to provide a functional electrical stimulation therapy device based on a brain-computer interface for a leg function and a gait function that enables the FES part mounted on the lower limb to be driven according to the concentration index, .

Another problem to be solved by the present invention is to provide a method and apparatus for functional electrical stimulation therapy based on a brain-computer interface, in which an FES unit is driven when an EEG concentration threshold is abnormal, a threshold value and a stimulus intensity can be adjusted according to a user, And to provide a functional electrical stimulation therapy device based on a brain-computer interface for a leg function and a gait function, which is adapted to be stored and applied to the next treatment.

In order to solve the technical problem of the present invention, a functional electrical stimulation therapy apparatus based on a brain-computer interface for a leg function and a gait function of the present invention includes a left front head Fp1 of a patient viewing a leg or foot training image through a monitor, An EEG electrode unit including two signal electrodes mounted on the right front head Fp2 to detect an EEG; An EEG signal preprocessing unit for removing noise from the EEG received from the EEG electrode unit and amplifying the EEG signal; A signal collecting unit for converting an EEG signal received by the EEG signal preprocessing unit into a digital signal; SMR beta, mid beta, and theta waves were detected from the EEGs received from the signal collecting unit, and SMR beta, mid beta, and theta waves were measured, and EEG concentration was measured A control unit for generating an FES driving signal if the FES driving signal is equal to or greater than the FES driving signal; And an FES unit for outputting a fine current to the FES electrode unit according to an FES (Functional Electric Stimulation) driving signal received from the control unit.

In addition, the functional electrical stimulation therapy apparatus based on the brain-computer interface for the leg function and the gait function of the present invention includes an electroencephalogram (EEG) electrode unit mounted on a frontal part of a patient who views a leg or foot training image through a monitor, ; An EEG signal preprocessing unit for removing noise from the EEG received from the EEG electrode unit and amplifying the EEG signal; A signal collecting unit for converting an EEG signal received by the EEG signal preprocessing unit into a digital signal; SMR beta, mid beta, and theta waves were detected from the EEGs received from the signal collecting unit, and SMR beta, mid beta, and theta waves were measured, and EEG concentration was measured A control unit for generating an FES driving signal if the FES driving signal is equal to or greater than the FES driving signal; And a FES unit having two stimulation electrodes mounted on the proximal and distal portions of the tibialis ankle, which is an antagonistic muscle of the plantar flexor, and outputting a fine current to the FES electrode unit according to the FES (functional electrical stimulation) driving signal received from the control unit .

The functional electrical stimulation therapy apparatus further includes a camera for capturing a motion image of the patient's foot equipped with the FES electrode unit and transmitting the motion image to the control unit, and the control unit outputs the motion image of the patient's foot to the monitor.

The FES electrode unit is composed of two magnetic pole electrodes, and the two magnetic pole electrodes are mounted on the proximal and distal portions of the tibialis ankle, which is the antagonistic muscle of the plantar flexor, and the EEG electrode unit is connected to the left frontal head Fp1 and the right front head Fp2 A reference electrode mounted on the back of the right earlobe, and a ground electrode mounted on the left earlobe.

The EEG concentration is the sum of the power spectrum of the SMR beta wave and the power spectrum of the mid beta wave, divided by theta wave power spectrum.

From the EEG received from the signal collecting unit, we obtain further alpha waves and beta waves through digital filtering, and further obtain power spectra of alpha waves and beta waves.

An absolute power spectrum, which is the power spectrum of the EEG that is received from the signal collecting unit but is not subjected to digital filtering, is obtained, and a relative power spectrum obtained by normalizing the power spectrum of the alpha wave and the beta wave to the absolute power spectrum is further obtained.

And outputs at least one of an absolute power spectrum, a relative alpha wave power spectrum, a relative beta wave power spectrum, and an EEG concentration indicator to the monitor unit.

In digital filtering, the alpha wave is detected by performing a band pass filter (band pass filter) ring of 8 to 12 Hz, the SMR beta wave is detected by performing band pass filtering of 12 to 15 Hz, and the mid beta wave is detected by band pass filtering of 16 to 20 Hz And theta waves are detected by band-pass filtering at 5 to 8 Hz.

The threshold value is obtained by performing an average of 10 concentration indices obtained by performing 10 intensive tests on the patient before treatment, and the threshold value is used as a threshold value. The magnitude of the fine current to the FES electrode portion is the intensity of the stimulation current Is changed from 1 mA to 50 mA, and the ankle joint reaction is initiated when the current is shed.

A key input unit having a start key and an end key and capable of setting a frequency, a contraction time, a relaxation time, a pulse width, and a stimulus intensity; And a memory unit for storing a threshold value and a stimulus intensity for each patient.

The EEG signal preprocessing unit includes a preamplifier for differentially amplifying the EEG signal output from the EEG electrode unit; A notch filter for eliminating 50 Hz or 60 Hz power supply noise from the EEG received from the preamplifier; A high-pass filter for passing an EEG signal at a frequency of 5 Hz or more from the EEG signal output from the notch filter; A first amplifier for amplifying an EEG signal output from the high-pass filter; A low pass filter for passing a signal of 50 Hz or less from the EEG signal output from the first amplifier; And a second amplifier for amplifying the EEG signal output from the low-pass filter.

The EEG electrode is attached to the front end of the band to which the EEG electrode is attached, and the velcro is provided at both ends of the band.

Further, the present invention is characterized in that an EEG electrode portion for detecting an EEG is mounted on a frontal portion of a patient who views a leg or foot training image through a monitor, and the controller detects an EEG concentration indicator from the EEG, And driving the FES unit mounted on the lower limb when the walking distance is greater than or equal to a predetermined distance, the method comprising: reading a training image of a leg and a walk from a memory, A video output step of outputting a video signal; An EEG detection step of receiving an EEG signal detected by the EEG electrode unit through a signal collecting unit and detecting EEG waves by frequency intervals of SMR beta waves, Mid beta waves, and seta waves through digital filtering of received EEG signals; Detecting the EEG concentration indicator by calculating a power spectrum of an EEG wave of each frequency interval of SMR beta, Mid beta wave, and Ceta wave, which is obtained in the EEG detection step for each frequency section; An EEG concentration indicator and a threshold value comparison step for determining whether the EEG concentration index obtained in the EEG concentration index detection step is greater than or equal to a predetermined threshold value; And an FES stimulation signal generation step of generating an FES stimulation signal and outputting the FES stimulation signal to the FES driving unit if the EEG concentration indicator is equal to or greater than a preset threshold value in the EEG concentration index and threshold comparison step.

And terminating the FES stimulation signal generation step, when the end key of the key input unit is turned on or the timer completes the set time, and if not, returning to the EEG detection step according to the frequency interval.

In the EEG detection step according to the frequency section, the EEG and BETA waves are further detected from the EEG signals received through the signal collecting unit by digital filtering, and the power spectra of the EEG, ALPHA, and BETA waves not subjected to digital filtering are obtained, Obtain an alpha wave power spectrum and a relative beta wave power spectrum.

If the EEG concentration indicator is smaller than the preset threshold value in the EEG concentration threshold comparison step, the controller goes to the end determination state without outputting the FES stimulation signal.

According to the functional electrical stimulation therapy apparatus based on the brain-computer interface for the leg function and the gait function of the present invention, the patient performs the same training while watching the training image of the legs and the gait of the monitor, The EEG concentration indicator is detected from the detected EEG, and the FES section is driven according to the EEG concentration index, thereby training the leg and the gait according to the patient's will.

Further, in the functional electrical stimulation therapy based on the brain-computer interface, the FES unit is driven when the EEG concentration is abnormal, and the threshold value can be adjusted according to the user and the situation. A personalized therapy using a functional electrical stimulation therapy device based on a brain-computer interface for the lower limb function and the gait function is possible.

1 is a conceptual diagram for explaining a functional electrical stimulation therapy apparatus based on the brain-computer interface of the present invention.
2 is a schematic block diagram of a functional electrical stimulation therapy apparatus based on a brain-computer interface according to an embodiment of the present invention.
3 is an explanatory view illustrating an electrode attachment site for EEG measurement in the present invention.
FIG. 4 is a block diagram for explaining an example of the configuration of the EEG detecting unit of FIG. 2. FIG.
5 is a block diagram for explaining another example of the configuration of the EEG detecting unit of FIG.
6 is an example of the EEG electrode portion of the present invention.
7 is an example of a presentation image presented by the display unit of FIG.
8 is an example of a presentation image in which ankle motion is performed at various dorsiflexion angles.
FIG. 9 shows a method of driving a control unit of a functional electrical stimulation apparatus based on the brain-computer interface of FIG. 2;

Hereinafter, a functional electrical stimulation therapy apparatus based on a brain-computer interface for a grounding function and a walking function of the present invention will be described in detail with reference to the accompanying drawings.

1 is a conceptual diagram for explaining a functional electrical stimulation therapy apparatus based on the brain-computer interface of the present invention.

In the functional electrical stimulation therapy apparatus based on the brain-computer interface of the present invention, a patient sits in a chair and watches a presentation image presented on one side of a monitor of the monitor unit 310, moves his / her foot The EEG electrode unit 110 mounted on the patient's head detects the EEG signal and transmits it to the control unit 300 through the EEG signal preprocessing unit 150 and the signal collecting unit 250. [

The control unit 300 obtains the concentration index from the received EEG, generates an FES driving signal according to the concentration index, and transmits the FES driving signal to the FES driving unit 450. The FES driving unit 450 drives the FES driving signal The FES electrode unit 410 flows a micro current to excite the muscles of the patient's legs, thereby moving the legs of the patient. At this time, the camera unit 500 captures the movement of the leg of the patient and transmits it to the control unit 300. The control unit 300 transmits the motion image of the patient's foot to the monitor unit 310, And outputs an image of the movement of the leg of the patient to the other side of the leg.

This allows the patient to move his / her feet by his or her own will, and rehabilitate his / her feet with the help of FES (Functional Electrical Stimulation).

In some cases, the camera unit 500 may be omitted. In this case, only the presentation image is output to the monitor unit 310. In FIG. 1, EEG transmission and FES driving signal transmission are shown by wire, but in some cases they can be wireless.

FIG. 2 is a schematic block diagram of a functional electrical stimulation apparatus based on a brain-computer interface according to an embodiment of the present invention, and FIG. 3 is an explanatory view illustrating an electrode attachment site for EEG measurement in the present invention.

2, the functional electrical stimulation apparatus based on the brain-computer interface of the present invention includes an EEG detecting unit 100, a signal collecting unit 250, a control unit 300, a monitor unit 310, a key input unit 320, A memory unit 330, a D / A conversion unit 350, an FES unit 400, and a camera unit 500.

The EEG detecting unit 100 includes an EEG electrode unit 110 and an EEG signal preprocessing unit 150 as means for detecting an EEG signal and detecting a beta wave and a set wave.

The EEG electrode unit 110 has two signal electrodes, and also has a reference electrode and a ground electrode (see FIG. 3). The two signal electrodes are mounted on the frontal lobe of both right and left sides with respect to the median. Electrode attachments were performed by monopolar derivation in two areas of the head surface. Electrode attachment locations were 10 to 20 electrodes according to the International Electrode Arrangement, Frontopolar 1, Fp1, The reference electrode is attached to the right earlobe, and the ground electrode is attached to the left earlobe. The EEG electrode unit 110 may use an AgCl electrode.

The EEG signal preprocessing unit 150 removes power source noise, amplifies, and detects an EEG signal including an alpha wave, a beta wave, and a setter wave.

The EEG signal preprocessing unit 150 passes and amplifies the EEG signal of 5 Hz to 50 Hz and then converts the EEG signal into a digital signal through the signal collecting unit 250 and transmits the digital signal to the controller 300. The controller 300 performs digital filtering To detect SMR beta waves, Mid beta waves, and theta waves.

The signal collecting unit 250 converts the output of the EEG signal preprocessing unit 150 into a digital signal and transmits the digital signal to the controller 300. An A / D converter may be used instead of the signal collecting unit 250.

The control unit 300 performs overall control of the functional electrical stimulation therapy apparatus based on the brain-computer interface. The control unit 300 reads an image for leg and walking stored in the memory unit 330 and outputs the read image to the monitor unit 310. The control unit 300 receives the start signal from the key input unit 320, , Mid beta wave, and theta wave are detected, and the power spectrum is obtained by performing FFT on each of the detected alpha wave, SMR beta wave, Mid beta wave, and theta wave, and EEG concentration index is obtained from the equation (1). That is, the EEG concentration index, which is the value obtained by dividing the sum of the power spectrum of the SMR beta wave and the power spectrum of the mid beta wave by the Seta power spectrum, is obtained.

If the EEG concentration indicator is higher than or equal to the threshold value, the controller 300 generates an FES stimulation signal and outputs the FES stimulation signal to the FES driver 450. In addition, the control unit 300 receives the photographed image of the motion of the leg of the patient from the camera unit 500, and transmits the received photographed image to the monitor unit 310 for output. Further, when the control unit 300 receives the end signal from the key input unit (that is, when the end flag is set), the control unit 300 ends.

In particular, the controller 300 detects an alpha wave, an SMR beta wave, a mid beta wave, and a theta wave from the received EEG signal through digital filtering in order to detect the alpha wave, the SMR beta wave, the mid beta wave and the theta wave . In this case, the alpha wave is an output detected by performing a band pass filter (band pass filter) ring of 8 to 12 Hz, the SMR beta wave is an output detected by performing a band pass filter (band pass filter) ring of 12 to 15 Hz, Wave is a detected output obtained by performing a band pass filter (band pass filter) ring of 16 to 20 Hz, and the theta wave is an output detected by performing a band pass filter (band pass filter) ring of 5 to 8 Hz.

In some cases, the EEG signal preprocessing unit 150 does not detect the alpha wave, the SMR beta wave, and the Mid beta wave through the digital filtering in the control unit 300 and outputs the alpha wave, SMR beta, Mid beta wave, And the controller 300 may receive the detected EEG waves, the SMR beta waves, and the EEG waves of the Mid beta waves through the signal collecting unit 250.

In the EEG measurement, the concentration index is quantified by Equation (1), and the theta rhythm is reduced in the concentrated state, and the SMR (12-15) indicating the unfocused attention ability and the focused attention ), Which means Mid-Beta rhythm (16-20).

The control unit 300 may be a microcontroller (MCU), a microprocessor, or a computer.

In the present invention, a current is manually controlled and flowed from 1 mA to 50 mA to the tibialis anterior muscle of the patient (subject) before the treatment (before training), and the magnitude of the current at which the ankle joint reaction of the patient (subject) Perform ten intensive examinations of the patient (subject) to obtain the average of the ten concentration indicators and set them as a threshold value (threshold value).

In addition, the present invention allows the patient (examinee) to concentrate on ankle movements while watching the monitor screen at the time of treatment, and when the value of the concentration index exceeds the threshold value, the control unit 300 generates an FES driving signal, 400). As a result, a functional electrical stimulation is induced according to brain changes (EEG signal) according to the concentration of the patient.

The application period of the functional electrical stimulation training based on the brain-computer interface of the present invention is applied once for 30 minutes and can be performed once a day, three times a week for 5 weeks.

The monitor unit 310 displays training images of the legs and the gait, and various ankle training related images as presented images. An ankle training-related image may be provided with a training image for training the tibial muscle and the like, and an ankle training-related image may be displayed on the ankle-related bending motion-related image. In addition, the monitor unit 310 displays the EEG concentration indicator, the power spectra of the EEG, and the like, thereby enabling the patient to know his / her degree of concentration. Also, the monitor unit 310 outputs the foot motion image of the patient received from the control unit 300.

The key input unit 320 includes a start key and an end key, and can set a frequency, a contraction time, a relaxation time, a pulse width, and a stimulus intensity.

The memory unit 330 stores a threshold value and a stimulus intensity for each patient, and also stores a training image of a leg and a gait to be displayed on the monitor unit 310, and the like.

The D / A converter 350 converts the FES driving signal into an analog signal by the controller 300 and transmits the analog signal to the FES driver 450 of the FES unit 400.

The FES unit 400 receives the FES driving signal from the control unit 300 through the D / A converter 350 and outputs a fine current to output a functional electrical stimulus. The FES unit 400 includes an FES electrode unit 410 and an FES driver 450.

The FES electrode unit 410 is a stimulation electrode, and is mounted on a muscle associated with a function to be trained. The FES electrode unit 410 may be formed of a pair of surface electrodes 50 x 50 mm in size.

FES electrodes can be placed at the proximal part of the tibialis anterior (5 cm below the fibular head), which is the antagonistic muscle of the plantar flexor, and the active electrodes can be placed at the distal part (5 cm above the fibula). The intensity of the stimulation current is manually adjustable from 1mA to 50mA depending on the reaction of the ankle to the stimulus. The application period of FES is 30 minutes once, and it can be carried out once a day, three times a week for 5 weeks.

The FES driving unit 450 receives the FES driving signal from the controller 300 through the D / A converter 350 and outputs a fine current through the FES electrode unit 410 according to the FES driving signal, .

The camera unit 500 photographs the movement of the legs of the patient and transmits them to the control unit 300. Only one camera unit 500 may be provided to photograph one side foot image of a patient or both left and right sides of a patient to photograph both side foot images of the patient or may be provided on left and right and front sides of the patient.

In the present invention, the controller 300 extracts and analyzes only the 5 to 50 Hz intervals of EEG, and not only calculates power spectra of alpha waves, beta waves, theta waves, etc., And a relative power spectrum obtained by normalizing each power spectrum of the alpha wave and the beta wave by the absolute power spectrum is obtained and these results are output to the monitor unit 310. [ That is, the detected EEG signal is subjected to a fast fourier transform (FFT), which is a filtering method for converting the signal to a frequency. The FFT is represented by the power spectral analysis, which represents the contribution by frequency component in the frequency space, the X axis represents the frequency, the Y axis represents the power value, and the amplitude according to the specific frequency. The value calculated at this time is an absolute band power, which is a value obtained by squaring the amplitude of the signal. Relative band power refers to the absolute power ratio of a specific frequency band to absolute power, has a value between 0 and 1, and is expressed as a percentage (0 to 100%). Relative power analysis can be different for each subject It is used to compensate for individual brain wave differences such as differences in skull thickness and differences in tension at the time of measurement. Particularly, in the present invention, relative alpha waves (8 to 12/5 to 50) and relative beta waves (12 to 20/5 to 50) are analyzed.

FIG. 4 is a block diagram for explaining an example of the configuration of the EEG detecting unit of FIG. 2. FIG.

The EEG detecting unit 100 includes an EEG electrode unit 110 and an EEG signal preprocessing unit 150. The EEG signal preprocessing unit 150 includes a preamplifier 160, a notch filter 170, a high-pass filter 180, A first amplifier 190, a low pass filter 210, and a second amplifier 220.

The preamplifier 160 differentially amplifies the EEG signals output from the two signal electrodes of the EEG electrode unit 110.

The notch filter 170 removes 50 Hz or 60 Hz power noise with the band-stop filter.

The high-pass filter 180 passes an EEG signal at a frequency of 5 Hz or more from the EEG signal output from the notch filter 170.

The first amplifier 190 amplifies the EEG signal output from the high-pass filter 180.

The low pass filter 210 passes a signal of 50 Hz or less from the EEG signal output from the first amplifier 190.

The second amplifier 220 amplifies the EEG signal output from the low-pass filter 210. The output signal of the second amplifier 220 is transmitted to the control unit 300 through the signal collecting unit 250.

Only the EEG waves of 5 to 50 Hz are detected through the high-pass filter 180 and the low-pass filter 210.

5 is a block diagram for explaining another example of the configuration of the EEG detecting unit of FIG.

The EEG detecting unit 100 includes an EEG electrode unit 110 and an EEG signal preprocessing unit 150. The EEG signal preprocessing unit 150 includes a preamplifier 160, a notch filter 170, 230, and the EEG electrode unit 110, the preamplifier 160, and the notch filter 170 are shown in FIG.

The signal pre-processing unit 230 according to the waveform includes a setter signal pre-processing unit 260, an SMR beta wave signal preprocessing unit 270, a Mid beta wave signal preprocessing unit 280 and an alpha wave signal preprocessing unit 290.

The prepaper signal preprocessing unit 260 includes a setter band-pass filter 263 and a set-wave amplifier 267. The set-band band-pass filter 263 performs a band-pass filter (band pass filter) ring of 5 to 8 Hz, The set-a-wave signal filtered and detected is amplified by a setter amplifier 267.

The SMR beta wave signal preprocessor 270 includes an SMR beta wave band pass filter 273 and an SMR beta wave wave amplifier 277. The SMR beta wave band pass filter 273 includes a 12 to 15 Hz band pass filter Pass filtering), and the SMR beta wave amplifier 277 amplifies the filtered and detected SMR beta wave signal.

The Mid beta wave signal preprocessor 280 includes a Mid beta wave band pass filter 283 and a Mid beta wave wave filter 287. The Mid beta wave band pass filter 283 includes a band pass filter Pass filter), and the Mid Beta wave amplifier 287 amplifies the detected Mid Beta wave signal filtered in this manner.

The alpha wave signal preprocessor 290 includes an alpha wave band pass filter 293 and an alpha wave amplifier 297. The alpha wave band pass filter 293 includes a band pass filter And the A / D converter 297 amplifies the filtered and detected alpha wave signal.

6 is an example of the EEG electrode portion of the present invention.

As shown in FIG. 6, the EEG electrode unit 110 has a band-type Velcro on both ends thereof and is fixed to the head by adjusting the circumference when it is attached to the head.

FIG. 7 is an example of a presentation image presented by the display unit of FIG. 2, and FIG. 8 is an example of a presentation image of performing ankle motion at various dorsiflexion angles.

As shown in FIG. 7, an image of the ankle which is raised up and down can be presented to the patient. In this case, according to the patient's condition, as shown in FIG. 8, it is possible to output the presentation image for ankle motion at various dorsiflexion angles to the display unit 310. FIG. Fig. 8A is a presentation image with a deflection angle of 10 degrees, Fig. 8B is a presentation image with a deflection angle of 15 degrees, Fig. 8C is a presentation image with a deflection angle of 20 degrees, ) Is a presentation image with a dorsiflexion of 25 degrees.

FIG. 9 shows a method of driving a control unit of a functional electrical stimulation apparatus based on the brain-computer interface of FIG. 2;

When the start key of the key input unit 320 is turned on, the start flag of the control unit 300 is set. If the start flag is not set, the start flag is set until the start flag is set (S105) .

In the initialization step, the setting mode, the threshold value, and the like are read, and the timer and the like are cleared (S110).

In the video output step, the training image of the legs and legs read from the memory 330 is output to the monitor unit 310 (S115).

In the EEG detection step according to the frequency interval, EEG signals received from the signal collecting unit 250 are subjected to digital filtering to detect EEG waves of frequency sections such as alpha waves, SMR beta waves, Mid beta waves, theta waves, and beta waves ).

In the power spectral computation step, the power spectrum of the EEG for each frequency interval, the relative alfa power spectrum and the relative beta power spectrum, which are obtained in the EEG detection step for each frequency interval, are obtained (S125).

In the EEG concentration detection step, an EEG concentration indicator is calculated using SMR beta wave, Mid beta wave, and power spectrum of a setta wave (S130).

In step S140, it is determined whether the EEG concentration index obtained in the EEG concentration detection step is equal to or greater than a preset threshold value in step S160. If the EEG concentration index is less than the threshold value, the FES stimulation signal is not output in step S145. , And goes to the termination judgment step S160.

In the FES stimulation signal generation step, if the EEG concentration indicator is equal to or greater than a preset threshold value in the EEG concentration threshold and threshold comparison step, the FES stimulation signal is generated and output to the FES driver 450 (S150).

When the end key of the key input unit 320 is turned on or the timer reaches the set time, the end flag of the control unit 300 is set and it is determined whether or not the end flag is set (S160). If the end flag is not set, the process returns to the EEG detection step (S120) for each frequency interval and ends if the end flag is set.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, but, on the contrary, Modification is possible. Accordingly, the spirit of the present invention should be understood only in accordance with the following claims, and all equivalents or equivalent variations thereof are included in the scope of the present invention.

100: EEG detecting unit 110: EEG electrode unit
150: EEG signal preprocessing unit 160: Preamplifier
170: notch filter 180: high-pass filter
190: first amplifier 210: low pass filter
220: second amplifier 250: signal collecting unit
300: control unit 310: monitor unit
320: key input unit 330: memory unit
350: D / A conversion unit 400: FES unit
410: FES electrode unit 450: FES driving unit

Claims (22)

An EEG electrode unit for detecting an EEG including two signal electrodes mounted on a left frontal head Fp1 and a right front head Fp2 of a patient viewing the lower or foot training image through a monitor;
An EEG signal preprocessing unit for removing noise from the EEG received from the EEG electrode unit and amplifying the EEG signal;
A signal collecting unit for converting an EEG signal received by the EEG signal preprocessing unit into a digital signal;
SMR beta, mid beta, and theta waves were detected from the EEGs received from the signal collecting unit, and SMR beta, mid beta, and theta waves were measured, and EEG concentration was measured A control unit for generating an FES driving signal if the FES driving signal is equal to or greater than the FES driving signal;
An FES unit for outputting a fine current to the FES electrode unit according to an FES (Functional Electric Stimulation) driving signal received from the control unit;
And a brain-computer interface for functional and gait functions. The method according to claim 1,
Further comprising a camera for picking up a motion image of the patient's foot equipped with the FES electrode unit and transmitting the motion image to the control unit, wherein the control unit outputs the motion image of the patient's foot to the monitor, Interface based functional electrical stimulation therapy. An EEG electrode unit mounted on a frontal part of the patient for monitoring the leg or foot training image through a monitor to detect an EEG;
An EEG signal preprocessing unit for removing noise from the EEG received from the EEG electrode unit and amplifying the EEG signal;
A signal collecting unit for converting an EEG signal received by the EEG signal preprocessing unit into a digital signal;
SMR beta, mid beta, and theta waves were detected from the EEGs received from the signal collecting unit, and SMR beta, mid beta, and theta waves were measured, and EEG concentration was measured A control unit for generating an FES driving signal if the FES driving signal is equal to or greater than the FES driving signal;
An FES unit having two stimulation electrodes mounted on a proximal and distal portions of an anterior tibialis muscle, which is an antagonistic muscle of the plantar flexor, and outputting a fine current to the FES electrode unit according to an FES (Functional Electrical Stimulation) driving signal received from the control unit;
And a brain-computer interface for functional and gait functions. The method of claim 3,
Further comprising a camera for picking up a motion image of the patient's foot equipped with the FES electrode unit and transmitting the motion image to the control unit, wherein the control unit outputs the motion image of the patient's foot to the monitor, Interface based functional electrical stimulation therapy. 3. The method according to any one of claims 1 to 3,
Wherein the FES electrode portion is composed of two magnetic pole electrodes and the two magnetic pole electrodes are mounted on a proximal and distal portion of an anterior tibialis muscle that is an antagonistic muscle of a plantar flexor. Electric stimulation therapy device. 5. The method according to any one of claims 3 to 4,
The EEG electrode unit includes two signal electrodes mounted on the left front head Fp1 and the right front head Fp2, a reference electrode mounted on the back of the right earlobe, a ground electrode mounted on the left earlobe, And a brain-computer interface for functional and gait functions. 5. The method according to any one of claims 1 to 4,
A functional electrical stimulus based on a brain-computer interface for the function of the lower limb and the gait function, characterized in that a value obtained by adding the power spectrum of the SMR beta wave and the power spectrum of the mid beta wave is divided by a seta power spectrum. Therapeutic equipment. 8. The method of claim 7,
A brain-computer interface for a leg function and a gait function, characterized by further obtaining an alpha wave and a beta wave from the EEG received from the signal collecting unit through digital filtering, and further obtaining a power spectrum of an alpha wave and a beta wave. Based functional electrical stimulation therapy. 9. The method of claim 8,
Characterized in that an absolute power spectrum which is a power spectrum of an EEG that is received from the signal collecting unit but is not subjected to digital filtering is obtained and further a relative power spectrum obtained by normalizing the power spectrum of the alpha wave and the beta wave respectively by the absolute power spectrum is further obtained. Functional electrical stimulation therapy based on brain - computer interface for functional and gait functions. 10. The method of claim 9,
Characterized in that at least one of an absolute power spectrum, a relative alpha wave power spectrum, a relative beta wave power spectrum, and an EEG concentration indicator is output to a monitor unit. 9. The method of claim 8,
In digital filtering,
The alpha wave is detected by performing a band pass filter (band pass filter) ring of 8 to 12 Hz,
The SMR beta wave is detected by band-pass filtering at 12 to 15 Hz,
The mid-beta wave is detected by band-pass filtering at 16 to 20 Hz,
Wherein the theta wave is detected by band-pass filtering at 5 to 8 Hz. The functional electrical stimulation therapy device is based on a brain-computer interface for the leg and the gait functions. 8. The method of claim 7,
The threshold value is obtained by performing an average of 10 concentration indices obtained by performing 10 intensive tests on a patient before treatment and using the average value as a threshold value. The functional electrical stimulation therapy apparatus based on a brain- . 8. The method of claim 7,
The magnitude of the microcurrent to the FES electrode section is the current magnitude at which ankle joint response begins to occur when the intensity of the stimulation current is varied from 1 mA to 50 mA in the patient ' s tibialis anterior muscle prior to treatment. Functional electrical stimulation therapy based on brain - computer interface. 8. The method of claim 7,
A key input unit having a start key and an end key and capable of setting a frequency, a contraction time, a relaxation time, a pulse width, and a stimulus intensity;
A memory unit for storing patient-specific threshold values and stimulus intensity;
Further comprising a brain-computer interface for functional and gait functions. 8. The method of claim 7,
The EEG signal pre-
A preamplifier for differentially amplifying the EEG signal output from the EEG electrode unit;
A notch filter for eliminating 50 Hz or 60 Hz power supply noise from the EEG received from the preamplifier;
A high-pass filter for passing an EEG signal at a frequency of 5 Hz or more from the EEG signal output from the notch filter;
A first amplifier for amplifying an EEG signal output from the high-pass filter;
A low pass filter for passing a signal of 50 Hz or less from the EEG signal output from the first amplifier;
A second amplifier for amplifying an EEG signal output from the low pass filter;
And a brain-computer interface for functional and gait functions. 8. The method of claim 7,
A functional electrical stimulation apparatus based on a brain-computer interface for a leg function and a gait function, characterized in that the band equipped with the EEG electrode unit is wound around the front head, and a velcro is provided at both ends of the band. (EEG) detector for detecting an EEG on the frontal part of the patient who views the leg or foot training image through a monitor, and when the controller detects the EEG concentration indicator from the EEG and the EEG concentration indicator is equal to or greater than a predetermined threshold A method for driving a functional electrical stimulation therapy apparatus based on a brain-computer interface for a leg function and a gait function for driving an FES unit mounted on a base,
Reading a training image of a leg or foot from a memory and outputting the training image to a monitor unit;
An EEG detection step of receiving an EEG signal detected by the EEG electrode unit through a signal collecting unit and detecting EEG waves by frequency intervals of SMR beta waves, Mid beta waves, and seta waves through digital filtering of received EEG signals;
Detecting the EEG concentration indicator by calculating a power spectrum of an EEG wave of each frequency interval of SMR beta, Mid beta wave, and Ceta wave, which is obtained in the EEG detection step for each frequency section;
An EEG concentration indicator and a threshold value comparison step for determining whether the EEG concentration index obtained in the EEG concentration index detection step is greater than or equal to a predetermined threshold value;
An FES stimulation signal generation step of generating an FES stimulation signal and outputting it to the FES driving unit if the EEG concentration indicator is equal to or greater than a preset threshold value in the EEG concentration index and threshold comparison step;
Wherein the computer-readable medium is a computer-readable medium having computer-executable instructions for performing the method. 18. The method of claim 17,
Ending step of stopping the key input unit when the end key of the key input unit is turned on or the timer is completed after the FES stimulation signal generation step, and if not, returning to the EEG detection step of each frequency interval;
Further comprising a brain-computer interface for a leg-function and a gait function. 18. The method of claim 17,
In the EEG detection step according to the frequency section, the EEG and BETA waves are further detected from the EEG signals received through the signal collecting unit by digital filtering, and the power spectra of the EEG, ALPHA, and BETA waves not subjected to digital filtering are obtained, A method for driving a functional electrical stimulation apparatus based on a brain-computer interface for a leg function and a gait function, characterized by obtaining an alpha wave power spectrum and a relative beta wave power spectrum. 19. The method of claim 18,
Wherein when the EEG concentration indicator is smaller than a preset threshold value in the step of comparing the EEG concentration index and the threshold value, the control unit goes to the end determination state without outputting the FES stimulation signal. A method for driving a functional electric stimulation therapy apparatus based on the method. 18. The method of claim 17,
Wherein the FES electrode portion of the FES portion is composed of two stimulating electrodes and the two stimulation electrodes are mounted on a proximal and distal portion of an anterior tibialis muscle that is an antagonistic muscle of a plantar flexural muscle. A method of driving a functional electric stimulation therapy apparatus. 18. The method of claim 17,
The EEG electrode unit includes two signal electrodes mounted on the left front head Fp1 and the right front head Fp2, a reference electrode mounted on the back of the right earlobe, a ground electrode mounted on the left earlobe, And a brain-computer interface for the functional and gait functions.

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