WO2003075760A1 - Method of determining the quality of an aep (auditory evoked potential) signal - Google Patents
Method of determining the quality of an aep (auditory evoked potential) signal Download PDFInfo
- Publication number
- WO2003075760A1 WO2003075760A1 PCT/DK2003/000143 DK0300143W WO03075760A1 WO 2003075760 A1 WO2003075760 A1 WO 2003075760A1 DK 0300143 W DK0300143 W DK 0300143W WO 03075760 A1 WO03075760 A1 WO 03075760A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- snr
- signal
- aep
- calculated
- value
- Prior art date
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4821—Determining level or depth of anaesthesia
-
- 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]
- A61B5/377—Electroencephalography [EEG] using evoked responses
- A61B5/38—Acoustic or auditory stimuli
Definitions
- This invention relates to a method of determining the quality of signals which are indicative of the level of consciousness of a patient, said signals being determined by subjecting a patient to a number N of audio stimulus, and monitoring auditory evoked potentials (AEP) produced by the patient.
- AEP auditory evoked potentials
- a measuring apparatus for carrying out measurements of AEP signals is described in the Danish patent application no. PA 2001 00381 , which was not published at the day of the filing of the present application.
- the AEP signal is an evoked electrical activity, embedded in EEG activity that is elicited in a neural pathway by acoustic sensory stimulus.
- the AEP is thus the synchronised response to the acoustic stimulus provided by a train of acoustic pulses.
- a problem in the analysis of the AEP activity occurs when background activity, such as EEG, Electro Encephalogram activity and EMG, Electro Myogram, artefacts and the like are present.
- a new method according to the invention is based on an estimation of an SNR (signal to noise potential) based on the use of a previous AEP, as explained in more detail later.
- This SNR estimation is evaluated as a ratio of an averaged synchronous signal measure with the acoustic stimulus to an average asynchronous signal measure.
- the averaged synchronous signal is the estimated AEP
- the averaged asynchronous signal is the estimation of the background noise and how it affects the AEP extraction.
- the SNR estimation will provide valuable information about the quality of the AEP activity and its extraction. This information will allow a monitor to determine whether or not an AEP is present in the measured signal and whether the applied averaging is not sufficient to extract the AEP, and therefore increase averaging until the desired SNR is achieved.
- An insufficient averaging or the lack of evoked activity (which can be the case if the headphones that provide the stimulus are not placed properly on the patient) can produce a low SNR, such as around 1.
- a calculated SNR value is supplied to a control circuit together with a desired SNR value, and on the basis of a difference signal calculated as a difference between the calculated value and the desired value, the control circuit is adapted to calculate the amount of necessary sweeps.
- fig. 1 shows the signals for extracting the AEP (Auditory Evoked
- fig. 2 A shows an example of the signals in the synchronised averaging process at a different number of synchronised averaging sweeps.
- fig. 2B shows an example of the signals in the unsynchronised averaging process at a different number of unsynchronised averaging sweeps
- fig. 2C shows the synchronised and the unsynchronised signals from an averaging process involving 256 sweeps
- fig. 3 shows a block diagram of a circuit for use in carrying out the method according to the invention.
- FIG 1 2 denotes an acoustic signal which is delivered to a patient not shown under anaesthesia.
- This signal is in the form of a click or the like, having a duration of approximately 1 - 2 ms.
- 1 denotes the response signal from the patient
- 3 denotes a segment or a time slot in which a plurality of K samples from the patient are detected, e.g. between 1 and 400 in each time slot, preferably about 100.
- the signal 1 contains both evoked activity and bagground activity, such as
- a group of segments 4 is divided in a synchronised way, whereas another group of segments 5 is divided in an unsynchronised way.
- Fig. 2 A shows an example of a plurality of signals, each of which has been subjected to a synchronised averaging process within a time slot 3, cf. fig. 1 , and averaged with different pluralities of sweeps.
- the shape of the signals is dependent on the plurality of sweeps used.
- fig 2B the averaging process is carried out in a way similar to that of fig. 2A, but in an unsynchronised random way.
- the method can be carried out by use of the circuit in the form of a control loop shown in fig. 3.
- This control loop consists of a PID (Proportional Integral Differential) regulator 15 having an input 14, to which the output from a summing circuit 14 is fed.
- PID Proportional Integral Differential
- Two signals are fed to the input of the summing circuit namely a desired value 12 representing a desired SNR and an actual value of SNR taken from a equipment not shown.
- the signal is fed from the output of the PID regulator to a calculation circuit 16, which on the basis of a linear or exponential calculation estimates a number N representing a plurality of necessary sweeps.
- An averaging process is initiated from circuit 16 on basis of the calculated N in 18, and an estimation of SNR is carried out in circuit 18.
- the so calculated SNR is again fed back to the summing circuit, and new values are fed to the control loop via the summation circuit in order to estimate a new SNR, perhaps on the basis of a smaller or higher N.
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Physics & Mathematics (AREA)
- Heart & Thoracic Surgery (AREA)
- Molecular Biology (AREA)
- Veterinary Medicine (AREA)
- Biophysics (AREA)
- Pathology (AREA)
- Engineering & Computer Science (AREA)
- Biomedical Technology (AREA)
- Public Health (AREA)
- Medical Informatics (AREA)
- General Health & Medical Sciences (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- Psychology (AREA)
- Acoustics & Sound (AREA)
- Psychiatry (AREA)
- Anesthesiology (AREA)
- Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
Abstract
In a method of determining the quality of AEP signals, which are indicative of the level of consciousness of a patient, a signal to noise ratio SNR is calculated on the basis of calculation of a ratio of a signal AAIs to a signal AAIu, where the signal AAIs is calculated by averaging a number of N synchronised measured successive segments of samples in response to N audio stimulus, and where the signal AAIu is calculated by averaging a number of N unsynchronised measured successive segments of samples in response to the same N audio stimulus. In this way the quality of a measured AEP signal is provided. If the calculated value of the SNR is 1, or even lower, then the quality of the AEP is low. However, if the calculated value of the SNR is high, then a good quality of the AEP is obtained. In order to limit the amount of calculations necessary to obtain a high SNR and thereby a good AEP, a use of a circuit for carrying out the method is provided, said circuit having a controlled loop, inter alia comprising a PID regulator which, on the basis of a given calculated SNR value and a desired SNR value, can estimate to what degree calculations are needed in order to obtain a sufficiently high SNR and thereby a good quality of the AEP.
Description
Method of determining the quality of an AEP signal
This invention relates to a method of determining the quality of signals which are indicative of the level of consciousness of a patient, said signals being determined by subjecting a patient to a number N of audio stimulus, and monitoring auditory evoked potentials (AEP) produced by the patient.
Such a method is disclosed in the published International patent application no. WO 01/74248.
According to this published application it is possible within a very .short time to measure a reliable AEP signal by use of an index which is calculated from an autoregressive model with exogenous input.
A measuring apparatus for carrying out measurements of AEP signals is described in the Danish patent application no. PA 2001 00381 , which was not published at the day of the filing of the present application.
Even though the method according to WO 01/74248 has shown good and reliable results it is not possible to evaluate the quality of the AEP signal.
The AEP signal is an evoked electrical activity, embedded in EEG activity that is elicited in a neural pathway by acoustic sensory stimulus. The AEP is thus the synchronised response to the acoustic stimulus provided by a train of acoustic pulses.
A problem in the analysis of the AEP activity occurs when background activity, such as EEG, Electro Encephalogram activity and EMG, Electro Myogram, artefacts and the like are present.
There are many techniques such as averaging (linear or exponential) and filtering, ARX modelling, etc that are required to extract the AEP activity
from the background activity.
All these techniques are based on the AEP activity and the lack of synchronisation between the other activities that compound the background activity.
A new method according to the invention is based on an estimation of an SNR (signal to noise potential) based on the use of a previous AEP, as explained in more detail later.
The method according to the invention is defined in claim 1 , and is characterised by the following steps:
a) estimation of a signal AAIS by averaging a number of K synchronised measured successive segments of samples,
b) estimation of a signal AAIU by averaging a number of K unsynchronised successive segments of samples
c) calculating the signal to noise ratio SNR = AAIS/AAIU.,
K where AAI = T|x(z) - x(z' + l)| and i=l
x (i) are sample points in the interval i=1 to i=K
This SNR estimation is evaluated as a ratio of an averaged synchronous signal measure with the acoustic stimulus to an average asynchronous signal measure.
Thus the averaged synchronous signal is the estimated AEP, whereas the averaged asynchronous signal is the estimation of the background noise and how it affects the AEP extraction.
In other words the SNR estimation will provide valuable information about the quality of the AEP activity and its extraction. This information will allow a monitor to determine whether or not an AEP is present in the measured signal and whether the applied averaging is not sufficient to extract the AEP, and therefore increase averaging until the desired SNR is achieved.
An SNR close to 1 implies bad signal conditions, which means that both averaging processes, (linear exponential) synchronous as well as asynchronous are nearly equal, and therefore there is either a weak synchronisation or no synchronisation with the stimulus.
An insufficient averaging or the lack of evoked activity (which can be the case if the headphones that provide the stimulus are not placed properly on the patient) can produce a low SNR, such as around 1.
In order to further improve the quality of the SNR signal it is expedient if, as stated in claim 2, that a plurality N of SNR values are calculated, and that an averaged value of the plurality of SNR values is calculated according to the formula:
i = 1 to i = Ν denotes a plurality of sweeps.
In this way the inherent fluctuation of the unsynchronised process is decreased, and an even better SNR ratio obtained.
In order to estimate whether any sweeps are necessary to obtain a sufficiently good SNR, it is expedient if, as stated in claim 3, that a calculated SNR value is supplied to a control circuit together with a desired SNR value, and on the basis of a difference signal calculated as a difference between the calculated value and the desired value, the control circuit is adapted to calculate the amount of necessary sweeps.
In this way time can be saved since no unnecessary calculations/estimations are needed. In other words only the number of calculations reasonably to obtain a good SNR is satisfactory.
Finally, it is expedient if the method is carried as stated in claim 4, i. e. by using a difference signal that is fed to an input of a PID control circuit and fed from an output from the PID control circuit to an input of a circuit adapted to calculate a number N of sweeps, said number being fed to a circuit for starting an averaging process, and on the basis of this to estimate a new SNR value which is feed back as a new SNR value for calculating a new difference which is fed to the PID control circuit.
The invention will now be described in more detail with reference to the drawing, in which:
fig. 1 shows the signals for extracting the AEP (Auditory Evoked
Potentials) and the time slots used for the calculations according to the invention,
fig. 2 A shows an example of the signals in the synchronised averaging process at a different number of synchronised averaging
sweeps.
fig. 2B shows an example of the signals in the unsynchronised averaging process at a different number of unsynchronised averaging sweeps
fig. 2C shows the synchronised and the unsynchronised signals from an averaging process involving 256 sweeps, and
fig. 3 shows a block diagram of a circuit for use in carrying out the method according to the invention.
In figure 1 , 2 denotes an acoustic signal which is delivered to a patient not shown under anaesthesia. This signal is in the form of a click or the like, having a duration of approximately 1 - 2 ms.
As can be seen from the figure, seven such signals are provided. In practice more than 10 or less than 50 are used.
1 denotes the response signal from the patient, whereas 3 denotes a segment or a time slot in which a plurality of K samples from the patient are detected, e.g. between 1 and 400 in each time slot, preferably about 100.
The signal 1 contains both evoked activity and bagground activity, such as
EMG, EEG, etc.
It is further noted that a group of segments 4 is divided in a synchronised way, whereas another group of segments 5 is divided in an unsynchronised way.
From the drawing it will be seen that the unsynchronised segments 5 are distributed vs. time in a random manner.
Fig. 2 A shows an example of a plurality of signals, each of which has been subjected to a synchronised averaging process within a time slot 3, cf. fig.
1 , and averaged with different pluralities of sweeps.
As will be seen, the shape of the signals is dependent on the plurality of sweeps used.
It is clear that when the plurality of sweeps used are increased, then the signal extraction is improved. For instance 256 sweeps yield good results.
In fig 2B, the averaging process is carried out in a way similar to that of fig. 2A, but in an unsynchronised random way.
It will be seen that when the plurality of sweeps used for the averaging process are increased, then the resulting signal is nearly constant, without leaving any signal extraction. For instance, this can be seen at the curve using 256 sweeps.
In fig 2C both signals extracted from the synchronised and unsynchronised process are shown, and in both cases created by using 256 sweeps,
In this situation the two signals are very different, and a measure related to the relation between the AAIS and the AA1U will give a high SNR, and thus a high quality of the desired signal AEP.
In contrast to this, a low ratio will exist when no AEP synchronised activity signal exists, which is the case when the synchronised and the unsynchronised signals are very similar.
In order to calculate how many sweeps are necessary in order to obtain a sufficiently good SNR, the method can be carried out by use of the circuit in the form of a control loop shown in fig. 3.
This control loop consists of a PID (Proportional Integral Differential) regulator 15 having an input 14, to which the output from a summing circuit 14 is fed.
Two signals are fed to the input of the summing circuit namely a desired
value 12 representing a desired SNR and an actual value of SNR taken from a equipment not shown.
The signal is fed from the output of the PID regulator to a calculation circuit 16, which on the basis of a linear or exponential calculation estimates a number N representing a plurality of necessary sweeps.
An averaging process is initiated from circuit 16 on basis of the calculated N in 18, and an estimation of SNR is carried out in circuit 18. The so calculated SNR is again fed back to the summing circuit, and new values are fed to the control loop via the summation circuit in order to estimate a new SNR, perhaps on the basis of a smaller or higher N.
In this way it is possible to survey the SNR in order to estimate the necessary calculations needed for obtaining a sufficiently high value of the SNR and thereby a good quality of the AEP.
Claims
1. A method of determining the quality of signals which are indicative of the level of consciousness of a patient, said signals being determined by subjecting a patient to a number N of audio stimulus, and monitoring auditory evoked potentials (AEP) produced by the patient comprising the steps of
d) estimation of a signal AAIS by averaging a number of K synchronised measured successive segments of samples,
e) estimation of a signal AAIU by averaging a number of K unsynchronised successive segments of samples
f) calculating the signal to noise ratio SNR = AAIS/AAIU.,
K where AAI = ∑|j ') - j ' + l)| and ι=l
x (i) are sample points in the interval i=1 to l=K
2. A method according to claim 1 , characterised in that a plurality N of SNR values are calculated, and in that an averaged value of the plurality of SNR values is calculated according to the formula:
• - -i f syncrh.measure \ X-^ AAIs ∑SNR, ∑ -i ∑ =^ 1=1 = -^ '"=1 unsynch.measurei J ^\^ AAIui SNR — >.X- = ^ X ----- , where
N N N
= 1 to I =Ν denotes a plurality of sweeps.
3. A method according to claim 2, characterised in that a calculated SNR value is supplied to a control circuit together with a desired SNR value, and on the basis of a difference signal calculated as a difference between the calculated value and the desires value, the control circuit is adapted to calculate the amount of necessary calculations of SNR values.
4. A method according to claim 3 characterised in that the difference signal is fed to an input of a PID control circuit and fed from an output from the PID control circuit to an input of a circuit adapted to calculate a number N of sweeps, said number being fed to a circuit for starting an averaging process, and on the basis of this to estimate a new SNR value which is fed back as a new SNR value for calculating a new difference which is fed to the PID control circuit.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| AU2003218956A AU2003218956A1 (en) | 2002-03-13 | 2003-03-07 | Method of determining the quality of an aep (auditory evoked potential) signal |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DKPA200200377 | 2002-03-13 | ||
| DKPA200200377 | 2002-03-13 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2003075760A1 true WO2003075760A1 (en) | 2003-09-18 |
Family
ID=27798728
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/DK2003/000143 WO2003075760A1 (en) | 2002-03-13 | 2003-03-07 | Method of determining the quality of an aep (auditory evoked potential) signal |
Country Status (2)
| Country | Link |
|---|---|
| AU (1) | AU2003218956A1 (en) |
| WO (1) | WO2003075760A1 (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2006122349A1 (en) * | 2005-05-17 | 2006-11-23 | Compumedics Medical Innovations Pty Ltd | Method and apparatus for monitoring consciousness during anaesthesia |
| CN100341462C (en) * | 2005-10-20 | 2007-10-10 | 上海交通大学 | Double ear alternative stimulated brainstem auditory evoked potential(BAEP) tracing device |
| CN102946797A (en) * | 2009-08-14 | 2013-02-27 | D·伯顿 | Anaesthesia and consciousness depth monitoring system |
| US9849241B2 (en) | 2013-04-24 | 2017-12-26 | Fresenius Kabi Deutschland Gmbh | Method of operating a control device for controlling an infusion device |
| US12053295B2 (en) | 2019-07-15 | 2024-08-06 | Massachusetts Institute of Tehnology | Tracking nociception under anesthesia using a multimodal metric |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4462411A (en) * | 1981-01-07 | 1984-07-31 | The University Of Melbourne | Evoked response audiometer |
| EP1114612A2 (en) * | 2000-01-07 | 2001-07-11 | Natus Medical, Inc. | Hearing evaluation device with noise detection and evaluation capability. |
| US20010034493A1 (en) * | 2000-02-14 | 2001-10-25 | Stone Robert T. | Multi-mode audiometric device and associated screening method |
| WO2001087147A2 (en) * | 2000-05-19 | 2001-11-22 | Michael Sasha John | System and method for objective evaluation of hearing using auditory steady-state responses |
| US6331164B1 (en) * | 2000-03-17 | 2001-12-18 | Etymotic Research, Inc. | Hearing test apparatus and method having adaptive artifact rejection |
-
2003
- 2003-03-07 AU AU2003218956A patent/AU2003218956A1/en not_active Abandoned
- 2003-03-07 WO PCT/DK2003/000143 patent/WO2003075760A1/en not_active Application Discontinuation
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4462411A (en) * | 1981-01-07 | 1984-07-31 | The University Of Melbourne | Evoked response audiometer |
| EP1114612A2 (en) * | 2000-01-07 | 2001-07-11 | Natus Medical, Inc. | Hearing evaluation device with noise detection and evaluation capability. |
| US20010034493A1 (en) * | 2000-02-14 | 2001-10-25 | Stone Robert T. | Multi-mode audiometric device and associated screening method |
| US6331164B1 (en) * | 2000-03-17 | 2001-12-18 | Etymotic Research, Inc. | Hearing test apparatus and method having adaptive artifact rejection |
| WO2001087147A2 (en) * | 2000-05-19 | 2001-11-22 | Michael Sasha John | System and method for objective evaluation of hearing using auditory steady-state responses |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2006122349A1 (en) * | 2005-05-17 | 2006-11-23 | Compumedics Medical Innovations Pty Ltd | Method and apparatus for monitoring consciousness during anaesthesia |
| CN100341462C (en) * | 2005-10-20 | 2007-10-10 | 上海交通大学 | Double ear alternative stimulated brainstem auditory evoked potential(BAEP) tracing device |
| CN102946797A (en) * | 2009-08-14 | 2013-02-27 | D·伯顿 | Anaesthesia and consciousness depth monitoring system |
| US9849241B2 (en) | 2013-04-24 | 2017-12-26 | Fresenius Kabi Deutschland Gmbh | Method of operating a control device for controlling an infusion device |
| US12053295B2 (en) | 2019-07-15 | 2024-08-06 | Massachusetts Institute of Tehnology | Tracking nociception under anesthesia using a multimodal metric |
Also Published As
| Publication number | Publication date |
|---|---|
| AU2003218956A1 (en) | 2003-09-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110338786B (en) | Epileptic discharge identification and classification method, system, device and medium | |
| JP3831788B2 (en) | Activity muscle display | |
| US7136696B2 (en) | Neuron signal analysis system and method | |
| CA2265610A1 (en) | Anaesthesia control system | |
| EP1934677A1 (en) | Method and system for detecting and classifying facial muscle movements | |
| AT515038B1 (en) | Method for quantifying the perceptibility of a person | |
| CA2383218A1 (en) | Seizure warning and prediction | |
| CN108601546B (en) | Biological signal processing method and biological signal processing apparatus | |
| JP2016526982A5 (en) | System and method for tracking non-stationary spectral structure and dynamics in physiological data | |
| KR100742296B1 (en) | Apparatus for extracting signals indicating the level of consciousness of a patient | |
| JP2016526982A (en) | System and method for observing non-stationary spectral structure and dynamics in physiological data | |
| Ibánez et al. | An EEG-based design for the online detection of movement intention | |
| US8620420B2 (en) | Method for filtering out artefacts of deep brain stimulation | |
| CN113576496A (en) | Vision tracking brain-computer interface detection system | |
| WO2003075760A1 (en) | Method of determining the quality of an aep (auditory evoked potential) signal | |
| Osorio et al. | Hurst parameter estimation for epleptic seizure detection | |
| CN107510451B (en) | pitch perception ability objective assessment method based on brainstem auditory evoked potentials | |
| CN105193409B (en) | A kind of brain electricity suppression level appraisal procedure and system | |
| US20040049484A1 (en) | Method and apparatus for separating and extracting information on physiological functions | |
| CN116088686A (en) | Electroencephalogram tracing motor imagery brain-computer interface training method and system | |
| CN112568873B (en) | Real-time sleep monitoring recording and analyzing method | |
| US20220183619A1 (en) | Method for classifying a polysomnography recording into defined sleep stages | |
| CN113907770A (en) | Method and system for detecting and identifying spike-slow complex wave based on feature fusion | |
| CN107374616B (en) | Autonomic nerve activity judgment method and device and electrocardiogram monitoring device | |
| CN112022155A (en) | Brain-computer interface system capable of evaluating auditory behaviors of patient with disturbance of consciousness |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| AK | Designated states |
Kind code of ref document: A1 Designated state(s): AE AG AL AM AT AU AZ BA BB BG BR BY BZ CA CH CN CO CR CU CZ DE DK DM DZ EC EE ES FI GB GD GE GH GM HR HU ID IL IN IS JP KE KG KP KR KZ LC LK LR LS LT LU LV MA MD MG MK MN MW MX MZ NI NO NZ OM PH PL PT RO RU SC SD SE SG SK SL TJ TM TN TR TT TZ UA UG US UZ VC VN YU ZA ZM ZW |
|
| AL | Designated countries for regional patents |
Kind code of ref document: A1 Designated state(s): GH GM KE LS MW MZ SD SL SZ TZ UG ZM ZW AM AZ BY KG KZ MD RU TJ TM AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HU IE IT LU MC NL PT RO SE SI SK TR BF BJ CF CG CI CM GA GN GQ GW ML MR NE SN TD TG |
|
| 121 | Ep: the epo has been informed by wipo that ep was designated in this application | ||
| DFPE | Request for preliminary examination filed prior to expiration of 19th month from priority date (pct application filed before 20040101) | ||
| 122 | Ep: pct application non-entry in european phase | ||
| NENP | Non-entry into the national phase |
Ref country code: JP |
|
| WWW | Wipo information: withdrawn in national office |
Country of ref document: JP |