JPWO2020220564A5

JPWO2020220564A5 -

Info

Publication number: JPWO2020220564A5
Application number: JP2021562859A
Authority: JP
Publication date: 2023-04-24

Claims

step A1 of acquiring a corresponding ABR recording at the starting sound intensity;
stepwise increasing the number of recordings averaged by iteration until the conditions for detection of the ABR signal are met, based on adaptive averaging calculations;
After the ABR signal detection conditions group the ABR recordings corresponding to the current sound intensity at the current iteration, respectively calculate the average curve of each group based on the current average number of times, and the interaction between the groups a step A2 of acquiring a time lag corresponding to the maximum value of the correlation function and determining whether or not there is an ABR signal having a time-lock characteristic based on whether or not the deviation of the time lag is within a predetermined range;
Step A3 of determining whether or not the ABR signal is detected in step A2, executing step A4 if the ABR signal is detected, and executing step A5 if the ABR signal is not detected;
determining whether the current sound intensity has reached the set minimum measured sound intensity, and if not, obtaining the corresponding ABR recording at the new sound intensity and combining it with the original data; re-executing step A2, wherein said new sound intensity is obtained after subtracting a set interval from the current sound intensity, and if the lowest measured sound intensity has been reached, step A4 of performing A6; ,
determining whether the ABR signal is not detected in the P consecutive sound intensities, if the ABR signal is not detected in the P consecutive sound intensities, perform step A6; otherwise, a step A5 that transitions to the execution of step A4;
The minimum sound intensity required to detect an ABR signal is the audible threshold, or the number of iterations used at each sound intensity from the starting sound intensity to the minimum measured sound intensity in the adaptive averaging calculation. obtaining a sound intensity corresponding to the audible threshold, A6, by function fitting and interpolation for
A method for automatically measuring an auditory brainstem response, comprising:

The calculation of the adaptive averaging method in step A2 is
a step S1' of dividing the ABR record into two groups randomly and calculating an average curve respectively, wherein the ABR record is a time curve whose input type is a single record repeated;
a step S2' of calculating the cross-correlation function after each of the two groups has been averaged;
Step S3' of obtaining a time lag corresponding to the maximum value of the cross-correlation function;
If the absolute value of the time lag is smaller than the k value, it means that the time lag deviation is within k data points, indicating that a stable time-locked signal has been detected, in which case data acquisition and collection and respond if an ABR signal is detected,
If the absolute value of the time lag is greater than the k value, it means that the time lag deviation is not within k data points, indicating that a stable time lock signal has not been detected, in which case further execute step S5′. characterized by
a step S4' of comparing the absolute value of the time lag with the k value and determining whether the time lag deviation is within k data points;
If the maximum number of iterations has been reached, stop data acquisition and collection, corresponding to the case where no ABR signal is detected, and if the maximum number of iterations has not been reached, then a new acquisition over the currently acquired ABR record. adding the recorded ABR recording and repeatedly performing the calculation process of S1' to S5' at the current acoustic intensity,
determining whether the maximum number of iterations at the current acoustic intensity has been reached;
2. The automatic auditory brainstem response of claim 1, wherein k is a preset fixed value or a value obtained after calculating all data points at a preset ratio. Measuring method.

The calculation of the adaptive averaging method in step A2 is
wherein said ABR record is a time curve whose input type is a single record repeated, determining it Q times in parallel, each time performing steps S1-S4 below;
step S1 of randomly dividing the currently collected ABR recordings into two groups and calculating mean curves respectively;
a step S2 of calculating the cross-correlation function after each of the two groups has been averaged;
Step S3 of obtaining a time lag corresponding to the maximum value of the cross-correlation function;
comparing the absolute value of the time lag and the k value to determine whether the time lag deviation is within k data points;
If the absolute value of the time lag is smaller than the k value, it means that the time lag deviation is within k data points, indicating that a stable timelock signal is detected, and the absolute value of the time lag is greater than or equal to the k value. if , step S4, meaning that the time lag deviation is not within k data points, indicating that a stable timelock signal has not been detected;
determining whether or not a stable time lock signal is detected in each of the Q parallel determinations;
stopping data acquisition and collection when a stable timelock signal is detected each of the Q times, corresponding to when an ABR signal is detected;
step S5 of further executing step S6 if a stable timelock signal is not necessarily detected each of the Q times;
Determine whether the maximum number of iterations at the current acoustic intensity has been reached,
if the maximum number of iterations has been reached, stop data acquisition and collection, and respond if no ABR signal is detected;
if the maximum number of iterations has not been reached, further adding newly acquired ABR records to the currently acquired ABR records and repeatedly performing the computational processes of S1-S6 at the current acoustic intensity;
k is a preset fixed value or a value obtained after calculating all data points with a preset ratio;
The method for automatically measuring an auditory brainstem response according to claim 1, characterized by:

The calculation of the adaptive averaging method in step A2 is
The ABR record is a time curve whose input type is multiple average records, and the new average curve avgA added in this iteration is combined with the average curve avgA of the previous iteration, and the current average Calculate the curve avgA new,

Here, there are Q groups of avgA new, avgA old, and avgA addition, and M is the current number of iterations in step S1'';
Step S2'' of calculating the cross-correlation function between each two groups for the current average curve avgA new of the Q group;
Step S3″ of obtaining the time lag of the Q group corresponding to the maximum value of the cross-correlation function;
In Q parallel judgments, the absolute value of the time lag of each group is respectively compared with the k value, and it is judged whether the time lag deviation is within k data points, and the absolute value of the time lag is less than the k value. If the time lag is within k data points, it means that a stable time lock signal has been detected. step S4'', meaning not within a point, indicating that a stable timelock signal has not been detected;
determining whether or not a stable time lock signal is detected in each of the Q parallel determinations;
stopping data acquisition and collection when a stable timelock signal is detected each of the Q times, corresponding to when an ABR signal is detected;
step S5'' of further executing step S6'' if a stable time-lock signal is not necessarily detected each of the Q times;
Determine whether the maximum number of iterations at the current acoustic intensity has been reached,
If the maximum number of iterations has been reached, data acquisition and collection is stopped, corresponding to the case where no ABR signal is detected, and if the maximum number of iterations has not been reached, the currently collected ABR measurement average data is updated. adding the collected averaged ABR measurement data to the current acoustic intensity and repeatedly performing the computational process of S1″-S6″ at the current acoustic intensity;
2. The auditory brainstem response of claim 1, wherein k is a preset fixed value or a value obtained after calculating all data points at a preset ratio. Automatic measurement method.

The number of averages used in calculating the ABR recording average curve at each sound intensity is the product of the number of iterations and the N value, where N corresponds to the number of groups of ABR recordings newly added at each iteration. The method for automatically measuring an auditory brainstem response according to any one of claims 1 to 4, characterized in that:

The sound intensity corresponding to the audible threshold is obtained by sigmoid function fitting and interpolation after normalizing the number of iterations used in each sound intensity in step A6. 1. The method for automatically measuring auditory brainstem response according to claim 1.

ABR recordings at each acoustic intensity are animal experimental data or clinical data, data acquired by real-time measurements or stored offline;
The ABR recording is
signal amplification and bandpass filtering;
adjusting the time interval for collecting the ABR waveforms and selecting an ABR time curve for the corresponding time interval after the onset of the audio stimulus for analysis;
eliminating ABR time curves corresponding to background noise;
removing low frequency background noise by a smoothing spline fitting function; and undergoing at least one preprocessing of the group consisting of:
The method for automatically measuring an auditory brainstem response according to any one of claims 1 to 4, characterized by:

An automatic auditory brainstem response measuring device for use in the method for automatically measuring an auditory brainstem response according to any one of claims 1 to 7,
an input module for obtaining ABR recordings collected at each acoustic intensity stimulus;
a control module that drives the input module to acquire batch-acquired ABR recordings at each acoustic intensity stimulus from a starting acoustic intensity to the minimum measured acoustic intensity;
By performing an adaptive averaging operation, the number of recording averaging steps is increased by iterations until the condition for ABR signal detection is met, the condition for ABR signal detection being the current sound intensity at the current iteration. After grouping the ABR records corresponding to , calculate the average curve of each group respectively based on the current average times, obtain the time lag corresponding to the maximum value of the cross-correlation function between the groups, and determine if the time lag deviation is an adaptive averaging computation module including determining whether an ABR signal having time-locked characteristics is present based on whether it is within a predetermined range of data points;
a storage module for storing the number of iterations used at each acoustic intensity when computing the adaptive averaging;
Based on the result output by the adaptive averaging calculation module, it is determined whether or not the ABR signal is detected during the adaptive averaging calculation, and if it is determined that the ABR signal is detected, the current sound It is determined whether the intensity has reached a set minimum value of measured sound intensities, or if it is determined that no ABR signal has been detected, further ABR signals have been detected at P consecutive sound intensities. a main determination module for determining whether there is
If it determines that the minimum measured sound intensity has not been reached, the main decision module commands the control module, which further drives the input module to acquire a corresponding ABR record at the new sound intensity. and the new sound intensity is obtained after subtracting the interval from the current sound intensity, or if it determines that the minimum measured sound intensity has been reached, the main decision module tells the control module issuing a command and recalling by the control module from the storage module the number of iterations used in computing the adaptive averaging method, and setting the audible threshold to be the minimum sound intensity required to detect the ABR signal. An automatic measurement device for auditory brainstem responses.

9. The auditory brainstem response of claim 8, further comprising a function fitting module for obtaining the acoustic intensity corresponding to the audible threshold by function fitting and interpolation based on the number of iterations used when computing the adaptive averaging method. automatic measuring device.

If the adaptive averaging module commands the control module to collect data and the data type input by the input module is a repeated single record, the adaptive averaging module will performing a single decision or performing multiple parallel decisions corresponding to the iteration of , and randomizing the currently collected ABR records at each decision of the single decision or multiple parallel decisions. After calculating the average curve for each of the two groups, calculate the time lag corresponding to the maximum value of the cross-correlation function, compare the absolute value of the time lag and the k value, and find that the time lag deviation is within k data points If the absolute value of the time lag is smaller than the k value, it indicates that a stable time lock signal has been detected; if the absolute value of the time lag is greater than the k value, the stable time lock signal is not detected; and
If the single determination or each of the multiple parallel determinations both indicate that a stable time-locked signal is being detected at the current acoustic intensity, the adaptive averaging computation module instructs the control module to issuing a command to stop collecting data, issuing return information indicating that an ABR signal is being detected at the current acoustic intensity, and storing the current number of iterations by the storage module;
Either a single determination indicates that a stable time-locked signal has not been detected at the current sound intensity, or each of multiple parallel determinations necessarily indicates a stable time-locked signal at the current sound intensity. has not been detected, the adaptive averaging computation module further determines whether the maximum number of iterations at the current acoustic intensity has been reached;
If the maximum number of iterations has been reached, the adaptive averaging computation module commands the control module to stop collecting data, issues return information indicating that no ABR signal can be detected at the current acoustic intensity, and the storage module saving the current iteration number by
If the maximum number of iterations has not been reached, the adaptive averaging calculation module further commands the control module to add new data, and after adding the newly acquired data to the original data, the adaptive averaging is performed at the current acoustic intensity. repeatedly performing the modulus computation process;
10. Auditory brainstem according to claim 8 or 9, characterized in that k is a preset fixed value or a value obtained after calculating all data points with a preset ratio. Automatic measurement device for reaction.

If the adaptive averaging computation module commands the control module to collect data and the data type input by the input module is multiple average records, the adaptive averaging computation module will newly in this iteration combining the added average curve avgA addition with the average curve avgA old of the previous iteration and calculating the current average curve avgA new according to the weight;

Here, avgA new, avgA old, and avgA addition are the ABR measurement average data of the Q group respectively, M is the current iteration number, and the adaptive averaging calculation module is the current average curve avgA new of the Q group. , calculating the cross-correlation function between each two groups, and obtaining the time lag of the Q group corresponding to the maximum value of the cross-correlation function;
In the Q parallel determinations, the absolute value of the time lag of each group is respectively compared with the k value, and it is determined whether the time lag deviation is within k data points, and the absolute value of the time lag is less than k. If the time lag is within k data points, it means that a stable time lock signal has been detected. means not within a point, indicating that no stable timelock signal has been detected;
The adaptive averaging calculation module determines whether a stable time-locked signal is detected in each of Q parallel determinations, and determines whether a stable time-locked signal is detected in each of Q parallel determinations. is detected, command the control module to stop collecting data, provide return information indicating that an ABR signal is being detected at the current acoustic intensity, and store the current number of iterations by the storage module. and
If a stable time lock signal is not necessarily detected in each of the Q times, further determine whether the maximum number of repetitions at the current sound intensity has been reached, and if the maximum number of repetitions has been reached, commanding the control module to stop collecting data, issuing return information indicating that an ABR signal is being detected at the current acoustic intensity, and storing the current number of iterations with the storage module;
if the maximum number of iterations has not been reached, adding newly collected ABR measured average data to the currently collected ABR measured average data, and repeatedly executing the adaptive averaging calculation process at the current acoustic intensity;
10. Auditory brainstem according to claim 8 or 9, characterized in that k is a preset fixed value or a value obtained after calculating all data points with a preset ratio. Automatic measurement device for reaction.