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Automatic detection of teeth clenching and/or teeth grinding

A technology for automatic detection and muscle activity, applied in medical automated diagnosis, diagnostic recording/measurement, sports accessories, etc., can solve problems such as inability to provide correct treatment, incorrect treatment, etc.

Active Publication Date: 2017-02-22
太阳星瑞士有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

An incorrect setting may be problematic if the detected signal can be used, for example by delivering a stimulating treatment to the patient, as the correct treatment may not be delivered

Method used

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  • Automatic detection of teeth clenching and/or teeth grinding
  • Automatic detection of teeth clenching and/or teeth grinding
  • Automatic detection of teeth clenching and/or teeth grinding

Examples

Experimental program
Comparison scheme
Effect test

example 1

[0102] For calculating the background level, the background level may be a low pass filtered EMG signal envelope as described herein.

[0103] The filter is a first-order autoregressive filter of the form:

[0104] y(n)=0.99·y(n-1)+0.01·x(n-80), where

[0105] x(n-80) is the 2.56 second old envelope value (80 samples / 31.25, samples / s = 2.56s),

[0106] y(n-1) is the latest value of the background level,

[0107] y(n) is the new value of the background level,

[0108] 0.99 is the filter coefficient,

[0109] 0.01 is a gain factor on the input signal to ensure an overall gain of 1.

[0110] The calculation is implemented in integer arithmetic to reduce the calculation load in the embedded processor. This is done by multiplying the value from the FFT algorithm (which is an 8-bit algorithm) with a scaling factor of 10000. Furthermore, the above filter is calculated as

[0111] y(n)=(99·y(n-1)+1·x(n-80)) / 100

[0112] Because decimal numbers cannot be represented by integer ...

example 2

[0115] figure 2 A diagram showing an embodiment of a method for automatic detection of teeth clenching. exist figure 2 In , data is EMG data obtained from multiple EMG signals. The signal envelope 23 is calculated by FFT of the raw EMG signal 24 . from figure 2 It can be seen that the estimated background level 22, 22' is constantly changing with respect to time (except for periods when the calculation is stopped), ie where the method fixes the threshold level and restarts the calculation thereafter. from figure 2 As can be seen in , a total of four bursts were detected25.

example 3

[0117] image 3 A diagram showing another embodiment of a method for automatic detection of teeth clenching. exist image 3 In , data is EMG data obtained from multiple EMG signals. image 3 Shown is the initial output from the method when no activity related to clenching was assigned. The raw EMG signal 34 is sampled at 2000 Hz. The signal envelope 33 is calculated by a 64-point FFT and averaging pins 7 to 13, as this corresponds to the RMS value for frequencies between 218 Hz and 406 Hz. from image 3It can be seen that the initial output of background level 31 is quite high, and the method waits 5 seconds before it starts calculating a new output (assuming the signal may have been present before the method started). The initial value of the background level 31 is set to a higher value than expected in the recorded signal 34 . Due to the high starting level and depending on the actual level of background activity, the filter may take 10s to find the exact level of back...

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PUM

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Abstract

The present disclosure provides a computer implemented method for automatic detection of teeth clenching and / or teeth grinding in a dataset representing the level of biting force vs. time of a subject, the method comprising the steps of a) calculating a threshold level of biting force assigned to time t=t1 based on a background level determined from the dataset at a prior time t=t1-Tback, where Tback is a first predefined period of time,b) checking the level of biting,and if the level of biting force at time,t, exceeds the threshold level assigned to time t for a second predefined period of time, Tclench / grind, then assigning an event of teeth clenching to time t,c) if an event of teeth clenching has been assigned to time t, then either waiting a predefined period of time 10 T wait,or waiting until the level of biting is below the threshold for another predefined period of time Tend, d) if no events of teeth clenching and / or teeth grinding have been assigned for a third predefined period of time Tsilence, then repeating steps a)-c),e)if events of teeth clenching and / or teeth grinding have been assigned for a third predefined period of time Tsilence, then repeating only steps b)-c).

Description

technical field [0001] The present disclosure relates to automatic detection of predetermined events in a data set, and more particularly, to a method, apparatus and system for automatic detection of clenching and / or bruxism. Background technique [0002] In many cases it is desirable to detect clenching and / or gnashing of teeth, especially in humans, in particular with the aim of being able to detect and avoid as far as possible undesired, unnecessary and / or potentially harmful clenching and / or gnashing of teeth. In particular, it is desirable to be able to detect such clenching and / or grinding of the teeth, with the aim of being able to intervene in such a way that the undesirable activity can be limited or even terminated. [0003] Teeth clenching and / or teeth grinding can occur more or less consciously or even completely unconsciously, for example during sleep, and can also cause damage or adverse effects. [0004] Both clenching and grinding can be classified as a cond...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/00A61B5/0488A61B5/1495A61B5/22
CPCA61B5/1495A61B5/228A61B5/4519A61B5/4557A61B5/486A61B5/7235A61B5/7264A61B2560/0223A61F2005/563A61B5/389G16H50/20A61B5/369A61B5/11A61B5/7257A61B5/726A61B7/006A61B2562/0219A61B2562/0261
Inventor M·豪格兰C·克里斯蒂安森N·高野
Owner 太阳星瑞士有限公司
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