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SCIENCE CHINA Information Sciences, Volume 64 , Issue 7 : 174201(2021) https://doi.org/10.1007/s11432-019-2674-2

Snoring detection based on a stretchable strain sensor

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  • ReceivedJul 2, 2019
  • AcceptedOct 6, 2019
  • PublishedNov 24, 2020

Abstract

There is no abstract available for this article.


Acknowledgment

This work was supported in part by National Natural Science Foundation of China (Grant Nos. 61873268, 61633016) and Beijing Natural Science Foundation (Grant No. L182060).


Supplement

Videos and other supplemental documents.


References

[1] Hu J Q, Li R, Liu Y. An overview of healthcare monitoring by flexible electronics. Sci China-Phys Mech Astron, 2018, 61: 94601 CrossRef Google Scholar

[2] Luboshitzky R, Aviv A, Hefetz A. Decreased pituitary-gonadal secretion in men with obstructive sleep apnea.. J Clin Endocrinol Metab, 2002, 87: 3394-3398 CrossRef PubMed Google Scholar

[3] McGrath M. Snoring 'linked to heart disease'. BBC News, 2008. Google Scholar

[4] Kushida C A, Littner M R, Morgenthaler T. Practice parameters for the indications for polysomnography and related procedures: an update for 2005.. Sleep, 2005, 28: 499-523 CrossRef PubMed Google Scholar

[5] Yin Y, Jiang H, Feng S. Bowel sound recognition using SVM classification in a wearable health monitoring system. Sci China Inf Sci, 2018, 61: 084301 CrossRef Google Scholar

[6] Qian K, Xu Z Y, Xu H J. Automatic detection, segmentation and classification of snore related signals from overnight audio recording. IET Signal Processing, 2015, 3: 21-29 CrossRef Google Scholar

[7] Sirohi J, Chopra I. Fundamental Understanding of Piezoelectric Strain Sensors. J Intelligent Material Syst Struct, 2000, 11: 246-257 CrossRef Google Scholar

[8] Arnardottir E S, Isleifsson B, Agustsson J S. How to measure snoring? A comparison of the microphone, cannula and piezoelectric sensor.. J Sleep Res, 2016, 25: 158-168 CrossRef PubMed Google Scholar

[9] Liu Z, Zhang S, Jin Y M. Flexible piezoelectric nanogenerator in wearable self-powered active sensor for respiration and healthcare monitoring. Semicond Sci Technol, 2017, 32: 064004 CrossRef Google Scholar

  • Figure 1

    (Color online) The strain sensor and some typical sleep data collected. (a) Attachment of the strain sensor to the subject's throat; (b) the measurement circuit; (c-I) snoring signal during sleep; (c-II) swallowing signal during light breathing; (c-III) deep breathing data; (d) the audio and strain sensor data displayed together during snoring.

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    Algorithm 1 Snoring detection algorithm

    while (1) do

    $T=0,a=0,p=0$, where $T$ denotes the total signal fluctuation time; $a$ denotes the times when the signal's relative amplitude is larger than $A_{\texttt{snore}}$, $p$ denotes the times when the signal's rising slope is between $P_{\min}$ and $P_{\max}$;

    $C=~\emptyset$, where $C$ denotes the set of total signal fluctuation times;

    Obtain $10$ cycles of fluctuating data $D$;

    Unbiased processing of the fluctuating data $D-E(D)$;

    Search $10$ local maximum amplitudes $D_m(1)\cdots~D_m(10)$ and $10$ local minimum amplitudes $D_n(1)\cdots~D_n(10)$;

    while $i~<~10$ do

    Calculate the time difference between two adjacent maximum amplitudes $T(i)=~S(D_m(i))-S(D_m(i-1))$, where $S(D_m(i))$ denotes the time when the $i$th local maximum amplitude occurs;

    Calculate the relative amplitude of each cycle $A(i)~=~D_m(i)-~D_n(i)$;

    Calculate the rising slope of the signal $P(i)~=~{A(i)}/{T(i)};$

    if $A(i)~>~A_{\texttt{light}}~$ then

    if $A(i)~>~A_{\texttt{snore}}~$ then

    $a=a+1$;

    end if

    if $A(i)-~A(i-1)~<~A_{\texttt{limit}}$ then

    $T=T+T(i)$;

    else

    $C=\{C,T\}$ and $T=0$;

    end if

    if $P(i)~>~P_{\min}$ and $P(i)~<~P_{\max}$ then

    $p=p+1$;

    end if

    end if

    end while

    if $a~>~5$ and $\max\{C\}~>~T_{\texttt{last}}$ and $p~>~5$ then

    Snoring is occurring;

    end if

    end while