Automatic detection of inspiration related snoring signals from original audio recording

Kun Qian; Zhiyong Xu; Huijie Xu; Boon Poh Ng

doi:10.1109/ChinaSIP.2014.6889209

Automatic detection of inspiration related snoring signals from original audio recording

Kun Qian, Zhiyong Xu, Huijie Xu, Boon Poh Ng

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

13 Citations (Scopus)

Abstract

Inspiration related snoring signals (IRSS) are essential for doctors and researchers to develop further study and establishment of personal health database. How to detect IRSS automatically from original audio recording is significant in methods of acoustic based Obstructive Sleep Apnea/Hypopnea Syndrome (OSAHS) diagnosis and monitoring. We proposed a systematic approach combining signal processing with machine learning techniques to detect IRSS from audio recording. Both the experimental results and computer studies demonstrate the efficiency of the proposed approach.

Original language	English
Title of host publication	2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	95-99
Number of pages	5
ISBN (Electronic)	9781479954032
DOIs	https://doi.org/10.1109/ChinaSIP.2014.6889209
Publication status	Published - 3 Sept 2014
Externally published	Yes
Event	2nd IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Xi'an, China Duration: 9 Jul 2014 → 13 Jul 2014

Publication series

Name	2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings

Conference

Conference	2nd IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014
Country/Territory	China
City	Xi'an
Period	9/07/14 → 13/07/14

Keywords

Apnea/Hypopnea Syndrome
Obstructive Sleep
inspiration related snoring signals
machine learning
signal processing

Access to Document

10.1109/ChinaSIP.2014.6889209

Cite this

Qian, K., Xu, Z., Xu, H., & Ng, B. P. (2014). Automatic detection of inspiration related snoring signals from original audio recording. In 2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings (pp. 95-99). Article 6889209 (2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ChinaSIP.2014.6889209

Qian, Kun ; Xu, Zhiyong ; Xu, Huijie et al. / Automatic detection of inspiration related snoring signals from original audio recording. 2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 95-99 (2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings).

@inproceedings{39812d84743d462f9bc79b53f0146249,

title = "Automatic detection of inspiration related snoring signals from original audio recording",

abstract = "Inspiration related snoring signals (IRSS) are essential for doctors and researchers to develop further study and establishment of personal health database. How to detect IRSS automatically from original audio recording is significant in methods of acoustic based Obstructive Sleep Apnea/Hypopnea Syndrome (OSAHS) diagnosis and monitoring. We proposed a systematic approach combining signal processing with machine learning techniques to detect IRSS from audio recording. Both the experimental results and computer studies demonstrate the efficiency of the proposed approach.",

keywords = "Apnea/Hypopnea Syndrome, Obstructive Sleep, inspiration related snoring signals, machine learning, signal processing",

author = "Kun Qian and Zhiyong Xu and Huijie Xu and Ng, {Boon Poh}",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2nd IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 ; Conference date: 09-07-2014 Through 13-07-2014",

year = "2014",

month = sep,

day = "3",

doi = "10.1109/ChinaSIP.2014.6889209",

language = "English",

series = "2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "95--99",

booktitle = "2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings",

address = "United States",

}

Qian, K, Xu, Z, Xu, H & Ng, BP 2014, Automatic detection of inspiration related snoring signals from original audio recording. in 2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings., 6889209, 2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 95-99, 2nd IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014, Xi'an, China, 9/07/14. https://doi.org/10.1109/ChinaSIP.2014.6889209

Automatic detection of inspiration related snoring signals from original audio recording. / Qian, Kun; Xu, Zhiyong; Xu, Huijie et al.
2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. p. 95-99 6889209 (2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Automatic detection of inspiration related snoring signals from original audio recording

AU - Qian, Kun

AU - Xu, Zhiyong

AU - Xu, Huijie

AU - Ng, Boon Poh

PY - 2014/9/3

Y1 - 2014/9/3

N2 - Inspiration related snoring signals (IRSS) are essential for doctors and researchers to develop further study and establishment of personal health database. How to detect IRSS automatically from original audio recording is significant in methods of acoustic based Obstructive Sleep Apnea/Hypopnea Syndrome (OSAHS) diagnosis and monitoring. We proposed a systematic approach combining signal processing with machine learning techniques to detect IRSS from audio recording. Both the experimental results and computer studies demonstrate the efficiency of the proposed approach.

AB - Inspiration related snoring signals (IRSS) are essential for doctors and researchers to develop further study and establishment of personal health database. How to detect IRSS automatically from original audio recording is significant in methods of acoustic based Obstructive Sleep Apnea/Hypopnea Syndrome (OSAHS) diagnosis and monitoring. We proposed a systematic approach combining signal processing with machine learning techniques to detect IRSS from audio recording. Both the experimental results and computer studies demonstrate the efficiency of the proposed approach.

KW - Apnea/Hypopnea Syndrome

KW - Obstructive Sleep

KW - inspiration related snoring signals

KW - machine learning

KW - signal processing

UR - http://www.scopus.com/inward/record.url?scp=84929408967&partnerID=8YFLogxK

U2 - 10.1109/ChinaSIP.2014.6889209

DO - 10.1109/ChinaSIP.2014.6889209

M3 - Conference contribution

AN - SCOPUS:84929408967

T3 - 2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings

SP - 95

EP - 99

BT - 2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014

Y2 - 9 July 2014 through 13 July 2014

ER -

Qian K, Xu Z, Xu H, Ng BP. Automatic detection of inspiration related snoring signals from original audio recording. In 2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2014. p. 95-99. 6889209. (2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings). doi: 10.1109/ChinaSIP.2014.6889209

Automatic detection of inspiration related snoring signals from original audio recording

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this