WiKiSpiro

Non-contact respiration volume monitoring during sleep

Phuc Nguyen, Shane Transue, Min Hyung Choi, Ann C. Halbower, Tam Vu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Respiration volume has been widely used as an important indication for diagnosis and treatment of pulmonary diseases and other health care related issues such as critically ill patients neonatal ventilation, post-operative monitoring and various others. Most of existing technologies for respiration volume monitoring require physical contact with the human body. While wireless-based approaches have also been discussed in the literature, there are still limitations in terms of estimation accuracy and time efficiency preventing these approaches from being realized in practice. In this paper, we present an automated, wireless-based, vision-supervised system, called WiKiSpiro, for monitoring an individual's respiration volume. In particular, we present a system design encompassing a wireless device, motion tracking and control system, and a set of methods to accurately derive breathing volume from the reflected signal and to address challenges caused by body movement and posture changes. We present our preliminary results of WikiSpiro, and identify possible challenges for future research and development.

Original languageEnglish (US)
Title of host publicationProceedings of the 8th Wireless of the Students, by the Students, and for the Students Workshop, S3
PublisherAssociation for Computing Machinery
Pages27-29
Number of pages3
Volume03-07-October-2016
ISBN (Electronic)9781450342551
DOIs
StatePublished - Oct 3 2016
Externally publishedYes
Event8th Wireless of the Students, by the Students, and for the Students Workshop, S3 - New York, United States
Duration: Oct 3 2016Oct 7 2016

Other

Other8th Wireless of the Students, by the Students, and for the Students Workshop, S3
CountryUnited States
CityNew York
Period10/3/1610/7/16

Fingerprint

Monitoring
Pulmonary diseases
Health care
Ventilation
Systems analysis
Control systems
Sleep

Keywords

  • Breathing bolume monitoring
  • Mobile healthcare
  • RF-sensing

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Software

Cite this

Nguyen, P., Transue, S., Choi, M. H., Halbower, A. C., & Vu, T. (2016). WiKiSpiro: Non-contact respiration volume monitoring during sleep. In Proceedings of the 8th Wireless of the Students, by the Students, and for the Students Workshop, S3 (Vol. 03-07-October-2016, pp. 27-29). [2987356] Association for Computing Machinery. https://doi.org/10.1145/2987354.2987356

WiKiSpiro : Non-contact respiration volume monitoring during sleep. / Nguyen, Phuc; Transue, Shane; Choi, Min Hyung; Halbower, Ann C.; Vu, Tam.

Proceedings of the 8th Wireless of the Students, by the Students, and for the Students Workshop, S3. Vol. 03-07-October-2016 Association for Computing Machinery, 2016. p. 27-29 2987356.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Nguyen, P, Transue, S, Choi, MH, Halbower, AC & Vu, T 2016, WiKiSpiro: Non-contact respiration volume monitoring during sleep. in Proceedings of the 8th Wireless of the Students, by the Students, and for the Students Workshop, S3. vol. 03-07-October-2016, 2987356, Association for Computing Machinery, pp. 27-29, 8th Wireless of the Students, by the Students, and for the Students Workshop, S3, New York, United States, 10/3/16. https://doi.org/10.1145/2987354.2987356
Nguyen P, Transue S, Choi MH, Halbower AC, Vu T. WiKiSpiro: Non-contact respiration volume monitoring during sleep. In Proceedings of the 8th Wireless of the Students, by the Students, and for the Students Workshop, S3. Vol. 03-07-October-2016. Association for Computing Machinery. 2016. p. 27-29. 2987356 https://doi.org/10.1145/2987354.2987356
Nguyen, Phuc ; Transue, Shane ; Choi, Min Hyung ; Halbower, Ann C. ; Vu, Tam. / WiKiSpiro : Non-contact respiration volume monitoring during sleep. Proceedings of the 8th Wireless of the Students, by the Students, and for the Students Workshop, S3. Vol. 03-07-October-2016 Association for Computing Machinery, 2016. pp. 27-29
@inproceedings{5472d60e18714fa2bdc56731e4b4917b,
title = "WiKiSpiro: Non-contact respiration volume monitoring during sleep",
abstract = "Respiration volume has been widely used as an important indication for diagnosis and treatment of pulmonary diseases and other health care related issues such as critically ill patients neonatal ventilation, post-operative monitoring and various others. Most of existing technologies for respiration volume monitoring require physical contact with the human body. While wireless-based approaches have also been discussed in the literature, there are still limitations in terms of estimation accuracy and time efficiency preventing these approaches from being realized in practice. In this paper, we present an automated, wireless-based, vision-supervised system, called WiKiSpiro, for monitoring an individual's respiration volume. In particular, we present a system design encompassing a wireless device, motion tracking and control system, and a set of methods to accurately derive breathing volume from the reflected signal and to address challenges caused by body movement and posture changes. We present our preliminary results of WikiSpiro, and identify possible challenges for future research and development.",
keywords = "Breathing bolume monitoring, Mobile healthcare, RF-sensing",
author = "Phuc Nguyen and Shane Transue and Choi, {Min Hyung} and Halbower, {Ann C.} and Tam Vu",
year = "2016",
month = "10",
day = "3",
doi = "10.1145/2987354.2987356",
language = "English (US)",
volume = "03-07-October-2016",
pages = "27--29",
booktitle = "Proceedings of the 8th Wireless of the Students, by the Students, and for the Students Workshop, S3",
publisher = "Association for Computing Machinery",

}

TY - GEN

T1 - WiKiSpiro

T2 - Non-contact respiration volume monitoring during sleep

AU - Nguyen, Phuc

AU - Transue, Shane

AU - Choi, Min Hyung

AU - Halbower, Ann C.

AU - Vu, Tam

PY - 2016/10/3

Y1 - 2016/10/3

N2 - Respiration volume has been widely used as an important indication for diagnosis and treatment of pulmonary diseases and other health care related issues such as critically ill patients neonatal ventilation, post-operative monitoring and various others. Most of existing technologies for respiration volume monitoring require physical contact with the human body. While wireless-based approaches have also been discussed in the literature, there are still limitations in terms of estimation accuracy and time efficiency preventing these approaches from being realized in practice. In this paper, we present an automated, wireless-based, vision-supervised system, called WiKiSpiro, for monitoring an individual's respiration volume. In particular, we present a system design encompassing a wireless device, motion tracking and control system, and a set of methods to accurately derive breathing volume from the reflected signal and to address challenges caused by body movement and posture changes. We present our preliminary results of WikiSpiro, and identify possible challenges for future research and development.

AB - Respiration volume has been widely used as an important indication for diagnosis and treatment of pulmonary diseases and other health care related issues such as critically ill patients neonatal ventilation, post-operative monitoring and various others. Most of existing technologies for respiration volume monitoring require physical contact with the human body. While wireless-based approaches have also been discussed in the literature, there are still limitations in terms of estimation accuracy and time efficiency preventing these approaches from being realized in practice. In this paper, we present an automated, wireless-based, vision-supervised system, called WiKiSpiro, for monitoring an individual's respiration volume. In particular, we present a system design encompassing a wireless device, motion tracking and control system, and a set of methods to accurately derive breathing volume from the reflected signal and to address challenges caused by body movement and posture changes. We present our preliminary results of WikiSpiro, and identify possible challenges for future research and development.

KW - Breathing bolume monitoring

KW - Mobile healthcare

KW - RF-sensing

UR - http://www.scopus.com/inward/record.url?scp=84994184650&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84994184650&partnerID=8YFLogxK

U2 - 10.1145/2987354.2987356

DO - 10.1145/2987354.2987356

M3 - Conference contribution

VL - 03-07-October-2016

SP - 27

EP - 29

BT - Proceedings of the 8th Wireless of the Students, by the Students, and for the Students Workshop, S3

PB - Association for Computing Machinery

ER -