Remote Pulmonary Function Testing using a Depth Sensor

Vahid Soleimani; Majid Mirmehdi; Dima Aldamen; Sion Hannuna; Massimo Camplani; Jason Viner; James Dodd

Remote Pulmonary Function Testing using a Depth Sensor

Vahid Soleimani, Majid Mirmehdi, Dima Aldamen, Sion Hannuna, Massimo Camplani, Jason Viner, James Dodd

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

16 Citations (Scopus)

Abstract

We propose a remote non-invasive approach to Pulmonary Function Testing using a time-of-flight depth sensor (Microsoft Kinect V2), and correlate our results to clinical-standard spirometry results. Given point clouds, we approximate 3D models of the subject's chest, estimate the volume throughout a sequence and construct volume-time and flow-time curves for two prevalent spirometry tests: Forced Vital Capacity and Slow Vital Capacity. From these, we compute clinical measures, such as FVC, FEV1, VC and IC. We correlate automatically extracted measures with clinical spirometry tests on 40 patients in an outpatient hospital setting. These demonstrate high within-test correlations.

Original language	English
Title of host publication	2015 IEEE Conference on Biomedical Circuits and Systems
Subtitle of host publication	Proceedings of IEEE/CAS-EMB Biomedical Circuits and Systems Conference (BioCAS) 22-24 October 2015, Atlanta, USA
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	1-4
Number of pages	4
Publication status	Published - 24 Oct 2015
Event	2015 IEEE Biomedical Circuits and Systems - Georgia, Atlanta, United States Duration: 22 Oct 2015 → 24 Oct 2015

Conference

Conference	2015 IEEE Biomedical Circuits and Systems
Country/Territory	United States
City	Atlanta
Period	22/10/15 → 24/10/15

Research Groups and Themes

Digital Health
SPHERE
Academic Respiratory Unit

Keywords

Digital Health

Access to Document

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7348445

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Persistent link

SPHERE (EPSRC IRC)
Craddock, I. J. (Principal Investigator), Coyle, D. T. (Principal Investigator), Flach, P. A. (Principal Investigator), Kaleshi, D. (Principal Investigator), Mirmehdi, M. (Principal Investigator), Piechocki, R. J. (Principal Investigator), Stark, B. H. (Principal Investigator), Ascione, R. (Co-Principal Investigator), Ashburn, A. M. (Collaborator), Burnett, M. E. (Collaborator), Damen, D. (Co-Principal Investigator), Gooberman-Hill, R. (Principal Investigator), Harwin, W. S. (Collaborator), Hilton, G. (Co-Principal Investigator), Holderbaum, W. (Collaborator), Holley, A. P. (Manager), Manchester, V. A. (Administrator), Meller, B. J. (Other ), Stack, E. (Collaborator) & Gilchrist, I. D. (Principal Investigator)
1/10/13 → 30/09/18
Project: Research, Parent

Cite this

Soleimani, V., Mirmehdi, M., Aldamen, D., Hannuna, S., Camplani, M., Viner, J., & Dodd, J. (2015). Remote Pulmonary Function Testing using a Depth Sensor. In 2015 IEEE Conference on Biomedical Circuits and Systems: Proceedings of IEEE/CAS-EMB Biomedical Circuits and Systems Conference (BioCAS) 22-24 October 2015, Atlanta, USA (pp. 1-4). Institute of Electrical and Electronics Engineers (IEEE). http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7348445

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title = "Remote Pulmonary Function Testing using a Depth Sensor",

abstract = "We propose a remote non-invasive approach to Pulmonary Function Testing using a time-of-flight depth sensor (Microsoft Kinect V2), and correlate our results to clinical-standard spirometry results. Given point clouds, we approximate 3D models of the subject's chest, estimate the volume throughout a sequence and construct volume-time and flow-time curves for two prevalent spirometry tests: Forced Vital Capacity and Slow Vital Capacity. From these, we compute clinical measures, such as FVC, FEV1, VC and IC. We correlate automatically extracted measures with clinical spirometry tests on 40 patients in an outpatient hospital setting. These demonstrate high within-test correlations.",

keywords = "Digital Health",

author = "Vahid Soleimani and Majid Mirmehdi and Dima Aldamen and Sion Hannuna and Massimo Camplani and Jason Viner and James Dodd",

year = "2015",

month = oct,

day = "24",

language = "English",

pages = "1--4",

booktitle = "2015 IEEE Conference on Biomedical Circuits and Systems",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "2015 IEEE Biomedical Circuits and Systems ; Conference date: 22-10-2015 Through 24-10-2015",

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Soleimani, V, Mirmehdi, M , Aldamen, D , Hannuna, S, Camplani, M, Viner, J & Dodd, J 2015, Remote Pulmonary Function Testing using a Depth Sensor. in 2015 IEEE Conference on Biomedical Circuits and Systems: Proceedings of IEEE/CAS-EMB Biomedical Circuits and Systems Conference (BioCAS) 22-24 October 2015, Atlanta, USA. Institute of Electrical and Electronics Engineers (IEEE), pp. 1-4, 2015 IEEE Biomedical Circuits and Systems, Atlanta, United States, 22/10/15. <http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7348445>

Remote Pulmonary Function Testing using a Depth Sensor. / Soleimani, Vahid; Mirmehdi, Majid ; Aldamen, Dima et al.
2015 IEEE Conference on Biomedical Circuits and Systems: Proceedings of IEEE/CAS-EMB Biomedical Circuits and Systems Conference (BioCAS) 22-24 October 2015, Atlanta, USA. Institute of Electrical and Electronics Engineers (IEEE), 2015. p. 1-4.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Remote Pulmonary Function Testing using a Depth Sensor

AU - Soleimani, Vahid

AU - Mirmehdi, Majid

AU - Aldamen, Dima

AU - Hannuna, Sion

AU - Camplani, Massimo

AU - Viner, Jason

AU - Dodd, James

PY - 2015/10/24

Y1 - 2015/10/24

N2 - We propose a remote non-invasive approach to Pulmonary Function Testing using a time-of-flight depth sensor (Microsoft Kinect V2), and correlate our results to clinical-standard spirometry results. Given point clouds, we approximate 3D models of the subject's chest, estimate the volume throughout a sequence and construct volume-time and flow-time curves for two prevalent spirometry tests: Forced Vital Capacity and Slow Vital Capacity. From these, we compute clinical measures, such as FVC, FEV1, VC and IC. We correlate automatically extracted measures with clinical spirometry tests on 40 patients in an outpatient hospital setting. These demonstrate high within-test correlations.

AB - We propose a remote non-invasive approach to Pulmonary Function Testing using a time-of-flight depth sensor (Microsoft Kinect V2), and correlate our results to clinical-standard spirometry results. Given point clouds, we approximate 3D models of the subject's chest, estimate the volume throughout a sequence and construct volume-time and flow-time curves for two prevalent spirometry tests: Forced Vital Capacity and Slow Vital Capacity. From these, we compute clinical measures, such as FVC, FEV1, VC and IC. We correlate automatically extracted measures with clinical spirometry tests on 40 patients in an outpatient hospital setting. These demonstrate high within-test correlations.

KW - Digital Health

M3 - Conference Contribution (Conference Proceeding)

SP - 1

EP - 4

BT - 2015 IEEE Conference on Biomedical Circuits and Systems

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 2015 IEEE Biomedical Circuits and Systems

Y2 - 22 October 2015 through 24 October 2015

ER -

Soleimani V, Mirmehdi M , Aldamen D , Hannuna S, Camplani M, Viner J et al. Remote Pulmonary Function Testing using a Depth Sensor. In 2015 IEEE Conference on Biomedical Circuits and Systems: Proceedings of IEEE/CAS-EMB Biomedical Circuits and Systems Conference (BioCAS) 22-24 October 2015, Atlanta, USA. Institute of Electrical and Electronics Engineers (IEEE). 2015. p. 1-4

Remote Pulmonary Function Testing using a Depth Sensor

Abstract

Conference

Research Groups and Themes

Keywords

Access to Document

Handle.net

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Projects

SPHERE (EPSRC IRC)

Cite this