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 proceedingConference Contribution (Conference Proceeding)

14 Citations (Scopus)


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 languageEnglish
Title of host publication2015 IEEE Conference on Biomedical Circuits and Systems
Subtitle of host publicationProceedings of IEEE/CAS-EMB Biomedical Circuits and Systems Conference (BioCAS) 22-24 October 2015, Atlanta, USA
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages4
Publication statusPublished - 24 Oct 2015
Event2015 IEEE Biomedical Circuits and Systems - Georgia, Atlanta, United States
Duration: 22 Oct 201524 Oct 2015


Conference2015 IEEE Biomedical Circuits and Systems
Country/TerritoryUnited States

Structured keywords

  • Digital Health


  • Digital Health


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