A data-driven approach to pre-operative evaluation of lung cancer patients

Oleksiy Budilovsky, Golnaz Alipour, André Knoesen, Lisa M Brown, Soheil Ghiasi

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

Abstract

Many early stage lung cancer patients have resectable tumors, however, their cardiopulmonary function needs to be properly evaluated before they are deemed operative candidates. Such patients are typically asked to undergo standard pulmonary function tests, including cardiopulmonary exercise tests (CPET) or stair climbs. The standard tests are conducted only at selected healthcare provider locations, and are labor intensive. In addition, they are sometimes ineffective due to patient co-morbidities, such as limited mobility, which limits patient participation. To address these shortcomings, we envision that cardiopulmonary function can be evaluated in the patient's environment using an inexpensive wearable device during routine physical activities. We present a cloud-connected mask that is fitted with CO2, O2, flow volume, and accelerometer sensors. The data collected from the device is transmitted to a cloud service, which facilitates utilization of various data mining algorithms for extraction of insights from the data. As a necessary first step toward cardiopulmonary function evaluation, we study automatic recognition of the user's physical activity from mask sensors data via an empirical analysis of several data representation and classification algorithms. The results demonstrate accurate activity recognition using mask sensors, and underscore the potential of our approach for cardiopulmonary function evaluation.

Original languageEnglish (US)
Title of host publication2017 IEEE 19th International Conference on e-Health Networking, Applications and Services, Healthcom 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
Volume2017-December
ISBN (Electronic)9781509067046
DOIs
StatePublished - Dec 14 2017
Event19th IEEE International Conference on e-Health Networking, Applications and Services, Healthcom 2017 - Dalian, China
Duration: Oct 12 2017Oct 15 2017

Other

Other19th IEEE International Conference on e-Health Networking, Applications and Services, Healthcom 2017
CountryChina
CityDalian
Period10/12/1710/15/17

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ASJC Scopus subject areas

  • Health Informatics
  • Computer Networks and Communications
  • Computer Science Applications
  • Health(social science)

Cite this

Budilovsky, O., Alipour, G., Knoesen, A., Brown, L. M., & Ghiasi, S. (2017). A data-driven approach to pre-operative evaluation of lung cancer patients. In 2017 IEEE 19th International Conference on e-Health Networking, Applications and Services, Healthcom 2017 (Vol. 2017-December, pp. 1-6). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HealthCom.2017.8210810