Smartphone Derived Movement Profiles to Detect Changes in Health Status in COPD Patients - A Preliminary Investigation

Daniel Kelly, Donnelly Seamas, Caulfield Brian

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

3 Citations (Scopus)
10 Downloads (Pure)

Abstract

Over 3.2 million people in the UK alone have the lung disease Chronic Obstructive Pulmonary Disease. Identifying when COPD patients are at risk of an exacerbation is a major problem and there is a need for smart solutions that provide us with a means of tracking patient health status. Smart-phone sensor technology provides us with an opportunity to automatically monitor patients. With sensors providing the ability to measure aspects of a patients daily life, such a motion, methods to interpret these signals and infer health related information are needed. In this work we aim to investigate the feasibility of utilizing motion sensors, built within smart-phones, to measure patient movement and to infer the health related information about the patient. We perform experiments, based on 7 COPD patients using data collected over a 12 week period for each patient, and identify a measure to distinguish between periods when a patient feels well Vs periods when a patient feels unwell.
Original languageEnglish
Title of host publicationUnknown Host Publication
PublisherIEEE
Number of pages4
Publication statusPublished - 25 Aug 2015
EventIEEE Conference of the Engineering in Medicine and Biology Society - Milan, Italy
Duration: 25 Aug 2015 → …

Conference

ConferenceIEEE Conference of the Engineering in Medicine and Biology Society
Period25/08/15 → …

Keywords

  • Smartphone Sensor
  • Chronic Obstructive Pulmonary Disease

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