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

2 Citations (Scopus)
9 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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