Early detection of neurological disease using a smartphone: A case study

Kun Chan Lan, Wen Yuah Shih

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

1 Scopus citations

Abstract

Diagnosing Parkinson's disease (PD) is often difficult, especially in its early stages. It has been estimated that nearly 40% of people with the disease may not be diagnosed. Traditionally, the diagnosis of Parkinson's disease often requires a doctor to observe the patient over time to recognize signs of rigidity. In this work, we propose a PDR-based method to continuously monitor and record the patient's gait characteristics using a smart-phone. Our tool could be useful in providing an early warning to the PD patient to seek medical assistance and help the doctor diagnose the disease earlier.

Original languageEnglish
Title of host publication2015 9th International Conference on Sensing Technology, ICST 2015
PublisherIEEE Computer Society
Pages461-467
Number of pages7
ISBN (Electronic)9781479963140
DOIs
StatePublished - 21 Mar 2016
Event9th International Conference on Sensing Technology, ICST 2015 - Auckland, New Zealand
Duration: 8 Dec 201511 Dec 2015

Publication series

NameProceedings of the International Conference on Sensing Technology, ICST
Volume2016-March
ISSN (Print)2156-8065
ISSN (Electronic)2156-8073

Conference

Conference9th International Conference on Sensing Technology, ICST 2015
CountryNew Zealand
CityAuckland
Period8/12/1511/12/15

Keywords

  • gait
  • Parkinson's Disease
  • smartphone

Fingerprint Dive into the research topics of 'Early detection of neurological disease using a smartphone: A case study'. Together they form a unique fingerprint.

  • Cite this

    Lan, K. C., & Shih, W. Y. (2016). Early detection of neurological disease using a smartphone: A case study. In 2015 9th International Conference on Sensing Technology, ICST 2015 (pp. 461-467). [7438443] (Proceedings of the International Conference on Sensing Technology, ICST; Vol. 2016-March). IEEE Computer Society. https://doi.org/10.1109/ICSensT.2015.7438443