Biometric and Mobile Gait Analysis for Early Detection and Therapy Monitoring in Parkinson's Disease

Barth J, Klucken J, Kugler P, Kammerer T, Steidl R, Winkler J, Hornegger J, Eskofier B (2011)

Publication Type: Conference contribution, Conference Contribution

Publication year: 2011

Journal

Original Authors: Barth Jens, Klucken Jochen, Kugler Patrick, Kammerer Thomas, Steidl Ralph, Winkler Jürgen, Hornegger Joachim, Eskofier Björn

Book Volume: null

Pages Range: 868-871

Conference Proceedings Title: Engineering in Medicine and Biology Society,EMBC, 2011 Annual International Conference of the IEEE

Event location: Boston, MA

Journal Issue: null

DOI: 10.1109/IEMBS.2011.6090226

Abstract

Parkinson's disease (PD) is the most frequent neurodegenerative movement disorder. Early diagnosis and effective therapy monitoring is an important prerequisite to treat patients and reduce health care costs. Objective and non-invasive assessment strategies are an urgent need in order to achieve this goal. In this study we apply a mobile, lightweight and easy applicable sensor based gait analysis system to measure gait patterns in PD and to distinguish mild and severe impairment of gait. Examinations of 16 healthy controls, 14 PD patients in an early stage, and 13 PD patients in an intermediate stage were included. Subjects performed standardized gait tests while wearing sport shoes equipped with inertial sensors (gyroscopes and accelerometers). Signals were recorded wirelessly, features were extracted, and distinct subpopulations classified using different classification algorithms. The presented system is able to classify patients and controls (for early diagnosis) with a sensitivity of 88% and a specificity of 86%. In addition it is possible to distinguish mild from severe gait impairment (for therapy monitoring) with 100% sensitivity and 100% specificity. This system may be able to objectively classify PD gait patterns providing important and complementary information for patients, caregivers and therapists. © 2011 IEEE.

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Related research project(s)

Involved external institutions

Astrum IT GmbH Germany (DE)

How to cite

APA:

Barth, J., Klucken, J., Kugler, P., Kammerer, T., Steidl, R., Winkler, J.,... Eskofier, B. (2011). Biometric and Mobile Gait Analysis for Early Detection and Therapy Monitoring in Parkinson's Disease. In Engineering in Medicine and Biology Society,EMBC, 2011 Annual International Conference of the IEEE (pp. 868-871). Boston, MA, US.

MLA:

Barth, Jens, et al. "Biometric and Mobile Gait Analysis for Early Detection and Therapy Monitoring in Parkinson's Disease." Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011, Boston, MA 2011. 868-871.

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