Multiscale evolution of attractor-shape descriptors for assessing Parkinson's disease severity

Anirudh Som, Narayanan Krishnamurthi, Vinay Venkataraman, Karthikeyan Natesan Ramamurthy, Pavan Turaga

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

1 Scopus citations

Abstract

We propose a nonparametric framework for analyzing and modeling dynamic postural shifts of human subjects. The postural shifts are represented in the phase space using time-delay embeddings and novel shape-theoretic features are extracted. The proposed multiscale descriptors are used as discriminative features to differentiate dynamical systems. The descriptors are simple and easy to compute, and model the multiscale characteristics of the attractor's multi-dimensional shape measurements. We demonstrate the usefulness of these features by using them to classify subjects into healthy and those affected by Parkinson's disease. We also use these features to assess the severity of the disease. In all these use cases, the proposed multiscale features perform better than their global counterparts.

Original languageEnglish (US)
Title of host publication2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages938-942
Number of pages5
Volume2018-January
ISBN (Electronic)9781509059904
DOIs
StatePublished - Mar 7 2018
Event5th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Montreal, Canada
Duration: Nov 14 2017Nov 16 2017

Other

Other5th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017
CountryCanada
CityMontreal
Period11/14/1711/16/17

    Fingerprint

Keywords

  • Multiscale
  • Parkinson's Disease Severity Assessment
  • Reconstructed Attractor
  • Shape Distributions

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

Cite this

Som, A., Krishnamurthi, N., Venkataraman, V., Ramamurthy, K. N., & Turaga, P. (2018). Multiscale evolution of attractor-shape descriptors for assessing Parkinson's disease severity. In 2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Proceedings (Vol. 2018-January, pp. 938-942). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobalSIP.2017.8309098