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 language | English (US) |
|---|---|
| Title of host publication | 2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 938-942 |
| Number of pages | 5 |
| Volume | 2018-January |
| ISBN (Electronic) | 9781509059904 |
| DOIs | |
| State | Published - Mar 7 2018 |
| Event | 5th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Montreal, Canada Duration: Nov 14 2017 → Nov 16 2017 |
Other
| Other | 5th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 |
|---|---|
| Country | Canada |
| City | Montreal |
| Period | 11/14/17 → 11/16/17 |
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Keywords
- Multiscale
- Parkinson's Disease Severity Assessment
- Reconstructed Attractor
- Shape Distributions
ASJC Scopus subject areas
- Information Systems
- Signal Processing
Cite this
Multiscale evolution of attractor-shape descriptors for assessing Parkinson's disease severity. / Som, Anirudh; Krishnamurthi, Narayanan; Venkataraman, Vinay; Ramamurthy, Karthikeyan Natesan; Turaga, Pavan.
2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Proceedings. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 938-942.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Multiscale evolution of attractor-shape descriptors for assessing Parkinson's disease severity
AU - Som, Anirudh
AU - Krishnamurthi, Narayanan
AU - Venkataraman, Vinay
AU - Ramamurthy, Karthikeyan Natesan
AU - Turaga, Pavan
PY - 2018/3/7
Y1 - 2018/3/7
N2 - 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.
AB - 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.
KW - Multiscale
KW - Parkinson's Disease Severity Assessment
KW - Reconstructed Attractor
KW - Shape Distributions
UR - http://www.scopus.com/inward/record.url?scp=85048048318&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85048048318&partnerID=8YFLogxK
U2 - 10.1109/GlobalSIP.2017.8309098
DO - 10.1109/GlobalSIP.2017.8309098
M3 - Conference contribution
VL - 2018-January
SP - 938
EP - 942
BT - 2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
ER -