Work

Predicting Parkinson's Disease Progression with Smartphone Data

Year: 2013

Type: article

Abstract: Most of the existing approaches for detecting diseases/risk score form observations (sensor and textual) ignore the presence of any prior knowledge of the disease. In this work, we start top-down by enumerating the symptoms of Parkinson's Disease (PD) and map the symptoms to its possible manifestations in sensor observations (bottom-up). We show such manifestations and further use these manifestations as features to build classifiers to differentiate between the PD patients and the control group. Submitted to the Parkinson's disease challenge sponsored by The Michael J. Fox Foundation for Parkinson's Research, March, 2013.

Source: Scholar Commons (University of South Carolina)

Authors: Pramod Anantharam, Krishnaprasad Thirunarayan, Vahid Taslimi, Amit Sheth

Language: English

Topic: Context-Aware Activity Recognition Systems

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W1605821577

FWCI: 1.124

Cites:

Cited by: 4

Related to: 10