skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: NOVELTY DETECTION FOR PREDICTING FALLS RISK USING SMARTPHONE GAIT DATA.

Abstract

Abstract not provided.

Authors:
; ;
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
Sandia University Part-Time Program
OSTI Identifier:
1427147
Report Number(s):
SAND2017-1981C
651396
DOE Contract Number:
AC04-94AL85000
Resource Type:
Conference
Resource Relation:
Conference: Proposed for presentation at the IEEE Internation Conference on Acoustics, Speech, and Signal Processing held March 5-9, 2017 in New Orleans, LA.
Country of Publication:
United States
Language:
English

Citation Formats

Martinez, Matthew Thomas, De Leon, Phillip, and Keeley, David. NOVELTY DETECTION FOR PREDICTING FALLS RISK USING SMARTPHONE GAIT DATA.. United States: N. p., 2017. Web. doi:10.1109/ICASSP.2017.7952547.
Martinez, Matthew Thomas, De Leon, Phillip, & Keeley, David. NOVELTY DETECTION FOR PREDICTING FALLS RISK USING SMARTPHONE GAIT DATA.. United States. doi:10.1109/ICASSP.2017.7952547.
Martinez, Matthew Thomas, De Leon, Phillip, and Keeley, David. Wed . "NOVELTY DETECTION FOR PREDICTING FALLS RISK USING SMARTPHONE GAIT DATA.". United States. doi:10.1109/ICASSP.2017.7952547. https://www.osti.gov/servlets/purl/1427147.
@article{osti_1427147,
title = {NOVELTY DETECTION FOR PREDICTING FALLS RISK USING SMARTPHONE GAIT DATA.},
author = {Martinez, Matthew Thomas and De Leon, Phillip and Keeley, David},
abstractNote = {Abstract not provided.},
doi = {10.1109/ICASSP.2017.7952547},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Feb 01 00:00:00 EST 2017},
month = {Wed Feb 01 00:00:00 EST 2017}
}

Conference:
Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

Save / Share: