IJIRCST

1	Title of the Article	Application of Discriminant Analysis in Predicting Fallers and Non-Fallers
2	Author's name	Sukwon Kim: Department of Physical Education, Chonbuk National University, Jeonju, South Korea, 82-63-270-2860 (e-mail: rockwallkim@naver.com).
3	Author's name
4	Subject	f Physical Education
5	Keyword(s)	Fallers, Gait, Non-fallers, Multivariate
6	Abstract	A laboratory study was conducted to discriminate fallers and non-fallers using many fall-related factors including gait parameters, strength, COP, muscle activation rate, and friction demand. The primary objective of this paper was to determine whether fallers and non-fallers differed with regard to the mean of variables, and then was to use those variables to predict if a new person would fall either in fallers or in non-fallers categories. Total of 42 people participated in the study. Fourteen younger (18-35 years old) individuals (7 male and 7 female), 14 middle-age individuals (7 male and 7 female) and 14 older (65 and older) individuals (7 male and 7 female) participated in this experiment. The result indicated that heel contact velocity, step length, RCOF, COP, and isometric strength best-predicted fallers.
7	Publisher	Innovative Research Publication
8	Journal Name; vol., no.	International Journal of Innovative Research in Computer Science & Technology (IJIRCST); Volume-3 Issue-5
9	Publication Date	September 2015
10	Type	Peer-reviewed Article
11	Format	PDF
12	Uniform Resource Identifier	https://ijircst.org/view_abstract.php?title=Application-of-Discriminant-Analysis-in-Predicting-Fallers-and-Non-Fallers&year=2015&vol=3&primary=QVJULTIzMw==
13	Digital Object Identifier(DOI)
14	Language	English
15	Page No	24-27