IJIRCSTJournal International Journal of Innovative Research in Computer Science and Technology I S Volume 3 Issue 5 f Physical Education English September - October 2015 N N Y 2019 12 04 Computer Sciences Application of Discriminant Analysis in Predicting Fallers and Non-Fallers English Y 24 27 Sukwon Kim English Y 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. English Fallers, Gait, Non-fallers, Multivariate https://ijircst.org/abstract.php?article_id=233