Data Mining in Analysis of Biomechanical Signals

Marcin Derlatka; Jolanta Pauk

doi:10.4028/www.scientific.net/SSP.147-149.588

Paper Titles

A Comparative Study of Different Neighborhood Topologies in WTM Kohonen Self-Organizing Maps
p.564

A Model-Less Method for Added Mass Identification
p.570

Analysis of Dynamic Method of Line Scales Detection
p.576

Application of Optical Flow and Methods of Group Lee Representation in Problems of Detecting of Movements and Pattern Detection on the Images
p.582

Data Mining in Analysis of Biomechanical Signals
p.588

Decomposition of Non-Stationary Signals Based on the Cochlea Function Principle
p.594

Human Gait Analysis and Classification Based on Neural Networks and Fuzzy Logic
p.600

Parametric Description of Vibration Using the Autocorrelation Function
p.606

Synthesis of a Sequential Model of Muscles of a Man during Drop Landing on a Hard Platform
p.612

HomeSolid State PhenomenaSolid State Phenomena Vols. 147-149Data Mining in Analysis of Biomechanical Signals

Data Mining in Analysis of Biomechanical Signals

Abstract:

In the paper the procedure of processing biomechanical data has been proposed. It consists of selecting proper noiseless data, preprocessing data by means of model’s identification and Kernel Principal Component Analysis and next classification using decision tree. The obtained results of classification into groups (normal and two selected pathology of gait: Spina Bifida and Cerebral Palsy) were very good.