Classification of Chronic Whiplash Associated Disorders With Artificial Neural Networks

Abstract

This study presents a new method for classification of subjects suffering from Whiplash Associated Disorders (WAD) with a supervised resilient Back Propagation Neural Network (BPN). The only input needed, from each subject, is features extracted from 3-dimensional motion data collected by a ProReflex system. The analysis with BPN results in a correct prediction for 84% of normal subjects and 89% percent of subjects with WAD.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA410227

Entities

People

  • F. Oehberg
  • H. Grip
  • L. Nystroem
  • U. Wiklund
  • Y. Sterner

Organizations

  • Umeå University

Tags

Communities of Interest

  • Engineered Resilient Systems

DTIC Thesaurus Topics

  • Biomedical Engineering
  • Body Regions
  • Classification
  • Computers
  • Data Sets
  • Diseases And Disorders
  • Engineering
  • Health Care
  • Health Services
  • Medical Personnel
  • Neural Networks
  • Pain
  • Reaction Time
  • Supervised Machine Learning
  • Transfer Functions
  • Whiplash
  • Wounds And Injuries

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Human-Computer Interaction (HCI).
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks