Applications of artificial neural nets in clinical biomechanics.
The purpose of this article is to provide an overview of current applications of artificial neural networks in the area of clinical biomechanics. The body of literature on artificial neural networks grew intractably vast during the last 15 years. Conventional statistical models may present certain limitations that can be overcome by neural networks. Artificial neural networks in general are introduced, some limitations, and some proven benefits are discussed.
Schöllhorn
W I
WI
Faculty for Psychology and Sport Science, University of Münster, Leonardo Campus 15, 48149 Münster, Germany. schoell@uni-muenster.de
D000465:Algorithms; D001185:Artificial Intelligence; D001696:Biomechanical Phenomena / Q000379:methods*; D015510:Clinical Medicine / Q000379:methods; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005684:Gait / Q000502:physiology; D008959:Models, Neurological; D009068:Movement / Q000502:physiology*; D009119:Muscle Contraction / Q000502:physiology; D018482:Muscle, Skeletal / Q000294:innervation / Q000502:physiology; D016571:Neural Networks, Computer; D012107:Research Design; D013813:Therapy, Computer-Assisted / Q000379:methods*