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Prediction of hand forces and moments using neural net modeling of ground reaction forces and kinematic data.

Authors
Wiker-S; Sinsel-E; McFerron-J
Source
J Biomech 2007 Jul; 40(S2):S28
NIOSHTIC No.
20039797
Abstract
Occupational biomechanical models require reasonably accurate hand forces and moments to sequentially compute joint reaction forces and moments through the body producing ground forces and moments. We have pursued development of Artificial Neural Network (ANN) models to predict independent hand forces and moments using limited postural data and measured ground reaction forces. This paper summarizes our initial findings regarding the validity of the proposed modeling schema.
Keywords
Biodynamics; Biokinetics; Biomechanical-modeling; Biomechanics; Body-mechanics; Body-regions; Ergonomics; Kinetics; Mathematical-models; Measurement-equipment; Simulation-methods; Neuromuscular-function; Neuromuscular-system; Physiological-response; Physiological-stress; Physiology; Posture
CODEN
JBMCB5
Publication Date
20070701
Document Type
Journal Article
Email Address
sfwiker@mail.wvu.edu
Fiscal Year
2007
NTIS Accession No.
NTIS Price
Issue of Publication
S2
ISSN
0021-9290
NIOSH Division
HELD
Source Name
Journal of Biomechanics
State
WV
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