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Inertial Motion Capture-Based Whole-Body Inverse Dynamics.
Diraneyya, Mohsen M; Ryu, JuHyeong; Abdel-Rahman, Eihab; Haas, Carl T.
Afiliação
  • Diraneyya MM; Institute for Aerospace Studies, University of Toronto, 4925 Dufferin Street, North York, Toronto, ON M3H 5T6, Canada.
  • Ryu J; Department of Civil and Environmental Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada.
  • Abdel-Rahman E; Department of System Design Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada.
  • Haas CT; Department of Civil and Environmental Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada.
Sensors (Basel) ; 21(21)2021 Nov 05.
Article em En | MEDLINE | ID: mdl-34770660
Inertial Motion Capture (IMC) systems enable in situ studies of human motion free of the severe constraints imposed by Optical Motion Capture systems. Inverse dynamics can use those motions to estimate forces and moments developing within muscles and joints. We developed an inverse dynamic whole-body model that eliminates the usage of force plates (FPs) and uses motion patterns captured by an IMC system to predict the net forces and moments in 14 major joints. We validated the model by comparing its estimates of Ground Reaction Forces (GRFs) to the ground truth obtained from FPs and comparing predictions of the static model's net joint moments to those predicted by 3D Static Strength Prediction Program (3DSSPP). The relative root-mean-square error (rRMSE) in the predicted GRF was 6% and the intraclass correlation of the peak values was 0.95, where both values were averaged over the subject population. The rRMSE of the differences between our model's and 3DSSPP predictions of net L5/S1 and right and left shoulder joints moments were 9.5%, 3.3%, and 5.2%, respectively. We also compared the static and dynamic versions of the model and found that failing to account for body motions can underestimate net joint moments by 90% to 560% of the static estimates.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Fenômenos Mecânicos / Músculos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Canadá País de publicação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Fenômenos Mecânicos / Músculos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Canadá País de publicação: Suíça