Literature DB >> 2733404

Three-dimensional kinematic modelling of the human shoulder complex--Part I: Physical model and determination of joint sinus cones.

A E Engin1, S T Tümer.   

Abstract

Modelling of the human shoulder complex is essential for the multi-segmented mathematical models as well as design of the shoulder mechanism of anthropometric dummies. In Part I of this paper a three-dimensional kinematic model is proposed by utilizing the concepts of kinematic links, joints, and joint sinuses. By assigning appropriate coordinate systems, parameters required for complete quantitative description of the proposed model are identified. The statistical in-vivo data base established by Engin and Chen (1986) is cast in a form compatible with the model by obtaining a set of unit vectors describing circumductory motion of the upper arm in a torso-fixed coordinate system. This set of unit vectors is then employed in determining the parameters of a composite shoulder complex sinus of a simplified version of the proposed model. Two methods, namely the flexible tolerance and the direct methods, are formulated and tested for the determination of an elliptical cone surface for a given set of generating unit vectors. Numerical results are presented for the apex angles and orientation of the composite joint sinus cone with respect to the anatomical directions.

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Year:  1989        PMID: 2733404

Source DB:  PubMed          Journal:  J Biomech Eng        ISSN: 0148-0731            Impact factor:   2.097


  3 in total

Review 1.  Glenohumeral motion: review of measurement techniques.

Authors:  A M Hill; A M J Bull; R J Dallalana; A L Wallace; G R Johnson
Journal:  Knee Surg Sports Traumatol Arthrosc       Date:  2007-04-13       Impact factor: 4.342

2.  Specimen-specific method for quantifying glenohumeral joint kinematics.

Authors:  Yeon Soo Lee; Thay Q Lee
Journal:  Ann Biomed Eng       Date:  2010-05-25       Impact factor: 3.934

3.  A bi-articular model for scapular-humeral rhythm reconstruction through data from wearable sensors.

Authors:  Federico Lorussi; Nicola Carbonaro; Danilo De Rossi; Alessandro Tognetti
Journal:  J Neuroeng Rehabil       Date:  2016-04-23       Impact factor: 4.262

  3 in total

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