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Jin Qin, Matthieu Trudeau, Bryan Buchholz, Jeffrey N. Katz, Xu Xu and Jack T. Dennerlein

Upper extremity kinematics during keyboard use is associated with musculoskeletal health among computer users; however, specific kinematics patterns are unclear. This study aimed to determine the dynamic roles of the shoulder, elbow, wrist and metacarpophalangeal (MCP) joints during a number entry task. Six subjects typed in phone numbers using their right index finger on a stand-alone numeric keypad. The contribution of each joint of the upper extremity to the fingertip movement during the task was calculated from the joint angle trajectory and the Jacobian matrix of a nine-degree-of-freedom kinematic representation of the finger, hand, forearm and upper arm. The results indicated that in the vertical direction where the greatest fingertip movement occurred, the MCP, wrist, elbow (including forearm) and shoulder joint contributed 10.2%, 55.6%, 27.7% and 6.5%, respectively, to the downward motion of the index finger averaged across subjects. The results demonstrated that the wrist and elbow contribute the most to the fingertip vertical movement, indicating that they play a major role in the keying motion and have a dynamic load beyond maintaining posture.

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Inge Tuitert, Tim A. Valk, Egbert Otten, Laura Golenia and Raoul M. Bongers

-finger position by means of a linear model (third step). These relations have to be approximated in goal-directed manual reaching movements and are represented in a Jacobian matrix. Lastly, this matrix is used to partition the joint-angle variability across trials. Variability within the null-space of the

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Ghazaleh Azizpour, Matteo Lancini, Giovanni Incerti, Paolo Gaffurini and Giovanni Legnani

transpose matrix of the Jacobian ( J ). The Jacobian was defined as J  = ∂ S /∂ Q , where vector S = [ x p y p ] t contained the Cartesian coordinates of the handles in the sagittal plane. The procedure for estimation of inertial parameters: The dynamic equation (Equation  3 ) can be rearranged as: C q

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Momoko Yamagata, Ali Falaki and Mark L. Latash

), and the 13-dimensional muscle activation space (except for FDS) was transformed into a three-dimensional factor space. The Kaiser criterion was used to determine the number of PCs, and each PC had to contain at least one muscle with absolute magnitude of the loading value >0.5. Defining the Jacobian

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Fariba Hasanbarani and Mark L. Latash

→ +   ω →   ·   δ t ) − Coordinate ( θ → ) δ t , (2) where δ t is a small time interval, 0.02 s. Partial derivatives of each of the PVs with respect to the EVs (joint angles) were used to form the Jacobian matrix (J). The UCM was estimated as the null space of the corresponding J estimated at each

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Christopher A. DiCesare, Scott Bonnette, Gregory D. Myer and Adam W. Kiefer

) and condition (successful and unsuccessful), a different UCM was calculated. In brief, a model relating the changes in COM ML to the variability in ankle, knee, hip, and trunk angle was computed, and a linear approximation to each UCM was calculated from the null space of the Jacobian matrix of the

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Mark L. Latash

functions. In some cases, if intertrial variability is relatively small, the two spaces—of the elemental variables and of the salient performance variable (which may be multi-dimensional)—may be linked using the Jacobian matrix, J . J  is a matrix of partial derivatives of the selected performance