Shoulder Weakness- Basketball And Weight Lifting

The quantification of plantar pressure distribution is widely done in the diagnosis of lower limbs deformities, gait analysis, footwear design, and sport applications. To date, a number of pressure insole layouts have been proposed, with different configurations according to their applications. The goal of this study is to assess the validity of a 16-sensors (1.5 × 1.5 cm) pressure insole to detect plantar pressure distribution during different tasks in the clinic and sport domains. The data of 39 healthy adults, acquired with a Pedar-X® system (Novel GmbH, Munich, Germany) during walking, weight lifting, and drop landing, were used to simulate the insole. The sensors were distributed by considering the location of the peak pressure on all trials: 4 on the hindfoot, 3 on the midfoot, and 9 on the forefoot. The following variables were computed with both systems and compared by estimating the Root Mean Square Error (RMSE): Peak/Mean Pressure, Ground Reaction Force (GRF), Center of Pressure (COP), the distance between COP and the origin, the Contact Area. The lowest (0.61%) and highest (82.4%) RMSE values were detected during gait on the medial-lateral COP and the GRF, respectively. This approach could be used for testing different layouts on various applications prior to production.

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Three-dimensional asymmetric maximum weight lifting prediction considering dynamic joint strength

Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine ◽

10.1177/0954411920987035 ◽

2021 ◽

pp. 095441192098703

Author(s):

Rahid Zaman ◽

Yujiang Xiang ◽

Jazmin Cruz ◽

James Yang

Keyword(s):

Experimental Data ◽

Degrees Of Freedom ◽

Inverse Dynamics ◽

Three Dimensional ◽

Optimization Method ◽

Weight Lifting ◽

Joint Torque ◽

Maximum Weight ◽

Angular Velocities ◽

Asymmetric Lifting

In this study, the three-dimensional (3D) asymmetric maximum weight lifting is predicted using an inverse-dynamics-based optimization method considering dynamic joint torque limits. The dynamic joint torque limits are functions of joint angles and angular velocities, and imposed on the hip, knee, ankle, wrist, elbow, shoulder, and lumbar spine joints. The 3D model has 40 degrees of freedom (DOFs) including 34 physical revolute joints and 6 global joints. A multi-objective optimization (MOO) problem is solved by simultaneously maximizing box weight and minimizing the sum of joint torque squares. A total of 12 male subjects were recruited to conduct maximum weight box lifting using squat-lifting strategy. Finally, the predicted lifting motion, ground reaction forces, and maximum lifting weight are validated with the experimental data. The prediction results agree well with the experimental data and the model’s predictive capability is demonstrated. This is the first study that uses MOO to predict maximum lifting weight and 3D asymmetric lifting motion while considering dynamic joint torque limits. The proposed method has the potential to prevent individuals’ risk of injury for lifting.

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