An artificial neural network for full-body posture prediction in dynamic lifting activities and effects of its prediction errors on model-estimated spinal loads.

Musculoskeletal models have indispensable applications in occupational risk assessment/management and clinical treatment/rehabilitation programs. To estimate muscle forces and joint loads, these models require body posture during the activity under consideration. Posture is usually measured via video-camera motion tracking approaches that are time-consuming, costly, and/or limited to laboratories.

Evaluating the effect of equipping an unloading knee orthosis with local muscle vibrators on clinical parameters, muscular activation level, and medial contact force in patients with medial knee osteoarthritis: A randomized trial.

Background: Unloading knee orthosis is prescribed for people with unicompartmental knee osteoarthritis (OA) to unload the damaged compartment. However, despite its benefits, wearing unloading knee orthoses in the long term may decrease knee muscle activity and have a side effect on knee OA progression rate.

Objectives: Therefore, this study aimed to determine whether equipping an unloading knee orthosis with local muscle vibrators improves its effectiveness in improving clinical parameters, medial contact force (MCF), and muscular activation levels.