Biomechanics / Biomechanical Engineering
Alireza Rezaie Zangene; Ramila Abedi Azar; Hamidreza Naserpour; seyyed hamed hosseini nasab
Volume 16, Issue 4 , March 2023, , Pages 51-60
Abstract
Knee joint contact force (KCF) plays a significant role in the occurrence and progression of knee osteoarthritis (KOA) disease. KCF can be used in monitoring rehabilitation progress after knee arthroplasty surgery and the design of prostheses. Currently, measuring KCF is dependent on the data extracted ...
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Knee joint contact force (KCF) plays a significant role in the occurrence and progression of knee osteoarthritis (KOA) disease. KCF can be used in monitoring rehabilitation progress after knee arthroplasty surgery and the design of prostheses. Currently, measuring KCF is dependent on the data extracted from gait laboratories. The combination of artificial neural networks (ANNs) and wearable technology can overcome the limitations imposed by lab-based analysis in measuring KCF. Therefore, the present study aimed to investigate the potential of a fully-connected neural network (FCNN) in predicting the KCF via three inertial measurement unit (IMU) sensors attached to the pelvis, thigh, and shank segments. Ten healthy male volunteers participated in this study. The 3D marker trajectories and ground reaction forces (GRF) were captured at 200 Hz and 1000 Hz sampling frequencies during level-ground walking. Using a generic OpenSim model, the KCF was estimated through static optimization. The resultant KCF estimated by the musculoskeletal model was then used as the target of the neural network, while linear acceleration and 3D angular velocity data captured by three IMUs were considered as the network inputs. The network performance was investigated at intra- and inter-subject levels. Based on our findings, the proposed network of this study enables the prediction of KCF with 89% and 79% accuracy (based on the Pearson correlation coefficient) at the intra- and inter-subject levels, respectively. The results of this study promise the possibility of using IMU sensors in predicting KCF outside the lab and during daily activities.
Biomechanics of Bone / Bone Biomechanics
Sara Sadat Farshidfar; Mohammad Reza Mallakzadeh; Hamid Reza Yazdi
Volume 6, Issue 1 , June 2012, , Pages 49-55
Abstract
The aim of this study was to compare the contact area and pressure within medial and lateral compartments of tibiofemoral joint during internal and external rotational deformities of tibia bone. Methods: five lower extremities of fresh frozen human cadavers were tested by using a mechanical system was ...
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The aim of this study was to compare the contact area and pressure within medial and lateral compartments of tibiofemoral joint during internal and external rotational deformities of tibia bone. Methods: five lower extremities of fresh frozen human cadavers were tested by using a mechanical system was designed for the first time in IRAN to simulate the static position loading of standing on two legs in full extension knee under 400N loading along the longitudinal axis of each foot. The contact area and pressure were measured by FUJIfilm Prescale films under axial loading in neutral rotation and serial mal-rotations of tibia from 40 degrees external to 40 degrees internal mal-rotations in 10 degrees increments by tibial osteotomy. Results: contact area and lateral compartment contact pressure was not significantly affected by mal-rotations. Medial compartment contact pressure increased with external and decreased with internal mal-rotations. Changing the medial compartment contact pressure of tibiofemoral joint in various rotational alignments of tibia can be very effective in rapid growth of knee osteoarthritis symptoms specially in people with unilateral medial knee osteoarthritis.
