Estimating lower-limb joint torques during gait using inertial measurement units (IMUs) has attracted growing attention in biomechanics and wearable sensing. Conventional approaches rely on inverse dynamics based on segmental kinematics and ground reaction forces, requiring force sensors or full-body sensor setups. This study proposes a recurrent neural network (RNN) method to estimate lower-limb joint torques using segmental kinematic data from a limited number of IMUs.Twelve healthy participants performed treadmill walking and running under twelve different conditions to generate training data. Model inputs included center-of-mass accelerations and angular velocities of the pelvis and shank.Results demonstrated two key findings. First, a model using three IMUs achieved performance comparable to a seven-IMU model, with hip flexion torque errors of approximately 0.18 Nm/kg, demonstrating strong effectiveness with a reduced sensor configuration. Second, while inverse dynamics exhibited an error increase of 0.28 Nm/kg from the ankle to the hip, the proposed model showed only a 0.01 Nm/kg increase and achieved approximately 0.13 Nm/kg lower error at the hip.These results indicate that accurate and efficient joint torque estimation is feasible using an RNN with fewer wearable sensors.
The purpose of this study was to examine the effect of gender and foot landing type (forefoot vs. rearfoot landing) on kinematics, kinetics, and energy absorption of lower extremity joint. Twenty males and twenty females performed single-leg landing with two different foot landing types: forefoot landing and rearfoot landing. Three-dimensional kinematic and kinetic parameters were measured using motion capture system. Greater knee valgus angle at peak vertical ground reaction force (p = 0.034) during rearfoot landing increased the risk of anterior cruciate ligament (ACL) injury in females as increasing valgus positioning from neutral alignment could increase the load on ACL. Greater contribution of ankle joint and less contribution of hip joint in energy dissipation were found in females during both forefoot (p = 0.029 and p = 0.016, respectively) and rearfoot landing (p = 0.003 and p = 0.016, respectively). These results suggest that increasing muscular activity of ankle plantarflexor could reduce shock transmission to the proximal joint in females. In addition, greater hip joint’s contribution to total negative work in males induced lower hip flexion angle found in both forefoot and rearfoot landing by elevated activation of the hip extensor. In conclusion, landing strategy differs between genders in both forefoot and rearfoot landing.
Citations
Citations to this article as recorded by
Predicting Three-Dimensional Gait Parameters with a Single Camera Video Sequence Jungbin Lee, Cong-Bo Phan, Seungbum Koo International Journal of Precision Engineering and Manufacturing.2018; 19(5): 753. CrossRef
First
Prev
