AI Medical Compendium Journal:
Journal of biomechanics

Showing 51 to 60 of 83 articles

A machine-learning method for classifying and analyzing foot placement: Application to manual material handling.

Journal of biomechanics
Foot placement strategy is an essential aspect in the study of movement involving full body displacement. To get beyond a qualitative analysis, this paper provides a foot placement classification and analysis method that can be used in sports, rehabi...

Coupled artificial neural networks to estimate 3D whole-body posture, lumbosacral moments, and spinal loads during load-handling activities.

Journal of biomechanics
Biomechanical modeling approaches require body posture to evaluate the risk of spine injury during manual material handling. The procedure to measure body posture via motion-analysis techniques as well as the subsequent calculations of lumbosacral mo...

A probabilistic method to estimate gait kinetics in the absence of ground reaction force measurements.

Journal of biomechanics
Human joint torques during gait are usually computed using inverse dynamics. This method requires a skeletal model, kinematics and measured ground reaction forces and moments (GRFM). Measuring GRFM is however only possible in a controlled environment...

Neural muscle activation detection: A deep learning approach using surface electromyography.

Journal of biomechanics
The timing of muscles activation which is a key parameter in determining plenty of medical conditions can be greatly assessed by the surface EMG signal which inherently carries an immense amount of information. Many techniques for measuring muscle ac...

On-field player workload exposure and knee injury risk monitoring via deep learning.

Journal of biomechanics
In sports analytics, an understanding of accurate on-field 3D knee joint moments (KJM) could provide an early warning system for athlete workload exposure and knee injury risk. Traditionally, this analysis has relied on captive laboratory force plate...

Differences in muscle activity and fatigue of the upper limb between Task-Specific training and robot assisted training among individuals post stroke.

Journal of biomechanics
OBJECTIVE: To compare the activity and fatigue of upper extremity muscles, pain levels, subject satisfaction levels, perceived exertion, and number of repetitions in Task-Specific Training (TST) compared with Robot-Assisted Training (RAT) in individu...

Computational modeling of neuromuscular response to swing-phase robotic knee extension assistance in cerebral palsy.

Journal of biomechanics
Predicting subject-specific responses to exoskeleton assistance may aid in maximizing functional gait outcomes, such as achieving full knee-extension at foot contact in individuals with crouch gait from cerebral palsy (CP). The purpose of this study ...

Markerless 2D kinematic analysis of underwater running: A deep learning approach.

Journal of biomechanics
Kinematic analysis is often performed with a camera system combined with reflective markers placed over bony landmarks. This method is restrictive (and often expensive), and limits the ability to perform analyses outside of the lab. In the present st...

A Deep Neural Network-based method for estimation of 3D lifting motions.

Journal of biomechanics
The aim of this study is developing and validating a Deep Neural Network (DNN) based method for 3D pose estimation during lifting. The proposed DNN based method addresses problems associated with marker-based motion capture systems like excessive pre...

A novel approach to predicting human ingress motion using an artificial neural network.

Journal of biomechanics
Due to the increased availability of digital human models, the need for knowing human movement is important in product design process. If the human motion is derived rapidly as design parameters change, a developer could determine the optimal paramet...