AI Medical Compendium Journal:
Journal of biomechanics

Showing 21 to 30 of 83 articles

Glenohumeral joint force prediction with deep learning.

Journal of biomechanics
Deep learning models (DLM) are efficient replacements for computationally intensive optimization techniques. Musculoskeletal models (MSM) typically involve resource-intensive optimization processes for determining joint and muscle forces. Consequentl...

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

Journal of biomechanics
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 c...

Acute effects of robot-assisted body weight unloading on biomechanical movement patterns during overground walking.

Journal of biomechanics
Body weight unloading (BWU) is used in rehabilitation/training settings to reduce kinetic requirements, however different BWU methods may be unequally capable of preserving biomechanical movement patterns. Biomechanical analysis of both kinetic and k...

Predicting trabecular arrangement in the proximal femur: An artificial neural network approach for varied geometries and load cases.

Journal of biomechanics
Machine learning (ML) and deep learning (DL) approaches can solve the same problems as the finite element method (FEM) with a high degree of accuracy in a fraction of the required time, by learning from previously presented data. In this work, the bo...

Validity of artificial intelligence-based markerless motion capture system for clinical gait analysis: Spatiotemporal results in healthy adults and adults with Parkinson's disease.

Journal of biomechanics
Markerless motion capture methods are continuously in development to target limitations encountered in marker-, sensor-, or depth-based systems. Previous evaluation of the KinaTrax markerless system was limited by differences in model definitions, ga...

Estimating individual minimum calibration for deep-learning with predictive performance recovery: An example case of gait surface classification from wearable sensor gait data.

Journal of biomechanics
Clinical datasets often comprise multiple data points or trials sampled from a single participant. When these datasets are used to train machine learning models, the method used to extract train and test sets must be carefully chosen. Using the stand...

Age-specific biomechanical challenges and engagement in dynamic balance training with robotic or virtual real-time visual feedback.

Journal of biomechanics
Challenging balance training that targets age-related neuromuscular and motor coordination deficits is needed for effective fall prevention therapy. Goal-directed training can provide intrinsically motivating balance activities but may not equally ch...

Auto-segmentation of the tibia and femur from knee MR images via deep learning and its application to cartilage strain and recovery.

Journal of biomechanics
The ability to efficiently and reproducibly generate subject-specific 3D models of bone and soft tissue is important to many areas of musculoskeletal research. However, methodologies requiring such models have largely been limited by lengthy manual s...

Electromyography-driven model-based estimation of ankle torque and stiffness during dynamic joint rotations in perturbed and unperturbed conditions.

Journal of biomechanics
The simultaneous modulation of joint torque and stiffness enables humans to perform large repertoires of movements, while versatilely adapting to external mechanical demands. Multi-muscle force control is key for joint torque and stiffness modulation...

Validity of an artificial intelligence, human pose estimation model for measuring single-leg squat kinematics.

Journal of biomechanics
Few studies have investigated the validity of 2D pose estimation models to evaluate kinematics throughout a motion and none have included adolescents. Adolescent athletes completed single-leg squats while 3D kinematic data and 2D sagittal and frontal...