Motion capture technology in industrial applications: A systematic review
The rapid technological advancements of Industry 4.0 have opened up new vectors for novel
industrial processes that require advanced sensing solutions for their realization. Motion …
industrial processes that require advanced sensing solutions for their realization. Motion …
Recent advances and applications of machine learning in experimental solid mechanics: A review
For many decades, experimental solid mechanics has played a crucial role in characterizing
and understanding the mechanical properties of natural and novel artificial materials …
and understanding the mechanical properties of natural and novel artificial materials …
CNN-based estimation of sagittal plane walking and running biomechanics from measured and simulated inertial sensor data
Machine learning is a promising approach to evaluate human movement based on
wearable sensor data. A representative dataset for training data-driven models is crucial to …
wearable sensor data. A representative dataset for training data-driven models is crucial to …
Real‐time biomechanics using the finite element method and machine learning: Review and perspective
R Phellan, B Hachem, J Clin, JM Mac‐Thiong… - Medical …, 2021 - Wiley Online Library
Purpose The finite element method (FEM) is the preferred method to simulate phenomena in
anatomical structures. However, purely FEM‐based mechanical simulations require …
anatomical structures. However, purely FEM‐based mechanical simulations require …
The use of synthetic imu signals in the training of deep learning models significantly improves the accuracy of joint kinematic predictions
Gait analysis based on inertial sensors has become an effective method of quantifying
movement mechanics, such as joint kinematics and kinetics. Machine learning techniques …
movement mechanics, such as joint kinematics and kinetics. Machine learning techniques …
Machine learning for rapid estimation of lower extremity muscle and joint loading during activities of daily living
Joint contact and muscle forces estimated with musculoskeletal modeling techniques offer
useful metrics describing movement quality that benefit multiple research and clinical …
useful metrics describing movement quality that benefit multiple research and clinical …
Estimating ground reaction forces from two-dimensional pose data: a biomechanics-based comparison of alphapose, blazepose, and openpose
M Mundt, Z Born, M Goldacre, J Alderson - Sensors, 2022 - mdpi.com
The adoption of computer vision pose estimation approaches, used to identify keypoint
locations which are intended to reflect the necessary anatomical landmarks relied upon by …
locations which are intended to reflect the necessary anatomical landmarks relied upon by …
Recent machine learning progress in lower limb running biomechanics with wearable technology: A systematic review
With the emergence of wearable technology and machine learning approaches, gait
monitoring in real-time is attracting interest from the sports biomechanics community. This …
monitoring in real-time is attracting interest from the sports biomechanics community. This …
Estimation of gait events and kinetic waveforms with wearable sensors and machine learning when running in an unconstrained environment
SR Donahue, ME Hahn - Scientific Reports, 2023 - nature.com
Wearable sensors and machine learning algorithms are becoming a viable alternative for
biomechanical analysis outside of the laboratory. The purpose of this work was to estimate …
biomechanical analysis outside of the laboratory. The purpose of this work was to estimate …
Estimating running ground reaction forces from plantar pressure during graded running
Ground reaction forces (GRFs) describe how runners interact with their surroundings and
provide the basis for computing inverse dynamics. Wearable technology can predict time …
provide the basis for computing inverse dynamics. Wearable technology can predict time …