Physics-informed deep learning for musculoskeletal modeling: Predicting muscle forces and joint kinematics from surface EMG
Musculoskeletal models have been widely used for detailed biomechanical analysis to
characterise various functional impairments given their ability to estimate movement …
characterise various functional impairments given their ability to estimate movement …
A review of simulation methods for human movement dynamics with emphasis on gait
Human gait analysis is a complex problem in biomechanics because of highly nonlinear
human motion equations, muscle dynamics, and foot-ground contact. Despite a large …
human motion equations, muscle dynamics, and foot-ground contact. Despite a large …
A deep learning approach to EMG-based classification of gait phases during level ground walking
C Morbidoni, A Cucchiarelli, S Fioretti, F Di Nardo - Electronics, 2019 - mdpi.com
Correctly identifying gait phases is a prerequisite to achieve a spatial/temporal
characterization of muscular recruitment during walking. Recent approaches have …
characterization of muscular recruitment during walking. Recent approaches have …
A review of rehabilitation robot
B Li, G Li, Y Sun, G Jiang, J Kong… - 2017 32nd Youth …, 2017 - ieeexplore.ieee.org
This paper gives an overall review of research status in rehabilitation robot technology. In
order to study the status of rehabilitation robot technology, they are divided into two …
order to study the status of rehabilitation robot technology, they are divided into two …
Multimodal fusion approach based on EEG and EMG signals for lower limb movement recognition
MS Al-Quraishi, I Elamvazuthi, TB Tang… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
In this study, the fusion of cortical and muscular activities based on discriminant correlation
analysis DCA) is developed to recognize bilateral lower limb movements. Electromyography …
analysis DCA) is developed to recognize bilateral lower limb movements. Electromyography …
Intra-subject approach for gait-event prediction by neural network interpretation of EMG signals
Background Machine learning models were satisfactorily implemented for estimating gait
events from surface electromyographic (sEMG) signals during walking. Most of them are …
events from surface electromyographic (sEMG) signals during walking. Most of them are …
Recognition of gait phases with a single knee electrogoniometer: A deep learning approach
F Di Nardo, C Morbidoni, A Cucchiarelli, S Fioretti - Electronics, 2020 - mdpi.com
Artificial neural networks were satisfactorily implemented for assessing gait events from
different walking data. This study aims to propose a novel approach for recognizing gait …
different walking data. This study aims to propose a novel approach for recognizing gait …
Integration of neural architecture within a finite element framework for improved neuromusculoskeletal modeling
VL Volk, LD Hamilton, DR Hume, KB Shelburne… - Scientific Reports, 2021 - nature.com
Neuromusculoskeletal (NMS) models can aid in studying the impacts of the nervous and
musculoskeletal systems on one another. These computational models facilitate studies …
musculoskeletal systems on one another. These computational models facilitate studies …
A new muscle activation dynamics model, that simulates the calcium kinetics and incorporates the role of store-operated calcium entry channels, to enhance the …
Hill-type models are frequently used in biomechanical simulations. They are attractive for
their low computational cost and close relation to commonly measured musculotendon …
their low computational cost and close relation to commonly measured musculotendon …
Assist-as-needed control of a hip exoskeleton, using central pattern generators in a stride management strategy
This paper proposes a novel stride management strategy for rehabilitation exoskeletons.
This method incorporates a Central Pattern Generator (CPG) into an Assist-As-Needed …
This method incorporates a Central Pattern Generator (CPG) into an Assist-As-Needed …