On the modeling of biomechanical systems for human movement analysis: a narrative review
The rising importance of movement analysis led to the development of more complex
biomechanical models to describe in detail the human motion patterns. The models scaled …
biomechanical models to describe in detail the human motion patterns. The models scaled …
Myoelectric control systems for upper limb wearable robotic exoskeletons and exosuits—A systematic review
In recent years, myoelectric control systems have emerged for upper limb wearable robotic
exoskeletons to provide movement assistance and/or to restore motor functions in people …
exoskeletons to provide movement assistance and/or to restore motor functions in people …
Deep learning for processing electromyographic signals: A taxonomy-based survey
Deep Learning (DL) has been recently employed to build smart systems that perform
incredibly well in a wide range of tasks, such as image recognition, machine translation, and …
incredibly well in a wide range of tasks, such as image recognition, machine translation, and …
Myoelectric model reference adaptive control with adaptive kalman filter for a soft elbow exoskeleton
Rehabilitation and assistance exoskeletons have been widely studied because they allow to
provide more effective, intensive, and adaptive therapies; in addition, they can be used to …
provide more effective, intensive, and adaptive therapies; in addition, they can be used to …
A feature-encoded physics-informed parameter identification neural network for musculoskeletal systems
Identification of muscle-tendon force generation properties and muscle activities from
physiological measurements, eg, motion data and raw surface electromyography (sEMG) …
physiological measurements, eg, motion data and raw surface electromyography (sEMG) …
Variability of muscle synergies in hand grasps: Analysis of intra-and inter-session data
Background. Muscle synergy analysis is an approach to understand the neurophysiological
mechanisms behind the hypothesized ability of the Central Nervous System (CNS) to reduce …
mechanisms behind the hypothesized ability of the Central Nervous System (CNS) to reduce …
A multi-resolution physics-informed recurrent neural network: formulation and application to musculoskeletal systems
This work presents a multi-resolution physics-informed recurrent neural network (MR PI-
RNN), for simultaneous prediction of musculoskeletal (MSK) motion and parameter …
RNN), for simultaneous prediction of musculoskeletal (MSK) motion and parameter …
A continuous estimation model of upper limb joint angles by using surface electromyography and deep learning method
Y Chen, S Yu, K Ma, S Huang, G Li, S Cai, L **e - IEEE Access, 2019 - ieeexplore.ieee.org
The continuous control of rehabilitation robots based on surface electromyography (sEMG)
is a natural control strategy that can ensure human safety and ease the discomfort of human …
is a natural control strategy that can ensure human safety and ease the discomfort of human …
A comparison between two semantic deep learning frameworks for the autosomal dominant polycystic kidney disease segmentation based on magnetic resonance …
Background The automatic segmentation of kidneys in medical images is not a trivial task
when the subjects undergoing the medical examination are affected by Autosomal Dominant …
when the subjects undergoing the medical examination are affected by Autosomal Dominant …
The number and structure of muscle synergies depend on the number of recorded muscles: a pilot simulation study with opensim
The muscle synergy approach is used to evaluate motor control and to quantitatively
determine the number and structure of the modules underlying movement. In experimental …
determine the number and structure of the modules underlying movement. In experimental …