Transferring sensor-based assessments to clinical practice: the case of muscle synergies

A Scano, V Lanzani, C Brambilla, A d'Avella - Sensors, 2024 - mdpi.com
Sensor-based assessments in medical practice and rehabilitation include the measurement
of physiological signals such as EEG, EMG, ECG, heart rate, and NIRS, and the recording of …

Noninvasive neural interfacing with wearable muscle sensors: Combining convolutive blind source separation methods and deep learning techniques for neural …

A Holobar, D Farina - IEEE signal processing magazine, 2021 - ieeexplore.ieee.org
Neural interfacing is essential for advancing our fundamental understanding of movement
neurophysiology and for develo** human-machine interaction systems. This can be …

Deep learning for processing electromyographic signals: A taxonomy-based survey

D Buongiorno, GD Cascarano, I De Feudis, A Brunetti… - Neurocomputing, 2021 - Elsevier
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 …

Evaluation of methods for the extraction of spatial muscle synergies

K Zhao, H Wen, Z Zhang, M Atzori, H Müller… - Frontiers in …, 2022 - frontiersin.org
Muscle synergies have been largely used in many application fields, including motor control
studies, prosthesis control, movement classification, rehabilitation, and clinical studies. Due …

Dissecting muscle synergies in the task space

D O'Reilly, I Delis - Elife, 2024 - elifesciences.org
The muscle synergy is a guiding concept in motor control research that relies on the general
notion of muscles 'working together'towards task performance. However, although the …

[HTML][HTML] Cardiovr-retone—robotic exoskeleton for upper limb rehabilitation following open heart surgery: Design, modelling, and control

B Mocan, C Schonstein, C Neamtu, M Murar, M Fulea… - Symmetry, 2022 - mdpi.com
Following cardiac surgery, patients experience difficulties with the rehabilitation process,
often finding it difficult, and therefore lack the motivation for rehabilitation activities. As the …

A Cable-Driven Upper Limb Rehabilitation Robot with Muscle-Synergy-Based Myoelectric Controller

C **e, Y Lyu, G Li, RKY Tong, H **a… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Surface electromyography (sEMG) signal has been used in upper limb rehabilitation robots
(ULRR). However, existing ULRR based on myoelectric controllers suffered from limited …

A Serious Game for the Assessment of Visuomotor Adaptation Capabilities during Locomotion Tasks Employing an Embodied Avatar in Virtual Reality

V Suglia, A Brunetti, G Pasquini, M Caputo, TM Marvulli… - Sensors, 2023 - mdpi.com
The study of visuomotor adaptation (VMA) capabilities has been encompassed in various
experimental protocols aimed at investigating human motor control strategies and/or …

Continuous Prediction of Wrist Joint Kinematics Using Surface Electromyography from the Perspective of Muscle Anatomy and Muscle Synergy Feature Extraction

Z Wei, M Li, ZQ Zhang, SQ **e - IEEE Journal of Biomedical …, 2024 - ieeexplore.ieee.org
Post-stroke upper limb dysfunction severely impacts patients' daily life quality. Utilizing
sEMG signals to predict patients' motion intentions enables more effective rehabilitation by …

How many muscles? Optimal muscles set search for optimizing myocontrol performance

C Camardella, M Junata, KC Tse, A Frisoli… - Frontiers in …, 2021 - frontiersin.org
In myo-control, for computational and setup constraints, the measurement of a high number
of muscles is not always possible: the choice of the muscle set to use in a myo-control …