A comprehensive analysis of task-specific hand kinematic, muscle and force synergies

Lapresa, Martina; Corradini, Virginia; Iacca, Antonio; Scotto di Luzio, Francesco; Zollo, Loredana; Cordella, Francesca

doi:10.1016/j.bbe.2024.01.006

Cited by 4 publications

(2 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Link to the task space . A major step toward the conception of synergy-driven approaches may also come from the linking of neural synergies to the task space variables [ 14 ], which has been addressed with recent novel algorithms that extend the concept of synergies by incorporating task variables to the neural drive [ 66 , 67 , 68 ] or factorizations based on multidomain approaches [ 18 ]. In such approaches, muscle weights are flanked with task weights (typically kinematic or force) that show how the neural synergy results in a task output.…”

Section: Challengesmentioning

confidence: 99%

Transferring Sensor-Based Assessments to Clinical Practice: The Case of Muscle Synergies

Scano,

Lanzani,

Brambilla

et al. 2024

Sensors

View full text Add to dashboard Cite

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 movement kinematics and interaction forces. Such measurements are commonly employed in clinics with the aim of assessing patients’ pathologies, but so far some of them have found full exploitation mainly for research purposes. In fact, even though the data they allow to gather may shed light on physiopathology and mechanisms underlying motor recovery in rehabilitation, their practical use in the clinical environment is mainly devoted to research studies, with a very reduced impact on clinical practice. This is especially the case for muscle synergies, a well-known method for the evaluation of motor control in neuroscience based on multichannel EMG recordings. In this paper, considering neuromotor rehabilitation as one of the most important scenarios for exploiting novel methods to assess motor control, the main challenges and future perspectives for the standard clinical adoption of muscle synergy analysis are reported and critically discussed.

show abstract

Section: Challengesmentioning

confidence: 99%

Transferring Sensor-Based Assessments to Clinical Practice: The Case of Muscle Synergies

Scano,

Lanzani,

Brambilla

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

“…Several studies have demonstrated the presence of muscle synergies in the human hand during various grasping and manipulation tasks [33]. These findings have inspired the development of robotic controllers that utilize muscle synergies to generate hand movements [34]. In these approaches, synergies are typically implemented as a set of predefined muscle activation commands that can be linearly combined to produce different hand postures and movements [35].…”

Section: Introductionmentioning

confidence: 99%

Anthropomorphic Tendon-Based Hands Controlled by Agonist–Antagonist Corticospinal Neural Network

García-Córdova,

Guerrero-González,

Hidalgo-Castelo

2024

Sensors

View full text Add to dashboard Cite

This article presents a study on the neurobiological control of voluntary movements for anthropomorphic robotic systems. A corticospinal neural network model has been developed to control joint trajectories in multi-fingered robotic hands. The proposed neural network simulates cortical and spinal areas, as well as the connectivity between them, during the execution of voluntary movements similar to those performed by humans or monkeys. Furthermore, this neural connection allows for the interpretation of functional roles in the motor areas of the brain. The proposed neural control system is tested on the fingers of a robotic hand, which is driven by agonist–antagonist tendons and actuators designed to accurately emulate complex muscular functionality. The experimental results show that the corticospinal controller produces key properties of biological movement control, such as bell-shaped asymmetric velocity profiles and the ability to compensate for disturbances. Movements are dynamically compensated for through sensory feedback. Based on the experimental results, it is concluded that the proposed biologically inspired adaptive neural control system is robust, reliable, and adaptable to robotic platforms with diverse biomechanics and degrees of freedom. The corticospinal network successfully integrates biological concepts with engineering control theory for the generation of functional movement. This research significantly contributes to improving our understanding of neuromotor control in both animals and humans, thus paving the way towards a new frontier in the field of neurobiological control of anthropomorphic robotic systems.

show abstract

A Radar-Based Concept for Simultaneous High-Resolution Imaging and Pixel-Wise Velocity Analysis for Tracking Human Motion

Bräunig,

Heinrich,

Coppers

et al. 2024

IEEE J. Microw.

View full text Add to dashboard Cite

A comprehensive analysis of task-specific hand kinematic, muscle and force synergies

Cited by 4 publications

References 36 publications

Transferring Sensor-Based Assessments to Clinical Practice: The Case of Muscle Synergies

Transferring Sensor-Based Assessments to Clinical Practice: The Case of Muscle Synergies

Anthropomorphic Tendon-Based Hands Controlled by Agonist–Antagonist Corticospinal Neural Network

A Radar-Based Concept for Simultaneous High-Resolution Imaging and Pixel-Wise Velocity Analysis for Tracking Human Motion

Contact Info

Product

Resources

About