AUTHOR=Scano Alessandro , Chiavenna Andrea , Molinari Tosatti Lorenzo , Müller Henning , Atzori Manfredo 

TITLE=Muscle Synergy Analysis of a Hand-Grasp Dataset: A Limited Subset of Motor Modules May Underlie a Large Variety of Grasps

JOURNAL=Frontiers in Neurorobotics

VOLUME=Volume 12 - 2018

YEAR=2018

URL=https://www.frontiersin.org/journals/neurorobotics/articles/10.3389/fnbot.2018.00057

DOI=10.3389/fnbot.2018.00057

ISSN=1662-5218

ABSTRACT=Background: Kinematic and muscle patterns underlying hand grasps have been widely investigated in the literature, especially exploiting feature extracting methods. However, due to limitations in the number of examined grasps and number of involved subjects, the identification of a reduced set of motor modules, generalizing across subjects and grasps, may be valuable for increasing the knowledge of hand motor control, and provide methods to be exploited in prosthesis control and hand rehabilitation.
Methods: Motor Muscle Synergies were extracted from a publicly available database including 28 healthy subjects, each one executing 20 hand grasps selected for daily-life activities. The spatial and temporal components of motor synergies were analyzed with a clustering algorithm to provide synthetic characterization of the basic patterns underlying hand-grasps.
Results: Motor synergies were successfully extracted on all 28 subjects, and the clustering algorithm was tested by comparing the reconstruction achieved with clustering orders ranging from 2 to 50. A subset of ten clusters, each one represented by a spatial motor module, approximates the original dataset with a mean maximum error of 5% on reconstructed modules; however, each spatial synergy might be employed with different timing and recruited at different grasp stages.
Conclusions: The results suggest that a limited number of motor modules, correctly elicited by a control activation signal, may underlie the execution of a large variety of hand grasps. However, spatial synergies are not strongly related to specific motor functions but may be recruited at different stages, depending on subject and grasp. This result can lead to applications in rehabilitation and assistive robotics, by joining robotics and neuroscience findings.