Despite the complex nature of human hands, neuroscientific studies suggested a simplified kinematic control underpinning motion generation, resulting in principal joint angle co-variation patterns, usually called postural hand synergies. Such a low dimensional description was observed in common grasping tasks, and was proven to be preserved also for grasps performed by exploiting the external environment (e.g., picking up a key by sliding it on a table). In this paper, we extend this analysis to the force domain. To do so, we performed experiments with six subjects, who were asked to grasp objects from a flat surface while force/torque measures were acquired at fingertip level through wearable sensors. The set of objects was chosen so that participants were forced to interact with the table to achieve a successful grasp. Principal component analysis was applied to force measurements to investigate the existence of co-variation schemes, i.e. a synergistic behavior. Results show that one principal component explains most of the hand force distribution. Applications to clinical assessment and robotic sensing are finally discussed.

A synergistic behavior underpins human hand grasping force control during environmental constraint exploitation / Averta, G.; Battaglia, E.; Della Santina, C.; Catalano, M. G.; Bianchi, M. (BIOSYSTEMS & BIOROBOTICS). - In: Converging Clinical and Engineering Research on Neurorehabilitation IIICham (Switzerland) : Springer International Publishing, 2019. - ISBN 978-3-030-01844-3. - pp. 67-71 [10.1007/978-3-030-01845-0_13]

A synergistic behavior underpins human hand grasping force control during environmental constraint exploitation

Averta G.;
2019

Abstract

Despite the complex nature of human hands, neuroscientific studies suggested a simplified kinematic control underpinning motion generation, resulting in principal joint angle co-variation patterns, usually called postural hand synergies. Such a low dimensional description was observed in common grasping tasks, and was proven to be preserved also for grasps performed by exploiting the external environment (e.g., picking up a key by sliding it on a table). In this paper, we extend this analysis to the force domain. To do so, we performed experiments with six subjects, who were asked to grasp objects from a flat surface while force/torque measures were acquired at fingertip level through wearable sensors. The set of objects was chosen so that participants were forced to interact with the table to achieve a successful grasp. Principal component analysis was applied to force measurements to investigate the existence of co-variation schemes, i.e. a synergistic behavior. Results show that one principal component explains most of the hand force distribution. Applications to clinical assessment and robotic sensing are finally discussed.
2019
978-3-030-01844-3
978-3-030-01845-0
Converging Clinical and Engineering Research on Neurorehabilitation III
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2970299