TY - CHAP
T1 - A synergistic behavior underpins human hand grasping force control during environmental constraint exploitation
AU - Averta, Giuseppe
AU - Battaglia, Edoardo
AU - Della Santina, Cosimo
AU - Catalano, Manuel G.
AU - Bianchi, Matteo
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2019.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85055319824&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-01845-0_13
DO - 10.1007/978-3-030-01845-0_13
M3 - Chapter
AN - SCOPUS:85055319824
T3 - Biosystems and Biorobotics
SP - 67
EP - 71
BT - Biosystems and Biorobotics
PB - Springer International Publishing
ER -