Analysis of hand synergies in healthy subjects during bimanual manipulation of various objects (original) (raw)
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Musculoskeletal Synergies in the Grasping Hand
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2022
Investigations on how the central nervous system (CNS) effortlessly conducts complex hand movements have led to an extensive study of synergies or movement primitives. Of the different types of hand synergies, kinematic and muscle synergies have been widely studied in literature, but only a few studies have fused both. In this paper kinematic and muscle activities recorded from the activities of daily living were first fused and then dimensionally reduced through principal component analysis (PCA). By using these principal components or musculoskeletal synergies in a weighted linear combination, the recorded kinematics and muscle activities were reconstructed. The performance of these musculoskeletal synergies in reconstructing the movements was compared to the kinematic and muscle synergies reported previously in the literature by us and others. The results from these findings indicate that musculoskeletal synergies perform better than the synergies extracted without fusion. These newly demonstrated musculoskeletal synergies might improve neural control of robotics, prosthetics and exoskeletons. Clinical Relevance-In this paper, musculoskeletal synergies were extracted from the fusion of kinematic and muscle activities recorded from the activities of daily living. These newly demonstrated musculoskeletal synergies might enhance our understanding of neural control of robotics, prosthetics and exoskeletons.
IEEE Transactions on Robotics, 2000
Robotic hands differ in kinematics, dynamics, programming, control and sensing frameworks. Their common character is redundancy, which undoubtedly represents a key feature for dexterity and flexibility, but it is also a drawback for integrated automation since it typically requires additional efforts to seamlessly integrate devices, particularly robotic hands, in industrial scenario. This paper focuses on the mapping between hands with dissimilar kinematics. It is based on the argument that the reflected optimality of the pattern of grasping forces emerging from human hand synergies should be matched, in some sense, by the sought for postural synergies of robotic hands. As a natural consequence of the proposed approach, postural synergies for different kinematic structures could look entirely different in geometric shape. This difference should be a consequence of aspects such as different dimensions, kinematic structures, number of fingers, compliance, contact properties which cannot come into play if a gross geometric mapping is applied. The proposed mapping is based on the use of a virtual sphere and will be mediated by a model of an anthropomorphic robotic hand able to capture the idea of synergies in human hands.
The International Journal of Robotics Research, 2014
This paper summarizes recent activities carried out for the development of an innovative anthropomorphic robotic hand called the DEXMART Hand. The main goal of this research is to face the problems that affect current robotic hands by introducing suitable design solutions aimed at achieving simplification and cost reduction while possibly enhancing robustness and performance. While certain aspects of the DEXMART Hand development have been presented in previous papers, this paper is the first to give a comprehensive description of the final hand version and its use to replicate humanlike grasping. In this paper, particular emphasis is placed on the kinematics of the fingers and of the thumb, the wrist architecture, the dimensioning of the actuation system, and the final implementation of the position, force and tactile sensors. The paper focuses also on how these solutions have been integrated into the mechanical structure of this innovative robotic hand to enable precise force and displacement control of the whole system.
Adaptive synergies: An approach to the design of under-actuated robotic hands
Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems
To match the richness and complexity of the sensory and motor functionalities of a human hand with a robust and economically reasonable robotic device remains one of the hardest challenges in the field. Previous work has explored the possibility to exploit insight from neuroscientific results on postural correlation patterns (synergies) taming the sensorimotor complexity of hands. The postural synergy model has been recently extended to account for grasp force control through a model of “soft synergies” which incorporate hand compliance. In this paper we propose a first translation of such principles in the design of a robot hand. It so turns out that the implementation of the soft synergy model in an effective design is not obvious. The solution proposed in this paper rests on ideas coming from under-actuated hand design. We give a synthesis method to realize a desired set of soft synergies through the principled design of adaptive under-actuated mechanisms, which we call the metho...
Experimental evaluation of postural synergies during reach to grasp with the UB hand IV
IEEE International Conference on Intelligent Robots and Systems, 2011
In this paper, the postural synergies configuration subspace given by the fundamental eigengrasps of the UB Hand IV (University of Bologna Hand, version IV) is derived through experiments. This study is based on the kinematic structure of the robotic hand and on the taxonomy of the grasps of common objects. Experimental results show that it is possible to obtain grasp synthesis for a large set of objects both in the case of precision or power grasps by using only a very limited set of dominant eigengrasps. The tasks here presented are planned with an initial hold of the hand followed by reach and grasp phases, that are unique for each object/grasp combination, during which the robotic hand posture evolves continuously within a subset of the hand configuration space given by the two predominant eigenpostures. The paper reports the method adopted to define from experiments the postural synergies for the UB Hand IV and the results of the grasp tasks performed adopting the defined synergies.
Mapping Grasps from the Human Hand to the DEXMART Hand by Means of Postural Synergies and Vision
Springer Tracts in Advanced Robotics, 2013
This work aims at defining a suitable postural synergies subspace for the DEXMART Hand from observation of human hand grasping postures. Previous works were carried out on a preliminary prototype (the UB Hand IV), without neither proprioceptive integrated sensors nor external sensors, by means of a jointto-joint mapping technique. Using an RGB camera and depth sensor for 3D motion capture, the human hand palm pose and fingertip positions have been measured for a reference set of grasping postures. The proposed method for the determination of the synergies subspace is based on the kinematics mapping from the human hand to the robotic hand using data from experiments involving five subjects. The subjects' hand configurations have been mapped to the robotic hand by matching the hand pose and fingertip positions and applying a closed-loop inverse kinematic algorithm. Suitable scaling factors have been used to adapt the DEXMART Hand kinematics to the subjects' hand dimension. By means of Principal Component Analysis (PCA), the kinematic patterns of the first three predominant synergies have been computed and a brief comparison with the previous method and kinematics is reported. Finally, a synergy-based control strategy has been used for testing the efficiency of the grasp synthesis method.
Differences between kinematic synergies and muscle synergies during two-digit grasping
Frontiers in human neuroscience, 2015
The large number of mechanical degrees of freedom of the hand is not fully exploited during actual movements such as grasping. Usually, angular movements in various joints tend to be coupled, and EMG activities in different hand muscles tend to be correlated. The occurrence of covariation in the former was termed kinematic synergies, in the latter muscle synergies. This study addresses two questions: (i) Whether kinematic and muscle synergies can simultaneously accommodate for kinematic and kinetic constraints. (ii) If so, whether there is an interrelation between kinematic and muscle synergies. We used a reach-grasp-and-pull paradigm and recorded the hand kinematics as well as eight surface EMGs. Subjects had to either perform a precision grip or side grip and had to modify their grip force in order to displace an object against a low or high load. The analysis was subdivided into three epochs: reach, grasp-and-pull, and static hold. Principal component analysis (PCA, temporal or s...
Postural synergies of the UB Hand IV for human-like grasping
Robotics and Autonomous Systems, 2014
h i g h l i g h t s • A method to derive the three predominant synergies of the UB Hand IV is proposed. • The control strategy exploiting synergies for reach to grasp action is described. • Synthesis of new grasps not in the set used for synergies evaluation is achieved. • The method for synergies derivation is applied to other two robot hands. • The obtained synergies for different hands kinematics have been compared.