@article {3697, title = {The SoftHand Pro: Functional evaluation of a novel, flexible, and robust myoelectric prosthesis}, journal = {PLOS One}, year = {2018}, author = {S. B. Godfrey and K. Zhao and A. Theuer and M. G. Catalano and M. Bianchi and R. Breighner and D. Bhaskaran and R. Lennon and G. Grioli and M. Santello and A. Bicchi and K. Andrews} } @conference {3747, title = {The softpro project: Synergy-based open-source technologies for prosthetics and rehabilitation}, booktitle = {International Symposium on Wearable Robotics}, year = {2018}, doi = {https://doi.org/10.1007/978-3-030-01887-0_71}, author = {C. Piazza and M. G. Catalano and M. Bianchi and E. Ricciardi and D. Pratichizzo and S. Haddadin and Luft, A. R. L. and O. Lambercy and R. Gassert and E. Jakubowitz and H. Van Der Kooij and F. Tonis and F. Bonomo and B. de Jonge and T. Ward and K. Zhao and M. Santello and A. Bicchi} } @article {3309, title = {Grasp Performance of a Soft Synergy-Based Prosthetic Hand: A Pilot Study}, journal = { IEEE Transactions on Neural Systems and Rehabilitation Engineering}, volume = {25}, year = {2017}, month = {12/2017}, pages = {2407 - 2417}, abstract = {

Current prosthetic hands are frequently rejected in part due to limited functionality and versatility. We assessed the feasibility of a novel prosthetic hand, the SoftHand Pro (SHP), whose design combines soft robotics and hand postural synergies. Able-bodied subjects (n = 23) tracked cursor motion by opening and closing the SHP and performed a grasp-lift-hold-release (GLHR) task with a sensorized cylindrical object of variable weight. The SHP control was driven by electromyographic (EMG) signals from two antagonistic muscles. Although the time to perform the GLHR task was longer for the SHP than native hand for the first few trials (10.2 {\textpm} 1.4 s and 2.13 {\textpm} 0.09 s, respectively), performance was much faster on subsequent trials (~5 s). The SHP steady-state grip force was significantly modulated as a function of object weight (p \<; 0.001). For the native hand, however, peak and steady-state grip forces were modulated to a greater extent (+68\% and +91\%, respectively). These changes were mediated by the modulation of EMG amplitude and co-contraction. These data suggest that the SHP has a promise for prosthetic applications and point-to-design modifications that could improve the SHP.

}, keywords = {Haptics, Robotics}, issn = {1534-4320}, doi = {10.1109/TNSRE.2017.2737539}, url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\&arnumber=8094246}, author = {A. S. Gailey and Godfrey, S.B. and R. Breighner and K. Andrews and K. Zhao and A. Bicchi and M. Santello} } @article {3216, title = {Postural Hand Synergies during Environmental Constraint Exploitation}, journal = {Fronters in Neurorobotics}, year = {2017}, month = {08/2017}, abstract = {

Humans are able to intuitively exploit the shape of an object and environmental constraints to achieve stable grasps and perform dexterous manipulations. In doing that, a vast range of kinematic strategies can be observed. However, in this work we formulate the hypothesis that such ability can be described in terms of a synergistic behavior in the generation of hand postures, i.e., using a reduced set of commonly used kinematic patterns. This is in analogy with previous studies showing the presence of such behavior in different tasks, such as grasping. We investigated this hypothesis in experiments performed by six subjects, who were asked to grasp objects from a flat surface. We quantitatively characterized hand posture behavior from a kinematic perspective, i.e., the hand joint angles, in both pre-shaping and during the interaction with the environment. To determine the role of tactile feedback, we repeated the same experiments but with subjects wearing a rigid shell on the fingertips to reduce cutaneous afferent inputs. Results show the persistence of at least two postural synergies in all the considered experimental conditions and phases. Tactile impairment does not alter significantly the first two synergies, and contact with the environment generates a change only for higher order Principal Components. A good match also arises between the first synergy found in our analysis and the first synergy of grasping as quantified by previous work. The present study is motivated by the interest of learning from the human example, extracting lessons that can be applied in robot design and control. Thus, we conclude with a discussion on implications for robotics of our findings.

}, keywords = {Haptics, Robotics}, doi = {https://doi.org/10.3389/fnbot.2017.00041}, url = {https://www.frontiersin.org/articles/10.3389/fnbot.2017.00041/full}, author = {C. Della Santina and M. Bianchi and G. Averta and S. Ciotti and V. Arapi and S. Fani and E. Battaglia and M. G. Catalano and M. Santello and A. Bicchi} } @article {2844, title = {Assessment of Myoelectric Controller Performance and Kinematic Behavior of a Novel Soft Synergy-inspired Robotic Hand for Prosthetic Applications}, journal = {Frontiers in Neurorobotics}, volume = {10}, year = {2016}, month = {10/2016}, abstract = {

Myoelectric-artificial limbs can significantly advance the state of the art in prosthetics, since they can be used to control mechatronic devices through muscular activity in a way that mimics how the subjects used to activate their muscles before limb loss. However, surveys indicate that dissatisfaction with the functionality of terminal devices underlies the widespread abandonment of prostheses. We believe that one key factor to improve acceptability of prosthetic devices is to attain human-likeness of prosthesis movements, a goal which is being pursued by research on social and human-robot interactions. Therefore, to reduce early abandonment of terminal devices, we propose that controllers should be designed such as to ensure effective task accomplishment in a natural fashion. In this work, we have analyzed and compared the performance of three types of myoelectric controller algorithms based on surface electromyography to control an under-actuated and multi-degrees of freedom prosthetic hand, the SoftHand Pro. The goal of the present study was to identify the myoelectric algorithm that best mimics the native hand movements. As a preliminary step, we first quantified the repeatability of the SoftHand Pro finger movements and identified the electromyographic recording sites for able-bodied individuals with the highest signal-to-noise ratio from two pairs of muscles, i.e. flexor digitorum superficialis/extensor digitorum communis, and flexor carpi radialis/extensor carpi ulnaris. Able-bodied volunteers were then asked to execute reach-to-grasp movements, while electromyography signals were recorded from flexor digitorum superficialis/extensor digitorum communis as this was identified as the muscle pair characterized by high signal-to-noise ratio and intuitive control. Subsequently, we tested three myoelectric controllers that mapped electromyography signals to position of the SoftHand Pro. We found that a differential electromyography-to-position mapping ensured the highest coherence with hand movements. Our results represent a first step towards a more effective and intuitive control of myoelectric hand prostheses.

}, keywords = {Haptics, Robotics}, doi = {10.3389/fnbot.2016.00011}, url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5066092/}, author = {S. Fani and M. Bianchi and S. Jain and J. Pimenta Neto and S. Boege and G. Grioli and A. Bicchi and M. Santello} } @article {2652, title = {Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands}, journal = {Physics of Life Reviews}, volume = {17}, year = {2016}, month = {07/2016}, pages = {1-23}, keywords = {Haptics, Robotics}, url = {http://www.sciencedirect.com/science/article/pii/S1571064516000269}, author = {M. Santello and M. Bianchi and M Gabiccini and E. Ricciardi and G. Salvietti and D Prattichizzo and M. Ernst and A. Moscatelli and H. Jorntell and A. Kappers and K. Kyriakopulos and A Albu-Schaeffer and C. Castellini and A. Bicchi} } @conference {2899, title = {Influence of Force Feedback on Grasp Force Modulation in Prosthetic Applications: a Preliminary Study}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2016 38th Annual International Conference }, year = {2016}, address = {Orlando, USA, August 16-20, 2016}, doi = {10.1109/EMBC.2016.7591957}, url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7591957}, author = {S. B. Godfrey and M. Bianchi and A. Bicchi and M. Santello} } @inbook {2865, title = {The SoftHand Pro: Translation from Robotic Hand to Prosthetic Prototype}, booktitle = {Converging Clinical and Engineering Research on Neurorehabilitation II}, volume = {15}, number = {Biosystems \& Biorobotics }, year = {2016}, note = {

Proceedings of the 3rd International Conference on NeuroRehabilitation (ICNR2016), October 18-21, 2016, Segovia, Spain

}, pages = {469-473}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, abstract = {

This work presents the translation from a humanoid robotic hand to a prosthetic prototype and its first evaluation in a set of 9 persons with amputation. The Pisa/IIT SoftHand is an underactuated hand built on the neuroscientific principle of motor synergies enabling it to perform natural, human-like movements and mold around grasped objects with minimal control input. These features motivated the development of the SoftHand Pro, a prosthetic version of the SoftHand built to interface with a prosthetic socket. The results of the preliminary testing of the SoftHand Pro showed it to be a highly functional design with an intuitive control system. Present results warrant further testing to develop the SoftHand Pro.

}, keywords = {Haptics, Robotics}, issn = {978-3-319-46668-2}, doi = {10.1007/978-3-319-46669-9_78}, url = {http://link.springer.com/chapter/10.1007/978-3-319-46669-9_78}, author = {S. B. Godfrey and M. Bianchi and K. Zhao and M. G. Catalano and R. Breighner and A. Theuer and K. Andrews and G. Grioli and M. Santello and A. Bicchi} } @article {2660, title = {A synergy-based hand control is encoded in human motor cortical areas}, journal = {eLIFE}, year = {2016}, abstract = {

How the human brain controls hand movements to carry out different tasks is still debated. The concept of\ synergy\ has been proposed to indicate functional modules that may simplify the control of hand postures by simultaneously recruiting sets of muscles and joints. However, whether and to what extent synergic hand postures are encoded as such at a cortical level remains unknown. Here, we combined kinematic, electromyography, and brain activity measures obtained by functional magnetic resonance imaging while subjects performed a variety of movements towards virtual objects. Hand postural information, encoded through kinematic synergies, were represented in cortical areas devoted to hand motor control and successfully discriminated individual grasping movements, significantly outperforming alternative somatotopic or muscle-based models. Importantly, hand postural synergies were predicted by neural activation patterns within primary motor cortex. These findings support a novel cortical organization for hand movement control and open potential applications for brain-computer interfaces and neuroprostheses.

}, doi = {http://dx.doi.org/10.7554/eLife.13420}, url = {http://elifesciences.org/content/5/e13420v2}, author = {A. Leo and G. Handjaras and M. Bianchi and H. Marino and M Gabiccini and Guidi, A. and E. P. Scilingo and P. Pietrini and A. Bicchi and M. Santello and E. Ricciardi} } @article {2544, title = {ThimbleSense: a fingertip-wearable tactile sensor for grasp analysis}, journal = {IEEE Transactions on Haptics}, volume = {9}, year = {2016}, note = {
This work was partially supported by the European Community funded projects WEARHAP, PACMAN and SOMA (contracts 601165, 600918 and 645599 respectively), by the ERC Advanced Grant no. 291166 SoftHands
}, month = {03/2016}, pages = {121-133}, abstract = {

Accurate measurement of contact forces between hand and grasped objects is crucial to study sensorimotor control during grasp and manipulation. In this work we introduce ThimbleSense, a prototype of individual-digit wearable force/torque sensor based on the principle of intrinsic tactile sensing. By exploiting the integration of this approach with an active marker-based motion capture system, the proposed device simultaneously measures absolute position and orientation of the fingertip, which in turn yields measurements of contacts and force components expressed in a global reference frame. The main advantage of this approach with respect to more conventional solutions is its versatility. Specifically, ThimbleSense can be used to study grasping and manipulation of a wide variety of objects, while still retaining complete force/torque measurements. Nevertheless, validation of the proposed device is a necessary step before it can be used for experimental purposes. In this work we present the results of a series of experiments designed to validate the accuracy of ThimbleSense measurements and evaluate the effects of distortion of tactile afferent inputs caused by the device{\textquoteright}s rigid shells on grasp forces.

}, keywords = {Haptics, Robotics}, issn = {1939-1412}, doi = {10.1109/TOH.2015.2482478}, url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\&arnumber=7294702}, author = {E. Battaglia and M. Bianchi and Altobelli, A and G. Grioli and M. G. Catalano and A. Serio and M. Santello and A. Bicchi} } @conference {2083, title = {ThimbleSense: A new wearable tactile device for human and robotic fingers }, booktitle = {Haptics Symposium (HAPTICS), 2014 IEEE}, year = {2014}, address = {Houston, TX}, keywords = {Haptics, Robotics}, doi = {10.1109/HAPTICS.2014.6775571}, author = {E. Battaglia and G. Grioli and M. G. Catalano and M. Bianchi and A. Serio and M. Santello and A. Bicchi} } @conference {2130, title = {ThimbleSense: An Individual-Digit Wearable Tactile Sensor for Experimental Grasp Studies}, booktitle = {IEEE International Conference on Robotics and Automation - ICRA 2014}, year = {2014}, pages = {2728 - 2735 }, publisher = {IEEE}, organization = {IEEE}, address = { Hong Kong, May 31 - June 7, 2014}, abstract = {

Measuring contact forces applied by a hand to a grasped object is a necessary step to understand the mysteries that still hide in the unparalleled human grasping ability. Nevertheless, simultaneous collection of information about the position of contacts and about the magnitude and direction of forces is still an elusive task. In this paper we introduce a wearable device that addresses this problem, and can be used to measure generalized forces during grasping. By assembling two supports around a commercial 6-axis force/torque sensor we obtain a thimble that can be easily positioned on a fingertip. The device is used in conjunction with an active marker-based motion capture system to simultaneously obtain absolute position and orientation of the thimbles, without requiring any assumptions on the kinematics of the hand. Finally, using the contact centroid algorithm, introduced in [1], position of contact points during grasping are determined. This paper shows the design and implementation of the device, as well as some preliminary experimental validation.

}, keywords = {Haptics, Robotics}, doi = {10.1109/ICRA.2014.6907250 }, url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\&arnumber=6907250}, author = {E. Battaglia and G. Grioli and M. G. Catalano and M. Santello and A. Bicchi} } @article {BGS11, title = {Modeling Natural and Artificial Hands with Synergies}, journal = {Philosophical Transactions of the Royal Society B}, volume = {366}, year = {2011}, pages = {3153 - 3161}, keywords = {Haptics, Robotics}, doi = {10.1098/rstb.2011.0152}, author = {A. Bicchi and M Gabiccini and M. Santello} } @conference {BGSSB, title = {Validation of a Virtual Reality Environment to Study Anticipatory Modulation of Digit Forces and Position}, booktitle = {Eurohaptics 2010}, series = {Lecture Notes in Computer Science}, volume = {6192/2010}, year = {2010}, month = {July, 8 - 10}, pages = {136 - 143}, address = {Amsterdam (The Netherlands)}, keywords = {Haptics, Robotics}, author = {M. Bianchi and G. Grioli and E. P. Scilingo and M. Santello and A. Bicchi} }