00760nas a2200217 4500008004100000245010000041210006900141100001900210700001300229700001500242700002000257700001600277700001800293700001800311700001500329700001500344700001600359700001500375700001600390856013600406 2018 eng d00aThe SoftHand Pro: Functional evaluation of a novel, flexible, and robust myoelectric prosthesis0 aSoftHand Pro Functional evaluation of a novel flexible and robus1 aGodfrey, S. B.1 aZhao, K.1 aTheuer, A.1 aCatalano, M. G.1 aBianchi, M.1 aBreighner, R.1 aBhaskaran, D.1 aLennon, R.1 aGrioli, G.1 aSantello, M1 aBicchi, A.1 aAndrews, K. uhttps://www.centropiaggio.unipi.it/publications/softhand-pro-functional-evaluation-novel-flexible-and-robust-myoelectric-prosthesis00932nas a2200289 4500008003900000245009900039210006900138100001400207700002000221700001600241700001700257700001900274700001600293700002000309700001700329700001500346700001900361700002200380700001400402700001400416700001700430700001300447700001300460700001600473700001500489856013800504 2018 d00aThe softpro project: Synergy-based open-source technologies for prosthetics and rehabilitation0 asoftpro project Synergybased opensource technologies for prosthe1 aPiazza, C1 aCatalano, M. G.1 aBianchi, M.1 aRicciardi, E1 aPratichizzo, D1 aHaddadin, S1 aLuft, A., R. L.1 aLambercy, O.1 aGassert, R1 aJakubowitz, E.1 aVan Der Kooij, H.1 aTonis, F.1 aBonomo, F1 ade Jonge, B.1 aWard, T.1 aZhao, K.1 aSantello, M1 aBicchi, A. uhttps://www.centropiaggio.unipi.it/publications/softpro-project-synergy-based-open-source-technologies-prosthetics-and-rehabilitation01904nas a2200241 4500008004100000022001400041245007700055210006900132260001200201300001600213490000700229520121800236653001201454653001301466100001901479700001801498700001801516700001601534700001301550700001501563700001601578856006801594 2017 eng d a1534-432000aGrasp Performance of a Soft Synergy-Based Prosthetic Hand: A Pilot Study0 aGrasp Performance of a Soft SynergyBased Prosthetic Hand A Pilot c12/2017 a2407 - 24170 v253 a
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 ± 1.4 s and 2.13 ± 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.
10aHaptics10aRobotics1 aGailey, A., S.1 aGodfrey, S.B.1 aBreighner, R.1 aAndrews, K.1 aZhao, K.1 aBicchi, A.1 aSantello, M uhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=809424602408nas a2200241 4500008004100000245007300041210006900114260001200183520171500195653001201910653001301922100001801935700001601953700001501969700001501984700001401999700001302013700001802026700002002044700001602064700001502080856007102095 2017 eng d00aPostural Hand Synergies during Environmental Constraint Exploitation0 aPostural Hand Synergies during Environmental Constraint Exploita c08/20173 aHumans 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.
10aHaptics10aRobotics1 aDella Santina1 aBianchi, M.1 aAverta, G.1 aCiotti, S.1 aArapi, V.1 aFani, S.1 aBattaglia, E.1 aCatalano, M. G.1 aSantello, M1 aBicchi, A. uhttps://www.frontiersin.org/articles/10.3389/fnbot.2017.00041/full02880nas a2200229 4500008004100000245015000041210006900191260001200260490000700272520216800279653001202447653001302459100001302472700001602485700001302501700001802514700001402532700001502546700001502561700001602576856005802592 2016 eng d00aAssessment of Myoelectric Controller Performance and Kinematic Behavior of a Novel Soft Synergy-inspired Robotic Hand for Prosthetic Applications0 aAssessment of Myoelectric Controller Performance and Kinematic B c10/20160 v103 aMyoelectric-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.
10aHaptics10aRobotics1 aFani, S.1 aBianchi, M.1 aJain, S.1 aNeto, Pimenta1 aBoege, S.1 aGrioli, G.1 aBicchi, A.1 aSantello, M uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5066092/00907nas a2200301 4500008004100000245012600041210006900167260001200236300000900248490000700257653001200264653001300276100001600289700001600305700001700321700001700338700001700355700002000372700001400392700001900406700001700425700001500442700002100457700002200478700001900500700001500519856007100534 2016 eng d00aHand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands0 aHand synergies Integration of robotics and neuroscience for unde c07/2016 a1-230 v1710aHaptics10aRobotics1 aSantello, M1 aBianchi, M.1 aGabiccini, M1 aRicciardi, E1 aSalvietti, G1 aPrattichizzo, D1 aErnst, M.1 aMoscatelli, A.1 aJorntell, H.1 aKappers, A1 aKyriakopulos, K.1 aAlbu-Schaeffer, A1 aCastellini, C.1 aBicchi, A. uhttp://www.sciencedirect.com/science/article/pii/S157106451600026900515nas a2200133 4500008003900000245010600039210006900145260003700214100001900251700001600270700001500286700001600301856006400317 2016 d00aInfluence of Force Feedback on Grasp Force Modulation in Prosthetic Applications: a Preliminary Study0 aInfluence of Force Feedback on Grasp Force Modulation in Prosthe aOrlando, USA, August 16-20, 20161 aGodfrey, S. B.1 aBianchi, M.1 aBicchi, A.1 aSantello, M uhttp://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=759195701531nas a2200277 4500008004100000022002200041245007600063210006900139260003800208300001200246490000700258520073400265653001200999653001301011100001901024700001601043700001301059700002001072700001801092700001501110700001601125700001501141700001601156700001501172856006601187 2016 eng d a978-3-319-46668-200aThe SoftHand Pro: Translation from Robotic Hand to Prosthetic Prototype0 aSoftHand Pro Translation from Robotic Hand to Prosthetic Prototy bSpringer International Publishing a469-4730 v153 aThis 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.
10aHaptics10aRobotics1 aGodfrey, S. B.1 aBianchi, M.1 aZhao, K.1 aCatalano, M. G.1 aBreighner, R.1 aTheuer, A.1 aAndrews, K.1 aGrioli, G.1 aSantello, M1 aBicchi, A. uhttp://link.springer.com/chapter/10.1007/978-3-319-46669-9_7802294nas a2200217 4500008004100000245007400041210006900115520167100184100001101855700001801866700001601884700001401900700001701914700001301931700002001944700001601964700001501980700001601995700001702011856004802028 2016 eng d00aA synergy-based hand control is encoded in human motor cortical areas0 asynergybased hand control is encoded in human motor cortical are3 aHow 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.
1 aLeo, A1 aHandjaras, G.1 aBianchi, M.1 aMarino, H1 aGabiccini, M1 aGuidi, A1 aScilingo, E. P.1 aPietrini, P1 aBicchi, A.1 aSantello, M1 aRicciardi, E uhttp://elifesciences.org/content/5/e13420v202077nas a2200253 4500008004100000022001400041245007300055210006900128260001200197300001200209490000600221520137200227653001201599653001301611100001801624700001601642700001701658700001501675700002001690700001401710700001601724700001501740856006801755 2016 eng d a1939-141200aThimbleSense: a fingertip-wearable tactile sensor for grasp analysis0 aThimbleSense a fingertipwearable tactile sensor for grasp analys c03/2016 a121-1330 v93 aAccurate 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’s rigid shells on grasp forces.
10aHaptics10aRobotics1 aBattaglia, E.1 aBianchi, M.1 aAltobelli, A1 aGrioli, G.1 aCatalano, M. G.1 aSerio, A.1 aSantello, M1 aBicchi, A. uhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=729470200660nas a2200193 4500008003900000245007900039210006900118260001600187653001200203653001300215100001800228700001500246700002000261700001600281700001400297700001600311700001500327856012400342 2014 d00aThimbleSense: A new wearable tactile device for human and robotic fingers 0 aThimbleSense A new wearable tactile device for human and robotic aHouston, TX10aHaptics10aRobotics1 aBattaglia, E.1 aGrioli, G.1 aCatalano, M. G.1 aBianchi, M.1 aSerio, A.1 aSantello, M1 aBicchi, A. uhttps://www.centropiaggio.unipi.it/publications/thimblesense-new-wearable-tactile-device-human-and-robotic-fingers.html01920nas a2200193 4500008003900000245009300039210006900132260004400201300001700245520128700262653001201549653001301561100001801574700001501592700002001607700001601627700001501643856006801658 2014 d00aThimbleSense: An Individual-Digit Wearable Tactile Sensor for Experimental Grasp Studies0 aThimbleSense An IndividualDigit Wearable Tactile Sensor for Expe a Hong Kong, May 31 - June 7, 2014bIEEE a2728 - 2735 3 aMeasuring 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.
10aHaptics10aRobotics1 aBattaglia, E.1 aGrioli, G.1 aCatalano, M. G.1 aSantello, M1 aBicchi, A. uhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=690725000515nas a2200157 4500008004100000245005700041210005700098300001600155490000800171653001200179653001300191100001500204700001700219700001600236856010500252 2011 eng d00aModeling Natural and Artificial Hands with Synergies0 aModeling Natural and Artificial Hands with Synergies a3153 - 31610 v36610aHaptics10aRobotics1 aBicchi, A.1 aGabiccini, M1 aSantello, M uhttps://www.centropiaggio.unipi.it/publications/modeling-natural-and-artificial-hands-synergies.html00811nas a2200205 4500008004100000024006600041245011000107210006900217260004600286300001400332490001400346653001200360653001300372100001600385700001500401700002000416700001600436700001500452856013800467 2010 eng d aVol. 6192/2012 Lecture Notes in Computer Science, pp. 136-14300aValidation of a Virtual Reality Environment to Study Anticipatory Modulation of Digit Forces and Position0 aValidation of a Virtual Reality Environment to Study Anticipator aAmsterdam (The Netherlands)cJuly, 8 - 10 a136 - 1430 v6192/201010aHaptics10aRobotics1 aBianchi, M.1 aGrioli, G.1 aScilingo, E. P.1 aSantello, M1 aBicchi, A. uhttps://www.centropiaggio.unipi.it/publications/validation-virtual-reality-environment-study-anticipatory-modulation-digit-forces-and