@article {2866, title = {A Multi-Modal Sensing Glove for Human Manual-Interaction Studies}, journal = {Electronics}, volume = { 5}, year = {2016}, note = {

This work is supported in part by the European Research Council under the Advanced Grant {\textquotedblleft}SoftHands: A Theory of Soft Synergies for a New Generation of Artificial Hands{\textquotedblright} (No. ERC-291166), by the EU H2020 projects {\textquotedblleft}SoftPro: Synergy-based Open-source Foundations and Technologies for Prosthetics and RehabilitatiOn{\textquotedblright} (No. 688857) and {\textquotedblleft}SOMA: Soft Manipulation{\textquotedblright} (No. 64559) and by the EU FP7 project (No. 601165) {\textquotedblleft}WEARable HAPtics for Humans and Robots (WEARHAP){\textquotedblright}.

}, abstract = {

We present an integrated sensing glove that combines two of the most visionary wearable sensing technologies to provide both hand posture sensing and tactile pressure sensing in a unique, lightweight, and stretchable device. Namely, hand posture reconstruction employs Knitted Piezoresistive Fabrics that allows us to measure bending. From only five of these sensors (one for each finger) the full hand pose of a 19 degrees of freedom (DOF) hand model is reconstructed leveraging optimal sensor placement and estimation techniques. To this end, we exploit a-priori information of synergistic coordination patterns in grasping tasks. Tactile sensing employs a piezoresistive fabric allowing us to measure normal forces in more than 50 taxels spread over the palmar surface of the glove. We describe both sensing technologies, report on the software integration of both modalities, and describe a preliminary evaluation experiment analyzing hand postures and force patterns during grasping. Results of the reconstruction are promising and encourage us to push further our approach with potential applications in neuroscience, virtual reality, robotics and tele-operation.

}, keywords = {Haptics}, doi = {10.3390/electronics5030042}, url = {http://www.mdpi.com/2079-9292/5/3/42/pdf}, author = {M. Bianchi and R. Haschke and G. B{\"u}scher and S. Ciotti and N. Carbonaro and A. Tognetti} } @article {2867, title = {A Synergy-Based Optimally Designed Sensing Glove for Functional Grasp Recognition}, journal = {Sensors}, volume = {16}, year = {2016}, abstract = {

Achieving accurate and reliable kinematic hand pose reconstructions represents a challenging task. The main reason for this is the complexity of hand biomechanics, where several degrees of freedom are distributed along a continuous deformable structure. Wearable sensing can represent a viable solution to tackle this issue, since it enables a more natural kinematic monitoring. However, the intrinsic accuracy (as well as the number of sensing elements) of wearable hand pose reconstruction (HPR) systems can be severely limited by ergonomics and cost considerations. In this paper, we combined the theoretical foundations of the optimal design of HPR devices based on hand synergy information, i.e., the inter-joint covariation patterns, with textile goniometers based on knitted piezoresistive fabrics (KPF) technology, to develop, for the first time, an optimally-designed under-sensed glove for measuring hand kinematics. We used only five sensors optimally placed on the hand and completed hand pose reconstruction (described according to a kinematic model with 19 degrees of freedom) leveraging upon synergistic information. The reconstructions we obtained from five different subjects were used to implement an unsupervised method for the recognition of eight functional grasps, showing a high degree of accuracy and robustness.

}, keywords = {Haptics}, doi = {10.3390/s16060811}, url = {http://www.mdpi.com/1424-8220/16/6/811}, author = {S. Ciotti and E. Battaglia and N. Carbonaro and A. Bicchi and A. Tognetti and M. Bianchi} } @conference {2233, title = {Exploiting hand kinematic synergies and wearable under-sensing for hand functional grasp recognition}, booktitle = { 4th International Conference on Wireless Mobile Communication and Healthcare - "Transforming healthcare through innovations in mobile and wireless technologies" }, year = {2014}, address = {November 3{\textendash}5, 2014 Athens, Greece}, keywords = {Haptics, Robotics}, doi = { http://dx.doi.org/10.4108/icst.mobihealth.2014.257228}, author = {M. Bianchi and N. Carbonaro and E. Battaglia and F. Lorussi and A. Bicchi and D. De Rossi and A. Tognetti} } @conference {BSTCB12, title = {On the Use of Postural Synergies to Improve Human Hand Pose Reconstruction}, booktitle = {Haptics Symposium}, year = {2012}, month = {March 4 - 7}, pages = {91 - 98}, address = {Vancouver, Canada}, keywords = {Haptics, Robotics}, author = {M. Bianchi and P Salaris and A. Turco and N. Carbonaro and A. Bicchi} }