@conference {3727,
	title = {Muscle fatigue assessment through electrodermal activity analysis during isometric contraction},
	booktitle = {Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS},
	year = {2017},
	doi = {10.1109/EMBC.2017.8036846},
	author = {A. Greco and A. Guidi and F. Felici and A. Leo and E. Ricciardi and M. Bianchi and A. Bicchi and L. Citi and G. Valenza and E. P. Scilingo}
}
@article {2866,
	title = {A Multi-Modal Sensing Glove for Human Manual-Interaction Studies},
	journal = {Electronics},
	volume = { 5},
	year = {2016},
	note = {<p>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}.</p>
},
	abstract = {<p class="rtejustify">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.</p>
},
	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}
}
