Next Article in Journal
Integrated Toolset for WSN Application Planning, Development, Commissioning and Maintenance: The WSN-DPCM ARTEMIS-JU Project
Previous Article in Journal
A Novel Location-Centric IoT-Cloud Based On-Street Car Parking Violation Management System in Smart Cities
Previous Article in Special Issue
Improving Pulse Rate Measurements during Random Motion Using a Wearable Multichannel Reflectance Photoplethysmograph
Open AccessArticle

A Synergy-Based Optimally Designed Sensing Glove for Functional Grasp Recognition

Centro di Ricerca “E. Piaggio”, University of Pisa, Largo Lucio Lazzarino 1, Pisa 56126, Italy
Advanced Robotics Department, Istituto Italiano di Tecnologia, via Morego 30, Genova 16163, Italy
Information Engineering Department, University of Pisa, via G. Caruso 16, Pisa 56122, Italy
Author to whom correspondence should be addressed.
Academic Editor: Oliver Amft
Sensors 2016, 16(6), 811;
Received: 8 February 2016 / Revised: 28 May 2016 / Accepted: 28 May 2016 / Published: 2 June 2016
(This article belongs to the Special Issue Wearable Sensors)
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. View Full-Text
Keywords: kinematic wearable sensing; human hand synergies; under-sensing; optimal design kinematic wearable sensing; human hand synergies; under-sensing; optimal design
Show Figures

Figure 1

MDPI and ACS Style

Ciotti, S.; Battaglia, E.; Carbonaro, N.; Bicchi, A.; Tognetti, A.; Bianchi, M. A Synergy-Based Optimally Designed Sensing Glove for Functional Grasp Recognition. Sensors 2016, 16, 811.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop