Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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University of Bristol

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2021B:Ionic Glove: A Soft Smart Wearable Sensory Feedback Device for Upper Limb Robotic Prostheses35citations

Places of action

Chart of shared publication
Diteesawat, Richard Suphapol
1 / 2 shared
Rossiter, Jonathan M.
1 / 34 shared
Zaghloul, Nouf
1 / 2 shared
Garrad, Martin S.
1 / 6 shared
Conn, Andrew T.
1 / 10 shared
Le, Hao
1 / 1 shared
Chen, Hsing-Yu
1 / 4 shared
Kent, Chris
1 / 2 shared
Chart of publication period
2021

Co-Authors (by relevance)

  • Diteesawat, Richard Suphapol
  • Rossiter, Jonathan M.
  • Zaghloul, Nouf
  • Garrad, Martin S.
  • Conn, Andrew T.
  • Le, Hao
  • Chen, Hsing-Yu
  • Kent, Chris
OrganizationsLocationPeople

article

B:Ionic Glove: A Soft Smart Wearable Sensory Feedback Device for Upper Limb Robotic Prostheses

  • Diteesawat, Richard Suphapol
  • Rossiter, Jonathan M.
  • Zaghloul, Nouf
  • Garrad, Martin S.
  • Carreira, Sara Correia
  • Conn, Andrew T.
  • Le, Hao
  • Chen, Hsing-Yu
  • Kent, Chris
Abstract

Upper limb robotic prosthetic devices currently lack adequate sensory feedback, contributing to a high rejection rate. Incorporating affective sensory feedback into these devices reduces phantom limb pain and increases control and acceptance. To address the lack of sensory feedback we present the B:Ionic glove, wearable over a robotic hand which contains sensing, computation and actuation on board. It uses shape memory alloy (SMA) actuators integrated into an armband to gently squeeze the user’s arm when pressure is sensed in novel electro-fluidic fingertip sensors and decoded through soft matter logic. We found that a circular electro-fluidic sensor cavity generated the most sensitive fingertip sensor and considered a computational configuration to convey different information from robot to user. A user study was conducted to characterise the tactile interaction capabilities of the device. No significant difference was found between the skin sensitivity threshold of participants’ lower and upper arm. They found it easier to distinguish stimulation locations than strengths. Finally, we demonstrate a proof-of-concept of the complete device, illustrating how it could be used to grip an object, solely from the affective tactile feedback provided by the B:Ionic glove. The B:Ionic glove is a step towards the integration of natural, soft sensory feedback into robotic prosthetic devices.

Topics
  • impedance spectroscopy
  • strength