Evidence map›Paper›PMID 31878001›Full record

ArticleSensors (Basel, Switzerland)2019

An Embedded, Multi-Modal Sensor System for Scalable Robotic and Prosthetic Hand Fingers.

Pascal Weiner, Caterina Neef, Yoshihisa Shibata, Yoshihiko Nakamura, Tamim Asfour

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Review
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  11. Fingerprint ridges allow primates to regulate grip.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  12. Tactile Sensors for Robotic Applications.Sensors (Basel, Switzerland) · 2020
    Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Pascal WeinerKIT Department of Informatics, Karlsruhe Institute of Technology, 76137 Karlsruhe, Germany.ORCID 0000-0002-2524-8454
Caterina NeefKIT Department of Informatics, Karlsruhe Institute of Technology, 76137 Karlsruhe, Germany.ORCID 0000-0003-4592-1711
Yoshihisa ShibataDepartment of Mechano-Informatics, University of Tokyo, Tokyo 113-8656, Japan.ORCID 0000-0002-5221-2772
Yoshihiko NakamuraDepartment of Mechano-Informatics, University of Tokyo, Tokyo 113-8656, Japan.
Tamim AsfourKIT Department of Informatics, Karlsruhe Institute of Technology, 76137 Karlsruhe, Germany.ORCID 0000-0003-4879-7680

Funding

Bundesministerium für Bildung und Forschung 16SV7665Horizon 2020 Framework Programme 643950
6 · The paper itself

Abstract

Grasping and manipulation with anthropomorphic robotic and prosthetic hands presents a scientific challenge regarding mechanical design, sensor system, and control. Apart from the mechanical design of such hands, embedding sensors needed for closed-loop control of grasping tasks remains a hard problem due to limited space and required high level of integration of different components. In this paper we present a scalable design model of artificial fingers, which combines mechanical design and embedded electronics with a sophisticated multi-modal sensor system consisting of sensors for sensing normal and shear force, distance, acceleration, temperature, and joint angles. The design is fully parametric, allowing automated scaling of the fingers to arbitrary dimensions in the human hand spectrum. To this end, the electronic parts are composed of interchangeable modules that facilitate the mechanical scaling of the fingers and are fully enclosed by the mechanical parts of the finger. The resulting design model allows deriving freely scalable and multimodally sensorised fingers for robotic and prosthetic hands. Four physical demonstrators are assembled and tested to evaluate the approach.

Indexed as

RoboticsEquipment DesignFingersHand StrengthHumansTouchanthropomorphic robotic handshand prosthesesparametric modelprosthetic fingersrobotic fingerssensorised fingerstactile sensors

Identifiers

PMID31878001
PMCPMC6983258

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.