Evidence map›Paper›PMID 35784093›Full record

ArticleIEEE robotics and automation letters2022

Object Recognition via Evoked Sensory Feedback during Control of a Prosthetic Hand.

Luis Vargas, He Huang, Yong Zhu, Xiaogang Hu

Open access · greenAbstract read
In one paragraph

Article in IEEE robotics and automation letters, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.1field-weighted citation impact, top 13% of its field
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

15 citing papers in PubMed, 35 citations in OpenAlex.

  1. Osseoperceptive EMG Feedback Improves Grasp Force Control in Myoelectric Prosthetic Hands.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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  8. Electrical Stimulation of Regenerative Peripheral Nerve Interfaces (RPNIs) Induces Referred Sensations in People With Upper Limb Loss.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2024
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  10. Sensory Restoration for Improved Motor Control of Prostheses.Current opinion in biomedical engineering · 2023
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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

4 authors at 2 institutions in 1 country.

Luis VargasJoint Department of Biomedical Engineering at University of North Carolina-Chapel Hill and NC State University.
He HuangJoint Department of Biomedical Engineering at University of North Carolina-Chapel Hill and NC State University.
Yong ZhuMechanical and Aerospace Engineering Department at NC State University.
Xiaogang HuJoint Department of Biomedical Engineering at University of North Carolina-Chapel Hill and NC State University.
University of North Carolina at Chapel Hill · USNorth Carolina State University · US

Funding

SCH: A personalized wearable rehabilitation sensing system for stroke survivorsR01HD108473 · NICHD · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI BARATTA, JOHN, BOZKURT, ALPER · 2021 to 2024
$1.1M
Evaluation of Haptic Sensation and Object Recognition using Transcutaneous Nerve StimulationF31NS110364 · NINDS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI VARGAS, LUIS · 2019 to 2021
$99k
NICHD NIH HHS R01 HD108473NINDS NIH HHS F31 NS110364
6 · The paper itself

Abstract

Haptic and proprioceptive feedback is critical for sensorimotor integration when we use our hand to perform daily tasks. Here, we evaluated how externally evoked haptic and proprioceptive feedback and myoelectric control strategies affected the recognition of object properties when participants controlled a prosthetic hand. Fingertip haptic sensation was elicited using a transcutaneous nerve stimulation grid to encode the prosthetic's fingertip forces. An array of tactors elicited patterned vibratory stimuli to encode tactile-proprioceptive kinematic information of the prosthetic finger joint. Myoelectric signals of the finger flexor and extensor were used to control the position or velocity of joint angles of the prosthesis. Participants were asked to perform object property (stiffness and size) recognition, by controlling the prosthetic hand with concurrent haptic and tactile-proprioceptive feedback. With the evoked feedback, intact and amputee participants recognized the object stiffness and size at success rates ranging from 50% to 100% in both position and velocity control with no significant difference across control schemes. Our findings show that evoked somatosensory feedback in a non-invasive manner can facilitate closed-loop control of the prosthetic hand and allowed for simultaneous recognition of different object properties. The outcomes can facilitate our understanding on the role of sensory feedback during bidirectional human-machine interactions, which can potentially promote user experience in object interactions using prosthetic hands.

Indexed as

Haptic and Proprioceptive SensationSize RecognitionStiffness RecognitionTranscutaneous Nerve StimulationVibrotactile Stimulation

Identifiers

PMID35784093
PMCPMC9248871
OpenAlexW3208293247

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.