Evidence map›Paper›PMID 35879359›Full record

ArticleExperimental brain research2022

Combined spatial and frequency encoding for electrotactile feedback of myoelectric signals.

Sara Nataletti, Fabrizio Leo, Jakob Dideriksen, Luca Brayda, Strahinja Dosen

Abstract read
In one paragraph

Article in Experimental brain research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

5 authors.

Sara NatalettiCognitive Architecture for Collaborative Technologies Unit, Istituto Italiano di Tecnologia (IIT), Genoa, Italy. sara.nataletti@iit.it.
Fabrizio LeoCognitive Architecture for Collaborative Technologies Unit, Istituto Italiano di Tecnologia (IIT), Genoa, Italy.ORCID http://orcid.org/0000-0002-4095-7785
Jakob DideriksenDepartment of Health Science and Technology, Aalborg University, Ålborg, Denmark.ORCID http://orcid.org/0000-0001-6587-0865
Luca BraydaAcoesis S.R.L., Genoa, Italy.ORCID http://orcid.org/0000-0002-6673-2971
Strahinja DosenDepartment of Health Science and Technology, Aalborg University, Ålborg, Denmark. sdosen@hst.aau.dk.ORCID http://orcid.org/0000-0003-3035-147X

Funding

Compagnia di San Paolo 2017.0559Independent Research Fund Denmark 8022-00226BIndependent Research Fund Denmark 8022-00243A
6 · The paper itself

Abstract

Electrotactile stimulation has been commonly used in human-machine interfaces to provide feedback to the user, thereby closing the control loop and improving performance. The encoding approach, which defines the mapping of the feedback information into stimulation profiles, is a critical component of an electrotactile interface. Ideally, the encoding will provide a high-fidelity representation of the feedback variable while being easy to perceive and interpret by the subject. In the present study, we performed a closed-loop experiment wherein discrete and continuous coding schemes are combined to exploit the benefits of both techniques. Subjects performed a muscle activation-matching task relying solely on electrotactile feedback representing the generated myoelectric signal (EMG). In particular, we investigated the performance of two different coding schemes (spatial and spatial combined with frequency) at two feedback resolutions (low: 3 and high: 5 intervals). In both schemes, the stimulation electrodes were placed circumferentially around the upper arm. The magnitude of the normalized EMG was divided into intervals, and each electrode was associated with one interval. When the generated EMG entered one of the intervals, the associated electrode started stimulating. In the combined encoding, the additional frequency modulation of the active electrode also indicated the momentary magnitude of the signal within the interval. The results showed that combined coding decreased the undershooting rate, variability and absolute deviation when the resolution was low but not when the resolution was high, where it actually worsened the performance. This demonstrates that combined coding can improve the effectiveness of EMG feedback, but that this effect is limited by the intrinsic variability of myoelectric control. Our findings, therefore, provide important insights as well as elucidate limitations of the information encoding methods when using electrotactile stimulation to convey a feedback signal characterized by high variability (EMG biofeedback).

Indexed as

Artificial LimbsFeedback, SensoryArmElectromyographyFeedbackHumansTouchClosed-loop controlElectrotactile stimulationEMG feedbackMyoelectric controlSensory feedback

Identifiers

PMID35879359
PMCPMC9458587

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Registered trials

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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.