Evidence map›Paper›PMID 39880874›Full record

ArticleScientific reports2025

Examining the physical and psychological effects of combining multimodal feedback with continuous control in prosthetic hands.

Digby Chappell, Zeyu Yang, Angus B Clark, Alexandre Berkovic, Colin Laganier, Weston Baxter, Fernando Bello, Petar Kormushev, Nicolas Rojas

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Digby ChappellDyson School of Design Engineering, Faculty of Engineering, Imperial College London, London, UK. dchappell@seas.harvard.edu.
Zeyu YangDepartment of Engineering Science, University of Oxford, Oxford, UK.
Angus B ClarkDepartment of Bioengineering, Faculty of Engineering, Imperial College London, London, UK.
Alexandre BerkovicMIT Sloane School of Management, Massachusetts Institute of Technology, Boston, USA.
Colin LaganierDepartment of Computer Science, Faculty of Engineering, University College London, London, UK.
Weston BaxterDyson School of Design Engineering, Faculty of Engineering, Imperial College London, London, UK.
Fernando BelloDepartment of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK.
Petar KormushevDyson School of Design Engineering, Faculty of Engineering, Imperial College London, London, UK.
Nicolas RojasThe AI Institute, Cambridge, MA, USA.

Funding

RCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/S023283/1
6 · The paper itself

Abstract

Myoelectric prosthetic hands are typically controlled to move between discrete positions and do not provide sensory feedback to the user. In this work, we present and evaluate a closed-loop, continuous myoelectric prosthetic hand controller, that can continuously control the position of multiple degrees of freedom of a prosthesis while rendering proprioceptive feedback to the user via a haptic feedback armband. Twenty-eight participants without and ten participants with upper limb difference (ULD) were recruited to holistically evaluate the physical and psychological effects of the controller via isolated control and sensory tasks, dexterity assessments, embodiment and task load questionnaires, and post-study interviews. The combination of proprioceptive feedback and continuous control enabled more accurate position and force modulation than without proprioceptive feedback, and restored blindfolded object identification ability to open-loop discrete controller levels. Dexterity assessment and embodiment questionnaire results revealed no significant physical performance or psychological embodiment differences between control types, with the exception of perceived sensation questions, which were significantly higher (p < 0.001) for closed-loop controllers. Key differences between participants with and without ULD were identified, including increasingly lower perceived body completeness and heterogeneity in frustration in participants with ULD, which can inform future development and rehabilitation.

Indexed as

Artificial LimbsFeedback, SensoryHandAdultFemaleHumansMaleMiddle AgedProprioceptionProsthesis DesignYoung Adult

Identifiers

PMID39880874
PMCPMC11779825

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.