Evidence map›Paper›PMID 37289675›Full record

ArticlePloS one2023

Comparing end-effector position and joint angle feedback for online robotic limb tracking.

Mattia Pinardi, Alessia Noccaro, Luigi Raiano, Domenico Formica, Giovanni Di Pino

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. 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.

Mattia PinardiNEXT: Neurophysiology and Neuroengineering of Human-Technology Interaction Research Unit, Università Campus Bio-Medico di Roma, Rome, Italy.ORCID 0000-0003-2183-3848
Alessia NoccaroNeurorobotics Group, Newcastle University, Newcastle, United Kingdom.
Luigi RaianoNEXT: Neurophysiology and Neuroengineering of Human-Technology Interaction Research Unit, Università Campus Bio-Medico di Roma, Rome, Italy.ORCID 0000-0002-3242-4057
Domenico FormicaNeurorobotics Group, Newcastle University, Newcastle, United Kingdom.
Giovanni Di PinoNEXT: Neurophysiology and Neuroengineering of Human-Technology Interaction Research Unit, Università Campus Bio-Medico di Roma, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Somatosensation greatly increases the ability to control our natural body. This suggests that supplementing vision with haptic sensory feedback would also be helpful when a user aims at controlling a robotic arm proficiently. However, whether the position of the robot and its continuous update should be coded in a extrinsic or intrinsic reference frame is not known. Here we compared two different supplementary feedback contents concerning the status of a robotic limb in 2-DoFs configuration: one encoding the Cartesian coordinates of the end-effector of the robotic arm (i.e., Task-space feedback) and another and encoding the robot joints angles (i.e., Joint-space feedback). Feedback was delivered to blindfolded participants through vibrotactile stimulation applied on participants' leg. After a 1.5-hour training with both feedbacks, participants were significantly more accurate with Task compared to Joint-space feedback, as shown by lower position and aiming errors, albeit not faster (i.e., similar onset delay). However, learning index during training was significantly higher in Joint space feedback compared to Task-space feedback. These results suggest that Task-space feedback is probably more intuitive and more suited for activities which require short training sessions, while Joint space feedback showed potential for long-term improvement. We speculate that the latter, despite performing worse in the present work, might be ultimately more suited for applications requiring long training, such as the control of supernumerary robotic limbs for surgical robotics, heavy industrial manufacturing, or more generally, in the context of human movement augmentation.

Indexed as

RoboticsExtremitiesFeedbackFeedback, SensoryHumansMovement

Identifiers

PMID37289675
PMCPMC10249844

What OpenQuestion holds

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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.