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Tactile feedback is an effective instrument for the training of grasping with a prosthesis at low- and medium-force levels

Overview of attention for article published in Experimental Brain Research, May 2017
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  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

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Title
Tactile feedback is an effective instrument for the training of grasping with a prosthesis at low- and medium-force levels
Published in
Experimental Brain Research, May 2017
DOI 10.1007/s00221-017-4991-7
Pubmed ID
Authors

Alessandro Marco De Nunzio, Strahinja Dosen, Sabrina Lemling, Marko Markovic, Meike Annika Schweisfurth, Nan Ge, Bernhard Graimann, Deborah Falla, Dario Farina

Abstract

Grasping is a complex task routinely performed in an anticipatory (feedforward) manner, where sensory feedback is responsible for learning and updating the internal model of grasp dynamics. This study aims at evaluating whether providing a proportional tactile force feedback during the myoelectric control of a prosthesis facilitates learning a stable internal model of the prosthesis force control. Ten able-bodied subjects controlled a sensorized myoelectric prosthesis performing four blocks of consecutive grasps at three levels of target force (30, 50, and 70%), repeatedly closing the fully opened hand. In the first and third block, the subjects received tactile and visual feedback, respectively, while during the second and fourth block, the feedback was removed. The subjects also performed an additional block with no feedback 1 day after the training (Retest). The median and interquartile range of the generated forces was computed to assess the accuracy and precision of force control. The results demonstrated that the feedback was indeed an effective instrument for the training of prosthesis control. After the training, the subjects were still able to accurately generate the desired force for the low and medium target (30 and 50% of maximum force available in a prosthesis), despite the feedback being removed within the session and during the retest (low target force). However, the training was substantially less successful for high forces (70% of prosthesis maximum force), where subjects exhibited a substantial loss of accuracy as soon as the feedback was removed. The precision of control decreased with higher forces and it was consistent across conditions, determined by an intrinsic variability of repeated myoelectric grasping. This study demonstrated that the subject could rely on the tactile feedback to adjust the motor command to the prosthesis across trials. The subjects adjusted the mean level of muscle activation (accuracy), whereas the precision could not be modulated as it depends on the intrinsic myoelectric variability. They were also able to maintain the feedforward command even after the feedback was removed, demonstrating thereby a stable learning, but the retention depended on the level of the target force. This is an important insight into the role of feedback as an instrument for learning of anticipatory prosthesis force control.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 157 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 157 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 17%
Student > Master 22 14%
Student > Bachelor 20 13%
Researcher 17 11%
Unspecified 13 8%
Other 22 14%
Unknown 37 24%
Readers by discipline Count As %
Engineering 48 31%
Medicine and Dentistry 16 10%
Neuroscience 14 9%
Unspecified 13 8%
Psychology 6 4%
Other 16 10%
Unknown 44 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 January 2018.
All research outputs
#7,472,827
of 22,977,819 outputs
Outputs from Experimental Brain Research
#887
of 3,239 outputs
Outputs of similar age
#118,622
of 313,455 outputs
Outputs of similar age from Experimental Brain Research
#23
of 50 outputs
Altmetric has tracked 22,977,819 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 3,239 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 72% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 313,455 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.
We're also able to compare this research output to 50 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.