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Upper-limb kinematic reconstruction during stroke robot-aided therapy

Overview of attention for article published in Medical & Biological Engineering & Computing, April 2015
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

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154 Mendeley
Title
Upper-limb kinematic reconstruction during stroke robot-aided therapy
Published in
Medical & Biological Engineering & Computing, April 2015
DOI 10.1007/s11517-015-1276-9
Pubmed ID
Authors

E. Papaleo, L. Zollo, N. Garcia-Aracil, F. J. Badesa, R. Morales, S. Mazzoleni, S. Sterzi, E. Guglielmelli

Abstract

The paper proposes a novel method for an accurate and unobtrusive reconstruction of the upper-limb kinematics of stroke patients during robot-aided rehabilitation tasks with end-effector machines. The method is based on a robust analytic procedure for inverse kinematics that simply uses, in addition to hand pose data provided by the robot, upper arm acceleration measurements for computing a constraint on elbow position; it is exploited for task space augmentation. The proposed method can enable in-depth comprehension of planning strategy of stroke patients in the joint space and, consequently, allow developing therapies tailored for their residual motor capabilities. The experimental validation has a twofold purpose: (1) a comparative analysis with an optoelectronic motion capturing system is used to assess the method capability to reconstruct joint motion; (2) the application of the method to healthy and stroke subjects during circle-drawing tasks with InMotion2 robot is used to evaluate its efficacy in discriminating stroke from healthy behavior. The experimental results have shown that arm angles are reconstructed with a RMSE of 8.3 × 10(-3) rad. Moreover, the comparison between healthy and stroke subjects has revealed different features in the joint space in terms of mean values and standard deviations, which also allow assessing inter- and intra-subject variability. The findings of this study contribute to the investigation of motor performance in the joint space and Cartesian space of stroke patients undergoing robot-aided therapy, thus allowing: (1) evaluating the outcomes of the therapeutic approach, (2) re-planning the robotic treatment based on patient needs, and (3) understanding pathology-related motor strategies.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 154 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Unknown 153 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 24 16%
Student > Ph. D. Student 22 14%
Student > Bachelor 20 13%
Researcher 13 8%
Lecturer 9 6%
Other 29 19%
Unknown 37 24%
Readers by discipline Count As %
Engineering 28 18%
Nursing and Health Professions 25 16%
Medicine and Dentistry 21 14%
Neuroscience 12 8%
Computer Science 7 5%
Other 21 14%
Unknown 40 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 20 September 2015.
All research outputs
#7,342,333
of 25,373,627 outputs
Outputs from Medical & Biological Engineering & Computing
#495
of 2,053 outputs
Outputs of similar age
#81,944
of 279,199 outputs
Outputs of similar age from Medical & Biological Engineering & Computing
#4
of 17 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 2,053 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done well, scoring higher than 75% 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 279,199 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 70% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.