↓ Skip to main content

Low-Dimensional Synergistic Representation of Bilateral Reaching Movements

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, February 2017
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
20 Dimensions

Readers on

mendeley
49 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Low-Dimensional Synergistic Representation of Bilateral Reaching Movements
Published in
Frontiers in Bioengineering and Biotechnology, February 2017
DOI 10.3389/fbioe.2017.00002
Pubmed ID
Authors

Martin K. Burns, Vrajeshri Patel, Ionut Florescu, Kishore V. Pochiraju, Ramana Vinjamuri

Abstract

Kinematic and neuromuscular synergies have been found in numerous aspects of human motion. This study aims to determine how effectively kinematic synergies in bilateral upper arm movements can be used to replicate complex activities of daily living (ADL) tasks using a sparse optimization algorithm. Ten right-handed subjects executed 18 rapid and 11 natural-paced ADL tasks requiring bimanual coordination while sitting at a table. A position tracking system was used to track the subjects' arms in space, and angular velocities over time for shoulder abduction, shoulder flexion, shoulder internal rotation, and elbow flexion for each arm were computed. Principal component analysis (PCA) was used to generate kinematic synergies from the rapid-paced task set for each subject. The first three synergies accounted for 80.3 ± 3.8% of variance, while the first eight accounted for 94.8 ± 0.85%. The first and second synergies appeared to encode symmetric reaching motions which were highly correlated across subjects. The first three synergies were correlated between left and right arms within subjects, whereas synergies four through eight were not, indicating asymmetries between left and right arms in only the higher order synergies. The synergies were then used to reconstruct each natural-paced task using the l1-norm minimization algorithm. Temporal dilations of the synergies were introduced in order to model the temporal scaling of movement patterns achieved by the cerebellum and basal ganglia as reported previously in the literature. Reconstruction error was reduced by introducing synergy dilations, and cumulative recruitment of several synergies was significantly reduced in the first 10% of training task time by introducing temporal dilations. The outcomes of this work could open new scenarios for the applications of postural synergies to the control of robotic systems, with potential applications in rehabilitation. These synergies not only help in providing near-natural control but also provide simplified strategies for design and control of artificial limbs. Potential applications of these bilateral synergies were discussed and future directions were proposed.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 2%
Unknown 48 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 14%
Student > Master 7 14%
Student > Doctoral Student 6 12%
Student > Bachelor 5 10%
Researcher 4 8%
Other 4 8%
Unknown 16 33%
Readers by discipline Count As %
Engineering 12 24%
Computer Science 6 12%
Nursing and Health Professions 4 8%
Sports and Recreations 3 6%
Business, Management and Accounting 2 4%
Other 5 10%
Unknown 17 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 10 February 2017.
All research outputs
#18,531,724
of 22,953,506 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#3,422
of 6,685 outputs
Outputs of similar age
#312,077
of 422,694 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#12
of 21 outputs
Altmetric has tracked 22,953,506 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,685 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
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 422,694 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.