↓ Skip to main content

Initial Clinical Evaluation of the Modular Prosthetic Limb

Overview of attention for article published in Frontiers in Neurology, March 2018
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
29 Dimensions

Readers on

mendeley
103 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
Initial Clinical Evaluation of the Modular Prosthetic Limb
Published in
Frontiers in Neurology, March 2018
DOI 10.3389/fneur.2018.00153
Pubmed ID
Authors

Briana N. Perry, Courtney W. Moran, Robert S. Armiger, Paul F. Pasquina, Jamie W. Vandersea, Jack W. Tsao

Abstract

The Modular Prosthetic Limb (MPL) was examined for its feasibility and usability as an advanced, dexterous upper extremity prosthesis with surface electromyography (sEMG) control in with two individuals with below-elbow amputations. Compared to currently marketed prostheses, the MPL has a greater number of sequential and simultaneous degrees of motion, as well as wrist modularity, haptic feedback, and individual digit control. The MPL was successfully fit to a 33-year-old with a trans-radial amputation (TR01) and a 30-year-old with a wrist disarticulation amputation (TR02). To preserve anatomical limb length, we adjusted the powered degrees of freedom of wrist motion between users. Motor training began with practicing sEMG and pattern recognition control within the virtual integration environment (VIE). Prosthetic training sessions then allowed participants to complete a variety of activities of daily living with the MPL. Training and Motion Control Accuracy scores quantified their ability to consistently train and execute unique muscle-to-motion contraction patterns. Each user also completed one prosthetic functional metric-the Southampton Hand Assessment Procedure (SHAP) for TR01 and the Jebsen-Taylor Hand Function Test (JHFT) for TR02. Haptic feedback capabilities were integrated for TR01. TR01 achieved 95% accuracy at 84% of his VIE sessions. He demonstrated improved scores over a year of prosthetic training sessions, ultimately achieving simultaneous control of 13 of the 17 (76%) attempted motions. His performance on the SHAP improved from baseline to final assessment with an increase in number of tasks achieved. TR01 also used vibrotactile sensors to successfully discriminate between hard and soft objects being grasped by the MPL hand. TR02 demonstrated 95% accuracy at 79% of his VIE sessions. He demonstrated improved scores over months of prosthetic training sessions, however there was a significant drop in scores initially following a mid-study pause in testing. He ultimately achieved simultaneous control of all 13 attempted powered motions, and both attempted passive motions. He completed 5 of the 7 (71%) JHFT tasks within the testing time limit. These case studies confirm that it is possible to use non-invasive motor control to increase functional outcomes with individuals with below-elbow amputation and will help to guide future myoelectric prosthetic studies.

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 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 103 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 16 16%
Student > Bachelor 13 13%
Student > Ph. D. Student 12 12%
Researcher 11 11%
Student > Doctoral Student 7 7%
Other 11 11%
Unknown 33 32%
Readers by discipline Count As %
Engineering 30 29%
Medicine and Dentistry 10 10%
Nursing and Health Professions 5 5%
Neuroscience 4 4%
Biochemistry, Genetics and Molecular Biology 4 4%
Other 16 16%
Unknown 34 33%
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 19 March 2018.
All research outputs
#20,469,520
of 23,028,364 outputs
Outputs from Frontiers in Neurology
#8,940
of 11,919 outputs
Outputs of similar age
#293,486
of 332,288 outputs
Outputs of similar age from Frontiers in Neurology
#199
of 262 outputs
Altmetric has tracked 23,028,364 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,919 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one is in the 1st percentile – i.e., 1% 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 332,288 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 262 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.