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A preliminary investigation into the design of pressure cushions and their potential applications for forearm robotic orthoses

Overview of attention for article published in BioMedical Engineering OnLine, May 2017
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Title
A preliminary investigation into the design of pressure cushions and their potential applications for forearm robotic orthoses
Published in
BioMedical Engineering OnLine, May 2017
DOI 10.1186/s12938-017-0345-8
Pubmed ID
Authors

N. Alavi, S. Zampierin, M. Komeili, S. Cocuzza, S. Debei, C. Menon

Abstract

Load cells are often used in rehabilitation robotics to monitor human-robot interaction. While load cells are accurate and suitable for the stationary end-point robots used in rehabilitation hospitals, their cost and inability to conform to the shape of the body hinder their application in developing affordable and wearable robotic orthoses for assisting individuals in the activities of daily living. This exploratory work investigates the possibility of using an alternative technology, namely compliant polymeric air cushions, to measure interaction forces between the user and a wearable rigid structure. A polymeric air cushion was designed, analyzed using a finite element model (FEM), and tested using a bench-top characterization system. The cushions underwent repeatability testing, and signal delay testing from a step response while increasing the length of the cushion's tubes. Subsequently, a 3D printed wrist brace prototype was integrated with six polymeric air cushions and tested in static conditions where a volunteer exerted isometric pronation/supination torque and forces in vertical and horizontal directions. The load measured by integrating data recorded by the six sensors was compared with force data measured by a high quality load cell and torque sensor. The FEM and experimental data comparison was within the error bounds of the external differential pressure sensor used to monitor the pressure inside the cushion. The ratio obtained experimentally between the pressure inside the pressure cushion and the 8 N applied load deviated by only 1.28% from the FEM. A drift smaller than 1% was observed over 10 cycles. The rise times of the cushion under an 8 N step response for a 0.46, 1.03, and 2.02 m length tube was 0.45, 0.39, and 0.37 s. Tests with the wrist brace showed a moderate root mean square error (RMSE) between the force estimated by the pressure cushions and the external load cells. Specifically, the RMSE was 13 mNm, 500 mN, and 1.24 N for forearm pronation/supination torque, vertical force, and horizontal force, respectively. The use of compliant pressure cushions was shown to be promising for monitoring interaction forces between the forearm and a rigid brace. This work lays the foundation for the future design of an array of pressure cushions for robotic orthoses. Future research should also investigate the compatibility of these polymeric cushions for data acquisition during functional magnetic resonance imaging in shielded rooms.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 1%
Unknown 76 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 21%
Student > Master 14 18%
Student > Bachelor 10 13%
Researcher 6 8%
Student > Doctoral Student 2 3%
Other 8 10%
Unknown 21 27%
Readers by discipline Count As %
Engineering 23 30%
Medicine and Dentistry 7 9%
Nursing and Health Professions 5 6%
Business, Management and Accounting 3 4%
Sports and Recreations 3 4%
Other 9 12%
Unknown 27 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 23 October 2017.
All research outputs
#20,450,513
of 23,006,268 outputs
Outputs from BioMedical Engineering OnLine
#692
of 824 outputs
Outputs of similar age
#270,439
of 310,622 outputs
Outputs of similar age from BioMedical Engineering OnLine
#11
of 15 outputs
Altmetric has tracked 23,006,268 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 824 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 15 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.