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A Sensor-Based Decision Support System for Transfemoral Socket Rectification
TWI Hellas, Halandri 15232, Greece..ORCID iD: 0000-0002-9411-2139
TWI Hellas, Halandri 15232, Greece..
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.ORCID iD: 0000-0002-0699-3889
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.ORCID iD: 0000-0001-7048-0108
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2021 (English)In: Sensors, E-ISSN 1424-8220, Vol. 21, no 11, article id 3743Article in journal (Refereed) Published
Abstract [en]

A decision support system (DSS) was developed that outputs suggestions for socket-rectification actions to the prosthetist, aiming at improving the fitness of transfemoral prosthetic socket design and reducing the time needed for the final socket design. For this purpose, the DSS employs a fuzzy-logic inference engine (IE) which combines a set of rectification rules with pressure measurements generated by sensors embedded in the socket, for deciding the rectification actions. The latter is then processed by an algorithm that receives, manipulates and modifies a 3D digital socket model as a triangle mesh formatted inside an STL file. The DSS results were validated and tested in an FEA simulation environment, by simulating and comparing the donning process among a good-fitting socket, a loose socket (poor-fit) and several rectified sockets produced by the proposed DSS. The simulation results indicate that volume reduction improves the pressure distribution over the stump. However, as the intensity of socket rectification increases, i.e., as volume reduction increases, high pressures appear in other parts of the socket which generate discomfort. Therefore, a trade-off is required between the amount of rectification and the balance of the pressure distributions experienced at the stump.

Place, publisher, year, edition, pages
MDPI AG , 2021. Vol. 21, no 11, article id 3743
Keywords [en]
transfemoral, prosthesis, socket rectification, pressure sensors, fuzzy-logic inference engine, FEA
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-315026DOI: 10.3390/s21113743ISI: 000660672800001PubMedID: 34071273Scopus ID: 2-s2.0-85106613578OAI: oai:DiVA.org:kth-315026DiVA, id: diva2:1677934
Note

QC 20220628

Available from: 2022-06-28 Created: 2022-06-28 Last updated: 2022-06-29Bibliographically approved

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Ottikkutti, SuranjanChen, DeJiu

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