Multi-objective optimization of prosthetic multi-cells foam liner

被引:2
|
作者
Benkhettou, Abdelkader [1 ]
Khatir, Omar [1 ]
Boudjemaa, Ismail [2 ]
Sahli, Abderahman [1 ]
Bouiadjra, Bel Abbes Bachir [1 ]
Benbarek, Smail [1 ]
机构
[1] Djillali Liabes Univ Sidi Bel Abbes, Fac Technol, Dept Mech Engn, Lab Mech Phys Mat LMPM, POB 89, Sidi Bel Abbes 22000, Algeria
[2] Univ Sci & Technol Oran Mohamed Boudiaf USTO MB, Dept Mech Engn, Gaseous Fuels & Environm Lab, Oran, Algeria
关键词
FEM; Foam liner; NSGA-II; prosthetic; transtibial limb; RESIDUAL LIMB; DESIGN; SOCKET; SATISFACTION; AMPUTEES;
D O I
10.1080/15376494.2024.2370035
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Restoring mobility using prosthetic limbs anchored in custom sockets is the primary goal of amputee rehabilitation. The contact pressure at the stump-liner interface is critical for improving prosthetic socket design and enhancing amputee satisfaction and comfort. This study aimed to develop and optimize a new customized multicellular foam liner model by identifying the optimal configuration of the liner's cells to achieve minimal contact pressure between the transtibial limb (stump) and the prosthetic interface while simultaneously minimizing the stump's immersion in the foam liner. The study employed a multi-objective optimization using the NSGA-II genetic algorithm to optimize the material configurations of the liner cells. The objective function was based on a finite element (FE) model of the customized foam liner, composed of 40 cells, each using one of six foam materials with varying firmness. The optimization process yielded nine different configurations representing the Pareto front. Contact pressure and immersion, represented by displacement in the load direction, were reduced from 140 KPa and 9 mm to 10 KPa and less than 1 mm, respectively. The results obtained in this study motivate future clinical trials on the efficacy of customized multicellular foam liners. These findings provide in-depth insights into prosthesis design and customization, potentially leading to further development in the use of foam rather than silicone for liner manufacturing.
引用
收藏
页数:8
相关论文
共 50 条
  • [21] Multi-objective optimization (MO)
    Balling, RJ
    [J]. OPTIMAIZATION IN INDUSTRY, 2002, : 337 - 338
  • [22] Multi-objective Whale Optimization
    Kumawat, Ishwar Ram
    Nanda, Satyasai Jagannath
    Maddila, Ravi Kumar
    [J]. TENCON 2017 - 2017 IEEE REGION 10 CONFERENCE, 2017, : 2747 - 2752
  • [23] Evolutionary Multi-Objective Optimization
    Deb, Kalyanmoy
    [J]. GECCO-2010 COMPANION PUBLICATION: PROCEEDINGS OF THE 12TH ANNUAL GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, 2010, : 2577 - 2602
  • [24] Multi-objective optimization of mechanisms
    Palcak, Frantisek
    Preszinsky, Gellert
    [J]. X. INTERNATIONAL CONFERENCE ON THE THEORY OF MACHINES AND MECHANISMS, PROCEEDINGS, 2008, : 447 - 452
  • [25] Progressive Multi-Objective Optimization
    Sorensen, Kenneth
    Springael, Johan
    [J]. INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING, 2014, 13 (05) : 917 - 936
  • [26] Splitting for Multi-objective Optimization
    Duan, Qibin
    Kroese, Dirk P.
    [J]. METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY, 2018, 20 (02) : 517 - 533
  • [27] The Multi-Objective Polynomial Optimization
    Nie, Jiawang
    Yang, Zi
    [J]. MATHEMATICS OF OPERATIONS RESEARCH, 2024, 49 (04) : 2723 - 2748
  • [28] Evolutionary multi-objective optimization
    Coello Coello, Carlos A.
    Hernandez Aguirre, Arturo
    Zitzler, Eckart
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2007, 181 (03) : 1617 - 1619
  • [29] Multi-objective chicken swarm optimization: A novel algorithm for solving multi-objective optimization problems
    Zouache, Djaafar
    Arby, Yahya Quid
    Nouioua, Farid
    Ben Abdelaziz, Fouad
    [J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2019, 129 : 377 - 391
  • [30] Multi-Objective Optimization of Tracking/Impedance Control for a Prosthetic Leg with Energy Regeneration
    Khademi, Gholamreza
    Richter, Hanz
    Simon, Dan
    [J]. 2016 IEEE 55TH CONFERENCE ON DECISION AND CONTROL (CDC), 2016, : 5322 - 5327