A study of particle swarm optimization on leukocyte adhesion molecules and control strategies for smart prosthetic hand

Cheng Hung Chen, Ken W. Bosworth, Marco P. Schoen, Shawn E. Bearden, D. Subbaram Naidu, Alba Perez

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

Hard computing based optimization algorithms usually require a lot of computational resources and generally do not have the ability to arrive at the global optimum solution. Soft computing algorithms on the other hand negate these deficiencies, by allowing for reduced computational loads and the ability to find global optimal solutions, even for complex cost surfaces. This paper presents two numerical case studies where a Particle Swarm Optimization (PSO) algorithm is applied to biomedical problems. In particular, the problem of identifying the rupture force for leukocyte adhesion molecules and the problem of finding the correct control parameters of a robotic hand, are addressed. Simulation results indicate that PSO is a feasible alternative to the computational expensive hard computing algorithms.

Original languageEnglish (US)
Title of host publication2008 IEEE Swarm Intelligence Symposium, SIS 2008
DOIs
StatePublished - Dec 22 2008
Event2008 IEEE Swarm Intelligence Symposium, SIS 2008 - St. Louis, MO, United States
Duration: Sep 21 2008Sep 23 2008

Other

Other2008 IEEE Swarm Intelligence Symposium, SIS 2008
CountryUnited States
CitySt. Louis, MO
Period9/21/089/23/08

Keywords

  • Leukocyte adhesion molecules
  • Particle swarm optimization
  • Proportional-derivative control
  • Prosthetic hand

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    Chen, C. H., Bosworth, K. W., Schoen, M. P., Bearden, S. E., Naidu, D. S., & Perez, A. (2008). A study of particle swarm optimization on leukocyte adhesion molecules and control strategies for smart prosthetic hand. In 2008 IEEE Swarm Intelligence Symposium, SIS 2008 [4668324] https://doi.org/10.1109/SIS.2008.4668324