Literature DB >> 29432118

A Mixed Integer Linear Programming Approach to Electrical Stimulation Optimization Problems.

Gehan Abouelseoud, Yasmine Abouelseoud, Amin Shoukry, Nour Ismail, Jaidaa Mekky.   

Abstract

Electrical stimulation optimization is a challenging problem. Even when a single region is targeted for excitation, the problem remains a constrained multi-objective optimization problem. The constrained nature of the problem results from safety concerns while its multi-objectives originate from the requirement that non-targeted regions should remain unaffected. In this paper, we propose a mixed integer linear programming formulation that can successfully address the challenges facing this problem. Moreover, the proposed framework can conclusively check the feasibility of the stimulation goals. This helps researchers to avoid wasting time trying to achieve goals that are impossible under a chosen stimulation setup. The superiority of the proposed framework over alternative methods is demonstrated through simulation examples.

Mesh:

Year:  2018        PMID: 29432118     DOI: 10.1109/TNSRE.2018.2789380

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  2 in total

1.  Maximizing clinical rotation placements for US medical students: exploring an optimization model.

Authors:  Gary L Beck Dallaghan; Xi Lin; J Kyle Melvin; Julie Golding; Beat Steiner; Vidyadhar Kulkarni
Journal:  Med Educ Online       Date:  2022-12

2.  A new hybrid Artificial Intelligence (AI) approach for hydro energy sites selection and integration.

Authors:  F Chen Jong; Musse Mohamud Ahmed; W Kin Lau; H Aik Denis Lee
Journal:  Heliyon       Date:  2022-09-21
  2 in total

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