Deep transcranial magnetic stimulation coil design and multi-objective slime mould algorithm.
10.7507/1001-5515.202412058
- Author:
Hui XIONG
1
;
Jibin ZHU
2
;
Jinzhen LIU
1
Author Information
1. School of Control Science and Engineering, Tiangong University, Tianjin 300387, P. R. China.
2. School of Electrical Engineering, Tiangong University, Tianjin 300387, P. R. China.
- Publication Type:Journal Article
- Keywords:
A-word coil;
Depth of stimulation;
Multi-objective optimization;
Slime mould algorithm;
Transcranial magnetic stimulation
- MeSH:
Algorithms;
Transcranial Magnetic Stimulation/instrumentation*;
Equipment Design;
Humans
- From:
Journal of Biomedical Engineering
2025;42(4):716-723
- CountryChina
- Language:Chinese
-
Abstract:
The therapeutic effects of transcranial magnetic stimulation (TMS) are closely related to the structure of the stimulation coil. Based on this, this study designed an A-word coil and proposed a multi-strategy fusion multi-objective slime mould algorithm (MSSMA) aimed at optimizing the stimulation depth, focality, and intensity of the coil. MSSMA significantly improved the convergence and distribution of the algorithm by integrating a dual-elite guiding mechanism, a hyperbolic tangent control strategy, and a hybrid polynomial mutation strategy. Furthermore, compared with other stimulation coils, the novel coil optimized by the MSSMA demonstrates superior performance in terms of stimulation depth. To verify the optimization effects, a magnetic field measurement system was established, and a comparison of the measurement data with simulation data confirmed that the proposed algorithm could effectively optimize coil performance. In summary, this study provides a new approach for deep TMS, and the proposed algorithm holds significant reference value for multi-objective engineering optimization problems.
