Optimized Temporal Interference Stimulation Based on Convex Optimization: A Computational Study
Temporal interference (TI) stimulation is a non-invasive method targeting deep brain regions by applying two pairs of high-frequency currents with a slight frequency difference to the scalp. However, optimizing electrode configurations for TI via computational modeling is challenging and time-consum...
Uloženo v:
| Vydáno v: | IEEE transactions on neural systems and rehabilitation engineering Ročník 33; s. 1400 - 1410 |
|---|---|
| Hlavní autoři: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
United States
IEEE
01.01.2025
|
| Témata: | |
| ISSN: | 1534-4320, 1558-0210, 1558-0210 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Shrnutí: | Temporal interference (TI) stimulation is a non-invasive method targeting deep brain regions by applying two pairs of high-frequency currents with a slight frequency difference to the scalp. However, optimizing electrode configurations for TI via computational modeling is challenging and time-consuming due to the non-convex nature of the optimization. We propose a convex optimization-based method (CVXTI) for optimizing TI electrode configurations. We decompose the TI optimization into two convex steps, enabling rapid determination of electrode pair configurations. CVXTI accommodates various optimization objectives by incorporating different objective functions, thereby enhancing the focality of the stimulation field. Performance analysis of CVXTI shows superior results compared to other methods, particularly in deep brain regions. Subject variability analysis on four individuals highlights the necessity of customized stimulus optimization. CVXTI leverages the distribution characteristics of the TI envelope electric field to optimize electrode configurations, enhancing the optimization efficiency. |
|---|---|
| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1534-4320 1558-0210 1558-0210 |
| DOI: | 10.1109/TNSRE.2025.3558306 |