Transcranial magnetic stimulation is a promising tool in neuroscience of which successful development is affected by the loud click noise originated when the stimulating coil is energized. This undesired sound is produced by the coil winding deformations generated by the Lorentz self-forces in the TMS device. Addressing the need for TMS systems that produce less noise, a quiet coil design technique is proposed in this work, where instead of minimizing directly the coil deflection, the Lorentz self-force is optimized in order to reduce the acoustic noise. The presented method is based on a stream function IBEM for TMS coil design in which new computational models have been incorporated into the optimization problem, which is efficiently solved by using supporting vector analysis. Several examples of coils of different geometries were designed and simulated to demonstrate the efficiency of the suggested IBEM approach to produce TMS devices that experience minimum Lorentz self-forces. In order to evaluate the acoustic response of the designed TMS coils, the commercial MSC/NASTRAN was used to find the coil deflection. The obtained results show that significant noise reduction can be achieved by minimizing the Lorentz self-force over the TMS coil surface.

经颅磁刺激是神经科学中的一种有前途的工具，其成功发展受到刺激线圈通电时发出的喀哒声的影响。这种不希望的声音是由TMS设备中的洛伦兹自力产生的线圈绕组变形产生的。为了解决对产生更少噪声的TMS系统的需求，在这项工作中提出了一种安静的线圈设计技术，该方法不是直接最小化线圈挠度，而是优化了Lorentz自力以降低声音噪声。提出的方法基于用于TMS线圈设计的流函数IBEM，其中新的计算模型已被纳入优化问题，可通过使用支持向量分析有效地解决该问题。设计和模拟了不同几何形状的线圈的几个示例，以证明所建议的IBEM方法生产经受最小Lorentz自力的TMS设备的效率。为了评估设计的TMS线圈的声学响应，使用了商用MSC / NASTRAN来查找线圈的挠度。获得的结果表明，通过最小化TMS线圈表面上的洛伦兹自力，可以显着降低噪声。