Energy-Efficient Peripheral Magnetic Stimulation via Pulse-Shape Optimization Using a Dual-Coil Architecture With...

Peripheral magnetic stimulation (PMS) has emerged as a non-contact neuromodulation technique for rehabilitation and neuroprosthetic applications. However, its practical use remains limited by high power consumption. While coil geometry optimization has been explored, the influence of individual pulse waveform phases on EMG-based functional responses remains largely uncharacterized in PMS. In this study, we present a dual-coil PMS architecture designed to enhance the axial electric-field gradient along the nerve and systematically investigate how pulse waveform parameters influence evoked responses and energy efficiency. Using an in vivo rat common peroneal nerve model, we independently varied the rising phase (RP), maintaining phase (MP), and falling phase (FP) of rectangular current pulses and quantified electromyographic (EMG) responses and per-pulse energy consumption. Decreasing MP reduced EMG amplitude, whereas increasing MP enhanced recruitment until saturation. Under the fixed-current condition, an MP of 100- $150~\mu $ s provided a practical low-energy range while maintaining a robust EMG-based response. Meanwhile, the energy-normalized response decreased monotonically as RP and FP increased, indicating that shorter transition phases are consistently advantageous from an energy-efficiency standpoint. The timing of the EMG-based functional response was most consistent with initiation by the first induced component, whereas the second component appeared to modulate the final response magnitude. Complementary electromagnetic simulations further showed that the nerve-axis electric-field component generated by the dual-coil configuration partially corresponds to that of a monopolar stimulation profile, providing a structural context for interpreting the observed waveform-dependent responses. Together, these results provide experimentally grounded pulse-design guidelines for energy-constrained PMS systems.