Lightning Impact Current Variables in Wearable and Implantable Devices on Different Evaluation Methods

Abstract

This work introduces a novel and expedient method to evaluate the impact of lightning-induced current variables on wearable and implantable devices. The method focuses on analyzing the waveform parameters of lightning intensity modulation, a crucial factor in assessing the vulnerability of these devices to lightning strikes. Key waveform properties such as maximum voltage (Up), frontal duration (T1), time to half (T2), and overrun frequency (Be) are evaluated following IEC specifications. To accurately determine these parameters, an optimization technique employing rear supervised learning is applied. This technique analyzes the baseline curvature and its variations using data collected from 14 distinct points along the waveforms, particularly focusing on 26% of a signal applied on the wave's front portion and 50% of an open-circuit voltage on the wave's rear portion. The prescribed 28 waveforms are incorporated into the network subject's training process, and multiple experimental cases are employed to validate the proposed method.