Slow Electronics has the potential to process time-series data on the same time scale as human activities while achieving ultra-low power consumption. To realize this technology, it is essential to develop dedicated devices such as neuron elements and circuits with long time constants, requiring long-term research and development efforts. In this chapter, as an initial step toward such long-term technological advancements, we aim to explore the potential application fields of Slow Electronics at an early stage. Rather than relying solely on simulations, we conduct hardware-based verification using an FPGA to investigate its practical applicability. To this end, we temporarily set aside power consumption considerations and focus on implementing and analyzing the design and challenges of reservoir computing, a foundational technology for Slow Electronics. Specifically, this study considers the application of Slow Electronics to handwriting authentication technology. By implementing a reservoir on an FPGA to reproduce handwritten input waveforms, we demonstrate its practical feasibility. Furthermore, we identify challenges associated with hardware-based reservoir computing and discuss the necessity of incorporating Slow Electronics elements to address these issues.