We have developed real-time biomimetic systems to study neurological disorders, which will aid in the development of new neuroprostheses. Neuroprostheses involve using artificial hardware to stimulate biological parts for learning purposes, such as in cases of diseases like stroke. We presented the hardware architecture, highlighting the need for precision in the single compartment model and the use of more complex differential equation solvers. Additionally, we showcased some applications of this technology.