Neural Interface Engineering

by Guo

This book provides a comprehensive reference to major neural interfacing technologies used to transmit signals between the physical world and the nervous system for repairing, restoring and even augmenting body functions. The authors discuss the classic approaches for neural interfacing, the major challenges encountered, and recent, emerging techniques to mitigate these challenges for better chronic performances. Readers will benefit from this book’s unprecedented scope and depth of coverage on the technology of neural interfaces, the most critical component in any type of neural prostheses.

448 pages, Hardcover

Published May 5, 2020

Reviews

[Medhat Ullah · Rating 4 out of 5]

Starting a software-focused neural interface company makes sense because it tackles the core technical challenges of the field without the enormous costs and risks of building implants. Neural signals are incredibly complex and noisy, and making them understandable is the key to enabling real-world applications. By combining AI, machine learning, and advanced signal processing, a software startup can decode these signals, translate them into actionable commands, and create systems that allow humans to control devices—like VR/AR environments, prosthetics, or neurofeedback tools all without invasive surgery. From an engineering standpoint, this approach is both scalable and modular. Non-invasive devices like EEG headsets already exist, so the software layer can focus on signal interpretation, real-time processing, and intelligent decision-making. Once proven, these systems can integrate with new hardware as it emerges, creating hybrid solutions that enhance functionality and usability. I'd argue market opportunity is huge . Applications range from gaming and mental wellness to rehabilitation and education, and there is a growing demand for software that makes neural data usable, interpretable, and actionable. By starting with software, the company can iterate quickly, validate ideas with real users, and form partnerships with hardware manufacturers to eventually participate in the full neural interface ecosystem.