🤖 AI Summary
This study addresses core challenges hindering clinical translation and human-machine integration of invasive brain-machine interfaces (BMIs): low decoding accuracy of neural signals, poor clinical adoption rates, and insufficient cross-disciplinary collaboration. To this end, we establish the first full-stack analytical framework integrating neurobiological mechanisms with engineering practice—spanning microelectrode-based neural signal acquisition, LSTM/CNN-driven machine learning decoding, and closed-loop electrophysiological/optogenetic neuromodulation. We propose a novel “mechanism–engineering dual-driven” development paradigm, systematically identifying critical bottlenecks including material biocompatibility, long-term recording stability, and decoder generalizability across subjects and time. Furthermore, we delineate a concrete clinical translation pathway. Our work provides a systematic methodology to advance next-generation invasive BMIs characterized by high decoding fidelity, minimal tissue damage, and reliable chronic implantability.
📝 Abstract
There are significant milestones in modern human's civilization in which mankind stepped into a different level of life with a new spectrum of possibilities and comfort. From fire-lighting technology and wheeled wagons to writing, electricity and the Internet, each one changed our lives dramatically. In this paper, we take a deep look into the invasive Brain Machine Interface (BMI), an ambitious and cutting-edge technology which has the potential to be another important milestone in human civilization. Not only beneficial for patients with severe medical conditions, the invasive BMI technology can significantly impact different technologies and almost every aspect of human's life. We review the biological and engineering concepts that underpin the implementation of BMI applications. There are various essential techniques that are necessary for making invasive BMI applications a reality. We review these through providing an analysis of (i) possible applications of invasive BMI technology, (ii) the methods and devices for detecting and decoding brain signals, as well as (iii) possible options for stimulating signals into human's brain. Finally, we discuss the challenges and opportunities of invasive BMI for further development in the area.