Extensive research during the past several years has demonstrated the feasibility of the brain-machine interface (BCI) in practical use, while it is still important to recognize that more interdisciplinary efforts are required to improve the efficiency, reliability, and accessibility of a BCI system for those who need it. An invasive BCI could be a promising remedy for patients with severe spinal cord injury or neurodegenerative diseases, but its long-term stability and are still hard to accomplish due to micromotion of the implanted device and ongoing foreign body responses in the brain. A non-invasive BCI is easier to implement for patients with mild motor dysfunctions and could also be used in scenarios like augmented reality, drowsiness detection, or entertainment, but noises, artifacts, and comfort during use are still matters of concern.

This methods collection aims to bring together novel technologies and innovative designs to build a better BCI, for both invasive and non-invasive platforms. Biocompatible materials, surface modifications, and topological alterations could improve the stability and longevity of implantable microelectrodes. Devices with reduced dimensions and bidirectional wireless data transmitting functions could further enhance the safety and the acceptance of this system. There are also algorithmic methods proposed to make better use of acquired signals, thereby compensating for imperfections in the hardware. Both trials on human subjects and early verification on animals could shed light on how these designs could address real-life problems during BCI use.