Although BMIs are rapidly maturing, several challenges remain before they could come into widespread use:
Thus, with the exception of helping people with motor disabilities, BMI has a long way to go before reaching levels of mind control that are expected from science fiction.
- Better technologies for measuring neural signals while remaining non-invasive. Ideally, one would like to measure outputs of thousands of neurons with a high signal-to-noise ratio. One alternative to fMRI that is attracting significant attention in recent years is functional near-infrared spectroscopy (fNIRS). Such signals can be used in combination with EEG to enhance measurement [134,227].
- Improved bandwidth in terms of bits-per-second that can be commanded by the user so that there are clear advantages over using body movements or controllers. VR systems with non-invasive BMI typically offer up to one bit per second, which is woefully inadequate .
- Better classification techniques that can recognize the intentions and decisions of the user with higher accuracy and detail. Modern machine learning methods may help advance this.
- Dramatic reduction in the amount of training that is required before using an interface. If it requires more work than learning how to type, then widespread adoption would be unlikely.
- A better understanding what kinds of body schemas can be learned through the feedback provided by VR systems so that the brain accepts the virtual body as being natural.
Steven M LaValle