Abstract
Studies using BCIs based upon non-invasive, scalp recorded electroen- cephalography (EEG) have consistently demonstrated utility, both as scientific tools for neuromodulation and for clinical neurorehabilitation purposes. They are partic- ularly appealing in clinical contexts where physical movement is impaired, for instance following stroke. The intrinsic advantage of Brain-Computer Interfaces (BCIs) over alternate rehabilitation strategies is that they work even when output at the behavioural level is non-existent. Patients exhibiting minimal or no residual limb movement after a stroke cannot partake in gold standard physiotherapy, but might still demonstrate brain activity patterns when attempting to move the impaired limb. These patterns can be targeted to enhance recovery. However, the role of BCI should evolve once behavioural output is available. We must not be seduced by the allure of cutting-edge technology at the expense of targeting the specific neurophys- iological features that are most likely to drive recovery. At the most basic mecha- nistic level, the majority of BCIs are driven by neural signals generated by imagination of movement. We need to revisit the question—could motor imagery alone could achieve the same outcomes, or what is the added clinical benefit of the BCI? Accordingly, what is the minimum required intervention using BCI (in terms of time and hardware) to establish a habit of good quality motor imagery that could then sustain rehabilitation without the technology? Motor imagery is free, available to every person and at any time. Using technology to harness its virtues
while not compromising its simplicity is the ultimate challenge for the field.
while not compromising its simplicity is the ultimate challenge for the field.
Original language | English |
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Title of host publication | Brain-computer interface research. A state-of-the-art summary 11 |
Editors | Christoph Guger, Brendan Allison, Tomasz Rutkowski, Milena Korostenskaja |
Publisher | Springer |
Pages | 75-82 |
ISBN (Electronic) | 9783031494574 |
ISBN (Print) | 9783031494567 |
DOIs | |
Publication status | Published - 01 Jan 2024 |
Publication series
Name | SpringerBriefs in Electrical and Computer Engineering |
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ISSN (Print) | 2191-8112 |
ISSN (Electronic) | 2191-8120 |
Keywords
- Brain Computer Interface