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Anyone that has seen the Netflix-show Black Mirror, might have become increasingly excited (and likely uncomfortable) with the possibilities of modern-day technology. The show depicts various sce-narios in a futuristic, technology driven world, showing us the effects that technology can have on our lives. The tv-show is presented as a science-fiction piece, but many of the scenarios presented have strong connections with reality. Though our contact lenses are not thought-controlled, and we don’t have microchips in our brain that manipulate what we see and feel, mind-controlled devices could soon have a large impact on some people recovering from a stroke.
The burden of stroke
Stroke is one of the leading causes of death and disability around the world. If trends con-tinue as estimated, there will be 23 million first ever strokes and 7.8 million stroke deaths in 2030, which means the amount of people suffering from a stroke is increasing.¹ Depending on its location and severity, a stroke often results in large loss of movement control. Although the intention of movement is there, the ability to move is severely impaired, which is a huge burden on daily life ac-tivities of this group of people. Could thought-controlled-devices really improve their quality of life?
From imagination to movement
Every time we imagine making a movement, we produce activity in our brain similar to when we actually make this movement. We can measure this activity with brain imaging methods like Electroencephalography (EEG), that measures changes in voltage at the scalp. Action imaging translates into EEG signalsthat can be used to control a computer and establish a Brain-Controlled-Interface (BCI). BCIs can function as a connection between the movement intention by picking up the EEG activation pattern, and translating it into a signal that controls the prosthetic device. Promis-ing results have already been reported by studies combining BCI training with behavioural therapy. An advantage of the use of the BCI is that it promotes brain plasticity by making stroke survivors use their affected limbs, which can help recover some of the lost movements.²
Though there are other ways to pick up signals from the brain, EEG-techniques are cur-rently being used most often, as they are relatively cheap and easy to use. However, the use of EEG for intention-controlled prosthetics comes with some limitations. For one, the equipments are not yet ready for use outside of the lab. Besides that, the EEG signals are relatively weak compared to the noise, and it is very difficult to know which part of the brain has generated the signals that are picked up by the EEG sensors. This reduces the ability to decipher the intention of the user.
From imagination to force
Another method of decoding intention is to measure the activity of the muscles with surface electromyography (sEMG). This method is similar to the EEG method, but instead of trying to inter-pret the intention from the brain, the signals from the muscles are measured. About 45% of the pa-tients with severe chronic stroke still have some muscle activity when trying to make a movement with the affected limb. There are a couple of advantages of using this method. When drinking a cup of coffee or making a sandwich, an excellent control of finger forces is needed. While BCIs mainly control the kinematics of movements (position, velocity, acceleration), sEMG can provide infor-mation about the intended forces and torques to help the control of the prosthetics. Some studies have already succeeded in combining EEG with sEMG to decode the intention of movement, and use this intention to move prosthetic devices. Though combining sEMG with EEG does not make it any easier to use outside of the lab, it does make it easier to interpret the intended movement from the EEG measurements.³
The demand for assistive and rehabilitation devices is increasing. The techniques and technologies are promising for this growing group of stroke survivors in the population, but not yet ready for every-day use. Some programs have been successful in implementing BCIs for communication purposes at home, for example to send an email or to browse the web. However, preparing an EEG recording can take hours, and prosthetic devices are often cumbersome, with a limited range of functions. For this reason it seems that stroke survivors currently can benefit the most from supervised training with a BCI to promote brain-plasticity. The future will bring new and more potent technologies to develop BCI-implementation further. Though we cannot be sure we will ever arrive at Black Mirror-like scenarios of brain control, advances in technology will certainly provide promising possibilities for future stroke survivors.
1. Mathers CD, Loncar D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med2006; 3:e442.
2. Cincotti, F., Pichiorri, F., Aricò, P., Aloise, F., Leotta, F., de Vico Fallani, F., & Mattia, D. (2012, August). EEG-based Brain-Computer Interface to support post-stroke motor rehabilitation of the upper limb. In Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE (pp. 4112-4115). IEEE.
3. Leeb, R., Sagha, H., & Chavarriaga, R. (2010, August). Multimodal fusion of muscle and brain signals for a hybrid-BCI. In Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE (pp. 4343-4346). IEEE.