**4. BCI applications in rehabilitation**

The applications for BCI systems in rehabilitation include motor neuroprosthetics, computer/machine interfaces, video games, speech and communication, meditation, and even art. The famous Hebbian theory, developed by Canadian psychologist Donald Hebb, described that with repeated stimulation of the postsynaptic neurons by presynaptic neurons, the efficacy of synaptic transmission would increase resulting in neuroplasticity. Besides, using the traditional rehabilitation therapy, BCI system can help "replace" and "restore" neurological functions by training patients to produce more reliable brain signals and to activate devices to assist movement [1, 3]. Patients with different cortical lesions may produce different oscillatory rhythm of neural activation [3].

#### **4.1 Motor imagery**

Evidence shows by using motor imagery, SMR can be trained to translate into commands to control and regulate voluntary activity. Just by imagining left or right hand movement, the right or left hemisphere respectively is activated, and the signals can be further processed and classified. To master MI-based BCI, subjects can undergo two approaches. The discrete trial, considered as tedious and lengthy, instructs them to perform cues within a timeframe while providing on-screen feedback on their results. On the other hand, continuous pursuit looks more promising as subjects are told to control a cursor in a moving icon on-screen. This provides a game-like approach so the subjects are more engaged with stronger brain signals being detected along with fewer training sessions required [9]. The challenges of using motor imagery are the requirement of a near-intact neurophysiological and psychological state of the users. This becomes a challenge to post-stroke patients with reduced in such mental and physical capacities [4].

#### **4.2 Other paradigms**

Other paradigms including spelling, induced emotions and facial-movement have also been tested to control wheelchair, prosthetic hand and robotic arm. Spelling the desired command has a higher accuracy but subjects may get fatigue with continuously spelling words to elicit the command. Inducing emotions is mentally demanding, while facial movement is more intuitive and easier to generate. Besides, this movement has lower illiteracy rates and higher accuracy rates. Merging different

paradigms, for example combining traditional MI and facial movement, can increase the number of classes or control functions to overcome poor classification accuracy of MI system. Some studies require subjects to perform sequential movement to bring out a command. This increases the latency as each command takes up around 3 seconds. Therefore, more time is required for execution. No comparisons have been made so far between traditional and sequential command paradigm. Whether it is feasible to increase accuracy at the expense of increasing latency remains a question to be explored [9]. Combining another biosignal to increase the number of commands is called hybrid BCIs. To enhance the control of prosthetics or orthotics, merging EEG with EMG has become increasingly popular [9].

## **4.3 EEG: EMG application**

Combined use of EEG and surface EMG in rehabilitative applications can control the effector's devices with a pathway starting from the cortical level down to the muscular level. EEG first explores the whole brain neuronal network, while EMG measures the train of motor unit action potentials that can help in motor planning with quantitative measurement in motor control abnormalities and muscular activation patterns. They combine with BCI or biofeedback methods to control external devices and guide rehabilitation. Using cortico-muscular coherence as signal analysis, it can "detect voluntary movements in spastic subjects, assess the effectiveness of rehabilitation strategies and serve as biomarker for motor recovery" [10]. As most of the experiments are done as pilot studies, more clinical trials are needed to evaluate the EEG–EMG applications [10].

### **4.4 Other studies**

Voznenko [11] studies the design of wheelchair control that uses thoughts, voice or gestures to mobilize a wheelchair. The use of combined BCI-FES (functional electrical stimulation) as designed by Muller-Putz study [4] helps send impulses to the patients' paralyzed arm/leg by artificially contracting the muscles. Therefore, the patients can have a more authentic experience. In [4], a number of studies have also been mentioned. Muller-Putz and Pfurtschscheller's study [12] uses 4 flickering stimuli with each one representing a different function of the arm based on SSVEP system. Subjects can select a movement by looking at a particular stimulus. Elstob and Secco [13] uses motor imagery-BCI to control a prosthetic arm that consists of 5 different types of movement. Using virtual reality, BCI controlled robotic arms can potentially guide subjects' arm movement in post-stroke rehabilitation, like the system proposed by Luu [14]. It is suggested that brain activities be measured while users are moving on a treadmill, and then "provide visual feedback to the user on their movements through a virtual avatar" [4].

## **4.5 Modalities in rehabilitation**

While research has mainly focused on motor rehabilitation, targets on improving tactile stimulus alone has been lacking. Sensory and motor cortices share the same somatic organization and are inseparable in improving and restoring function. Without sensory input, the rehabilitation of limbs would not be complete. Development of sensory-motor closed loop systems, or the bidirectional BCI, should improve the efficiency of rehabilitation in the future. In communication rehabilitation, patients with aphasia can regulate their evoked potentials (SCP, SMR, P300)

*Brain-Computer Interface: Use of Electroencephalogram in Neuro-Rehabilitation DOI: http://dx.doi.org/10.5772/intechopen.110162*

to communicate by producing letters via a speller system. Limited by the severity of cognitive impairment in poststroke or neurodegenerative patients, they may not be benefited from BCI as some basic cognitive levels are required to understand and manipulate the application. Providing neurofeedback via motor imagery and P300 system may enhance the rehabilitative process in this group of populations. In sum, there is still a lot of research required in poststroke cognitive training [3].
