Effect of Dual-task Training on the Number of EEG Band in Stroke Patients

Stroke is one of the most common diseases and causes of disability worldwide. This condition occurs when the blood supply to the brain tissue is disrupted, leading to ischaemia of the brain tissue and the functional impairments in the different systems of the body that this entails. One of the most prevalent and disabling dysfunctions in stroke patients is that related to the upper limb, with more than 80% experiencing this condition acutely and being permanent in approximately 60% of stroke survivors despite rehabilitation. The alteration of the functionality of the upper limbs of the person after stroke, including muscle weakness, sensory disorders, increased muscle tone and lack of neuromuscular control and coordination means that the person is not able to carry out normal activities of daily living (ADLs), thus affecting their autonomy and independence.

Most ADLs often require a combination of cognitive and motor tasks at the same time. These tasks are especially difficult for people who have suffered a stroke as their mental and physical capacity is impaired and therefore performing more than one task becomes a challenge. On the other hand, dual-task training (DTT) understood as a treatment method based on exercises involving 2 or more tasks at the same time related to the person's ADLs can be a interesting approach to improve the above mentioned upper limb disorders.

One of the tools recommended to analyse how a treatment or intervention affects the central nervous system of the person with stroke is the electroencephalogram (EEG), as it provides a continuous, real-time, non-invasive measurement of brain function that provides new insights into the pathophysiology of the brain. EEG analysis of brain disorders can be carried out with different methods such as network analysis and connectivity examination, machine learning, graph neural networks and examination of band frequency changes.

Among the EEG analysis methods that have not yet been tested in the stroke population following DTT intervention is the Fast Fourier Transform (FFT), a powerful tool for analysing the frequency of signals. When applied to a signal, the FFT function converts the signal from a time domain to a frequency domain. The main objective of this study is to analyse how in the different EEG bands (delta, theta, alpha and beta) of stroke patients are modified after converting the brain signal into Fourier series/transforms before and after a DTT intervention.

The intervention will consist of three different tasks that participants have to carry out while performing mental calculations (counting backwards from 100 by ones, twos, and threes). The three tasks will be as follows: grouping blocks of different colours into groups according to colour; picking up beans with a spoon and carrying them to a specific place; opening and closing a bottle cap with the affected hand. The total duration of the intervention will be 12 sessions, divided into three days per week for four weeks.

The main outcome is EEG data, which will be collected both before and after intervention, under the supervision of a neurologist, with the participant in a resting state and eyes closed. EEG recording is carried out during 3 minutes with 10-20 system, 19 electrodes (Fp1, Fp2, F7, F3, Fz, F4, F8, T7, C3, Cz, C4, T8, T10, P3, Pz, P4, P8, T9, P7) and a sampling rate of 256 Hz. The Fast Fourier Transform (FFT), which has proven to have less order complexity, will be used for the data analysis.

In addition, other variables on upper limb function, elbow flexor muscle tone, wrist extension range of motion and handling in activities of daily living will be collected.