## 3 Materials and Methods
### Fuzzy Inference
#### 3.2.6 Experiments  
Participants and Ethical Considerations  
Fifty-three volunteers participated in the experiments (mean age = 27.88, standard deviation = 9.71). All the volunteers gave their informed consent for inclusion prior participating in the experiments. The participants met the following inclusion criteria: (i) they were healthy, and (ii) they were over eighteen years old. The exclusion criteria for participants were as follows: (i) they were pregnant, (ii) they had a motor impairment or motor medical condition (e.g., Parkinson), and (iii) they had a hand injury. This study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethical Committee of the School of Engineering and Science at Tecnologico de Monterrey (Protocol identification code: CA-EIC-2403-01). Experiment  
Each participant played the non-tailored game and the tailored game. Each game mode was played for three minutes. During the playing, EEG signals were collected using the respective EEG sensor according to the experimental group. Specifically, EEG signals were collected for 3 min per game mode and per participant. A numerical id was given to each participant. Participants with an odd id played the non-tailored game mode first, whereas participants with even id played the tailored game mode first, to reduce the \"learning effect\". Experimental group 1--Bitalino sensor  
EEG signals from AF3 and P7 positions were recorded at a sampling rate of 1000 Hz using two Bitalino sensors (i.e., one Bitalino sensor per position) on twenty participants (see Figure 7). Two participants were left-handed, whereas the remaining participants were right-handed. Three volunteers had experience in using LMC. The experimental setting of the Bitalino sensors was as follows:  
1. First, the distance between each participant's inion and nasion was measured. 2. Then, following the 10-20 system, AF3 and P7 positions were localized. 3. The AF3 and P7 positions, and the earlobes, were cleaned with alcohol. 4. Then, the electrodes of one Bitalino were placed at AF3 and the electrodes of the other Bitalino were placed at P7. The reference electrodes were placed on the earlobes. 5. Finally, OpenSignals Version 1 was used to acquire the EEG data. Before starting the experiments, the EEG activity was revised in OpenSignals while participants were resting, so that abnormal activity could be detected visually from the acquisition software (i.e., a flat line signal or high activity signal when volunteers were resting). Figure 7: Experimental setting using the Bitalino sensor to collect the EEG signal. Specifically, a Butterworth bandpass filter of the 6 th order with the frequency range of 4-12 Hz was used to preprocess the EEG signals. Then, the power spectral density was computed to the filtered EEG signal using the Welch method. Finally, the \(\alpha\) and \(\theta\) bands were computed from the power spectral density. This processing was performed using Python 3.10.12. Experimental group 2--Unicorn sensor EEG signals were recorded at a sampling rate of 250 Hz using the Unicorn sensor on thirty-three participants (see Figure 8). Only one participant was left-handed, whereas the remaining participants were right-handed. Only one participant had experience in using LMC. The experimental setting of the Unicorn sensor was as follows:  
1. First, the distance between each participant's inion and nasion was measured. 2. Then, following the 10-20 system, the Cz position was localized. 3. The EEG cap of the Unicorn sensor was placed based on the Cz position. 4. Then, saline solution was placed on eight positions of the EEG cap. 5. Electrodes were placed on the eight positions of the EEG cap. The reference electrodes were placed on the mastoids. 6. Finally, EEGLab v2023.1. was used to acquire the EEG data.