Table 3.
Summary of articles on BCI-based applications for students with spatial and visuospatial disabilities.
| Study (year) | Sample | Study contents | Key findings |
|---|---|---|---|
| Hammer et al., (2012) | 83 healthy BCI novices (range 17–65, 79% of them were students) | The psychological test-battery included performance, personality and clinical tests and the vividness of movement imagery questionnaire. Brain signals were recorded from the scalp with a 128-channel EEG amplifier using 119 Ag/AgCl electrodes. | It is concluded that visuo-motor coordination, concentration and μ-peak when relaxed are greatly important determinants of success with an SMR-BCI that is mostly using machine-learning processes. |
| Hammer et al., (2014) | 33 healthy participants aged 19–32 (most of them were students) | A considerable number of clinical, personality and performance tests were collected. EEG was acquired from 16 passive Ag/AgCl electrodes, mounted into a 64-channel cap at positions FP1, FP2, F3, Fz, F4, T7, C3, Cz, C4, T8, CP3, CP4, P3, Pz, P4, Oz. | Visuo-motor coordination ability and impulsivity were positively correlated with SMR feedback performance. Mean SMR-BCI performance across all feedback sessions was M = 79.00% |
| Jeunet et al., (2015) | 18 participants, aged 21.5 ± 1.2, | The EEG signals were recorded using 30 scalp electrodes (F3, Fz, F4, FT7, FC5, FC3, FCz, FC4, FC6, FT8, C5, C3, C1, Cz, C2, C4, C6, CP3, CPz, CP4, P5, P3, P1, Pz, P2, P4, P6, PO7, PO8). Each user took part in 6 sessions, on 6 different days spread out over several weeks, performing 3 MI-tasks, 2 of which were non-motor tasks. | The study showed the way that a user's profile can influence their MI-BCI control skills. Therefore, they proposed a novel method of designing new protocls for MI-BCI training, that are adjusted to each user's profile. |
| Wang et al., (2007) | 2 ADHD subjects aged 8 and 11 years | Both participants underwent assessment by an IVA - CPT. Three electrodes (Cz, Fp1, Fp2), were placed on their head as described in the International 10–20 system. | It is argued that the BCI–NFB-VR system helps ADHD subjects recover their cognitive function visualizing EEG signals techniques for restoring the movements. |
| Yang et al., (2017) | 10 university students | A brain-controlled game based on MI is created. Both the BCI system and the game were designed. EEG output was obtained by Neuroscan using 27 different channels of electrodes. | The analysis of bandpower outcomes showed that participants' attention level increased throughout the experiment performing MI tasks. |
EEG: electroencephalogram; ME: Motor execution; EO: Eyes Open; MIK: kinesthetic motor imagery; MIV: visual–motor imagery; OOM: observation of movement; ADHD: attention deficit/hyperactivity disorder; VR: virtual reality; NF: neurofeedback; BCI: brain computer interface; MI: motor imagery; IVA: Integrated Visual & Auditory; CPT: Continuous Performance Test; SMR: sensorimotor rhythms; Ag/AgCl: Silver/Silver Chloride.