Successful BCI communication via high-frequency SSVEP or visual, audio or tactile P300 in 30 tested volunteers

Abstract

In the pursuit to clarify the concept of "BCI illiteracy", we investigated the possibilities of attaining basic binary (yes/no) communication via brain-computer interface (BCI). We tested four BCI paradigms: steady-state visual evoked potentials (SSVEP), tactile, visual, and auditory evoked potentials (P300). The proposed criterion for assessing for the possibility of communication are based on the number of correct choices obtained in a given BCI paradigm after a short calibration session, without prior training. In this study users answered 20 simple "yes/no" questions. Fourteen or more correct answers rejected the null hypothesis of random choices at P=0.05. All of the 30 healthy volunteers were able to attain above-chance choices in at least one of the four paradigms. Additionally, we tested the system in clinical settings on a patient recovering from disorders of consciousness, achieving successful communication in 2 out of 3 paradigms. In light of these facts, after a review of the sparse literature, and in the interest of motivating further research, we propose a paraphrase of de Finetti's provocative statement: "BCI illiteracy does not exist".

EEG-based vibrotactile evoked brain-computer interfaces system: A systematic review

“…Surprisingly, only around one-fifth of EVE-BCI studies were carried out for patients. These patients suffered from multiple levels of motor functioning loses caused by different diseases including the unresponsive wakefulness syndrome (UWS) [ 8 , 79 ], disorder of consciousness (DOC) [ 9 , 49 , 61 , 63 , 70 ], amyotrophic lateral sclerosis (ALS) [ 54 , 57 , 87 , 89 , 103 ], locked-in syndrome (LIS) [ 58 , 63 , 70 , 78 ], stroke [ 94 ], and minimally conscious state (MCS) [ 86 ]. On the other hand, most studies (83.54% of cases) alternatively focused on healthy subjects covering adults of all ages, including young people, the middle-aged, and elders.…”

“…Unlike the vibration frequency or the SOA, the location of vibration draws a lot of interest from researchers in the EVE-BCI area. Many locations throughout the body including fingers [ 30 , 31 , 50 , 95 ], wrist [ 8 , 9 ], back [ 37 , 48 , 58 ], foot [ 43 , 61 ], ankle [ 1 , 63 ], shoulder [ 76 , 88 ], waist [ 37 , 60 , 62 ], arm [ 34 , 57 ], leg [ 34 , 88 ], cheek [ 1 ], neck [ 66 , 86 ], chest [ 73 ], elbow [ 76 , 92 ], hand palms [ 89 ], scapula [ 96 ] and knee [ 103 ] were explored in publications. More than 1/3 (N = 30) of articles carried out the experiments with tactors attached in multiple parts of the body such as the wrist-back [ 78 , 79 , 87 ], finger-toe [ 24 , 42 ], arm-waist-leg [ 34 , 88 ].…”

“…Despite its simplicity, LDA often brought out robust and acceptable classification results for previous EVE-BCIs. Depending on various parameter settings, other deformed DAs such as Bayesian Linear Discriminant Analysis (BLDA) [ 1 , 4 , 36 , 75 ], Shrinkage LDA [ 30 , 31 , 38 , 55 , 86 ], Regularized Discriminant Analysis (RDA)) [ 24 , 33 , 42 , 43 , 51 , 62 , 99 ], and step-wise Linear Discriminant Analysis (SWLDA) [ 74 , 88 , 91 , 92 , 98 ] were also used. In terms of popularity, followed by the DA, another robust supervised learning model, linear Support Vector Machine (linear SVM), was also implemented in [ 32 , 33 , 73 , 82 , 84 , 89 , 95 ].…”

Leveraging Grating-Based Flickers: A Leap Toward Practical, Visually Comfortable, and High-Performance Dry EEG Code-VEP BCI

“…To address visual discomfort in VEP-based rBCIs, recent research has prioritized on the optimization of user experience while maintaining classification accuracy. Various approaches to the design of RVS stimuli have been explored to improve visual comfort, including the increase of flicker frequency range [15][16][17][18], the reduction of contrast between flicker phases [15,19,20], and the use of textured stimuli [21,22]. However, while these approaches hold promise in enhancing the user experience of stimuli presented in central vision, they do not prevent users from being distracted by neighboring stimuli in peripheral vision.…”