Asynchronous P300-Based Brain-Computer Interface to Control a Virtual Environment: Initial Tests on End Users

Abstract

Motor disability and/or ageing can prevent individuals from fully enjoying home facilities, thus worsening their quality of life. Advances in the field of accessible user interfaces for domotic appliances can represent a valuable way to improve the independence of these persons. An asynchronous P300-based Brain-Computer Interface (BCI) system was recently validated with the participation of healthy young volunteers for environmental control. In this study, the asynchronous P300-based BCI for the interaction with a virtual home environment was tested with the participation of potential end-users (clients of a Frisian home care organization) with limited autonomy due to ageing and/or motor disabilities. System testing revealed that the minimum number of stimulation sequences needed to achieve correct classification had a higher intra-subject variability in potential end-users with respect to what was previously observed in young controls. Here we show that the asynchronous modality performed significantly better as compared to the synchronous mode in continuously adapting its speed to the users' state. Furthermore, the asynchronous system modality confirmed its reliability in avoiding misclassifications and false positives, as previously shown in young healthy subjects. The asynchronous modality may contribute to filling the usability gap between BCI systems and traditional input devices, representing an important step towards their use in the activities of daily living

Challenges in clinical applications of brain computer interfaces in individuals with spinal cord injury

“…First results in end users with handicaps show that environmental control by an asynchronous P300 BCI is possible. However, system testing also revealed that the minimum number of stimulation sequences needed for correct classification had a higher intra-subject variability in end users with respect to what was previously observed in young, non-disabled controls (Aloise et al, 2011). Also special focus must be put on the design of the visual control interface to achieve high accuracy while keeping mental effort low (Carabalona et al, 2012).…”

Effectiveness of the P3-speller in brain–computer interfaces for amyotrophic lateral sclerosis patients: a systematic review and meta-analysis

“…Of these, 440 articles were excluded because P3-spellers were not tested with ALS patients. Four studies described only single cases of ALS patients (Escolano et al, 2010; Sellers et al, 2010; Aloise et al, 2011; Manyakov et al, 2011), and, thus, they could not be included in the meta-analysis. The averaged CA of the four single cases tested with P3-spellers was 71.82%.…”

Performance measurement for brain–computer or brain–machine interfaces: a tutorial

“…The applications are similarly varied, including both communication and control of devices such as virtual keyboard (18–20), prostheses (21,22), wheelchairs (23–26), or environmental controls (27,28). Depending on the application, aspects of BCI performance (e.g., accuracy and speed) may differ in their relative importance.…”