This paper illustrates a new architecture for a human-humanoid interaction based on EEG-Brain Computer Interface(EEG-BCI) for patients affected by locked-in syndrome caused by Amyotrophic Lateral Sclerosis (ALS). The proposed architecture isable to recognise users’ mental state accordingly to the biofeedback factor Bf , based on users’ Attention, Intention and Focus, that isused to elicit a robot to perform customised behaviours. Experiments have been conducted with a population of 8 subjects: 4 ALSpatients in a near Locked-in status with normal ocular movement and 4 healthy control subjects enrolled for age, education andcomputer expertise. The results showed as three ALS patients have completed the task with 96.67% success; the healthy controls with100% success; the fourth ALS has been excluded from the results for his low general attention during the task; the analysis of Bffactor highlights as ALS subjects have shown stronger Bf (81.20%) than healthy controls (76.77%). Finally, a post-hoc analysis isprovided to show how robotic feedback helps in maintaining focus on expected task. These preliminary data suggest that ALS patientscould successfully control a humanoid robot through a BCI architecture, potentially enabling them to conduct some everyday tasks andextend their presence in the environment.
|Numero di pagine||11|
|Rivista||IEEE Transactions on Neural Systems and Rehabilitation Engineering|
|Stato di pubblicazione||Published - 2018|
All Science Journal Classification (ASJC) codes
- Internal Medicine
- Biomedical Engineering
- Computer Science Applications