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 is able to recognise users’ mental state accordingly to the biofeedback factor Bf , based on users’ Attention, Intention and Focus, that is used to elicit a robot to perform customised behaviours. Experiments have been conducted with a population of 8 subjects: 4 ALS patients in a near Locked-in status with normal ocular movement and 4 healthy control subjects enrolled for age, education and computer expertise. The results showed as three ALS patients have completed the task with 96.67% success; the healthy controls with 100% success; the fourth ALS has been excluded from the results for his low general attention during the task; the analysis of Bf factor highlights as ALS subjects have shown stronger Bf (81.20%) than healthy controls (76.77%). Finally, a post-hoc analysis is provided to show how robotic feedback helps in maintaining focus on expected task. These preliminary data suggest that ALS patients could successfully control a humanoid robot through a BCI architecture, potentially enabling them to conduct some everyday tasks and extend their presence in the environment.

Sorbello, R., Tramonte, S., Giardina, M., La Bella, V., Spataro, R., Allison, B., et al. (2018). A Human-Humanoid Interaction through the use of BCI for Locked-In ALS Patients using neuro-biological feedback fusion. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 26(2), 487-497 [10.1109/TNSRE.2017.2728140].

A Human-Humanoid Interaction through the use of BCI for Locked-In ALS Patients using neuro-biological feedback fusion

SORBELLO, Rosario
;
Tramonte, Salvatore;GIARDINA, Marcello Emanuele;LA BELLA, Vincenzo;SPATARO, Rossella;CHELLA, Antonio
2018-01-01

Abstract

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 is able to recognise users’ mental state accordingly to the biofeedback factor Bf , based on users’ Attention, Intention and Focus, that is used to elicit a robot to perform customised behaviours. Experiments have been conducted with a population of 8 subjects: 4 ALS patients in a near Locked-in status with normal ocular movement and 4 healthy control subjects enrolled for age, education and computer expertise. The results showed as three ALS patients have completed the task with 96.67% success; the healthy controls with 100% success; the fourth ALS has been excluded from the results for his low general attention during the task; the analysis of Bf factor highlights as ALS subjects have shown stronger Bf (81.20%) than healthy controls (76.77%). Finally, a post-hoc analysis is provided to show how robotic feedback helps in maintaining focus on expected task. These preliminary data suggest that ALS patients could successfully control a humanoid robot through a BCI architecture, potentially enabling them to conduct some everyday tasks and extend their presence in the environment.
2018
Sorbello, R., Tramonte, S., Giardina, M., La Bella, V., Spataro, R., Allison, B., et al. (2018). A Human-Humanoid Interaction through the use of BCI for Locked-In ALS Patients using neuro-biological feedback fusion. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 26(2), 487-497 [10.1109/TNSRE.2017.2728140].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/264356
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