ON THE USE OF BRAIN-COMPUTER INTERFACES OUTSIDE SCIENTIFIC LABORATORIES: TOWARD AN APPLICATION IN DOMOTIC ENVIRONMENTS

被引:10
|
作者
Babiloni, F. [1 ,2 ]
Cincotti, F. [1 ]
Marciani, M. [1 ]
Salinari, S. [3 ,4 ,5 ]
Astolfi, L. [1 ,2 ]
Aloise, F. [1 ]
Fallani, F. De Vico [1 ]
Mattia, D. [1 ]
机构
[1] Fdn Santa Lucia, IRCCS, Rome, Italy
[2] Univ Roma La Sapienza, Dip Fisiol & Farmacol, Rome, Italy
[3] Univ Roma La Sapienza, Dipartimento Informat & Sistemist, Rome, Italy
[4] Scuola Super Sant Anna, ARTS Lab, Pisa, Italy
[5] Scuola Super Sant Anna, CRIM Lab, Pisa, Italy
关键词
EEG; SYSTEM;
D O I
10.1016/S0074-7742(09)86010-8
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Brain computer interface (BCI) applications were initially designed to provide final users with special capabilities, like writing letters on a screen, to communicate with others without muscular effort. In these last few years, the BCI scientific community has been interested in bringing BCI applications outside the scientific laboratories, initially to provide useful applications in everyday life and in future in more complex environments, such as space. Recently, we implemented a control of a domestic environment realized with BCI applications. In the present chapter, we analyze the methodological approach employed to allow the interaction between subjects and domestic devices by use of noninvasive EEG recordings. In particular, we analyze whether the cortical activity estimated from noninvasive EEG recordings could be useful in detecting mental states related to imagined limb movements. We estimate cortical activity from high-resolution EEG recordings in a group of healthy subjects by using realistic head models. Such cortical activity was estimated in a region of interest associated with the subjects' Brodmann areas by use of depth-weighted minimum norm solutions. Results show that the use of the estimated cortical activity instead of unprocessed EEG improves the recognition of the mental states associated with limb-movement imagination in a group of healthy subjects. The BCI methodology here presented has been used in a group of disabled patients to give them suitable control of several electronic devices disposed in a three-room environment devoted to neurorehabilitation. Four of six patients were able to control several electronic devices in the domotic context with the BCI system, with a percentage of correct responses averaging over 63%.
引用
收藏
页码:133 / 146
页数:14
相关论文
共 50 条
  • [41] Towards Bidirectional Brain-computer Interfaces that Use fNIRS and tDCS
    Hincks, Samuel W.
    DeBellis, Maya
    Lee, Eun Youb
    ten Brink, Ronna
    Moell, Birger
    Jacob, Robert J. K.
    PHYCS: PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON PHYSIOLOGICAL COMPUTING SYSTEMS, 2017, : 57 - 64
  • [42] Ethical considerations for the use of brain-computer interfaces for cognitive enhancement
    Gordon, Emma C.
    Seth, Anil K.
    PLOS BIOLOGY, 2024, 22 (10)
  • [43] Brain-computer interface (BCI)-generated speech to control domotic devices
    Velasco-Álvarez, Francisco
    Fernández-Rodríguez, Álvaro
    Ron-Angevin, Ricardo
    Neurocomputing, 2022, 509 : 121 - 136
  • [44] A Survey on the Use of Haptic Feedback for Brain-Computer Interfaces and Neurofeedback
    Fleury, Mathis
    Lioi, Giulia
    Barillot, Christian
    Lecuyer, Anatole
    FRONTIERS IN NEUROSCIENCE, 2020, 14
  • [45] Brain-machine and brain-computer interfaces
    Friehs, GM
    Zerris, VA
    Ojakangas, CL
    Fellows, MR
    Donoghue, JP
    STROKE, 2004, 35 (11) : 2702 - 2705
  • [46] Brain-computer interface (BCI)-generated speech to control domotic devices
    Velasco-Alvarez, Francisco
    Fernandez-Rodriguez, Alvaro
    Ron-Angevin, Ricardo
    NEUROCOMPUTING, 2022, 509 : 121 - 136
  • [47] Alternative Classification Techniques for Brain-Computer Interfaces for Smart Sensor Manufacturing Environments
    Balderas, David
    Molina, Arturo
    Ponce, Pedro
    IFAC PAPERSONLINE, 2015, 48 (03): : 680 - 685
  • [48] Brain-Computer Interfaces in Disorders of Consciousness
    He, Qiheng
    He, Jianghong
    Yang, Yi
    Zhao, Jizong
    NEUROSCIENCE BULLETIN, 2023, 39 (02) : 348 - 352
  • [49] Optimizing the Usability of Brain-Computer Interfaces
    Zhang, Yin
    Chase, Steve M.
    NEURAL COMPUTATION, 2018, 30 (05) : 1323 - 1358
  • [50] Recent advances in brain-computer interfaces
    Ebrahimi, Touradj
    2007 IEEE NINTH WORKSHOP ON MULTIMEDIA SIGNAL PROCESSING, 2007, : 17 - 17