Feasibility of BCI Control in a Realistic Smart Home Environment.
Smart homes have been an active area of research, however despite considerable investment, they are not yet a reality for end-users. Moreover, there are still accessibility challenges for the elderly or the disabled, two of the main potential targets for home automation. In this exploratory study we design a control mechanism for smart homes based on Brain Computer Interfaces (BCI) and apply it in the "Domus" smart home platform in order to evaluate the potential interest of users about BCIs at home. We enable users to control lighting, a TV set, a coffee machine and the shutters of the smart home. We evaluate the performance (accuracy, interaction time), usability and feasibility (USE questionnaire) on 12 healthy subjects and 2 disabled subjects. We find that healthy subjects achieve 77% task accuracy. However, disabled subjects achieved a better accuracy (81% compared to 77%).
Team Hybrid, InriaRennes, France; Team EHCI, Université Grenoble AlpesSt Martin D'Heres, France.
Nataliya
N
Kosmyna
Team EHCI, Université Grenoble Alpes St Martin D'Heres, France.
Franck
F
Tarpin-Bernard
Inria Montbonnot Montbonnot St Martin, France.
Nicolas
N
Bonnefond
Gipsa Lab, Grenoble INP Grenoble, France.
Bertrand
B
Rivet
EEG; brain computer interfaces; conceptual imagery; smart home; usability