Robust human machine interface based on head movements applied to assistive robotics.
This paper presents an interface that uses two different sensing techniques and combines both results through a fusion process to obtain the minimum-variance estimator of the orientation of the user's head. Sensing techniques of the interface are based on an inertial sensor and artificial vision. The orientation of the user's head is used to steer the navigation of a robotic wheelchair. Also, a control algorithm for assistive technology system is presented. The system is evaluated by four individuals with severe motors disability and a quantitative index was developed, in order to objectively evaluate the performance. The results obtained are promising since most users could perform the proposed tasks with the robotic wheelchair.
Gabinete de Tecnología Médica, Facultad de Ingeniería, Universidad Nacional de San Juan, 5400 San Juan, Argentina.
Elisa
E
Perez
Gabinete de Tecnología Médica, Facultad de Ingeniería, Universidad Nacional de San Juan, 5400 San Juan, Argentina.
Natalia
N
López
Instituto de Automática, Facultad de Ingeniería, Universidad Nacional de San Juan, 5400 San Juan, Argentina.
Eugenio
E
Orosco
Instituto de Automática, Facultad de Ingeniería, Universidad Nacional de San Juan, 5400 San Juan, Argentina.
Carlos
C
Soria
Instituto de Automática, Facultad de Ingeniería, Universidad Nacional de San Juan, 5400 San Juan, Argentina.
Vicente
V
Mut
Departamento de Engenharia Elétrica, Universidade Federal do Espírito Santo, 29075910 Vitoria, ES, Brazil.
Teodiano
T
Freire-Bastos
D000465:Algorithms; D001185:Artificial Intelligence; D001696:Biomechanical Phenomena; D006233:Persons with Disabilities; D004867:Equipment Design; D019416:Head Movements; D006801:Humans; D012371:Robotics / Q000295:instrumentation*; D012656:Self-Help Devices; D013647:Task Performance and Analysis; D014584:User-Computer Interface; D014910:Wheelchairs