title: Continuous shared control for stabilizing reaching and grasping with brain-machine interfaces.
abstract: Research on brain-machine interfaces (BMI's) is directed toward enabling paralyzed individuals to manipulate their environment through slave robots. Even for able-bodied individuals, using a robot to reach and grasp objects in unstructured environments can be a difficult telemanipulation task. Controlling the slave directly with neural signals instead of a hand-master adds further challenges, such as uncertainty about the intended trajectory coupled with a low update rate for the command signal. To address these challenges, a continuous shared control (CSC) paradigm is introduced for BMI where robot sensors produce reflex-like reactions to augment brain-controlled trajectories. To test the merits of this approach, CSC was implemented on a 3-degree-of-freedom robot with a gripper bearing three co-located range sensors. The robot was commanded to follow eighty-three reach-and-grasp trajectories estimated previously from the outputs of a population of neurons recorded from the brain of a monkey. Five different levels of sensor-based reflexes were tested. Weighting brain commands 70% and sensor commands 30% produced the best task performance, better than brain signals alone by more than seven-fold. Such a marked performance improvement in this test case suggests that some level of machine autonomy will be an important component of successful BMI systems in general.
authors.affiliation: Touch Laboratory, Massachusetts Institute of Technology, Cambridge 02139, USA. hyunkim@mit.edu
authors.forename: Hyun K
authors.initials: HK
authors.lastname: Kim
authors.forename: S James
authors.initials: SJ
authors.lastname: Biggs
authors.forename: David W
authors.initials: DW
authors.lastname: Schloerb
authors.forename: Jose M
authors.initials: JM
authors.lastname: Carmena
authors.forename: Mikhail A
authors.initials: MA
authors.lastname: Lebedev
authors.forename: Miguel A L
authors.initials: MA
authors.lastname: Nicolelis
authors.forename: Mandayam A
authors.initials: MA
authors.lastname: Srinivasan
mesh_terms: D001132:Arm / Q000503:physiopathology*; D001921:Brain / Q000502:physiology*; D004569:Electroencephalography / Q000379:methods; D005071:Evoked Potentials / Q000502:physiology; D005246:Feedback; D018737:Hand Strength / Q000502:physiology; D006801:Humans; D007092:Imagination / Q000502:physiology; D009068:Movement; D009069:Movement Disorders / Q000534:rehabilitation*; D012371:Robotics / Q000295:instrumentation / Q000379:methods*; D018511:Systems Integration; D017216:Telemedicine / Q000295:instrumentation / Q000379:methods; D013813:Therapy, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D014584:User-Computer Interface