title: A reconfigurable neural signal processor (NSP) for brain machine interfaces.
abstract: In this paper, we present a design for a wearable computational DSP system that alleviates the issues of a previous design and provides a much smaller and lower power solution for the overall BMI goals. The system first acquires the neural data through a high speed data bus in order to train and evaluate prediction models. Then it wirelessly transmits the predicted results to a simulated robot arm. This system has been built and successfully tested with real and simulated data.
authors.affiliation: Dept. of Electr. & Comput. Eng., Univ. of FL, Gainesville, FL 32611-6200, USA.
authors.forename: Shalom
authors.initials: S
authors.lastname: Darmanjian
authors.forename: Grzegorz
authors.initials: G
authors.lastname: Cieslewski
authors.forename: Scott
authors.initials: S
authors.lastname: Morrison
authors.forename: Benjamin
authors.initials: B
authors.lastname: Dang
authors.forename: Karl
authors.initials: K
authors.lastname: Gugel
authors.forename: Jose
authors.initials: J
authors.lastname: Principe
mesh_terms: D001921:Brain / Q000502:physiology*; D004569:Electroencephalography / Q000295:instrumentation* / Q000379:methods; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005071:Evoked Potentials / Q000502:physiology*; D006801:Humans; D008328:Man-Machine Systems; D008904:Miniaturization; D012371:Robotics / Q000295:instrumentation*; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D013686:Telemetry / Q000295:instrumentation* / Q000379:methods; D013813:Therapy, Computer-Assisted / Q000295:instrumentation / Q000379:methods; D014584:User-Computer Interface