Slow Firing Single Units Are Essential for Optimal Decoding of Silent Speech.

The motivation of someone who is locked-in, that is, paralyzed and mute, is to find relief for their loss of function. The data presented in this report is part of an attempt to restore one of those lost functions, namely, speech. An essential feature of the development of a speech prosthesis is optimal decoding of patterns of recorded neural signals during speech, that is, speaking "inside the head" with output that is inaudible due to the paralysis of the articulators.

Classification of intended phoneme production from chronic intracortical microelectrode recordings in speech-motor cortex.

We conducted a neurophysiological study of attempted speech production in a paralyzed human volunteer using chronic microelectrode recordings. The volunteer suffers from locked-in syndrome leaving him in a state of near-total paralysis, though he maintains good cognition and sensation. In this study, we investigated the feasibility of supervised classification techniques for prediction of intended phoneme production in the absence of any overt movements including speech.

Brain-Computer Interfaces for Speech Communication.

This paper briefly reviews current silent speech methodologies for normal and disabled individuals. Current techniques utilizing electromyographic (EMG) recordings of vocal tract movements are useful for physically healthy individuals but fail for tetraplegic individuals who do not have accurate voluntary control over the speech articulators. Alternative methods utilizing EMG from other body parts (e.

A wireless brain-machine interface for real-time speech synthesis.

Background: Brain-machine interfaces (BMIs) involving electrodes implanted into the human cerebral cortex have recently been developed in an attempt to restore function to profoundly paralyzed individuals. Current BMIs for restoring communication can provide important capabilities via a typing process, but unfortunately they are only capable of slow communication rates. In the current study we use a novel approach to speech restoration in which we decode continuous auditory parameters for a real-time speech synthesizer from neuronal activity in motor cortex during attempted speech.

Computer control using human intracortical local field potentials.

We describe the use of human cortical control signals to operate two assistive technology tools--a virtual keyboard speller and a computer-simulated digit. The cortical signals used for control are local field potentials recorded through an implanted neurotrophic electrode. In this system, the patients' cortical signals are transmitted wirelessly to a receiver and translated by computer software into either a computer cursor movement (for the virtual keyboard) or flexion of a cyber digit on a virtual hand.