California Institute of Technology

Lucent Technologies Inc.

Bijan Pesaran

Richard A Andersen

Partha Pratim Mitra

Joel W Burdick

Krishna V Shenoy

Daniella Meeker

Michael Sean Fee

Shiyan Cao

Ching Elizabeth Ho

Prosthetic devices, methods and systems are disclosed. Eye position and/or neural activity of a primate are recorded and combined. The combination signal is compared with a predetermined signal. The result of the comparison step is used to actuate the prosthetic device.

Prosthetic devices and methods and systems related thereto

A prosthetic system may use a decoder to predict an intended action, such as a reach, from processed signals generated from measured neural activity. The decoder may included a cognitive state machine, which transitions between cognitive states based on transition rules.

Cognitive state machine for prosthetic systems

In an embodiment, neural activity of a subject may be measured with an implant in the sensory motor cortex of the subject and used to predict an intended movement. The measured neural activity may be the local field potential (LFP) at an electrode or single unit (SU) activity. The spectral structure of the LFP and the SU activity may be estimated using spectral analysis techniques. The estimated LFP and SU responses may be used to predict and intended movement by the subject.

Neural prosthetic using temporal structure in the local field potential

A technique for obtaining an intermediate set of frequency dependant features from a speech signal for use in speech processing and in obtaining estimates of speech pitch. The technique utilizes multiple tapers derived from Slepian sequences to obtain a product of the speech signal and the Slepian functions. Multiple tapered Fourier transforms are then obtained from the product, from which the set of frequency dependent features are calculated. In a preferred embodiment, a derivative of the cepstrum of the speech signal is used as an estimate of speech signal pitch. In another preferred embodiment, the F-spectrum is calculated from the product and the F-cepstrum is obtained therefrom by calculating the Fourier transform of the smoothed derivative of the log of the F-spectrum. The maximum of the F-cepstrum also provides a pitch estimation.

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Los Angeles, CA, United States of America

Bijan Pesaran