Daniel D Morris

US Patent:

7751877, Jul 6, 2010

Filed:

Nov 19, 2004

Appl. No.:

10/992111

Inventors:

J. Christopher Flaherty - Topsfield MA, US
L. Renée Capachione - Acton MA, US
Daniel S. Morris - Stanford CA, US
Abraham H. Caplan - Cambridge MA, US
Maryam Saleh - Providence RI, US
K. Shane Guillory - Salt Lake City UT, US

Assignee:

BrainGate Co., LLC - Ponte Vedra Beach FL

International Classification:

A61B 5/00

US Classification:

600544

Abstract:

A system and method for a neural interface system with a unique identification code includes a sensor including a plurality of electrodes to detect multicellular signals, an processing unit to process the signals from the sensor into a suitable control signal for a controllable device such as a computer or prosthetic limb. The unique identification code is embedded in one or more discrete components of the system. Internal and external system checks for compatibility and methods of ensuring safe and effective performance of a system with detachable components are also disclosed.

US Patent:

7991461, Aug 2, 2011

Filed:

Dec 23, 2005

Appl. No.:

11/315225

Inventors:

J. Christopher Flaherty - Topsfield MA, US
Mijail D. Serruya - Providence RI, US
Daniel S. Morris - Stanford CA, US
Abraham H. Caplan - Cambridge MA, US
Maryam Saleh - Chicago IL, US
John P. Donoghue - Providence RI, US

Assignee:

BrainGate Co., LLC - Ponte Vedra Beach FL

International Classification:

A61B 5/04

US Classification:

600545, 600544

Abstract:

Various embodiments of a biological interface system and related methods are disclosed. The system may comprise a sensor comprising a plurality of electrodes for detecting multicellular signals emanating from one or more living cells of a patient and a processing unit configured to receive the multicellular signals from the sensor and process the multicellular signals to produce a processed signal. The processing unit may be configured to transmit the processed signal to a controlled device that is configured to receive the processed signal. The system is configured to perform an integrated patient training routine to generate one or more system configuration parameters that are used by the processing unit to produce the processed signal.

US Patent:

20050273890, Dec 8, 2005

Filed:

Aug 2, 2005

Appl. No.:

11/194544

Inventors:

J. Flaherty - Topsfield MA, US
L. Capachione - Acton MA, US
Daniel Morris - Stanford CA, US
Abraham Caplan - Cambridge MA, US
Maryam Saleh - Providence RI, US
K. Guillory - Salt Lake City UT, US

International Classification:

B25J011/00
G06K009/46

US Classification:

901050000

Abstract:

A system and method for a neural interface system with a unique identification code includes a sensor including a plurality of electrodes to detect multicellular signals, an processing unit to process the signals from the sensor into a suitable control signal for a controllable device such as a computer or prosthetic limb. The unique identification code is embedded in one or more discrete components of the system. Internal and external system checks for compatibility and methods of ensuring safe and effective performance of a system with detachable components are also disclosed.

US Patent:

20060253166, Nov 9, 2006

Filed:

Dec 23, 2005

Appl. No.:

11/315254

Inventors:

J. Flaherty - Topsfield MA, US
Mijail Serruya - Providence RI, US
Daniel Morris - Stanford CA, US
Abraham Caplan - Cambridge MA, US
Maryam Saleh - Chicago IL, US
John Donoghue - Providence RI, US

International Classification:

A61N 1/36

US Classification:

607048000

Abstract:

Various embodiments of a biological interface system and related methods are disclosed. The system may comprise a sensor comprising a plurality of electrodes for detecting multicellular signals emanating from one or more living cells of a patient and a processing unit configured to receive the multicellular signals from the sensor and process the multicellular signals to produce a processed signal. The processing unit may be configured to transmit the processed signal to a controlled device that is configured to receive the processed signal. The system is configured to perform an integrated patient training routine to provide a time varying stimulus to the patient and to generate one or more system configuration parameters used by the processing unit to produce the processed signal.

US Patent:

20070032738, Feb 8, 2007

Filed:

Dec 23, 2005

Appl. No.:

11/315226

Inventors:

J. Flaherty - Topsfield MA, US
Mijail Serruya - Providence RI, US
Daniel Morris - Stanford CA, US
Abraham Caplan - Cambridge MA, US
Maryam Saleh - Chicago IL, US
John Donoghue - Providence RI, US

International Classification:

A61B 5/04

US Classification:

600545000

Abstract:

Various embodiments of a biological interface system and related methods are disclosed. The system may comprise a sensor comprising a plurality of electrodes for detecting multicellular signals emanating from one or more living cells of a patient and a processing unit configured to receive the multicellular signals from the sensor and process the multicellular signals to produce a processed signal. The processing unit may be configured to transmit the processed signal to a controlled device that is configured to receive the processed signal. The system is configured to perform an integrated patient training routine to generate one or more system configuration parameters that are used by the processing unit to produce the processed signal.

US Patent:

6240198, May 29, 2001

Filed:

Apr 13, 1998

Appl. No.:

9/059478

Inventors:

James Matthew Rehg - Arlington MA
Daniel D. Morris - Pittsburgh PA

Assignee:

Compaq Computer Corporation - Houston TX

International Classification:

G06K 900

US Classification:

382103

Abstract:

In a computerized method, a moving articulated figure is tracked in a sequence of 2-D images measured by a monocular camera. The images are individually registered with each other using a 2-D scaled prismatic model of the figure. The 2-D model includes a plurality of links connected by revolute joints to form is a branched, linear-chain of connected links. The registering produces a state trajectory for the figure in the sequence of images. During a reconstructing step, a 3-D model is fitted to the state trajectory to estimate kinematic parameters, and the estimated kinematic parameters are refined using an expectation maximization technique.

US Patent:

62564188, Jul 3, 2001

Filed:

Apr 13, 1998

Appl. No.:

9/059194

Inventors:

James Matthew Rehg - Arlington MA
Daniel D. Morris - Pittsburgh PA

Assignee:

Compaq Computer Corporation - Houston TX

International Classification:

G06K 936
G06K 9646

US Classification:

382236

Abstract:

A computerized method compresses an input sequence of 2-D images captured by a monocular camera. The input sequence of images includes a moving articulated 3-D figure. A pose of the figure in each image is registered using a 2-D scaled prismatic model to produce a state trajectory for the figure in each image of the input sequence. The state trajectory of the figure in the images is reconstructed to determine kinematic parameters of a 3-D kinematic model that best fit the state trajectories, The 3-D kinematic model represents the 3-D movement of the figure in the input sequence of 2-D images. Static information of a first image of the input sequence is encoded. For subsequent images of the input sequence, a time series of state vectors containing the kinematic parameters of the moving figure are encoded. The static information of the first image and the time series of state vectors can be used to generate an output sequence of images including the moving articulated 3-D figure on a viewing device.

US Patent:

62691724, Jul 31, 2001

Filed:

Apr 13, 1998

Appl. No.:

9/059651

Inventors:

James Matthew Rehg - Arlington MA
Daniel D. Morris - Pittsburgh PA

Assignee:

Compaq Computer Corporation - Houston TX

International Classification:

G06K 900

US Classification:

382103

Abstract:

In a computerized method, a moving articulated figure is tracked in a sequence of 2-D images measured by a monocular camera. The images are individually registered with each other using a 2-D scaled prismatic model of the figure. The 2-D model includes a plurality of links connected by revolute joints to form is a branched, linear-chain of connected links. The registering produces a state trajectory for the figure in the sequence of images. During a reconstructing step, a 3-D model is fitted to the state trajectory to estimate kinematic parameters, and the estimated kinematic parameters are refined using an expectation maximization technique.