Thomas J Reardon

US Patent:

20210405750, Dec 30, 2021

Filed:

Apr 12, 2021

Appl. No.:

17/228351

Inventors:

- Menlo Park CA, US
Timothy Machado - Palo Alto CA, US
Thomas Reardon - New York NY, US
Erik Schomburg - Brooklyn NY, US

International Classification:

G06F 3/01
G06F 3/0487
G06F 3/02

Abstract:

Methods and apparatus for providing a dynamically-updated computerized musculo-skeletal representation comprising a plurality of rigid body segments connected by joints. The method comprises recording, using a plurality of autonomous sensors arranged on one or more wearable devices, a plurality of autonomous signals from a user, wherein the plurality of autonomous sensors include a plurality of neuromuscular sensors configured to record neuromuscular signals. The method further comprises providing as input to a trained statistical model, the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals. The method further comprises determining, based on an output of the trained statistical model, musculo-skeletal position information describing a spatial relationship between two or more connected segments of the plurality of rigid body segments of the computerized musculo-skeletal representation, and updating the computerized musculo-skeletal representation based, at least in part, on the musculo-skeletal position information.

US Patent:

20200069210, Mar 5, 2020

Filed:

Aug 30, 2019

Appl. No.:

16/557383

Inventors:

- New York NY, US
Thomas Reardon - New York NY, US
Christopher Osborn - Brooklyn NY, US
Brett Jurman - New York NY, US
Daniel Wetmore - Brooklyn NY, US

Assignee:

CTRL-labs Corporation - New York NY

International Classification:

A61B 5/0488
A61B 5/04
A61B 90/00
A61B 5/00
G06F 3/01

Abstract:

Computerized systems, methods, and computer-readable storage media storing code for implementing the methods are described for providing dynamically-updated musculoskeletal information. One such system includes a processor is programmed to: provide, as an input to a trained inference model, information based on a plurality of neuromuscular signals from a user and information based on at least one image of the user; determine, based on an output of the trained inference model, position information describing a spatial relationship between two or more connected musculoskeletal segments of the user and/or force information describing a force exerted by at least one musculoskeletal segment of the user; and output the position information and/or the force information.

US Patent:

20200069211, Mar 5, 2020

Filed:

Aug 30, 2019

Appl. No.:

16/557427

Inventors:

- New York NY, US
Thomas Reardon - New York NY, US
Christopher Osborn - New York NY, US
Brett Jurman - New York NY, US
Daniel Wetmore - Brooklyn NY, US

Assignee:

CTRL-labs Corporation - New York NY

International Classification:

A61B 5/0488
G06F 3/01
A61B 5/00
A61B 90/00
A61B 5/04

Abstract:

Computerized systems, methods, and computer-readable storage media storing code for implementing the methods are provided for training an inference model used to generate a musculoskeletal representation. One such system includes a processor programmed to: determine, based on information obtained from at least one image, position information describing a spatial relationship between two or more connected musculoskeletal segments of a user; determine, based on a plurality of neuromuscular signals, force information; associate the position information with the force information; train an inference model to output a musculoskeletal representation consistent with the position information and/or the force information when neuromuscular input signals provided to the inference model have at least one predetermined characteristic, to produce an updated inference model; and cause the updated inference model to be stored in a memory.

US Patent:

20200073483, Mar 5, 2020

Filed:

Aug 30, 2019

Appl. No.:

16/557342

Inventors:

- New York NY, US
Thomas Reardon - New York NY, US
Christopher Osborn - Brooklyn NY, US
Brett Jurman - New York NY, US
Daniel Wetmore - Brooklyn NY, US

Assignee:

CTRL-labs Corporation - New York NY

International Classification:

G06F 3/01
G06K 9/00
G06K 9/62
G06T 7/70
G06N 20/00
G06N 5/04

Abstract:

Computerized systems, methods, and computer-readable storage media storing code for implementing the methods are provided, in which camera information is used to calibrate one or more inference models used to generate a musculoskeletal representation. One such system includes at least one camera configured to capture at least one image, a plurality of neuromuscular sensors configured to sense and record a plurality of neuromuscular signals from a user, and at least one computer processor. The plurality of neuromuscular sensors are arranged on one or more wearable devices structured to be worn by the user to obtain the plurality of neuromuscular signals. The at least one computer processor is programmed to calibrate the one or more inference models by updating at least one parameter associated with the one or more inference models based, at least in part, on the plurality of neuromuscular signals and the at least one image.

US Patent:

20190354182, Nov 21, 2019

Filed:

Jul 30, 2019

Appl. No.:

16/526401

Inventors:

- New York NY, US
Timothy Machado - Palo Alto CA, US
Thomas Reardon - New York NY, US
Erik Schomburg - Brooklyn NY, US

Assignee:

CTRL-labs Corporation - New York NY

International Classification:

G06F 3/01
A61B 5/0488
G06N 3/04
G06N 7/00
G06N 20/00
A61B 5/00

Abstract:

Methods and system for predicting the onset of a motor action using neuromuscular signals. The system comprises a plurality of sensors configured to continuously record a plurality of neuromuscular signals from a user and at least one computer processor programmed to provide as input to a trained statistical model, the plurality of neuromuscular signals or information based on the plurality of neuromuscular signals, predict, based on an output of the trained statistical model, whether an onset of a motor action will occur within a threshold amount of time; and send a control signal to at least one device based, at least in part, on the output probability, wherein the control signal is sent to the at least one device prior to completion of the motor action by the user.

US Patent:

20190212817, Jul 11, 2019

Filed:

Mar 14, 2019

Appl. No.:

16/353998

Inventors:

- New York NY, US
Timothy Machado - Palo Alto CA, US
Thomas Reardon - New York NY, US
Erik Schomburg - Brooklyn NY, US

Assignee:

CTRL-labs Corporation - New York NY

International Classification:

G06F 3/01

Abstract:

Methods and apparatus for providing a dynamically-updated computerized musculo-skeletal representation comprising a plurality of rigid body segments connected by joints. The method comprises recording, using a plurality of autonomous sensors arranged on one or more wearable devices, a plurality of autonomous signals from a user, wherein the plurality of autonomous sensors include a plurality of neuromuscular sensors configured to record neuromuscular signals. The method further comprises providing as input to a trained statistical model, the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals. The method further comprises determining, based on an output of the trained statistical model, musculo-skeletal position information describing a spatial relationship between two or more connected segments of the plurality of rigid body segments of the computerized musculo-skeletal representation, and updating the computerized musculo-skeletal representation based, at least in part, on the musculo-skeletal position information.

US Patent:

20180020951, Jan 25, 2018

Filed:

Jul 25, 2017

Appl. No.:

15/659487

Inventors:

Timothy Machado - Palo Alto CA, US
Thomas Reardon - New York NY, US
Erik Schomburg - Brooklyn NY, US
Joshua Merel - London, GB
Steven Demers - Manchester NH, US

International Classification:

A61B 5/11
A61B 5/00
A61B 5/04
A61B 5/0484

Abstract:

Methods and apparatus for adapting a control mapping associating sensor signals with control signals for controlling an operation of a device. The method comprises obtaining first state information for an operation of the device, providing the first state information as input to an intention model associated with an operation of the device and obtaining corresponding first intention model output, providing a plurality of neuromuscular signals recorded from a user and/or signals derived from the neuromuscular signals as inputs to a first control mapping and obtaining corresponding first control mapping output, and updating the first control mapping using the inputs provided to the first control mapping and the first intention model output to obtain a second control mapping.

US Patent:

20180020978, Jan 25, 2018

Filed:

Jul 25, 2017

Appl. No.:

15/659504

Inventors:

Timothy Machado - Palo Alto CA, US
Thomas Reardon - New York NY, US
Erik Schomburg - Brooklyn NY, US
Calvin Tong - Seattle WA, US

International Classification:

A61B 5/00
G01C 21/18
G06F 3/01

Abstract:

A method for determining spatial information for a multi-segment articulated rigid body system having at least an anchored segment and a non-anchored segment coupled to the anchored segment, each segment in the multi-segment articulated rigid body system representing a respective body part of a user, the method comprising: obtaining signals recorded by a first autonomous movement sensor coupled to a body part of the user represented by the non-anchored segment; providing the obtained signals as input to a trained statistical model and obtaining corresponding output of the trained statistical model; and determining, based on the corresponding output of the trained statistical model, spatial information for at least the non-anchored segment of the multi-segment articulated rigid body system. Determining the spatial information may include determining the position and/or orientation of the non-anchored segment relative to the anchor point and/or determining a spatial relationship between the anchored and non-anchored segments.