Patents by Inventor Tudor Giurgica-Tiron

Tudor Giurgica-Tiron has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20230218202
    Abstract: A system comprising a plurality of neuromuscular sensors, each of which is configured to record a time-series of neuromuscular signals from a surface of a user's body; and at least one computer hardware processor programmed to perform: applying a source separation technique to the time series of neuromuscular signals recorded by the plurality of neuromuscular sensors to obtain a plurality of neuromuscular source signals and corresponding mixing information; providing features, obtained from the plurality of neuromuscular source signals and/or the corresponding mixing information, as input to a trained statistical classifier and obtaining corresponding output; and identifying, based on the output of the trained statistical classifier, and for each of one or more of the plurality of neuromuscular source signals, an associated set of one or more biological structures.
    Type: Application
    Filed: March 21, 2023
    Publication date: July 13, 2023
    Inventors: Patrick Kaifosh, Tudor Giurgica-Tiron, Timothy Machado, Thomas Reardon, Erik Schomburg
  • Patent number: 11635736
    Abstract: A system comprising a plurality of neuromuscular sensors, each of which is configured to record a time-series of neuromuscular signals from a surface of a user's body; and at least one computer hardware processor programmed to perform: applying a source separation technique to the time series of neuromuscular signals recorded by the plurality of neuromuscular sensors to obtain a plurality of neuromuscular source signals and corresponding mixing information; providing features, obtained from the plurality of neuromuscular source signals and/or the corresponding mixing information, as input to a trained statistical classifier and obtaining corresponding output; and identifying, based on the output of the trained statistical classifier, and for each of one or more of the plurality of neuromuscular source signals, an associated set of one or more biological structures.
    Type: Grant
    Filed: October 19, 2018
    Date of Patent: April 25, 2023
    Assignee: Meta Platforms Technologies, LLC
    Inventors: Patrick Kaifosh, Tudor Giurgica-Tiron, Timothy Machado, Thomas Reardon, Erik Schomburg
  • Patent number: 11587242
    Abstract: System and methods are provided for providing a dynamically-updated musculoskeletal representation of a hand. The system includes a plurality of neuromuscular 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 and temporally smooth in real-time an output of the trained statistical model. The system is also programmed to determine, based on the smoothed output of the trained statistical model, position information describing a spatial relationship between two or more connected segments of the musculoskeletal representation, force information describing a force exerted by at least one segment of the musculoskeletal representation, and update the musculoskeletal representation of the hand based, at least in part, on the position information and the force information.
    Type: Grant
    Filed: August 20, 2021
    Date of Patent: February 21, 2023
    Assignee: Meta Platforms Technologies, LLC
    Inventors: Tudor Giurgica-Tiron, Adam Al-natsheh, Nathan Danielson
  • Publication number: 20220164691
    Abstract: This disclosure relates to enhanced methods of operating quantum computing systems to perform amplitude estimation. More than that, the methods may be tuned to accommodate for specific noise levels (e.g., in given a quantum device). Embodiments also enable quantum computing systems to perform amplitude estimation faster than amplitude estimation algorithms performed using a classical (non-quantum) computer.
    Type: Application
    Filed: November 22, 2021
    Publication date: May 26, 2022
    Inventors: Tudor Giurgica-Tiron, Farrokh Labib, Iordanis Kerenidis, Anupam Prakash, William Joseph Zeng
  • Patent number: 11331045
    Abstract: The disclosed systems and methods are generally directed to interpreting neuromuscular signals. The system includes (A) a plurality of neuromuscular sensors that detect a plurality of neuromuscular signals from a user and (B) at least one multiplexer in communication with the plurality of neuromuscular sensors and that is capable of dynamically adjusting neuromuscular sensor processing based on neuromuscular signal characteristics. A computer processor is programmed to (i) receive a set of neuromuscular signals from the plurality of neuromuscular sensors, (ii) determine, via a real-time system, at least one signal characteristic included in a neuromuscular signal, where the neuromuscular signal is associated with a first neuromuscular sensor included in the plurality of neuromuscular sensors; and (iii) dynamically reconfigure the processing of neuromuscular signals from the plurality of neuromuscular sensors based on an output from the multiplexer.
    Type: Grant
    Filed: April 29, 2020
    Date of Patent: May 17, 2022
    Assignee: Facebook Technologies, LLC
    Inventors: Anthony D. Moschella, Daniel Wetmore, Patrick Kaifosh, Adam Al-natsheh, Tudor Giurgica-Tiron, Qiushi Mao
  • Patent number: 11163361
    Abstract: Methods and apparatus for calibrating performance of one or more statistical models used to generate a musculoskeletal representation. The method comprises controlling presentation of instructions via a user interface to instruct the user to perform the at least one gesture and updating at least one parameter of the one or more statistical models based, at least in part on a plurality of neuromuscular signals recorded by a plurality of neuromuscular sensors during performance of the at least one gesture by the user.
    Type: Grant
    Filed: October 31, 2019
    Date of Patent: November 2, 2021
    Assignee: Facebook Technologies, LLC
    Inventors: Patrick Kaifosh, Tudor Giurgica-Tiron, Adam Berenzweig, Steven Kober, Adam Al-natsheh, Alexandre Barachant, Zhuo Wang
  • Patent number: 11127143
    Abstract: System and methods are provided for providing a dynamically-updated musculoskeletal representation of a hand. The system includes a plurality of neuromuscular 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 and temporally smooth in real-time an output of the trained statistical model. The system is also programmed to determine, based on the smoothed output of the trained statistical model, position information describing a spatial relationship between two or more connected segments of the musculoskeletal representation, force information describing a force exerted by at least one segment of the musculoskeletal representation, and update the musculoskeletal representation of the hand based, at least in part, on the position information and the force information.
    Type: Grant
    Filed: October 1, 2019
    Date of Patent: September 21, 2021
    Assignee: Facebook Technologies, LLC
    Inventors: Tudor Giurgica-Tiron, Adam Al-natsheh, Nathan Danielson
  • Patent number: 11069148
    Abstract: Method and apparatus for rendering a visual representation based on a musculoskeletal representation. The method comprises updating the musculoskeletal representation based, at least in part, on a plurality of neuromuscular signals recorded from a user, wherein the musculoskeletal representation is updated based at least in part on: position information describing a spatial relationship between two or more connected segments of the musculoskeletal representation, and force information describing a force exerted by at least one segment of the musculoskeletal representation, and rendering, via a user interface, the visual representation based on the updated musculoskeletal representation, wherein the visual representation includes a visual indication of the position information and a visual indication of the force information.
    Type: Grant
    Filed: January 25, 2019
    Date of Patent: July 20, 2021
    Assignee: Facebook Technologies, LLC
    Inventors: Tudor Giurgica-Tiron, Adam Berenzweig, Attila Maczak, Michael Astolfi, Mason Remaley
  • Patent number: 10950047
    Abstract: Methods and apparatus for anonymizing neuromuscular signals used to generate a musculoskeletal representation. The method comprises recording, using a plurality of neuromuscular sensors arranged on one or more wearable devices, a plurality of neuromuscular signals from a user, providing as input to a trained statistical model, the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals; and generating, the musculoskeletal representation based, at least in part, on an output of the trained statistical model, wherein the musculoskeletal representation is an anonymized musculoskeletal representation from which at least one personal characteristic of the user has been removed.
    Type: Grant
    Filed: October 16, 2019
    Date of Patent: March 16, 2021
    Assignee: Facebook Technologies, LLC
    Inventors: Patrick Kaifosh, Tudor Giurgica-Tiron, Steven Kober, Adam Al-natsheh, Alexandre Barachant
  • Patent number: 10817795
    Abstract: Methods and systems for dynamically reconstructing handstate information based on multiple inputs are described. The methods and systems use data from multiple inputs including a plurality of neuromuscular sensors arranged on one or more wearable devices and one or more cameras. The multimodal data is provided as input to a trained statistical model. The methods and systems determine, based on the data from the multiple inputs, an estimate and representation of the spatial relationship between two or more connected segments of the musculoskeletal representation and force information describing a force exerted by at least one segment of the musculoskeletal representation. The methods and systems further update the computerized musculoskeletal representation based, at least in part, on the position information and the force information.
    Type: Grant
    Filed: January 25, 2019
    Date of Patent: October 27, 2020
    Assignee: Facebook Technologies, LLC
    Inventors: Patrick Kaifosh, Tudor Giurgica-Tiron, Brett Jurman
  • Publication number: 20200125172
    Abstract: Methods and apparatus for calibrating performance of one or more statistical models used to generate a musculoskeletal representation. The method comprises controlling presentation of instructions via a user interface to instruct the user to perform the at least one gesture and updating at least one parameter of the one or more statistical models based, at least in part on a plurality of neuromuscular signals recorded by a plurality of neuromuscular sensors during performance of the at least one gesture by the user.
    Type: Application
    Filed: October 31, 2019
    Publication date: April 23, 2020
    Applicant: CTRL-labs Corporation
    Inventors: Patrick Kaifosh, Tudor Giurgica-Tiron, Adam Berenzweig, Steven Kober, Adam Al-natsheh, Alexandre Barachant, Zhuo Wang
  • Publication number: 20200118334
    Abstract: Methods and apparatus for anonymizing neuromuscular signals used to generate a musculoskeletal representation. The method comprises recording, using a plurality of neuromuscular sensors arranged on one or more wearable devices, a plurality of neuromuscular signals from a user, providing as input to a trained statistical model, the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals; and generating, the musculoskeletal representation based, at least in part, on an output of the trained statistical model, wherein the musculoskeletal representation is an anonymized musculoskeletal representation from which at least one personal characteristic of the user has been removed.
    Type: Application
    Filed: October 16, 2019
    Publication date: April 16, 2020
    Applicant: CTRL-labs Corporation
    Inventors: Patrick Kaifosh, Tudor Giurgica-Tiron, Steven Kober, Adam Al-natsheh, Alexandre Barachant
  • Publication number: 20200034978
    Abstract: System and methods are provided for providing a dynamically-updated musculoskeletal representation of a hand. The system includes a plurality of neuromuscular 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 and temporally smooth in real-time an output of the trained statistical model. The system is also programmed to determine, based on the smoothed output of the trained statistical model, position information describing a spatial relationship between two or more connected segments of the musculoskeletal representation, force information describing a force exerted by at least one segment of the musculoskeletal representation, and update the musculoskeletal representation of the hand based, at least in part, on the position information and the force information.
    Type: Application
    Filed: October 1, 2019
    Publication date: January 30, 2020
    Applicant: CTRL-labs Corporation
    Inventors: Tudor Giurgica-Tiron, Adam Al-natsheh, Nathan Danielson
  • Patent number: 10504286
    Abstract: Methods and apparatus for anonymizing neuromuscular signals used to generate a musculoskeletal representation. The method comprises recording, using a plurality of neuromuscular sensors arranged on one or more wearable devices, a plurality of neuromuscular signals from a user, providing as input to a trained statistical model, the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals; and generating, the musculoskeletal representation based, at least in part, on an output of the trained statistical model, wherein the musculoskeletal representation is an anonymized musculoskeletal representation from which at least one personal characteristic of the user has been removed.
    Type: Grant
    Filed: January 25, 2019
    Date of Patent: December 10, 2019
    Assignee: CTRL-labs Corporation
    Inventors: Patrick Kaifosh, Tudor Giurgica-Tiron, Steven Kober, Adam Al-natsheh, Alexandre Barachant
  • Patent number: 10496168
    Abstract: Methods and apparatus for calibrating performance of one or more statistical models used to generate a musculoskeletal representation. The method comprises controlling presentation of instructions via a user interface to instruct the user to perform the at least one gesture and updating at least one parameter of the one or more statistical models based, at least in part on a plurality of neuromuscular signals recorded by a plurality of neuromuscular sensors during performance of the at least one gesture by the user.
    Type: Grant
    Filed: January 25, 2019
    Date of Patent: December 3, 2019
    Assignee: CTRL-labs Corporation
    Inventors: Patrick Kaifosh, Tudor Giurgica-Tiron, Adam Berenzweig, Steven Kober, Adam Al-natsheh, Alexandre Barachant, Zhuo Wang
  • Patent number: 10460455
    Abstract: System and methods are provided for providing a dynamically-updated musculoskeletal representation of a hand. The system includes a plurality of neuromuscular 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 and temporally smooth in real-time an output of the trained statistical model. The system is also programmed to determine, based on the smoothed output of the trained statistical model, position information describing a spatial relationship between two or more connected segments of the musculoskeletal representation, force information describing a force exerted by at least one segment of the musculoskeletal representation, and update the musculoskeletal representation of the hand based, at least in part, on the position information and the force information.
    Type: Grant
    Filed: January 25, 2019
    Date of Patent: October 29, 2019
    Assignee: CTRL-labs Corporation
    Inventors: Tudor Giurgica-Tiron, Adam Al-natsheh, Nathan Danielson
  • Publication number: 20190223748
    Abstract: Methods and apparatus for mitigating neuromuscular signal artifacts are described. The method comprises detecting in real-time, by at least one computer processor, one or more artifacts in a plurality of neuromuscular signals recorded by a plurality of neuromuscular sensors, determining, based at least in part, on the detected one or more artifacts, a plurality of derived neuromuscular signals to mitigate the one or more artifacts, and providing, as input to one or more trained statistical models, the plurality of derived neuromuscular signals.
    Type: Application
    Filed: January 25, 2019
    Publication date: July 25, 2019
    Applicant: CTRL-labs Corporation
    Inventors: Adam Al-natsheh, Tudor Giurgica-Tiron, Qiushi Mao, Patrick Kaifosh
  • Publication number: 20190228579
    Abstract: Methods and apparatus for anonymizing neuromuscular signals used to generate a musculoskeletal representation. The method comprises recording, using a plurality of neuromuscular sensors arranged on one or more wearable devices, a plurality of neuromuscular signals from a user, providing as input to a trained statistical model, the plurality of neuromuscular signals and/or information based on the plurality of neuromuscular signals; and generating, the musculoskeletal representation based, at least in part, on an output of the trained statistical model, wherein the musculoskeletal representation is an anonymized musculoskeletal representation from which at least one personal characteristic of the user has been removed.
    Type: Application
    Filed: January 25, 2019
    Publication date: July 25, 2019
    Applicant: CTRL-labs Corporation
    Inventors: Patrick Kaifosh, Tudor Giurgica-Tiron, Steven Kober, Adam Al-natsheh, Alexandre Barachant
  • Publication number: 20190228591
    Abstract: Method and apparatus for rendering a visual representation based on a musculoskeletal representation. The method comprises updating the musculoskeletal representation based, at least in part, on a plurality of neuromuscular signals recorded from a user, wherein the musculoskeletal representation is updated based at least in part on: position information describing a spatial relationship between two or more connected segments of the musculoskeletal representation, and force information describing a force exerted by at least one segment of the musculoskeletal representation, and rendering, via a user interface, the visual representation based on the updated musculoskeletal representation, wherein the visual representation includes a visual indication of the position information and a visual indication of the force information.
    Type: Application
    Filed: January 25, 2019
    Publication date: July 25, 2019
    Applicant: CTRL-LABS Corporation
    Inventors: Tudor Giurgica-Tiron, Adam Berenzweig, Attila Maczak, Michael Astolfi, Mason Remaley
  • Publication number: 20190228330
    Abstract: Methods and systems for dynamically reconstructing handstate information based on multiple inputs are described. The methods and systems use data from multiple inputs including a plurality of neuromuscular sensors arranged on one or more wearable devices and one or more cameras. The multimodal data is provided as input to a trained statistical model. The methods and systems determine, based on the data from the multiple inputs, an estimate and representation of the spatial relationship between two or more connected segments of the musculoskeletal representation and force information describing a force exerted by at least one segment of the musculoskeletal representation. The methods and systems further update the computerized musculoskeletal representation based, at least in part, on the position information and the force information.
    Type: Application
    Filed: January 25, 2019
    Publication date: July 25, 2019
    Applicant: CTRL-labs Corporation
    Inventors: Patrick Kaifosh, Tudor Giurgica-Tiron, Brett Jurman