Patents by Inventor Erik Schomburg
Erik Schomburg 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).
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Publication number: 20230218202Abstract: 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: ApplicationFiled: March 21, 2023Publication date: July 13, 2023Inventors: Patrick Kaifosh, Tudor Giurgica-Tiron, Timothy Machado, Thomas Reardon, Erik Schomburg
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Patent number: 11635736Abstract: 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: GrantFiled: October 19, 2018Date of Patent: April 25, 2023Assignee: Meta Platforms Technologies, LLCInventors: Patrick Kaifosh, Tudor Giurgica-Tiron, Timothy Machado, Thomas Reardon, Erik Schomburg
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Patent number: 11337652Abstract: 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.Type: GrantFiled: July 25, 2017Date of Patent: May 24, 2022Assignee: Facebook Technologies, LLCInventors: Patrick Kaifosh, Timothy Machado, Thomas Reardon, Erik Schomburg, Calvin Tong
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Publication number: 20210405750Abstract: 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.Type: ApplicationFiled: April 12, 2021Publication date: December 30, 2021Inventors: Patrick Kaifosh, Timothy Machado, Thomas Reardon, Erik Schomburg
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Patent number: 11000211Abstract: 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.Type: GrantFiled: July 25, 2017Date of Patent: May 11, 2021Assignee: Facebook Technologies, LLCInventors: Patrick Kaifosh, Timothy Machado, Thomas Reardon, Erik Schomburg, Joshua Merel, Steven Demers
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Patent number: 10990174Abstract: 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.Type: GrantFiled: July 25, 2017Date of Patent: April 27, 2021Assignee: Facebook Technologies, LLCInventors: Patrick Kaifosh, Timothy Machado, Thomas Reardon, Erik Schomburg
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Patent number: 10656711Abstract: 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.Type: GrantFiled: July 30, 2019Date of Patent: May 19, 2020Assignee: Facebook Technologies, LLCInventors: Patrick Kaifosh, Timothy Machado, Thomas Reardon, Erik Schomburg
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Publication number: 20190354182Abstract: 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.Type: ApplicationFiled: July 30, 2019Publication date: November 21, 2019Applicant: CTRL-labs CorporationInventors: Patrick Kaifosh, Timothy Machado, Thomas Reardon, Erik Schomburg
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Patent number: 10409371Abstract: 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.Type: GrantFiled: July 25, 2017Date of Patent: September 10, 2019Assignee: CTRL-labs CorporationInventors: Patrick Kaifosh, Timothy Machado, Thomas Reardon, Erik Schomburg
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Publication number: 20190212817Abstract: 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.Type: ApplicationFiled: March 14, 2019Publication date: July 11, 2019Applicant: CTRL-labs CorporationInventors: Patrick Kaifosh, Timothy Machado, Thomas Reardon, Erik Schomburg
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Publication number: 20190121306Abstract: A method, comprising 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; aligning the plurality of neuromuscular source signals to a plurality of template neuromuscular source signals, the aligning comprising: determining, using a cost function, a distance between first features and second features, the first features obtained from the plurality of neuromuscular source signals and/or the corresponding mixing information, the second features obtained from the template neuromuscular source signals and/or corresponding template mixing information; and identifying, based on results of the aligning and for each of one or more of the plurality of neuromuscular source signals, an associated set of one or more biological structures.Type: ApplicationFiled: October 19, 2018Publication date: April 25, 2019Applicant: CTRL-labs CorporationInventors: Patrick Kaifosh, Tudor Giurgica-Tiron, Timothy Machado, Thomas Reardon, Erik Schomburg
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Publication number: 20190121305Abstract: 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: ApplicationFiled: October 19, 2018Publication date: April 25, 2019Applicant: CTRL-labs CorporationInventors: Patrick Kaifosh, Tudor Giurgica-Tiron, Timothy Machado, Thomas Reardon, Erik Schomburg
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Publication number: 20180020978Abstract: 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.Type: ApplicationFiled: July 25, 2017Publication date: January 25, 2018Inventors: Patrick Kaifosh, Timothy Machado, Thomas Reardon, Erik Schomburg, Calvin Tong
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Publication number: 20180024634Abstract: 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.Type: ApplicationFiled: July 25, 2017Publication date: January 25, 2018Inventors: Patrick Kaifosh, Timothy Machado, Thomas Reardon, Erik Schomburg
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Publication number: 20180020951Abstract: 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.Type: ApplicationFiled: July 25, 2017Publication date: January 25, 2018Inventors: Patrick Kaifosh, Timothy Machado, Thomas Reardon, Erik Schomburg, Joshua Merel, Steven Demers
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Publication number: 20180024635Abstract: 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.Type: ApplicationFiled: July 25, 2017Publication date: January 25, 2018Inventors: Patrick Kaifosh, Timothy Machado, Thomas Reardon, Erik Schomburg