公开(公告)号：US10716485B2

公开(公告)日：2020-07-21

申请号：US15521987

申请日：2015-11-09

Applicant: THE GENERAL HOSPITAL CORPORATION ,  MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Inventor： Pavitra Krishnaswamy ,  Patrick Purdon ,  Gabriel Obregon-Henao ,  Matti Hamalainen ,  Behtash Babadi

IPC: A61B5/0436 ,  A61B5/0476 ,  A61B5/055 ,  A61B5/00

Abstract: A method for non-invasively resolving electrophysiological activity in sub-cortical structures located deep in the brain by comparing amplitude-insensitive M/EEG field patterns arising from activity in subcortical and cortical sources under physiologically relevant sparse constraints is disclosed. The method includes a sparse inverse solution for M/EEG subcortical source modeling. Specifically, the method employs a subspace-pursuit algorithm rooted in compressive sampling theory, performs a hierarchical search for sparse subcortical and cortical sources underlying the measurement, and estimates millisecond-scale currents in these sources to explain the data. The method can be used to recover thalamic and brainstem contributions to non-invasive M/EEG data, and to enable non-invasive study of fast timescale dynamical and network phenomena involving widespread regions across the human brain.

公开(公告)号：US20170332933A1

公开(公告)日：2017-11-23

申请号：US15521987

申请日：2015-11-09

Applicant: THE GENERAL HOSPITAL CORPORATION ,  MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Inventor： Pavitra Krishnaswamy ,  Patrick Purdon ,  Gabriel Obregon-Henao ,  Matti Hamalainen ,  Behtash Babadi

IPC: A61B5/0436 ,  A61B5/0476 ,  A61B5/055 ,  A61B5/00

CPC classification number: A61B5/0436 ,  A61B5/0476 ,  A61B5/055 ,  A61B5/4064

Abstract: A method for non-invasively resolving electrophysiological activity in sub-cortical structures located deep in the brain by comparing amplitude-insensitive M/EEG field patterns arising from activity in subcortical and cortical sources under physiologically relevant sparse constraints is disclosed. The method includes a sparse inverse solution for M/EEG subcortical source modeling. Specifically, the method employs a subspace-pursuit algorithm rooted in compressive sampling theory, performs a hierarchical search for sparse subcortical and cortical sources underlying the measurement, and estimates millisecond-scale currents in these sources to explain the data. The method can be used to recover thalamic and brainstem contributions to non-invasive M/EEG data, and to enable non-invasive study of fast timescale dynamical and network phenomena involving widespread regions across the human brain.

公开(公告)号：US20130310979A1

公开(公告)日：2013-11-21

申请号：US13865840

申请日：2013-04-18

Applicant: Massachusetts Institute of Technology

Inventor： Hugh M. Herr ,  Ken Endo ,  Pavitra Krishnaswamy ,  Jared Markowitz ,  Michael Frederick Eilenberg ,  Jing Wang

IPC: B25J9/16

CPC classification number: B25J9/1694 ,  B62D57/032 ,  G05B2219/40324 ,  Y10S901/01

Abstract: A neuromuscular model-based controller for a robotic limb having at least one joint includes a neuromuscular model having a muscle model, muscle geometry and reflex feedback loop to determine at least one torque or impedance command to be sent to the robotic limb. One or more parameters that determine relation between feedback data and activation of the muscle model are adjusted consequent to sensory data from at least one of an intrinsic sensor and an extrinsic sensor. A controller in communication with the neuromuscular model is configured to receive the at least one torque or impedance command and controls at least one of position, torque and impedance of the robotic limb joint.

Abstract translation: 用于具有至少一个关节的机器人肢体的基于神经肌肉模型的控制器包括具有肌肉模型，肌肉几何形状和反射反馈回路的神经肌肉模型，以确定要发送到机器人肢体的至少一个扭矩或阻抗命令。 确定反馈数据与肌肉模型激活之间的关系的一个或多个参数是根据来自内部传感器和外在传感器中的至少一个的感觉数据进行调整的。 与神经肌肉模型通信的控制器被配置为接收至少一个扭矩或阻抗命令并且控制机器人肢体关节的位置，扭矩和阻抗中的至少一个。

公开(公告)号：US09975249B2

公开(公告)日：2018-05-22

申请号：US14978445

申请日：2015-12-22

Applicant: Massachusetts Institute of Technology

Inventor： Hugh M. Herr ,  Ken Endo ,  Pavitra Krishnaswamy ,  Jared Markowitz ,  Michael Frederick Eilenberg ,  Jing Wang

IPC: B25J9/16 ,  B62D57/032

CPC classification number: B25J9/1694 ,  B62D57/032 ,  G05B2219/40324 ,  Y10S901/01

Abstract: A neuromuscular model-based controller for a robotic limb having at least one joint includes a neuromuscular model having a muscle model, muscle geometry and reflex feedback loop to determine at least one torque or impedance command to be sent to the robotic limb. One or more parameters that determine relation between feedback data and activation of the muscle model are adjusted consequent to sensory data from at least one of an intrinsic sensor and an extrinsic sensor. A controller in communication with the neuromuscular model is configured to receive the at least one torque or impedance command and controls at least one of position, torque and impedance of the robotic limb joint.

公开(公告)号：US20160207201A1

公开(公告)日：2016-07-21

申请号：US14978445

申请日：2015-12-22

Applicant: Massachusetts Institute of Technology

Inventor： Hugh M. Herr ,  Ken Endo ,  Pavitra Krishnaswamy ,  Jared Markowitz ,  Michael Frederick Eilenberg ,  Jing Wang

IPC: B25J9/16 ,  B62D57/032

CPC classification number: B25J9/1694 ,  B62D57/032 ,  G05B2219/40324 ,  Y10S901/01

Abstract: A neuromuscular model-based controller for a robotic limb having at least one joint includes a neuromuscular model having a muscle model, muscle geometry and reflex feedback loop to determine at least one torque or impedance command to be sent to the robotic limb. One or more parameters that determine relation between feedback data and activation of the muscle model are adjusted consequent to sensory data from at least one of an intrinsic sensor and an extrinsic sensor. A controller in communication with the neuromuscular model is configured to receive the at least one torque or impedance command and controls at least one of position, torque and impedance of the robotic limb joint.

公开(公告)号：US09221177B2

公开(公告)日：2015-12-29

申请号：US13865840

申请日：2013-04-18

Applicant: Massachusetts Institute of Technology

Inventor： Hugh M. Herr ,  Ken Endo ,  Pavitra Krishnaswamy ,  Jared Markowitz ,  Michael Frederick Eilenberg ,  Jing Wang

IPC: B25J9/16 ,  B62D57/032

CPC classification number: B25J9/1694 ,  B62D57/032 ,  G05B2219/40324 ,  Y10S901/01

Abstract: A neuromuscular model-based controller for a robotic limb having at least one joint includes a neuromuscular model having a muscle model, muscle geometry and reflex feedback loop to determine at least one torque or impedance command to be sent to the robotic limb. One or more parameters that determine relation between feedback data and activation of the muscle model are adjusted consequent to sensory data from at least one of an intrinsic sensor and an extrinsic sensor. A controller in communication with the neuromuscular model is configured to receive the at least one torque or impedance command and controls at least one of position, torque and impedance of the robotic limb joint.

Abstract translation: 用于具有至少一个关节的机器人肢体的基于神经肌肉模型的控制器包括具有肌肉模型，肌肉几何形状和反射反馈回路的神经肌肉模型，以确定要发送到机器人肢体的至少一个扭矩或阻抗命令。 确定反馈数据与肌肉模型激活之间的关系的一个或多个参数是根据来自内部传感器和外部传感器中的至少一个的感觉数据进行调整的。 与神经肌肉模型通信的控制器被配置为接收至少一个扭矩或阻抗命令并且控制机器人肢体关节的位置，扭矩和阻抗中的至少一个。