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公开(公告)号：US11491071B2
公开(公告)日：2022-11-08
申请号：US16907182
申请日：2020-06-20
Applicant: SOUTHEAST UNIVERSITY
Inventor： Aiguo Song , Ke Shi , Hong Zeng , Huijun Li , Baoguo Xu , Xinyu Tang
Abstract: A virtual scene interactive rehabilitation training robot based on a lower limb connecting rod model and force sense information and a control method thereof are disclosed. The thigh, calf and foot of a leg of a human body are equated to a three-connecting rod series-connected mechanical arm. A human body leg gravity compensation model is constructed. The leg posture of a patient is detected by Kinect. An interaction force between a limb of the patient and a rehabilitation robot is detected by a force sensor on the rehabilitation robot. Then, a progressive rehabilitation training method is designed for the model. According to a set weight reduction ratio, the motion of the rehabilitation robot is controlled by judging plantar force data.
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2.发明授权公开(公告)号：US12269161B2
公开(公告)日：2025-04-08
申请号：US17628753
申请日：2020-06-03
Applicant: Southeast University
Inventor： Aiguo Song , Xuhui Hu , Zhikai Wei , Huijun Li , Baoguo Xu , Hong Zeng
Abstract: Provided are a multi-degree-of-freedom myoelectric artificial hand control system and a method for using same. The system comprises a robotic hand, a robotic wrist (2), a stump receiving cavity (1) and a data processor (3), wherein the robotic hand and the stump receiving cavity (1) are respectively mounted on two ends of the robotic wrist (2); a multi-channel myoelectric array electrode oversleeve, a control unit circuit board, and a battery are connected in the stump receiving cavity (1); and the other end of the control unit circuit board is connected to the robotic hand and the robotic wrist (2). The method for using the system comprises the following steps: (S1) a user wearing a multi-channel myoelectric array electrode oversleeve, and connecting a battery and a control unit circuit board; (S2) the user completing a gesture, collecting a surface electromyography signal and then uploading same to a data processor (3); (S3) the data processor (3) receiving the surface electromyography signal and inputting same into a neural network algorithm to generate a gesture prediction model; and (S4) the user controlling the multi-degree-of-freedom movement of the robotic wrist (2) and the robotic hand. By means of the system, continuous gestures and the gesture strength thereof can be identified, and multi-degree-of-freedom gestures can be made.
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公开(公告)号：US12083064B2
公开(公告)日：2024-09-10
申请号：US17311325
申请日：2020-06-28
Applicant: SOUTHEAST UNIVERSITY
Inventor： Aiguo Song , Jianwei Lai , Huijun Li , Jianqing Li , Baoguo Xu , Hong Zeng , Jun Zhang
IPC: A61H1/02
CPC classification number: A61H1/0288 , A61H2201/1207 , A61H2201/165 , A61H2201/1659
Abstract: A exoskeleton finger rehabilitation training device includes an exoskeleton finger rehabilitation training mechanism including a supporting base, a finger sleeve actuating mechanism, and a finger joint sleeve connected to a power output end of the finger sleeve actuating mechanism, wherein the finger joint sleeve can be sheathed at the periphery of a finger joint to be rehabilitated, and the finger joint sleeve can be driven by the power actuation of the finger sleeve actuating mechanism to drive the finger joint to be rehabilitated in order to passively bend or stretch; the supporting base includes a profiled shell, with an inner surface of the profiled shell being configured based on the profile of the complete back of a palm or part of the back of the palm, and with the back of the profiled shell being provided with a power fixed base.
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公开(公告)号：US11379039B2
公开(公告)日：2022-07-05
申请号：US16977751
申请日：2019-03-21
Applicant: SOUTHEAST UNIVERSITY
Inventor： Aiguo Song , Wenbin Zhang , Hong Zeng , Baoguo Xu
Abstract: Brain-computer interface method and system include displaying and providing a motor imagery task to a subject, and collecting a generated digital electroencephalogram signal; reading the digital electroencephalogram signal, performing interception if a preset time period is exceeded, and performing continuous reading if not; performing band-pass filtering, obtaining time-frequency characteristics of the digital electroencephalogram signal, and extracting a frequency value with highest frequency energy as a main frequency; obtaining an instantaneous phase of the digital electroencephalogram signal; generating predicted sine waves by respectively using the main frequency and the instantaneous phase as a frequency and an initial phase of sine waves, and predicting and obtaining real-time phase information; and judging whether the real-time phase is in a vibration stimulation application phase interval, generating and outputting a control instruction, and controlling a vibration motor to vibrate and to stimulate a sensory channel of the subject according to the control instruction.
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公开(公告)号：US10994416B2
公开(公告)日：2021-05-04
申请号：US16954207
申请日：2018-05-23
Applicant: SOUTHEAST UNIVERSITY
Inventor： Aiguo Song , Ke Shi , Xinyu Tang , Huijun Li , Baoguo Xu , Hong Zeng
IPC: G06F17/00 , B25J9/16 , A61B5/11 , B25J13/08 , B25J13/02 , G05B19/4155 , G16H20/30 , G16H40/63 , A61B90/00
Abstract: A method for controlling a limb motion intention recognizing and rehabilitation training robot based on force sense information includes: acquiring data of a three-dimensional force and a three-dimensional moment by a six-dimensional force sensor held in a hand; calculating forces and moments produced by a palm, a forearm and an upper arm of a human body according to a constructed human arm model to achieve recognition of limb motion intention; fixing the six-dimensional force sensor on a rocker at an end of the three-degree-of-freedom upper limb rehabilitation training robot, acquiring motion intention of an arm of the human body according to the motion intention recognition method, and controlling the rehabilitation training robot to achieve auxiliary active training under a weak active force.
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Patent Agency Ranking
公开(公告)号：US12057224B2
公开(公告)日：2024-08-06
申请号：US18031152
申请日：2022-07-25
Applicant: SOUTHEAST UNIVERSITY
Inventor： Hong Zeng , Qingqing Chen , Xiao Li , Yinxin Duan , Jianxi Zhang , Aiguo Song
CPC classification number: G16H40/63 , A61H1/0274 , G05B13/027 , A61H2201/1659 , A61H2201/5007 , A61H2230/605
Abstract: An adaptive control method and system for an upper limb rehabilitation robot based on a game theory and surface Electromyography (sEMG) is disclosed. A movement trajectory that a robot is controlled to run within a training time is designed during subject operation. An sEMG-based Back Propagation Neural Network (BPNN) muscle force estimation model establishes a nonlinear dynamic relationship between an sEMG signal and end force by constructing a three-layer neural network. A human-computer interaction system is analyzed by the game theory principle, and a role of the robot is deduced. The control rate between the robot and a subject is updated by Nash equilibrium, and adaptive weight factors of the robot and the subject are determined. The robot adaptively adjusts the training mode thereof according to a movement intention of the subject during operation and a weight coefficient obtained by the game theory principle.
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公开(公告)号：US11717461B2
公开(公告)日：2023-08-08
申请号：US17293448
申请日：2019-03-21
Applicant: SOUTHEAST UNIVERSITY
Inventor： Aiguo Song , Jianwei Lai , Huijun Li , Hong Zeng , Baoguo Xu
IPC: A61H1/02
CPC classification number: A61H1/0288 , A61H2201/018 , A61H2201/1207 , A61H2201/1463 , A61H2201/5061
Abstract: A palm-supported finger rehabilitation training device comprises a mounting base, a finger rehabilitation training mechanism mounted on the mounting base, and a driving mechanism for driving the finger rehabilitation training mechanism; wherein the finger rehabilitation training mechanism comprises four independent and structurally identical combined transmission devices for finger training corresponding to a forefinger, a middle finger, a ring finger and a little finger of a human hand, respectively, and the mounting base is provided with a supporting surface capable of supporting a human palm; wherein each combined transmission device for finger training comprises an MP movable chute, a PIP fingerstall, a DIP fingerstall and a connecting rod transmission mechanism; a force sensor is provided to acquire force feedback information to determine and control force stability, and a space sensor is provided to acquire space angle information to control space positions of fingers in real time.
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公开(公告)号：US11607815B2
公开(公告)日：2023-03-21
申请号：US17609446
申请日：2021-01-29
Applicant: SOUTHEAST UNIVERSITY
Inventor： Aiguo Song , Bincheng Shao , Huijun Li , Hong Zeng , Baoguo Xu
Abstract: The present invention provides a two-degree-of-freedom rope-driven finger force feedback device. The two-degree-of-freedom rope-driven finger force feedback device includes a hand support mechanism, a thumb movement mechanism, an index finger movement mechanism, and a handle mechanism. The hand support mechanism includes a motor, a motor shaft sleeve, a sliding rail, and an inertial measurement unit (IMU) sensor. The thumb movement mechanism includes a long rotary disc, a torque sensor, an angle sensor, a thumb sleeve, a pressure sensor, two links, a thumb brace, and a thumb fixing ring. The handle mechanism includes a cylindrical handle, a pressure sensor, a flexible fixing band, and a slider. Torque is driven between the rotary disc and the motor by using a rope. The handle mechanism is movable forward and backward and is capable of automatic restoration. By means of the present invention, the problems of the high costs of a conventional finger force feedback device and the unadjustable characteristic of the conventional finger force feedback device are overcome. The device can be tightly worn and has a self-adaptive degree of freedom. Rope driving can ensure a gentle, smooth, and real feedback force. By means of the mounted sensors, information such as a hand posture, a rotation angle and a grip force of a thumb and an index finger, and a contact force of a middle finger can be transmitted in real time.
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公开(公告)号：US11278464B2
公开(公告)日：2022-03-22
申请号：US17416468
申请日：2019-03-21
Applicant: SOUTHEAST UNIVERSITY
Inventor： Aiguo Song , Jianwei Lai , Huijun Li , Jianqing Li , Baoguo Xu , Hong Zeng , Jun Zhang
Abstract: An exoskeleton finger rehabilitation training apparatus includes a housing. A first motor and a second motor are disposed inside the housing. A direction of an output shaft of the first motor is opposite to a direction of an output shaft of the second motor. The output shaft of the first motor is provided with a first motor gear. A right side of the first motor gear is engaged with a first transmission gear. An edge of the first transmission gear is sequentially connected to an index finger sleeve and a middle finger sleeve that are axially arranged. The output shaft of the second motor is provided with a second motor gear. A right side of the second motor gear is engaged with a second transmission gear. An edge of the second transmission gear is sequentially connected to a pinky sleeve and a ring finger sleeve that are axially arranged.
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公开(公告)号：US10698476B2
公开(公告)日：2020-06-30
申请号：US16467984
申请日：2018-05-23
Applicant: SOUTHEAST UNIVERSITY
Inventor： Aiguo Song , Huanhuan Qin , Huijun Li , Baoguo Xu , Hong Zeng
Abstract: The present invention discloses a minitype haptic rendering method based on active and passive devices, which comprises the following steps of: firstly, calibrating a magnetorheological damper and a direct current motor, and obtaining a relationship between an input current and an output torque; converting an expected force/torque value to a current input of the magnetorheological damper, outputting a corresponding torque through the magnetorheological damper, and applying the torque to a body of an operator through a haptic transmission device; secondly, measuring an actually applied force/torque by a sensor mounted at a force/torque application point, comparing an actually outputted force/torque value with the expected force/torque value, and calculating a force/torque error; and finally, converting the force/torque error to an input signal of the direct current motor, and driving the direct current motor to generate a torque corresponding to the error.
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