Abstract: A whisker sensor includes an upper circuit board, a lower circuit board, a flexible whisker, and a magnet. The magnet is fixed to the flexible whisker through a central through hole, and the location of the magnet changes with the swinging of the whisker; the upper and lower circuit boards are identical in shape and size, and are connected through an upright column. A circular hole is formed at the center of the upper circuit board, four Hall sensors are symmetrically distributed on the edge of the circular hole, and the displacement of the whisker in X and Y directions can be obtained by detecting the change in magnetic field generated by the change in location of the magnet; a contact sensor is mounted on the lower circuit board, and is connected to the whisker through a connecting piece, to detect displacement of the whisker in the Z direction.

Abstract: A natural human-computer interaction system based on multi-sensing data fusion comprises a MEMS anti tracking device, a visual tracking device, a force feedback device and a PC terminal. The MEMS arm tracking device is composed of three sets of independent MEMS sensors for collecting arm joint angle information and measuring an arm motion trajectory. The visual tracking device is composed of a binocular camera for collecting image information and measuring a finger motion trajectory. The force feedback device is mounted in a palm of an operator for providing a feedback force to the finger. The PC terminal comprises a data display module, an arm motion calculating module, an image processing module, a mechanics calculating module and a virtual scene rendering module. The system tracks the arm motion trajectory and the finger motion trajectory of the operator and provides force feedback interaction to the finger of the operator.

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

Abstract: A exoskeleton finger rehabilitation training device comprises an exoskeleton finger rehabilitation training mechanism comprising 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 comprises 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.

Abstract: The present invention discloses a care robot controller, which includes: a controller body that includes slide rails, finger slot sliders and a joystick, wherein the finger slot sliders are movably arranged on the slide rails and configured to receive pressing, and the joystick is configured to control the care robot; a gesture parsing unit configured to parse three-dimensional gestures of the controller body, and control the care robot to perform corresponding actions when the three-dimensional gestures of the controller body are in line with preset gestures; and a tactile sensing unit configured to sense the pressing received by the finger slot sliders and initiate a user mode corresponding to the pressing information, so that the controller body provides corresponding vibration feedback. Thus the user can control the controller efficiently and conveniently, the control accuracy is improved, and effective man-machine interaction is realized.

Abstract: A method for reducing hysteresis error and high frequency noise error of capacitive tactile sensors includes the following steps: step 1: calibration, specifically including positive stroke calibration to form n positive stroke curves and negative stroke calibration to form n negative stroke curves; step 2: averaging, specifically including positive stroke averaging to form an average positive stroke curve, negative stroke averaging to form an average negative stroke curve, and comprehensive averaging to form a comprehensive stroke curve; step 3: fitting modeling, to obtain a positive stroke fitting function, a negative stroke fitting function, and a comprehensive fitting function; step 4: measurement; step 5: noise filtering; step 6: stroke direction discrimination; and step 7: resolving, to obtain the force at the current time by using a corresponding fitting function based on the stroke direction discrimination result.

Abstract: A flexible finger-wearable haptic feedback device includes a fingertip sleeve sheathing a distal phalanx of a finger, a middle sleeve sheathing a middle phalanx of the finger, a proximal sleeve sheathing a proximal phalanx of the finger, outer and inner transmission rods having bending elasticity. The outer transmission rod is fixed on the fingertip sleeve at one end, positioned at a back of a hand at the other end and connected with an outer driver. The inner transmission rod is fixed on the fingertip sleeve at one end, positioned at a palm at the other end and connected with an inner driver. The fingertip sleeve is provided with first and second contact pressure sensors respectively connected with the ends of the outer and inner transmission rods, and an inner wall of the fingertip finger sleeve contacting the finger is provided with a film pressure sensor.

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.

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.

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.

Abstract: A wearable upper limb rehabilitation training robot with precise force control includes a wearable belt, a multi-degree-of-freedom robot arm, and a control box. The robot is worn on the waist of a person by using a belt, and driven by active actuators, to implement active and passive rehabilitation training in such degrees of freedom as adduction/abduction/anteflexion/extension of left and right shoulder joints and anteflexion/extension of left and right elbow joints. In addition, a force/torque sensor is mounted on a tip of the robot arm, to obtain a force between the tip of the robot arm and the human hand during rehabilitation training as a feedback signal, to adjust an operating state of the robot, thereby realizing the precise force control during the rehabilitation training.

Abstract: A robot system for active and passive upper limb rehabilitation training based on a force feedback technology includes a robot body and an active and passive training host computer system. Active and passive rehabilitation training may be performed at degrees of freedom such as adduction/abduction and flexion/extension of left and right shoulder joints, and flexion/extension of left and right elbow joints according to a condition of a patient. In a passive rehabilitation training mode, the robot body drives the upper limb of the patient to move according to a track specified by the host computer, to gradually restore a basic motion function of the upper limb. In an active rehabilitation training mode, the patient holds the tail ends of the robot body with both hands to interact with a rehabilitation training scene, and can feel real and accurate force feedback.

Abstract: A flexible finger-wearable haptic feedback device includes a fingertip sleeve sheathing a distal phalanx of a finger, a middle sleeve sheathing a middle phalanx of the finger, a proximal sleeve sheathing a proximal phalanx of the finger, outer and inner transmission rods having bending elasticity. The outer transmission rod is fixed on the fingertip sleeve at one end, positioned at a back of a hand at the other end and connected with an outer driver. The inner transmission rod is fixed on the fingertip sleeve at one end, positioned at a palm at the other end and connected with an inner driver. The fingertip sleeve is provided with first and second contact pressure sensors respectively connected with the ends of the outer and inner transmission rods, and an inner wall of the fingertip finger sleeve contacting the finger is provided with a film pressure sensor.

Abstract: The present invention discloses a six-dimensional force sensor with high sensitivity and low inter-dimensional coupling, including a clockwise or counterclockwise swastika-shaped beam, vertical beams, a rectangular outer frame, and strain gauges; the clockwise or counterclockwise swastika-shaped beam includes a cross-shaped transverse beam and four rectangular transverse beams; a center of the cross-shaped transverse beam is provided with several force application holes used for applying forces and moments; four tail ends of the cross-shaped transverse beam are each connected to one of the rectangular transverse beams to form a clockwise or counterclockwise swastika-shaped structure; a top end of a vertical beam is connected to a tail end of a corresponding rectangular transverse beam, and bottom ends of the vertical beams are connected to the rectangular outer frame; and there are a plurality of strain gauges to form six groups of Wheatstone bridges that are respectively used for measuring an X-direction for

Abstract: An artificial fingertip sliding tactile sensor includes a PVDF film, a rubber fingertip, a filling liquid, a sealing plug, a hydraulic sensor, a housing, an inner framework, and strain gauges. The rubber fingertip is a hemispherical cavity. The PVDF film is attached to the outside of the rubber fingertip. The sealing plug seals the rubber fingertip, and the hydraulic sensor is installed at the bottom of the sealing plug. The main body of the housing is a rigid cylindrical structure. The top of the housing is provided with a circular opening, and the bottom of the housing is a flange-like structure. Four circular through holes are uniformly distributed on the flange-like structure. The inner framework includes a cylindrical head, a vertical strain rod and a base. The strain gauges are respectively attached on four sides of the vertical strain rod and adjacent to the base.

Abstract: An artificial fingertip sliding tactile sensor includes a PVDF film, a rubber fingertip, a filling liquid, a sealing plug, a hydraulic sensor, a housing, an inner framework, and strain gauges. The rubber fingertip is a hemispherical cavity. The PVDF film is attached to the outside of the rubber fingertip. The sealing plug seals the rubber fingertip, and the hydraulic sensor is installed at the bottom of the sealing plug. The main body of the housing is a rigid cylindrical structure. The top of the housing is provided with a circular opening, and the bottom of the housing is a flange-like structure. Four circular through holes are uniformly distributed on the flange-like structure. The inner framework includes a cylindrical head, a vertical strain rod and a base. The strain gauges are respectively attached on four sides of the vertical strain rod and adjacent to the base.

Abstract: A natural human-computer interaction system based on multi-sensing data fusion comprises a MEMS anti tracking device, a visual tracking device, a force feedback device and a PC terminal. The MEMS aim tracking device is composed of three sets of independent MEMS sensors for collecting arm joint angle information and measuring an arm motion trajectory. The visual tracking device is composed of a binocular camera for collecting image information and measuring a finger motion trajectory. The force feedback device is mounted in a palm of an operator for providing a feedback force to the finger. The PC terminal comprises a data display module, an arm motion calculating module, an image processing module, a mechanics calculating module and a virtual scene rendering module. The system tracks the arm motion trajectory of the operator by taking and tracks the finger motion trajectory of the operator and provides force feedback interaction to the finger of the operator.

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.

Abstract: The present invention discloses a multi-dimensional surface electromyogram signal prosthetic hand control method based on principal component analysis. The method comprises the following steps. Wear an armlet provided with a 24-channel array electromyography sensor to a front arm of a subject, and respectively wear five finger joint attitude sensors at a distal phalanx of a thumb and at middle phalanxes of remaining fingers of the subject. Perform independent bending and stretching training on the five fingers of the subject, and meanwhile, collect data of an array electromyography sensor and data of the finger joint attitude sensors. Decouple the data of the array electromyography sensor by principal component analysis to form a finger motion training set. Perform data fitting on the finger motion training set by a neural network method, and construct a finger continuous motion prediction model. Predict a current bending angle of the finger through the finger continuous motion model.

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.