Abstract: Disclosed is a lightweight hand exoskeleton force feedback apparatus, including a driver, a first rotating link, a second rotating link, a first linkage link, a second linkage link, a finger sleeve, and a pressure sensor fixing member; the driver is worn on a back of metacarpal bone of a human hand, the finger sleeve is fixed on an index finger, and the pressure sensor fixing member is fixed below the index finger; when the human hand bends to simulate a state of grasping an object, the driver drives the first rotating link to couple with the first linkage link and the second linkage link through the second rotating link to drive the finger sleeve to bend and stretch, force feedback is applied to the fingertip, and a pressure is accordingly imposed on a pressure sensor of the pressure sensor fixing member, so that closed-loop force feedback control is implemented.

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).

Abstract: Disclosed is an optimization modeling and robust control method for a soft robot based on a fusion prediction equation, including the following steps: deriving measurement coordinates based on the fusion prediction equation; designing an observation function based on the measurement coordinates; identifying a Koopman model based on the observation function; and designing a robust model predictive controller based on the Koopman model. Further disclosed are a fusion prediction equation and a derivation method thereof, which can derive correct, abundant but non-redundant measurement coordinates, overcoming the problem of single measurement coordinates in a soft robot system, thereby being conducive to simplifying a design process of the observation function and further improving the accuracy of the Koopman model for the soft robot.

Abstract: Disclosed is a lightweight hand exoskeleton force feedback apparatus, including a driver, a first rotating link, a second rotating link, a first linkage link, a second linkage link, a finger sleeve, and a pressure sensor fixing member; the driver is worn on a back of metacarpal bone of a human hand, the finger sleeve is fixed on an index finger, and the pressure sensor fixing member is fixed below the index finger; when the human hand bends to simulate a state of grasping an object, the driver drives the first rotating link to couple with the first linkage link and the second linkage link through the second rotating link to drive the finger sleeve to bend and stretch, force feedback is applied to the fingertip, and a pressure is accordingly imposed on a pressure sensor of the pressure sensor fixing member, so that closed-loop force feedback control is implemented.

Abstract: Disclosed is a safety shared control system based on performance of teleoperator, including a master teleoperation system, a slave robotic manipulator system and a communication module; where the master teleoperation system includes EEG signal measurement of a teleoperator, hand controller operation input, and upper computer software, and the upper computer software includes a graphical user interface (GUI), safety simulation for protecting the safety of a robot, and a PoT model; and the slave robotic manipulator system includes a robotic manipulator, a vision camera and lower computer software, and the lower computer software includes a target recognition algorithm, an autonomous controller, and a shared controller for dynamically allocating human-robot control weights.

Abstract: Disclosed are an affective haptic regulation system and method based on multimodal fusion, including a haptic optimal parameter adjustment module, a haptic generation module, a visual-auditory generation module, a multi-physiological signal acquisition module, a multi-sensory signal acquisition module, and a multimodal fusion emotion recognition module.

Abstract: Disclosed is an EEG recognition method for a natural hand movement based on a time-domain and frequency-domain multi-layer brain network, including: (1) acquiring a multi-channel EEG signal of the natural hand movement; (2) preprocessing the multi-channel EEG signal, and extracting a ? wave, a ? wave, a ? wave, a ? wave, and a ? wave at each time point; (3) constructing a time-domain multi-layer brain network using a wSAR model; (4) calculating the frequency-domain multi-layer brain network using the phase-amplitude coupling; (5) combining the time-domain multi-layer brain network and the frequency-domain multi-layer brain network, and performing standardization; and (6) calculating metrics of the time-domain and frequency-domain multi-layer brain network and a super-adjacency matrix of a decomposed time-domain and frequency-domain multi-layer brain network, inputting the same to a two-layer graph convolutional network (GCN), and fusing manual, shallow, and deep features for analysis.

Abstract: Disclosed is an online estimation method for wrist torque based on neural features and LSTM, including following steps: (1) an experimenter keeps his/her arms stationary and applies torque to a torque sensor through his/her wrist; (2) acquiring data from the torque sensor and high-density surface EMG ((HD-sEMG) synchronously; (3) decomposing the HD-sEMG using a blind source separation algorithm to obtain a motor unit spike train (MUST); (4) constructing input and output vectors on the basis of the original HD-sEMG and the decomposed MUST, performing training of the LSTM, and performing polynomial regression of a discharge rate and torque of a neural feature; and (5) calculating a real-time discharge rate (DR) of the CST using a sliding window approach for real-time estimation of the torque.

Abstract: A process system of a follower fixture for tank moving support is provided and includes a conveying table slidably provided with a bearing platform through a screw slide rail assembly and provided with an outer frame assembly; a lifting platform is slidably installed in the outer frame assembly; positions of the lifting platform and the bearing platform are corresponded up and down; the outer frame assembly is slidably provided with a robot component; both sides of the conveying table are provided with loading platforms; workpieces are placed on one loading platform, and a fixture system is placed on the other loading platform; the fixture system and the workpieces are both placed in the moving range of the robot component, and positions of the fixture system and the workpieces are corresponded. problems including processing flexibility cannot be realized can be solved.

Abstract: Systems and methods for non-invasively scanning and analyzing one or more characteristics of a sample utilizing electromagnetic radiation are described. More particularly, the systems and methods utilize an electromagnetic radiation source connected to a transmitter and an analyzer connected to a receiver. A sample to be analyzed is placed between the transmitter and receiver in a variety of different manners and a frequency sweep of electromagnetic radiation is transmitted through the sample to create a series of spectral data sets that are used to create one or more composite spectrograms, which are then analyzed to determine one or more characteristics of the sample. A magnetic field can alternatively be applied around the transmitter, receiver and sample to enhance some characteristic analysis applications. Samples include inert and living items, and the characteristics include a wide variety of different applications.

Abstract: Systems and methods for non-invasively scanning and analyzing one or more characteristics of a sample utilizing electromagnetic radiation are described. More particularly, the systems and methods utilize an electromagnetic radiation source connected to a transmitter and an analyzer connected to a receiver. A sample to be analyzed is placed between the transmitter and receiver in a variety of different manners and a frequency sweep of electromagnetic radiation is transmitted through the sample to create a series of spectral data sets that are used to create one or more composite spectrograms, which are then analyzed to determine one or more characteristics of the sample. A magnetic field can alternatively be applied around the transmitter, receiver and sample to enhance some characteristic analysis applications. Samples include inert and living items, and the characteristics include a wide variety of different applications.