Accurate classification of EEG left and right hand motor imagery is an important issue in brain-computer interface. Firstly, discrete wavelet transform method was used to decompose the average power of C3 electrode an...
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Accurate classification of EEG left and right hand motor imagery is an important issue in brain-computer interface. Firstly, discrete wavelet transform method was used to decompose the average power of C3 electrode and C4 electrode in left-right hands imagery movement during some periods of time. The reconstructed signal of approximation coefficient A6 on the 6al level was selected to build up a feature signal. Secondly, the performances by Fisher Linear Discriminant Analysis with two different threshold calculation ways and Support Vector Machine methods were compared. The final classification results showed that false classification rate by Support Vector Machine was lower and gained an ideal classification results.
In this paper, we use PID motion controllers to control underactuated Autonomous Underwater Vehicles (AUVs) to follow three-dimensional paths. Based on the path-following errors expressed in the Serret-Frenet coordina...
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This paper introduces an originally designed wheelchair robot. This robot is equipped with a novel type of Variable Geometry Single Tracked Mechanism (VGSTM) that can actively control the robot shape and the track ten...
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ISBN:
(纸本)9781457721366
This paper introduces an originally designed wheelchair robot. This robot is equipped with a novel type of Variable Geometry Single Tracked Mechanism (VGSTM) that can actively control the robot shape and the track tension. So it becomes possible to improve the obstacle clearing capability of the robot by adapting the robot shape for the obstacle. The track tension is closely related to the performance of this original wheelchair robot, so with the aim of stair-climbing, which is the most fundamental obstacle clearing performance of the wheelchair robot, the optimization model of the track tension is established based on the geometric model and the static model of the robot. Then the simulation is performed, and the optimal track tension values of the robot for different phases of stair-climbing are obtained. Finally, these track tension values are verified through the experiment.
In this paper, a multiple-rotorcraft-flying-robot (MRFR) testbed is introduced. Firstly, physical structure, as well as hardware and software system, is described in detail. Subsequently, in order to realize the auton...
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ISBN:
(纸本)9781457721366
In this paper, a multiple-rotorcraft-flying-robot (MRFR) testbed is introduced. Firstly, physical structure, as well as hardware and software system, is described in detail. Subsequently, in order to realize the autonomous flight of each single rotorcraft-flying-robot (RFR), modeling, identification and flight control experiments are conducted. Then, formation flying demonstration is presented to verify the basic functions of the new-designed MRFR testbed. Finally, two points should be emphasized: 1) both cooperation/coordination algorithm of MRFR and advanced flight control algorithm of single RFR can be verified on this testbed;2) experiments on this testbed can approach real flight test much better because three real RFR systems are used.
The dynamics of the myosin molecular motor as it binds to actin filaments during muscle contraction are still not clearly *** this paper,we focus on the coupling mechanism of multi-force interactions in the myosin mol...
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The dynamics of the myosin molecular motor as it binds to actin filaments during muscle contraction are still not clearly *** this paper,we focus on the coupling mechanism of multi-force interactions in the myosin molecule during its interaction with *** forces include the electrostatic force,the van der Waals force and the Casimir force in molecular dynamic simulations of the molecules in solvent with thermal *** on the Hamaker approach,van der Waals and Casimir potentials and forces are calculated between myosin and *** have developed a Monte Carlo method to simulate the dynamic activity of the molecular *** have shown that because of the retardation effect,the van der Waals force falls into the Casimir force when the distance between the surfaces is larger than 3 *** the distance is smaller than 3 nm,the electrostatic force and the van der Waals force increase until the myosin becomes attached to the *** the distances studied in the present work,the electrostatic force dominates the attractive *** calculations are in good agreement with recently reported experimental results.
A silicon nanochannel system with integrated transverse electrodes was designed and fabricated by combining MEMS microfabrication and AFM nanolithography. The fabrication process began with the patterning of microscal...
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A silicon nanochannel system with integrated transverse electrodes was designed and fabricated by combining MEMS microfabrication and AFM nanolithography. The fabrication process began with the patterning of microscale reservoirs and electrodes on an oxidized silicon chip using conventional MEMS techniques. A nanochannel, approximately 30μm long with a small semi-circular cross-sectional area of 20nm by 200nm, was then mechanically machined on the oxide surface between the micro reservoirs by applying AFM nanolithography with an all-diamond probe. Anodic bonding was used to seal off the nanochannel with a matching Pyrex cover. Continuous flow in the nanochannel was verified by pressurizing a solution of fluorescein isothiocyanate (FITC) in ethanol through the channel in a vacuum chamber. It was further demonstrated by driving carboxyl-modified FluoSpheres ® (diameter ~ 20 nm) through the nanochannel with an external electric field. Presence of the FluoSpheres ® in the channel was indicated by a sharp increase in current between the transverse electrodes.
In order to eliminate the drawbacks of conventional force feedback gloves, a new type of master fin- ger has been developed. By utilizing three "four-bar mechanism joint" in series and wire coupling mecha- nism, the...
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In order to eliminate the drawbacks of conventional force feedback gloves, a new type of master fin- ger has been developed. By utilizing three "four-bar mechanism joint" in series and wire coupling mecha- nism, the master finger transmission ratio is kept exactly 1:1.4:1 in the whole movement range and it can make active motions in both extension and flexion directions. Additionally, to assure faster data transmission and near zero delay in the master-slave operation, a digital signal processing/field programmable gate array (DSP/FPGA-FPGA) structure with 200μs cycle time is designed. The operating modes of the master finger can be contact or non-contact, which depends on the motion states of a slave finger, free motion or constrained motion. The position control employed in non-contact mode ensures unconstrained motion and the force control adopted in contact mode guarantees natural contact sensation. To evaluate the performances of the master finger, an experiment between the master finger and a DLR/HTT dexterous finger is conducted. The results demonstrate that this new type master finger can augment telepresence.
Time domain features of slow potentials ≤2 Hz) during periodic movement and motor imagery at fast and slow (4 Hz and 2 Hz) were investigated in 4 healthy subjects by event-related potentials in t...
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Time domain features of slow potentials ≤2 Hz) during periodic movement and motor imagery at fast and slow (4 Hz and 2 Hz) were investigated in 4 healthy subjects by event-related potentials in the paper. EEG was recorded from 64 electrodes and 9 closely spaced electrodes overlaying the left and right sensorimotor area were analyzed. The subjects performed 40 fast and 40 slow (paced by metronome) movement and motor imagery of six tasks that involved three limbs (left and right index fingers and right toes) at first-person perspective. In addition, the subjects also performed motor imagery involved left and right arms and feet at third-person perspective. Based on brain processing mainly involved with the slow potentials during periodic movement and motor imagery, event-related potentials were low-pass filtered with 2 Hz cut-off frequency (24 dB/oct). At C1, Cz, and C2, fast movement-related potentials had a larger positive slow potentials tendency than slow movement-related potentials 1.5 s after movement onset. In contrast to movement, slow motor imagery-related potentials had a larger positive slow potentials tendency than fast motor imagery-related potentials 1.75 s after motor imagery onset at these electrodes. Time delays reaching positive peak and rebound rate after peak were also explored. These results may be very important for further exploring relationship between speed and EEG activity during periodic movement and motor imagery. The study may provide a strategy to realize fine control of robots by brain-controlled robot interface.
Empirical mode decomposition(EMD) is a new signal decomposition method, which could decompose the non-stationary signal into several single-component intrinsic mode functions (IMFs) and each IMF has some physical mean...
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Empirical mode decomposition(EMD) is a new signal decomposition method, which could decompose the non-stationary signal into several single-component intrinsic mode functions (IMFs) and each IMF has some physical meanings. This paper studies the single trial extraction of visual evoked potential by combining EMD and wavelet threshold filter. Experimental results showed that the EMD based method can separate the noise out of the event related potentials (ERPs) and effectively extract the weak ERPs in strong background noise, which manifested as the waveform characteristics and root mean square error (RMSE).
This paper studies the problem of learning robust regression for real world head pose estimation. The performance and applicability of traditional regression methods in real world head pose estimation are limited by a...
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This paper studies the problem of learning robust regression for real world head pose estimation. The performance and applicability of traditional regression methods in real world head pose estimation are limited by a lack of robustness to outlying or corrupted observations. By introducing low- rank and sparse regularizations, we propose a novel regression method, named Convex Regularized Sparse Regression (CRSR), for simultaneously removing the noise and outliers from the training data and learning the regression between image features and pose angles. We verify the efficiency of the proposed robust regression method with extensive experiments on real data, demonstrating lower error rates and efficiency than existing methods.
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