Origin of potential errors in the quantitative determination of terahertz optical properties in time-domain terahertz spectroscopy

We demonstrate theoretically and experimentally how changes of a terahertz （THz） beam induced by the sample affect the accuracy of the determination of THz dielectric properties in THz time-domain transmission spectros- copy （TDTS）. We apply a Gaussian beam and the ABCD matrix formalism to describe the propagation of the THz beam in a focused beam setup. The insertion of the sample induces a focus displacement which is absent in the reference t without a sample. We show how the focus displacement can be corrected. The THz optical properties after focus displacement correction reported in this Letter are in quantitative agreement with those obtained using collimated beam THz-TDTSinpreviouswork.

Motor Imagery and Error Related Potential Induced Position Control of a Robotic Arm

The paper introduces an electroencephalography(EEG) driven online position control scheme for a robot arm by utilizing motor imagery to activate and error related potential(ErrP) to stop the movement of the individual links, following a fixed(pre-defined) order of link selection. The right(left)hand motor imagery is used to turn a link clockwise(counterclockwise) and foot imagery is used to move a link forward. The occurrence of ErrP here indicates that the link under motion crosses the visually fixed target position, which usually is a plane/line/point depending on the desired transition of the link across 3D planes/around 2D lines/along 2D lines respectively. The imagined task about individual link's movement is decoded by a classifier into three possible class labels: clockwise, counterclockwise and no movement in case of rotational movements and forward, backward and no movement in case of translational movements. One additional classifier is required to detect the occurrence of the ErrP signal, elicited due to visually inspired positional link error with reference to a geometrically selected target position. Wavelet coefficients and adaptive autoregressive parameters are extracted as features for motor imagery and ErrP signals respectively. Support vector machine classifiers are used to decode motor imagination and ErrP with high classification accuracy above 80%. The average time taken by the proposed scheme to decode and execute control intentions for the complete movement of three links of a robot is approximately33 seconds. The steady-state error and peak overshoot of the proposed controller are experimentally obtained as 1.1% and4.6% respectively.