Signal Subspace Smoothing Technique for Time Delay Estimation Using MUSIC Algorithm.

In civil engineering, Time Delay Estimation (TDE) is one of the most important tasks for the media structure and quality evaluation. In this paper, the MUSIC algorithm is applied to estimate the time delay. In practice, the backscattered echoes are highly correlated (even coherent). In order to apply the MUSIC algorithm, an adaptation of signal subspace smoothing is proposed to decorrelate the correlation between echoes. Unlike the conventional sub-band averaging techniques, we propose to directly use the signal subspace, which can take full advantage of the signal subspace and reduce the influence of noise. Moreover, the proposed method is adapted to deal with any radar pulse shape. The proposed method is tested on both numerical and experimental data. Both results show the effectiveness of the proposed method.

Joint Maximum Likelihood Time Delay Estimation of Unknown Event-Related Potential Signals for EEG Sensor Signal Quality Enhancement.

Electroencephalograms (EEGs) measure a brain signal that contains abundant information about the human brain function and health. For this reason, recent clinical brain research and brain computer interface (BCI) studies use EEG signals in many applications. Due to the significant noise in EEG traces, signal processing to enhance the signal to noise power ratio (SNR) is necessary for EEG analysis, especially for non-invasive EEG. A typical method to improve the SNR is averaging many trials of event related potential (ERP) signal that represents a brain's response to a particular stimulus or a task. The averaging, however, is very sensitive to variable delays. In this study, we propose two time delay estimation (TDE) schemes based on a joint maximum likelihood (ML) criterion to compensate the uncertain delays which may be different in each trial. We evaluate the performance for different types of signals such as random, deterministic, and real EEG signals. The results show that the proposed schemes provide better performance than other conventional schemes employing averaged signal as a reference, e.g., up to 4 dB gain at the expected delay error of 10°.

Model-free robust adaptive integral sliding mode impedance control of knee-ankle-toe active transfemoral prosthesis.

BACKGROUND: Wearing appropriate active prosthesis is the guarantee of daily life for amputees. Normally the controller of the traditional active transfemoral prosthesis is designed based on the mathematical model. The modelling error and the external interference will reduce the control accuracy of the system and make the prosthesis unable to operate in the desired trajectory. METHODS: Firstly, combined with time delay estimation (TDE), a model-free robust integral sliding mode impedance controller is designed. This method not only suppress the impedance error, but also eliminate the nonlinear relationship and disturbance in the dynamic model. Secondly, an adaptive law is proposed to update the controller gain, which provide stable control effect. Thirdly, the stability of prosthesis closed-loop system is proved by Lyapunov stability theory. Finally, the motor torque is used to drive each joint, and Matlab/Simscape is used to verify the prosthesis control system. RESULTS: From the result of the simulation experiment, the control method has a good tracking effect on each joint. The root mean square error and mean absolute errors of each joint's angle tracking error are 0.6123°, 1.9976°, 0.5574° and 0.2635°, 1.8175°, 0.4796°. Compared with the controller without adaptive gain and impedance control, the control effect is improved, and the plantar pressure of amputees is closer to the sound side. CONCLUSIONS: Comparing the results of different controllers, the adaptive integral sliding mode impedance controller with TDE can better track the expected angles of each joint. The gait is more normal. The walking performance of the prosthesis wearers is improved.

Novel adaptive impedance control for exoskeleton robot for rehabilitation using a nonlinear time-delay disturbance observer.

A new adaptive impedance, augmented with backstepping control, time-delay estimation, and a disturbance observer, was designed to perform passive-assistive rehabilitation motion. This was done using a rehabilitation robot whereby humans' musculoskeletal conditions were considered. This control scheme aimed to mimic the movement behavior of the user and to provide an accurate compensation for uncertainties and torque disturbances. Such disturbances were excited by constraints of input saturation of the robot's actuators, friction forces and backlash, several payloads of the attached upper-limb of each patient, and time delay errors. The designed impedance control algorithm would transfer the stiffness of the human upper limb to the developed impedance model via the measured user force. In the proposed control scheme, active rejection of disturbances would be achieved through the direct connection between such disturbances from the observer's output and the control input via the feedforward loop of the system. Furthermore, the computed control input does not require any precise knowledge of the robot's dynamic model or any knowledge of built-in torque-sensing units to provide the desirable physiotherapy treatment. Experimental investigations performed by two subjects were exhibited to support the benefits of the designed approach.

Time-delay structure predicts clinical scores for patients with disorders of consciousness using resting-state fMRI.

BACKGROUND: The detection of intrinsic brain activity (iBA) could assist clinical assessment for disorder of consciousness (DOC) patients. Previous studies have revealed the altered iBA in thalamocortical, frontoparietal, and default mode network in DOC patients using functional connectivity (FC) analysis. However, due to the assumption of synchronized iBA in FC, these studied may be inadequate for understanding the effect of severe brain injury on the temporal organization of iBA and the relationship between temporal organization and clinical feature in DOC patients. Recently, the time delay estimation (TDE) and probabilistic flow estimation (PFE) were proposed to analyze temporal organization, which could provide propagation structure and propagation probability at whole-brain level. METHODS: We applied voxel-wise TDE and PFE to assess propagation structure and propagation probability for the DOC patients and then applied the connectome-based predictive modeling (CPM) to predict clinical scores for patients based on the ROI-wise TDE and PFE. RESULTS: We found that: 1) the DOC patients showed abnormal voxel-wise time delay (TD) and probabilistic flow (PF) in the precentral gyrus, precuneus, middle cingulate cortex, and postcentral gyrus, 2) the range of TD value in the patients was shorter than that in the controls, and 3) the ROI-wise TD had a better predictive performance for clinical scores of the patients compared with that based on ROI-wise PF. CONCLUSION: Our findings may suggest that the propagation structure of iBA could be used to predict clinical scores in DOC patients.

Adaptive super-twisting fractional-order nonsingular terminal sliding mode control of cable-driven manipulators.

This paper proposes a novel adaptive super-twisting fractional-order nonsingular terminal sliding mode (AST-FONTSM) control scheme using time delay estimation (TDE) for the cable-driven manipulators. The designed control scheme utilizes TDE to obtain the estimation of system dynamics, and therefore no system dynamic model information will be required. Afterwards, AST and FONTSM schemes are applied to ensure good control performance in both reaching and sliding mode phases. Due to the adoption of AST scheme, good robustness and high control precision are obtained in the reaching phase, while the boundary information of the lumped uncertainties will be no longer required. Thanks to the utilization of FONTSM error dynamics, fast convergence and accurate tracking and strong robustness can be simultaneously ensured in the sliding mode phase. Corresponding comparative simulation and experimental results demonstrate the effectiveness and superiorities of our proposed method over the existing control methods.