Kalman estimator- and general linear model-based on-line brain activation mapping by near-infrared spectroscopy

<p>Abstract</p> <p>Background</p> <p>Near-infrared spectroscopy (NIRS) is a non-invasive neuroimaging technique that recently has been developed to measure the changes of cerebral blood oxygenation associated with brain activities. To date, for functional brain mapping applications, there is no standard on-line method for analysing NIRS data.</p> <p>Methods</p> <p>In this paper, a novel on-line NIRS data analysis framework taking advantages of both the general linear model (GLM) and the Kalman estimator is devised. The Kalman estimator is used to update the GLM coefficients recursively, and one critical coefficient regarding brain activities is then passed to a <it>t</it>-statistical test. The <it>t</it>-statistical test result is used to update a topographic brain activation map. Meanwhile, a set of high-pass filters is plugged into the GLM to prevent very low-frequency noises, and an autoregressive (AR) model is used to prevent the temporal correlation caused by physiological noises in NIRS time series. A set of data recorded in finger tapping experiments is studied using the proposed framework.</p> <p>Results</p> <p>The obtained results suggest that the method can effectively track the task related brain activation areas, and prevent the noise distortion in the estimation while the experiment is running. Thereby, the potential of the proposed method for real-time NIRS-based brain imaging was demonstrated.</p> <p>Conclusions</p> <p>This paper presents a novel on-line approach for analysing NIRS data for functional brain mapping applications. This approach demonstrates the potential of a real-time-updating topographic brain activation map.</p

Impedance adaptation for optimal robot–environment interaction

In this paper, impedance adaptation is investigated for robots interacting with unknown environments. Impedance control is employed for the physical interaction between robots and environments, subject to unknown and uncertain environments dynamics. The unknown environments are described as linear systems with unknown dynamics, based on which the desired impedance model is obtained. A cost function that measures the tracking error and interaction force is defined, and the critical impedance parameters are found to minimize it. Without requiring the information of the environments dynamics, the proposed impedance adaptation is feasible in a large number of applications where robots physically interact with unknown environments. The validity of the proposed method is verified through simulation studies

Neural network control of a rehabilitation robot by state and output feedback

In this paper, neural network control is presented for a rehabilitation robot with unknown system dynamics. To deal with the system uncertainties and improve the system robustness, adaptive neural networks are used to approximate the unknown model of the robot and adapt interactions between the robot and the patient. Both full state feedback control and output feedback control are considered in this paper. With the proposed control, uniform ultimate boundedness of the closed loop system is achieved in the context of Lyapunov’s stability theory and its associated techniques. The state of the system is proven to converge to a small neighborhood of zero by appropriately choosing design parameters. Extensive simulations for a rehabilitation robot with constraints are carried out to illustrate the effectiveness of the proposed control

Adaptive neural network controller design for flexible joint robots using singular perturbation technique

Transactions of the Institute of Measurement and Control173120-131TICO

Robust welding seam tracking and recognition

Khyam, MO ORCiD: 0000-0002-1988-2328In the process of automatic welding based on structured light vision, the precise localization of the welding seam in an image has an important influence on the quality of the welding. However, in practice, there is much interference, such as spatter and arc, which introduces great challenges for accurate welding seam localization. In this paper, we considered welding seam localization problem as visual target tracking and based on that, we proposed a robust welding seam tracking algorithm. Prior to the start of welding, the seam is separated using a cumulative gray frequency, which is utilized to adaptively determine the initial position and size of the search window. During the welding process, large seam motion range may result in only a portion of the welding seam exists in the search window. To prevent that, a tracking-by-detection method is used to calculate the location of the search window. Usually, the intersection of seam and noise, e.g., spatter, has a severe influence on the accuracy of feature points localization. In order to solve this problem, a sequence gravity method (SGM) for extracting a smoother center line of welding seam is proposed, which is able to reduce the impact of interference. The double-threshold recursive least square method is used to fit the curve obtained by SGM with the aim of improving the real-time performance and accuracy of the system. Finally, the superiority of the proposed algorithm is well demonstrated by comparison with other solutions for seam tracking and recognition through extensive experiments

Multiple access chirp-based ultrasonic positioning

Khyam, MO ORCiD: 0000-0002-1988-2328Distance-based ultrasonic positioning systems (UPSs) using trilateration have been adopted in various types of applications across a wide variety of fields. Recently, the use of a chirp signal in conjunction with cross correlation has drawn a considerable amount of attention for UPSs. However, when a chirp signal is used for positioning, these algorithms suffer from problems due to signal interference. In this paper, to solve this problem, we propose using four sets of orthogonal chirps, each of which contains three waveforms. The first three sets use chirp rates as a mechanism for assigning uniquely modulated chirp signals to transmitters while the basic idea behind the last one is to exploit the orthogonality of the subcarriers of a chirp waveform, i.e., the discrete frequency components of a chirp waveform. All the waveforms contained in each set have good orthogonality (i.e., the waveforms contained in sets 1 to 3 and set 4 are, respectively, quasi-orthogonal and perfectly orthogonal) and also have all the advantages of a classic chirp waveform. First, the performance of the waveforms is investigated through correlation analysis and then, in an indoor environment, evaluated through simulations and experiments for ultrasonic positioning. For sets 1 to 4, for an operational range of approximately 1000 mm, the positioning root-mean-square-errors 90% error were 6.20 9.13 mm, 6.05 8.90 mm, 7.38 10.85 mm, and 4.54 6.68 mm, respectively

Highly accurate time-of-flight measurement technique based on phase-correlation for ultrasonic ranging

Khyam, MO ORCiD: 0000-0002-1988-2328Ultrasonic-based distance measurements using time-of-flight (TOF) is a fundamental technique for different applications across a wide variety of fields. In general, cross correlation between a transmitted and received signal is considered to be the optimal TOF estimation technique, which produces a peak at the time delay between them. Cross correlation provides a superior performance in conjunction with a linear chirp. However, as its accuracy depends on the width of the peak, which is inversely proportional to the signal's bandwidth, it can only be said to be highly accurate if the reflected signal at the receiver is separated in time by more than the width of the correlation peak; otherwise, errors are introduced into the system. To improve its accuracy, the bandwidth of the transmitted signal must be increased, which increases the system cost. In this paper, to solve this problem, a \text {threshold-based}\,\,\text {phase-correlation} technique is proposed, which is able to provide a much narrower peak than cross correlation without increasing the signal's physical bandwidth. To evaluate the proposed method, in a controlled environment, two experiments were performed under low and high multipath conditions. For an operational range of 600 mm (indoor), the root-mean-square errors were [0.10, 0.56] mm and [0.19, 1.19] mm for low and high multipath environments, respectively, which indicate that the proposed technique is precise enough to support high accuracy applications

Mobile ultrasonic transducer positioning

Khyam, MO ORCiD: 0000-0002-1988-2328For positioning a moving ultrasonic transmitter, most of the existing ultrasonic positioning systems require the use of a bank of correlators to estimate the Doppler shift associated with its movement which require high computational complexity. In this paper, for positioning a moving transmitter, a computationally efficient a Doppler shift estimation and compensation technique is proposed. As the proposed approach has the ability to measure the Doppler shift directly from the received signal, it does not require to use a bank of correlators to estimate the Doppler shift associated with its movement of the transmitter