A Hybrid Brain-Computer Interface for Closed-Loop Position Control of a Robot Arm

Brain-Computer interfacing (BCI) has currently added a new dimension in assistive robotics. Existing brain-computer interfaces designed for position control applications suffer from two fundamental limitations. First, most of the existing schemes employ open-loop control, and thus are unable to track positional errors, resulting in failures in taking necessary online corrective actions. There are examples of a few works dealing with closed-loop electroencephalography (EEG)-based position control. These existing closed-loop brain-induced position control schemes employ a fixed order link selection rule, which often creates a bottleneck preventing time-efficient control. Second, the existing brain-induced position controllers are designed to generate a position response like a traditional first-order system, resulting in a large steady-state error. This paper overcomes the above two limitations by keeping provisions for steady-state visual evoked potential (SSVEP) induced link-selection in an arbitrary order as required for efficient control and generating a second-order response of the position-control system with gradually diminishing overshoots/undershoots to reduce steady-state errors. Other than the above, the third innovation is to utilize motor imagery and P300 signals to design the hybrid brain-computer interfacing system for the said application with gradually diminishing error-margin using speed reversal at the zero-crossings of positional errors. Experiments undertaken reveal that the steady-state error is reduced to 0.2%. The paper also provides a thorough analysis of the stability of the closed-loop system performance using the Root Locus technique.      

DCT-based iris recognition

This paper presents a novel iris coding method based on differences of discrete cosine transform (DCT) coefficients of overlapped angular patches from normalized iris images. The feature extraction capabilities of the DCT are optimized on the two largest publicly available iris image data sets, 2,156 images of 308 eyes from the CASIA database and 2,955 images of 150 eyes from the Bath database. On this data, we achieve 100 percent correct recognition rate (CRR) and perfect receiver-operating characteristic (ROC) curves with no registered false accepts or rejects. Individual feature bit and patch position parameters are optimized for matching through a product-of-sum approach to Hamming distance calculation. For verification, a variable threshold is applied to the distance metric and the false acceptance rate (FAR) and false rejection rate (FRR) are recorded. A new worst-case metric is proposed for predicting practical system performance in the absence of matching failures, and the worst case theoretical equal error rate (EER) is predicted to be as low as 2.59 times 10^-1 available data sets     

A self-organizing fuzzy inference system for electric fieldoptimization of HV electrode systems

Development of efficient methods for optimum design of electrode and insulator contour in a HV apparatus has been an important area of research in the recent past. A self-organizing fuzzy inference system is developed for electrode optimization which is an improved version over traditional iterative approach of optimization and more recent methods employing neural networks. This fuzzy system has been implemented for two practical examples of an axisymmetric single-phase gas-insulated system (GIS) bus termination and a disconnecter switch configuration. Improved electric stress distribution demonstrates the usefulness of the proposed method. A new methodology for automatic generation of the fuzzy rule base from the input-output data set is also proposed in this scheme. This fuzzy system is much simpler and less time consuming to implement compared to other optimization techniques presently available for optimization of HV electrodes     

Terpolymers of acrylamide,acrylic acid and acrylonitrile: further characterization and biodegradation studies

Tercopolymers of acrylamide (AM), acrylic acid (AA) and acrylonitrile (AN) synthesized by free radical solution polymerization have been characterized using ¹³C NMR and thermal analysis (DSC) techniques. Incorporation of the above three monomers was confirmed by ¹³C NMR analysis. The tercopolymers have similar polymer backbone structures, and a limited branching in the main chain was found as evidenced by DSC analysis. Microbiological observations of polymer‐dependent growth and of respiration studies using a soil bacterial isolate, suggested that these tercopolymers were used as growth substrate and were therefore biodegradable. © 2000 Society of Chemical Industry     

Subject-specific strength percentile determination for two-dimensional symmetric lifting considering dynamic joint strength

Multibody System Dynamics - This paper describes an efficient optimization method for determining the subject-specific strength percentile and predicting the maximum weight lifting motion by...     

Optical and bio-sensing characteristics of ZnO nanotubes grown by hydrothermal method

ZnO nanostructures were fabricated on copper substrates by hydrothermal method at an optimized growth temperature of -95 degrees C. Structural properties were investigated by field emission scanning electron and transmission electron microscopy. Distinct morphologies were found to be formed at different growth times. The formation of nanotubes mainly involved the initial nucleation followed by the growth of nanorods at 95 degrees C, and then with the increase of dissolution time at room temperature, the preferential chemical dissolution of the metastable Zn-rich [0001] polar surfaces resulted in removing the atoms from the surfaces, thus leading to the thinning of the wall of the nanostructures. Completely hollow ZnO nanotubes could be obtained at a high dissolution time. The room temperature photoluminescence and optical absorption properties of ZnO nanotubes have been studied as a function of dissolution time. The efficacy of ZnO nanotubes for glucose sensing applications has been studied.     

A semiautomatic approach for segmentation of carotid vasculature from patients’ CTA images

Segmentation of vasculature specific to the patients’ carotid vasculature is a complicated and challenging task because of its complex geometrical structure and interconnections. Accurate or approximate digital phantoms of the vasculature are extremely useful in quick analysis of the vascular geometry and the modelling of blood flow in the cerebrovasculature. All these analyses lead to effective diagnosis and detection/localization of the diseased arterial segment in the cerebrovasculature. In this work, we have proposed a semiautomatic geodesic path propagation algorithm based on fuzzy distance transform to generate digital cerebrovascular phantoms from the patients’ CT angiogram (CTA) images. We have also custom-developed a 2-D/3-D user interface for accurate placement of user-specified seeds on the input images. The proposed method effectively separates the artery/vein regions from the soft bones in the overlapping intensity regions using minimal human interaction. Qualitative results along with 3-D rendition of the segmented cerebrovasculature on eight patients’ CTA images are presented here.     

Use of Essential Oils From Various Plants to Change the Fatty Acids Profiles of Lipids Obtained From Oleaginous Yeasts

We studied the ability of seven essential oils to alter the fatty acid composition of lipids produced by an oleaginous yeast Rhodosporidium toruloides. All of the essential oils, except thyme, significantly increased the stearic acid content of the lipids. The amount of essential oils in the media determined the fatty acid composition obtained. Subsequently, we studied the effect of the major monoterpenes present in these essential oils. When R. toruloides was grown on limonene, a major monoterpene in orange essential oil, the composition of lipid obtained was found to be quite similar to natural orange essential oil. This proved that limonene has a major role in the changes in fatty acid profiles of the lipids. The effect of orange essential oil on another oleaginous yeast, Cryptococcus curvatus, was also carried out. Although the effect of the essential oil on the fatty acid composition and biomass (cell mass) was similar for both these two yeasts, the reduction of the activity of some enzymes involved in the metabolic pathways was quite different. From these results, it can be concluded that the effect of essential oils differs with species and it is possible to produce lipids with alternate fatty acid profiles suitable for different applications and with good market value.