Design and Development of Smart Brain-Machine-Brain Interface (SBMIBI) for Deep Brain Stimulation and Other Biomedical Applications

Machine collaboration with the biological body/brain by sending electrical information back and forth is one of the leading research areas in neuro-engineering during the twenty-first century. Hence, Brain-Machine-Brain Interface (BMBI) is a powerful tool for achieving such machine-brain/body collaboration. BMBI generally is a smart device (usually invasive) that can record, store, and analyze neural activities, and generate corresponding responses in the form of electrical pulses to stimulate specific brain regions. The Smart Brain-Machine-Brain-Interface (SBMBI) is a step forward with compared to the traditional BMBI by including smart functions, such as in-electrode local computing capabilities, and availability of cloud connectivity in the system to take the advantage of powerful cloud computation in decision making. In this dissertation work, we designed and developed an innovative form of Smart Brain-Machine-Brain Interface (SBMBI) and studied its feasibility in different biomedical applications. With respect to power management, the SBMBI is a semi-passive platform. The communication module is fully passive—powered by RF harvested energy; whereas, the signal processing core is battery-assisted. The efficiency of the implemented RF energy harvester was measured to be 0.005%. One of potential applications of SBMBI is to configure a Smart Deep-Brain-Stimulator (SDBS) based on the general SBMBI platform. The SDBS consists of brain-implantable smart electrodes and a wireless-connected external controller. The SDBS electrodes operate as completely autonomous electronic implants that are capable of sensing and recording neural activities in real time, performing local processing, and generating arbitrary waveforms for neuro-stimulation. A bidirectional, secure, fully-passive wireless communication backbone was designed and integrated into this smart electrode to maintain contact between the smart electrodes and the controller. The standard EPC-Global protocol has been modified and adopted as the communication protocol in this design. The proposed SDBS, by using a SBMBI platform, was demonstrated and tested through a hardware prototype. Additionally the SBMBI was employed to develop a low-power wireless ECG data acquisition device. This device captures cardiac pulses through a non-invasive magnetic resonance electrode, processes the signal and sends it to the backend computer through the SBMBI interface. Analysis was performed to verify the integrity of received ECG data

Management and Complications of Arnold Chiari Hydrocephalus at Tertiary Health Care Center

Objective: to investigate the role of CT and MRI in diagnosis of Arnold chiari malformation of hydrocephalus and its treatment with VP shunt along with complications. Study Design: Prospective study Place and duration: Department of Neurosurgery, DG Khan Medical College from May 4, 2018 to May 4, 2019. Methodology: Fifty patients of congenital hydrocephalus who were not treated previously were selected. Detailed history about disease and clinical examination of patients was performed. Follow ups were done at neurosurgery OPD. SPSS software for data analysis was used and mean ± SD, frequency and percentages were calculated for variables. P value ≤0.05 was considered as significant. Results: Treatment in case of congenital hydrocephalus as VP shunt, intra-aneurysmal coiling, excision of meningomyelocele with VP shunt and suboccipital craniectomy + upper cervical laminectomy (scucl) were observed as 10%, 6%, 8% and 8% respectively.  Twelve percent of patients were not treated. Conclusion: CT and MRI are the main diagnostic tools for diagnosis of Arnold chiari malformation and VP shunt is the treatment of choice. Among complications of VP shunt infection of shunt and shunt block are the main complications

Piezoelectric metamaterial with negative and zero Poisson's ratios

This study presents the finite element–based micromechanical modeling approach to obtain the electromechanical properties of the piezoelectric metamaterial based on honeycomb (HC) cellular networks. The symmetry of the periodic structure was employed to derive mixed boundary conditions (MBCs) analogous to periodic boundary conditions (PBCs). Three classes of hexagonal HC cellular networks, namely, a conventional HC (CHC), a re-entrant HC (RE), and a semi-re-entrant HC (SRE) were considered. The representative volume elements (RVEs) of these three classes of cellular materials were created, and finite element analyses were carried out to analyze the effect of orientation of the ligament on their effective electromechanical properties and their suitability in specific engineering applications. The longitudinally poled piezoelectric HC cellular networks showed an enhanced behavior as compared to the monolithic piezoelectric materials. Moreover, longitudinally poled HC cellular networks demonstrated that, as compared to the bulk constituent, their hydrostatic figure of merit increased and their acoustic impedance decreased by one order of magnitude, respectively, indicating their applicability for the design on hydrophones. Moreover, results showed that cellular metamaterial with tunable electromechanical characteristics and a variety of auxetic behaviors such as negative, positive, or zero Poisson’s ratios could be developed. Such novel HC network-based functional cellular materials are likely to facilitate the design of light-weight devices for various next-generation sensors and actuators

Accurate monitoring and fault detection in wind measuring devices through wireless sensor networks

Many wind energy projects report poor performance as low as 60% of the predicted performance. The reason for this is poor resource assessment and the use of new untested technologies and systems in remote locations. Predictions about the potential of an area for wind energy projects (through simulated models) may vary from the actual potential of the area. Hence, introducing accurate site assessment techniques will lead to accurate predictions of energy production from a particular area. We solve this problem by installing a Wireless Sensor Network (WSN) to periodically analyze the data from anemometers installed in that area. After comparative analysis of the acquired data, the anemometers transmit their readings through a WSN to the sink node for analysis. The sink node uses an iterative algorithm which sequentially detects any faulty anemometer and passes the details of the fault to the central system or main station. We apply the proposed technique in simulation as well as in practical implementation and study its accuracy by comparing the simulation results with experimental results to analyze the variation in the results obtained from both simulation model and implemented model. Simulation results show that the algorithm indicates faulty anemometers with high accuracy and low false alarm rate when as many as 25% of the anemometers become faulty. Experimental analysis shows that anemometers incorporating this solution are better assessed and performance level of implemented projects is increased above 86% of the simulated models

Numerical and experimental investigation of the effect of process parameters on sheet deformation during the electromagnetic forming of AA6061-T6 alloy.

Electromagnetic forming is a high-speed sheet metal forming technique to form metallic sheets by applying magnetic forces. In comparison to the conventional sheet metal forming process, electromagnetic forming is a process with an extremely high velocity and strain rate, which can be effectively used for the forming of certain difficult-to-form metals. During electromagnetic forming, it is important to recognise the effects of process parameters on the deformation and sheet thickness variation of the sheet metal. This research focuses on the development of a numerical model for aluminium alloy (AA6061-T6) to analyse the effects of three process parameters, namely voltage, sheet thickness and number turns of the coils, on the deformation and thickness variation of the sheet. A two-dimensional fully coupled finite-element (FE) model consisting of an electrical circuit, magnetic field and solid mechanics was developed and used to determine the effect of changing magnetic flux and system inductance on sheet deformation. Experiment validation of the results was performed on a 28 KJ electromagnetic forming system. The Taguchi orthogonal array approach was used for the design of experiments using the three input parameters (voltage, sheet thickness and number of turns of the coil). The maximum error between numerical and experimental values for sheet thickness variation was observed to be 4.9 %. Analysis of variance (ANOVA) was performed on the experimental results. Applied voltage and sheet thickness were the significant parameters, while the number of turns of the coil had an insignificant effect on sheet deformation. The contribution ratio of voltage and sheet thickness was 46.21 % and 45.12 % respectively. The sheet deformation from simulations was found to be in good agreement with the experimental results

A Short Review on the Development of Salt Tolerant Cultivars in Rice

Rice is staple food for half of the world. With a population of almost 9.6 billion by the year 2050, there is a dire need of developing techniques to improve the crop plants, not only in terms of better yield but also to withstand harsh environmental conditions and stresses like drought, temperature, flood and salinity. Salinity is second to drought stress and hence it is very important to develop crops tolerant to salinity stress. This review discusses the mechanisms of salt tolerance and the recent developments in understanding the complex tolerance phenomena. One way to address the salinity issue is to develop tolerant rice varieties using conventional and modern breeding techniques for which screening the rice germplasm for the varieties with desired traits is critical. Conventional methods to develop tolerant rice varieties are discussed along with modern biotechnology techniques are also discussed. Quantitative Trait Loci (QTL) and Marker Assisted Selection (MAS) are promising techniques. In addition to these modern techniques, some recent developments in the fields of transgenic plants, haploid breeding and Somaclonal variations have also been discussed. The limited knowledge about molecular and genetic mechanisms to tolerate abiotic stresses, however is a barrier to efficiently develop tolerant cultivars. A combination of conventional and modern biotechnology techniques could possibly open up the new ways