A study of the polishing process of a turbine blade for automation

Master'sMASTER OF ENGINEERIN

Validating the Comparison Framework for the Finite Dimensions Model of Concentric Ring Electrodes Using Human Electrocardiogram Data

[EN] While progress has been made in design optimization of concentric ring electrodes maximizing the accuracy of the surface Laplacian estimation, it was based exclusively on the negligible dimensions model of the electrode. Recent proof of concept of the new finite dimensions model that adds the radius of the central disc and the widths of concentric rings to the previously included number of rings and inter-ring distances provides an opportunity for more comprehensive design optimization. In this study, the aforementioned proof of concept was developed into a framework allowing direct comparison of any two concentric ring electrodes of the same size and with the same number of rings. The proposed framework is illustrated on constant and linearly increasing inter-ring distances tripolar concentric ring electrode configurations and validated on electrocardiograms from 20 human volunteers. In particular, ratios of truncation term coefficients between the two electrode configurations were used to demonstrate the similarity between the negligible and the finite dimension models analytically (p = 0.077). Laplacian estimates based on the two models were calculated on electrocardiogram data for emulation of linearly increasing inter-ring distances tripolar concentric ring electrode. The difference between the estimates was not statistically significant (p >> 0.05) which is consistent with the analytic result.This research was funded by the National Science Foundation (NSF) Division of Human Resource Development (HRD) Tribal Colleges and Universities Program (TCUP), grants number 1622481 and 1914787 to Oleksandr Makeyev. The authors would like to thank Rafael Rodriguez de Sanabria for his help with the human ECG data collection and Eduardo Garcia-Breijo for his help with the CRE implementation.Makeyev, O.; Musngi, M.; Moore, L.; Ye Lin, Y.; Prats-Boluda, G.; Garcia-Casado, J. 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Annals of Biomedical Engineering, 42(3), 651-660. doi:10.1007/s10439-013-0935-yZena-Giménez, V., Garcia-Casado, J., Ye-Lin, Y., Garcia-Breijo, E., & Prats-Boluda, G. (2018). A Flexible Multiring Concentric Electrode for Non-Invasive Identification of Intestinal Slow Waves. Sensors, 18(2), 396. doi:10.3390/s18020396Ye-Lin, Y., Alberola-Rubio, J., Prats-boluda, G., Perales, A., Desantes, D., & Garcia-Casado, J. (2014). Feasibility and Analysis of Bipolar Concentric Recording of Electrohysterogram with Flexible Active Electrode. Annals of Biomedical Engineering, 43(4), 968-976. doi:10.1007/s10439-014-1130-5Prats-Boluda, G., Ye-Lin, Y., Pradas-Novella, F., Garcia-Breijo, E., & Garcia-Casado, J. (2018). Textile Concentric Ring Electrodes: Influence of Position and Electrode Size on Cardiac Activity Monitoring. Journal of Sensors, 2018, 1-9. doi:10.1155/2018/7290867Wang, Y.-C., Chang, C.-F., Lin, H.-C., Lin, K.-S., Lin, K.-T., Hung, C.-M., & Lin, T.-M. (2010). Functional characterisation of a complex mutation in the α(1,4)galactosyltransferase gene in Taiwanese individuals with p phenotype. Transfusion Medicine, 21(2), 84-89. doi:10.1111/j.1365-3148.2010.01055.xMakeyev, O., Ding, Q., & Besio, W. G. (2016). Improving the accuracy of Laplacian estimation with novel multipolar concentric ring electrodes. Measurement, 80, 44-52. doi:10.1016/j.measurement.2015.11.017Makeyev, O., & Besio, W. (2016). Improving the Accuracy of Laplacian Estimation with Novel Variable Inter-Ring Distances Concentric Ring Electrodes. Sensors, 16(6), 858. doi:10.3390/s16060858Makeyev, O. (2018). Solving the general inter-ring distances optimization problem for concentric ring electrodes to improve Laplacian estimation. BioMedical Engineering OnLine, 17(1). doi:10.1186/s12938-018-0549-6Ye-Lin, Y., Bueno-Barrachina, J. M., Prats-boluda, G., Rodriguez de Sanabria, R., & Garcia-Casado, J. (2017). Wireless sensor node for non-invasive high precision electrocardiographic signal acquisition based on a multi-ring electrode. Measurement, 97, 195-202. doi:10.1016/j.measurement.2016.11.009Besio, W., & Chen, T. (2007). Tripolar Laplacian electrocardiogram and moment of activation isochronal mapping. Physiological Measurement, 28(5), 515-529. doi:10.1088/0967-3334/28/5/006Hamilton, P. S., & Tompkins, W. J. (1986). Quantitative Investigation of QRS Detection Rules Using the MIT/BIH Arrhythmia Database. IEEE Transactions on Biomedical Engineering, BME-33(12), 1157-1165. doi:10.1109/tbme.1986.325695Prats-Boluda, G., Ye-Lin, Y., Bueno-Barrachina, J., Rodriguez de Sanabria, R., & Garcia-Casado, J. (2016). Towards the clinical use of concentric electrodes in ECG recordings: influence of ring dimensions and electrode position. Measurement Science and Technology, 27(2), 025705. doi:10.1088/0957-0233/27/2/025705Mittal, S., Movsowitz, C., & Steinberg, J. S. (2011). Ambulatory External Electrocardiographic Monitoring. Journal of the American College of Cardiology, 58(17), 1741-1749. doi:10.1016/j.jacc.2011.07.026Garcia-Casado, J., Ye-Lin, Y., Prats-Boluda, G., & Makeyev, O. (2019). Evaluation of Bipolar, Tripolar, and Quadripolar Laplacian Estimates of Electrocardiogram via Concentric Ring Electrodes. Sensors, 19(17), 3780. doi:10.3390/s19173780Xu, Y., Luo, M., Li, T., & Song, G. (2017). ECG Signal De-noising and Baseline Wander Correction Based on CEEMDAN and Wavelet Threshold. Sensors, 17(12), 2754. doi:10.3390/s17122754Ortigueira, M. D., Laleg-Kirati, T.-M., & Machado, J. A. T. (2014). Riesz potential versus fractional Laplacian. Journal of Statistical Mechanics: Theory and Experiment, 2014(9), P09032. doi:10.1088/1742-5468/2014/09/p0903

Three Experimental Phases of Cornstarch-Based Biodegradable Plastic

Three Experimental Phases of Cornstarch-Based Biodegradable Plastic is the focus of this current study whose purpose was to create a bio-plastic from eco-friendly materials as a platform for an alternative commercial plastic. This study used a pre-experimental research design where three bio-plastic experiments were monitored to identify which among them was likely to produce the most efficient bio-plastic. At the end of the study, it was concluded that in terms of elasticity, tear resistance, appearance, texture, and odor, Experimental Two with four tablespoons of cornstarch, one cup of water, two tablespoons of vinegar, and two tablespoons of glycerin, is the most reliable among the three experiments.                 Hence, this study recommends to the biologists and scientists that may use this study to help them find ways to lessen biological problems caused by non-biodegradable plastics; to the producers that the study may help them to create and manufacture bio-plastics and to improve the study using other materials for the product to last longer indoors; to the consumers that the study may let them know the reliability and liability of the plastic they use in their everyday life; and to the future researchers who will want to conduct a further study about bio-plastics, this study may serve as a related study and think of an intervention to improve the results from the problem

Fall detection algorithms using accelerometers, gyroscopes and a barometric pressure sensor

Falls commonly occur in older adults and could result in long-lies when no one is around to assist, which could result to additional emotional and physical consequences. The use of inertial sensors allows a portable and unobtrusive way to detect motion, enabling the automatic detection of falls when used with a fall detection algorithm. The wrist and trunk are two locations that are favorable for fall detection as the former provides a convenient location for the user, while the latter provides a good location for capturing the body’s general motion. The objective of this thesis is to further improve the performance of a wrist-mounted and a trunk-mounted threshold-based fall detection algorithm using inertial sensors comprised of tri-axial accelerometer, tri-axial gyroscope, and a barometric pressure sensor. The algorithms were tested using a comprehensive set of laboratory-simulated falls, activities of daily living (ADL), and near-falls. In the first study, a wrist-based fall detection algorithm for a commercially available smartwatch was proposed. The algorithm used forearm angle to filter the forearm’s downward vertical orientation that could be associated to a non-fall event’s post-activity position. Additionally, to deal with disturbance in barometric pressure data during dynamic motion, barometric pressure was used selectively in a Kalman filter. The algorithm gave 100% sensitivity, 97.2% ADL specificity, and 97.1% non-fall (i.e. including both ADLs and near-falls) specificity. In the second study, the addition of either difference in altitude or average vertical velocity to a trunk-based algorithm that uses vertical velocity + vertical acceleration + trunk-angle (base algorithm) was investigated. The experimental results show that adding either difference in altitude or average vertical velocity was able to increase the algorithm’s non-fall specificity from 91.8% to 98.0% and 99.6%, respectively

Physical and recreational wellness

Physical Education Department Chair Martin Ronda talked about physical and recreational wellness during a discussion on Wellness: your edge to living. Other speakersweare Eric Musngi from the Parents of University Students Organization and Msgr. Augusto Pedrosa

Feasibility of Automatic Detection of High-Frequency Oscillations in Human Tripolar Laplacian Electroencephalogram Using Exponentially Embedded Family

Epilepsy affects approximately 67 million people worldwide with up to 75% from developing countries. Diagnosing epilepsy using electroencephalogram (EEG) is complicated due to its poor signal-to-noise ratio, high sensitivity to various forms of artifacts, and low spatial resolution. Laplacian EEG signal via novel and noninvasive tripolar concentric ring electrodes (tEEG) is superior to EEG via conventional disc electrodes due to its unique capabilities, which allow automatic attenuation of common movement and muscle artifacts. In this work, we apply exponentially embedded family (EEF) to show feasibility of automatic detection of gamma band high-frequency oscillations (HFOs) in tEEG data from two human patients with epilepsy as a step toward the ultimate goal of using the automatically detected HFOs as auxiliary features for seizure onset detection to improve diagnostic yield of tEEG for epilepsy. Obtained preliminary results suggest the potential of the approach and feasibility of detecting HFOs in tEEG data using the EEF based detector with high accuracy. Further investigation on a larger dataset is needed for a conclusive proof

Recent Advances in High-Frequency Oscillations and Seizure Onset Detection Using Laplacian Electroencephalography via Tripolar Concentric Ring Electrodes

Laplacian electroencephalogram signal from novel and noninvasive tripolar concentric ring electrodes has been demonstrated to have superior performance compared to the electroencephalogram from conventional disc electrodes due to its unique capabilities which allow automatic attenuation of common movement and muscle artifacts in applications including brain-computer interface, seizure onset detection, and detection of high-frequency oscillations and seizure onset zones. This review paper covers the recent advances in the fields of high-frequency oscillations and seizure onset detection based on tripolar Laplacian electroencephalography in animal models and human data to improve the diagnostic yield of electroencephalography for epilepsy. Progression of methodologies utilized including integration of multiple sensors using exponentially embedded families and results obtained including a comparison to the results of others as well as to the performance of the same detector on simultaneously recorded electroencephalogram via conventional disc electrodes is discussed in detail. Specific advantages of using this particular sensor for these particular applications are highlighted. Promising directions for the future work and an overview of currently ongoing research are discussed along with the potential of combining the two detectors and using automatically detected high-frequency oscillations that have been shown to be indicative of early seizure development as auxiliary features for the seizure onset detection