Counterpulsation cardiac assist device controller defection filter simulation and canine experiments

Electronic control systems for counterpulsation Cardiac Assist Devices (CADs) are an essential part of cardiac assistance. Synchronization of the counterpulsation CAD controller with the cardiac cycle is critical to the efficacy of the CAD. The robustness of counterpulsation CAD controllers varies with the ability of the CAD controller to properly trigger on aortic pressure (Pa) and electrocardiogram (ECG) signals for sinusoid rhythms, non-sinusoid rhythms and non-ideal signals resulting from surgical intervention. An analog-to-digital converter and digital-to-analog converter based CAD controller development platform was devised on a 33Mhz PC-AT. Counterpulsation Pa systolic rise and dicrotic notch detectors were demonstrated with a 15cc pediatric Intraaortic Balloon (IAB) and 50cc Extraaortic Counterpulsation Device (EACD) CADs using mongrel canine experimental models in which biological variation due to changing heart rate and arrhythmia as well as surgical interference due to mechanical ventilation, electrocautery, signal attenuation and random noise was present. The robust Pa triggering algorithm was based on a derivative comparator riding clipper algorithm for the Pa-based controller. In order to empirically determine the robustness of the Pa triggering algorithms, a simulation platform, Pa trace model, and Pa trace artifact and physiological variation models were devised. Each set of simulation experiments utilized a different Pa trace artifact or physiological variation model to determine the capability of the Pa trigger algorithm to withstand the effects of the Pa detection impediments while maintaining 100% accuracy of the dicrotic notch detection. Multiple simulation experiments were conducted in which the same nominally adjusted interference was increased to benchmark the immunity threshold of the dicrotic notch detector. Biological variation and deviations in Pa artifacts due to clinical conditions experienced in cardiothoracic surgery were investigated. Pa triggering was unhindered by biological variation of a Pa trace with a 3 mmHg dicrotic notch deflection along with a Pa trace with no dicrotic notch deflection present. Pa triggering was unhindered by heart rate variability ranging from 60 to 80 bpm due to respiration. Pa triggering was unhindered by clinical conditions including 40 mmHg changes in the Pa baseline modeling mechanical ventilation, aortic trace attenuation modeling variations in pressure transducer positioning and blood coagulation on the pressure catheter tip ranging from 100% to 200% of the Pa trace amplitude every four seconds, uniformly distributed noise with a mean of 0.5mmHg and standard deviation of 0.289mmHg and Gaussian distributed noise with a zero mean and standard deviation of 0.6nunHg. The results of the simulation experiments performed quantified the robustness of the Pa detection algorithm. Development of a fault tolerant counterpulsation CAD control system required the development of a robust ECG triggering algorithm to operate in tandem with the Pa triggering algorithm. An ECG detector was developed to provide robust control for a range of ECG traces due to biological variation and signal interference. The ECG R-wave detection algorithm is based on a modified version of the Washington University QRS-complex DD/1 algorithm (Detection and Delineation 1) which uses the associated AZTEC (Amplitude Zero Threshold Epic Coding) preprocessing algorithm and provides accurate ECG-based CAD control R-wave detection for 96.56% of the R-waves stored within the MIT/BIH ECG Arrhythmia database with a maximum detection delay of 8 milliseconds. Further IAB experiments performed with mongrel canine experimental models demonstrated that the systolic time interval to heart rate relationship existing in humans (essential to human patient CAD control inflation prediction) is not prevalent in canine mongrels particularly when treated with beta-blockers. In order to execute both Pa and ECG C software detection algorithms for a fault tolerant counterpulsation CAD controller, investigation into the communications throughput of a quad-transputer board was performed. Development of streamlined communication primitives led to a communication processor utilization of 8.3%, deemed efficient enough for fault tolerant multiprocessor CAD control implementation

National Aeronautics and Space Administration (NASA)/American Society for Engineering Education (ASEE) Summer Faculty Fellowship Program, 1993, volume 1

The JSC NASA/ASEE Summer Faculty Fellowship Program was conducted by Texas A&M University and JSC. The objectives of the program, which began nationally in 1964 and at JSC in 1965, are as follows: (1) to further the professional knowledge of qualified engineering and science faculty members; (2) to stimulate an exchange of ideas between participants and NASA; (3) to enrich and refresh the research and teaching activities of participants' institutions; and (4) to contribute to the research objectives of the NASA centers. Each faculty fellow spent at least 10 weeks at JSC engaged in a research project in collaboration with a NASA/JSC colleague. This document is a compilation of the final reports on the research projects completed by the faculty fellows during the summer of 1993

Parallel processing for fault tolerant aircraft control.

This thesis addresses the problem of real-time optimal control of aircraft systems using parallel processing techniques. It is shown that transputer hardware can be used in designing a suitable optimal controller for general nonlinear time-varying aircraft. In the first part of the thesis, nonlinearties and time varying aspects of the aircraft system, together with the current available solutions are investigated and suitable designs presented. Here the linear regulator approach for linear time-varying aircraft is investigated first but it is shown that real-time performance is difficult to achieve. The problem is then approached differently in that the aircraft is considered as a linear time-invariant system for short time intervals and it is then found possible to implement an optimal control solution in real-time, and suitable multi-transputer architectures are presented. The receding/moving horizon approach is applied to the aircraft system and is shown to be adequate for achieving satisfactory results. The problem of selection of the weights in the performance index of the optimal control problem is then studied and a design procedure is presented. The modeling of the aircraft as decoupled longitudinal and lateral dynamics is investigated and approached in such a way as to reduce the cross-coupling effects. Another important aspect of this research involves the consideration of failure detection and diagnosis in the aircraft hardware. Problems including actuator failure are studied and some remedial methods for handling the failures by enabling system reconfiguration after the occurrence of the failure are presented. The multi-processor based control system design is shown to offer a viable solution to solving complicated optimisation problems without the need for the simplification of the system dynamical equations and thereby loosing accuracy. Such simplification is usually a prerequisite for enabling practical designs. However with the use of parallel processing techniques such designs can be achieved for the more complicated (and more computationally demanding) cases as well

Optimized Biosignals Processing Algorithms for New Designs of Human Machine Interfaces on Parallel Ultra-Low Power Architectures

The aim of this dissertation is to explore Human Machine Interfaces (HMIs) in a variety of biomedical scenarios. The research addresses typical challenges in wearable and implantable devices for diagnostic, monitoring, and prosthetic purposes, suggesting a methodology for tailoring such applications to cutting edge embedded architectures. The main challenge is the enhancement of high-level applications, also introducing Machine Learning (ML) algorithms, using parallel programming and specialized hardware to improve the performance. The majority of these algorithms are computationally intensive, posing significant challenges for the deployment on embedded devices, which have several limitations in term of memory size, maximum operative frequency, and battery duration. The proposed solutions take advantage of a Parallel Ultra-Low Power (PULP) architecture, enhancing the elaboration on specific target architectures, heavily optimizing the execution, exploiting software and hardware resources. The thesis starts by describing a methodology that can be considered a guideline to efficiently implement algorithms on embedded architectures. This is followed by several case studies in the biomedical field, starting with the analysis of a Hand Gesture Recognition, based on the Hyperdimensional Computing algorithm, which allows performing a fast on-chip re-training, and a comparison with the state-of-the-art Support Vector Machine (SVM); then a Brain Machine Interface (BCI) to detect the respond of the brain to a visual stimulus follows in the manuscript. Furthermore, a seizure detection application is also presented, exploring different solutions for the dimensionality reduction of the input signals. The last part is dedicated to an exploration of typical modules for the development of optimized ECG-based applications

Research and technology

Significant research and technology activities at the Johnson Space Center (JSC) during Fiscal Year 1990 are reviewed. Research in human factors engineering, the Space Shuttle, the Space Station Freedom, space exploration and related topics are covered

Bibliography of Lewis Research Center technical publications announced in 1992

This compilation of abstracts describes and indexes the technical reporting that resulted from the scientific and engineering work performed and managed by the Lewis Research Center in 1992. All the publications were announced in the 1992 issues of STAR (Scientific and Technical Aerospace Reports) and/or IAA (International Aerospace Abstracts). Included are research reports, journal articles, conference presentations, patents and patent applications, and theses

Evaluation of EEG-based depth of anaesthesia monitoring

In 2001 a University of Bristol team patented a novel data reduction method of the EEG for characterising categorical changes in consciousness. After pre-whitening the EEG signal with Gaussian white noise a parametric spectral estimation technique was applied. Two frequency domain indices were then proposed: the relative power found between 8Hz to 12Hz and 0.5Hz to 32Hz termed the 'alpha index', and the relative power between 0.5Hz to 4Hz and 0.5Hz to 32Hz termed the 'delta index'. The research and development of a precision EEG monitoring device designed to embody the novel algorithm is described in this thesis. The efficacy of the technique was evaluated using simulated and real EEG data recorded during Propofol anaesthesia. The simulated data showed improvements could be made to the patented method. Real EEG data collected whilst patients were wakeful and data from patients unresponsive to noxious stimuli were cleaned of obvious artefacts and analysed using the proposed algorithm. A Bayesian diagnostic test showed the alpha index had 65% sensitivity and selectivity to patient state. The delta index showed 72% sensitivity and selectivity. Taking a pragmatic approach, the literature is reviewed in this thesis to evaluate the use of EEG in depth of anaesthesia monitoring. Pertinent aspects of the sciences are profiled to identify physiological links to the characteristics of the EEG signal. Methods of data reduction are also reviewed to identify useful features and possible sources of error. In conclusion it is shown that the proposed indices do not provide a robust measure of depth of anaesthesia. An approach for further research is proposed based on the review work.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Industrial Robotics

This book covers a wide range of topics relating to advanced industrial robotics, sensors and automation technologies. Although being highly technical and complex in nature, the papers presented in this book represent some of the latest cutting edge technologies and advancements in industrial robotics technology. This book covers topics such as networking, properties of manipulators, forward and inverse robot arm kinematics, motion path-planning, machine vision and many other practical topics too numerous to list here. The authors and editor of this book wish to inspire people, especially young ones, to get involved with robotic and mechatronic engineering technology and to develop new and exciting practical applications, perhaps using the ideas and concepts presented herein