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

Study on training of a statistical acoustic model for speech recognition

制度:新 ; 文部省報告番号:乙1419号 ; 学位の種類:博士(情報科学) ; 授与年月日:1999/2/4 ; 早大学位記番号:新2744 ; 理工学図書館請求番号:2310本文PDFは平成22年度国立国会図書館の学位論文(博士)のデジタル化実施により作成された画像ファイルをPDFに変換したものである

Optical measurement and signal evaluation relating to particulate properties during purification of biological suspensions

The variable nature of conditions in downstream processing operations in biotechnological and other areas necessitates the on-line monitoring of process variables for rapid analysis and possibly subsequent control to optimise yield in a multi-stage purification process. Optical measurement of such parameters offers a fast and non-invasive method to interrogate the process with the added advantage of the possibility to construct a robust, miniaturised measurement system using modern optical components. The problems encountered are turbulent and turbid conditions which are usually unsuitable for light scattering measurements. Also access to the process stream is often not simple and a method of automatic sampling must be employed. This thesis describes the application of dynamic light scattering to downstream processing operations and particularly to the measurement of virus-like particles and separation from their yeast host. The construction of a miniaturised dynamic light scattering system is also described. Several data analysis methods are assessed with a view to using them in a rapid analysis configuration. Most of the methods require moderate processing power but consideration is given to extensions to the standard techniques to apply them in a parallel processing environment which today is on the increase. The improvement of the convergence of such routines is discussed with the addition of prior information. A particular area of interest is the rapid sample preparation required before analysis by light scattering to improve the data quality. Large particulate material is usually not tolerated well in this method of measurement and should be removed. A technique is described and tested which facilitates rapid in-situ sample preparation and optical analysis. Otherwise sample preparation is carried out prior to analysis. As well as a dynamic light scattering study, an overview of optical measurement by other means in yeast-based systems is discussed with a view to optimising the system configuration

Aeropropulsion 1987

Papers from the Aeropropulsion '87 Conference, held at the NASA Lewis Research Center (LeRC), are presented. Unclassified presentations by LeRC and NASA Headquarters senior management and many LeRC technical authors covered the philosophy and major directions of the LeRC aeropropulsion program, and presented a broad spectrum of recent research results in materials, structures, internal fluid mechanics, instrumentation and controls, and both subsonic and high-speed propulsion technology

Bibliography of Lewis Research Center technical publications announced in 1993

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 1993. All the publications were announced in the 1993 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

XXIII Congreso Argentino de Ciencias de la Computación - CACIC 2017 : Libro de actas

Trabajos presentados en el XXIII Congreso Argentino de Ciencias de la Computación (CACIC), celebrado en la ciudad de La Plata los días 9 al 13 de octubre de 2017, organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y la Facultad de Informática de la Universidad Nacional de La Plata (UNLP).Red de Universidades con Carreras en Informática (RedUNCI

Brain Computations and Connectivity [2nd edition]

This is an open access title available under the terms of a CC BY-NC-ND 4.0 International licence. It is free to read on the Oxford Academic platform and offered as a free PDF download from OUP and selected open access locations. Brain Computations and Connectivity is about how the brain works. In order to understand this, it is essential to know what is computed by different brain systems; and how the computations are performed. The aim of this book is to elucidate what is computed in different brain systems; and to describe current biologically plausible computational approaches and models of how each of these brain systems computes. Understanding the brain in this way has enormous potential for understanding ourselves better in health and in disease. Potential applications of this understanding are to the treatment of the brain in disease; and to artificial intelligence which will benefit from knowledge of how the brain performs many of its extraordinarily impressive functions. This book is pioneering in taking this approach to brain function: to consider what is computed by many of our brain systems; and how it is computed, and updates by much new evidence including the connectivity of the human brain the earlier book: Rolls (2021) Brain Computations: What and How, Oxford University Press. Brain Computations and Connectivity will be of interest to all scientists interested in brain function and how the brain works, whether they are from neuroscience, or from medical sciences including neurology and psychiatry, or from the area of computational science including machine learning and artificial intelligence, or from areas such as theoretical physics