La lecture en ligne est gratuite
Le téléchargement nécessite un accès à la bibliothèque YouScribe
Tout savoir sur nos offres
Télécharger Lire

Investigation of electrodes as bidirectional human machine interface for neuro-technical control of prostheses [Elektronische Ressource] / Thilo B. Krüger

De
251 pages
Investigation of Electrodes as Bidirectional Human Machine Interface for Neuro-Technical Control of Prostheses Dissertation zur Erlangung des Doktorgrades der Technischen Fakultät der Albert-Ludwigs-Universität Freiburg im Breisgau Dipl.-Ing. Thilo B. Krüger 2009 Laboratory for Biomedical Microtechnology Department of Microsystems Engineering (IMTEK) University of Freiburg Georges-Koehler-Allee 102 79110 Freiburg Germany Author Dipl.-Ing. Thilo B. Krüger Page Title Schematic of different afferent stimuli, automatically decoded Dean: Prof. Dr. H. Zappe 1. Referee: Prof. Dr. T. Stieglitz 2. Referee: Prof. Dr. G. Bretthauer Chairman: Prof. Dr. G. Paul Assessor: Prof. Dr. G. Urban thDate of the examination: 16 November 2009 Abstract Neuroprostheses have found their place in the field of medically untreatable neuronal diseases and in neural rehabilitation to replace lost sensory or motor functions. Often available neuroprostheses provide only the possibility of a forward control without a feedback for the patient. The pursuit of this PhD is to establish a bidirectional link between man and machine. Electrodes are the main component of a neuro-interface and they are researched in their behavior and possible optimization. All necessary components of a bidirectional interface are identified as peripheral nerve, contacting electrodes, analog electric circuitry and digital processing units.
Voir plus Voir moins




Investigation of Electrodes as Bidirectional Human
Machine Interface for Neuro-Technical Control of
Prostheses



Dissertation zur Erlangung des Doktorgrades der
Technischen Fakultät
der Albert-Ludwigs-Universität Freiburg im
Breisgau

Dipl.-Ing. Thilo B. Krüger
2009


Laboratory for Biomedical Microtechnology
Department of Microsystems Engineering (IMTEK)
University of Freiburg
Georges-Koehler-Allee 102
79110 Freiburg
Germany


Author Dipl.-Ing. Thilo B. Krüger
Page Title Schematic of different afferent stimuli, automatically decoded



Dean: Prof. Dr. H. Zappe

1. Referee: Prof. Dr. T. Stieglitz
2. Referee: Prof. Dr. G. Bretthauer
Chairman: Prof. Dr. G. Paul
Assessor: Prof. Dr. G. Urban

th
Date of the examination: 16 November 2009

Abstract
Neuroprostheses have found their place in the field of medically untreatable
neuronal diseases and in neural rehabilitation to replace lost sensory or motor
functions. Often available neuroprostheses provide only the possibility of a forward
control without a feedback for the patient. The pursuit of this PhD is to establish a
bidirectional link between man and machine. Electrodes are the main component
of a neuro-interface and they are researched in their behavior and possible
optimization. All necessary components of a bidirectional interface are identified as
peripheral nerve, contacting electrodes, analog electric circuitry and digital
processing units. A recorded neural signal reveals not all available information at
once. For this purpose high sophisticated signal processing routines were used.
An automatic signal processing chain, including electrodes, analog signal
conditioning, and analog to digital conversion was established. Digital processing
algorithms were optimized to recognize automatically different events in the
afferent neural signals and discriminate them with high accuracy. The decoding of
afferent neural signals is estimated as one last important missing link to establish
a reliable neuro-interface. With sufficient afferent decoding working this thesis
proved that a robust bidirectional interface to the peripheral nervous system is
possible.
IX

X
Zusammenfassung
Neuroprothesen haben ihren Platz im Bereich von medikamentös nicht
therapierbaren neuronalen Krankheiten ebenso gefunden wie in der neuronalen
Rehabilitation, um verloren gegangene Funktionen der Sinne oder Motorik zu
ersetzen. Oftmals bieten erhältliche Neuroprothesen nur die Möglichkeit einer
Steuerung ohne dem Patienten eine Rückkopplungsmöglichkeit zur Verfügung zu
stellen. Das Ziel dieser Doktorarbeit ist es, eine bidirektionale Verbindung
zwischen Mensch und Maschine aufzubauen. Die Elektroden sind die
Hauptkomponente einer Neuro-technischen Schnittstelle und werden daher auf
ihre Eigenschaften und eine mögliche Optimierung hin untersucht. Als benötigte
Komponenten einer bidirektionalen Schnittstelle seien der periphere Nerv,
kontaktierende Elektroden, analoge Schaltungstechnik und digitale
Verarbeitungsroutinen genannt. Ein einfach aufgenommenes neuronales Signal
stellt nicht alle darin erhaltene Information auf den ersten Blick dar. Für diesen
Zweck wurden hoch entwickelte Signalverarbeitungsroutinen verwendet. Eine
automatische Verarbeitungskette, bestehend aus Elektroden, analoger
Signalaufbereitung und Analog-Digital Wandlung wurde aufgestellt. Digitale
Signalverarbeitungsroutinen wurden optimiert, um automatisch verschiedene
Ereignisse in einem afferenten Nervensignal zu erkennen. Die Detektion konnte so
erfolgreich mit einer hohen Genauigkeit realisiert werden. Die Dekodierung von
neuronalen Signalen wurde als eine letzte fehlende wichtige Verbindung
angesehen, um eine verlässliche Neuro-Schnittstelle zu etablieren. Mit der
Dekodierung von afferenten Signalen zeigt diese Arbeit, dass eine stabile
bidirektionale Schnittstelle zum peripheren Nervensystem möglich ist.
XI



XII
Table of Contents
Abstract IX
Zusammenfassung XI
Table of Contents XIII
List of Figures XVIII
List of Tables XXI
Glossary XXII

1 Introduction 1
1.1 Problem ..................................................................................................2
1.2 Scientific Objectives ...............................................................................3
2 Physiology - to understand Neural Prostheses 5
2.1 Nervous System .....................................................................................6
2.2 Peripheral Nervous System....................................................................7
2.2.1 Information Transfer...................................................................8
2.2.2 Classification of Nerves ...........................................................10
2.2.3 Pathology and Degeneration of Nerves ...................................11
2.3 Muscular System..................................................................................11
2.4 Bioelectrical Signals .............................................................................13
3 Electrodes as Neuro-Technical Interface 17
3.1 Coupling Overview ...............................................................................17
3.2 Electrochemical Processes ..................................................................19
3.2.1 Phase Boundary ......................................................................19
3.2.2 Polarization of the Interface .....................................................21
3.3 Electrical Stimulation ............................................................................23
3.3.1 Stimulation Methods ................................................................26
3.3.2 Different Pulse Shapes ............................................................26

XIII


3.4 Electrode Interfaces............................................................................. 27
3.4.1 Non Invasive Electrodes - Surface Electrodes ........................ 29
3.4.2 Muscle Electrodes - Epimysial and Intramuscular Electrodes. 30
3.4.3 Extraneural Electrodes............................................................ 31
3.4.4 Intraneural Electrodes............................................................. 34
3.4.5 Bioelectronic Interfaces........................................................... 39
3.5 Electrode Geometry............................................................................. 41
3.6 Mechanical and Electrical Characterization ......................................... 42
4 System Analysis and Signal Processing 44
4.1 System Identification............................................................................ 44
4.2 Considerations from Communications Theory..................................... 46
4.3 Signal Processing................................................................................ 49
4.3.1 Signal definition....................................................................... 50
4.3.2 Filtering ................................................................................... 51
4.3.3 Analog Filtering ....................................................................... 51
4.3.4 Control by threshold detection ................................................ 54
4.3.5 Analog Digital Conversion....................................................... 54
4.3.6 Feature Extraction................................................................... 55
4.3.7 Features in Time Domain........................................................ 56
4.3.8 Features in Frequency Domain............................................... 57
4.3.9 Principal Component Analysis ................................................ 59
4.3.10 Onset Detection ...................................................................... 61
4.3.11 Classification........................................................................... 62
4.3.12 Artificial Neural Networks........................................................ 66
4.3.13 Outcome of Signal Processing................................................ 67
5 Implants and Artifacts 68
5.1 Implant Signal Transmission................................................................ 68
5.2 Electrical Stimulation as Information Input........................................... 70
5.3 Biocompatibility.................................................................................... 70


XIV
5.4 Exemplary Implants..............................................................................71
5.4.1 Precision Mechanics – Freehand System................................71
5.4.2 Stiff Hermetic Housing – Bionic Neuron...................................72
5.4.3 Microsystem Technology - Cortical Applications......................73
5.4.4 Flexible Substrates - Retinal Implant .......................................74
5.5 Controllable Artifacts ............................................................................74
5.5.1 Actuators..................................................................................77
5.5.2 Sensors....................................................................................77
5.5.3 Further Approaches for Control ...............................................77
6 Own Approach 80
6.1 Scientific Aims ......................................................................................80
6.2 Goals of this Thesis..............................................................................81
7 Modules for Bidirectional Signal Transmission 83
7.1 Modeling the Signal Flow .....................................................................84
7.2 Data Needed and Available..................................................................85
7.3 Adequate and non Adequate Control Signals.......................................86
7.4 System Borders, Input and Output Parameters....................................87
7.4.1 Information Flow ......................................................................87
7.4.2 Modularity ................................................................................89
7.4.3 Robustness..............................................................................89
7.4.4 Parameters ..............................................................................90
8 Characterization of Electrodes 91
8.1 Electrode Designs ................................................................................92
8.1.1 Electrochemical Effects at the Interface...................................94
8.1.2 Spectroscopy of Electrodes .....................................................94
8.1.3 Electrical Field Distribution.......................................................95
8.2 Three Dimensional Characterization ....................................................96
8.2.1 Measured Electrode Types......................................................96
8.2.2 Characterization by Stimulation ...............................................97
8.2.3 Electrical Potential Field Scanner Measurement Setup ...........98
8.2.4 Effects at Test Electrodes........................................................99
XV

8.3 Electrode Simulation.......................................................................... 101
8.3.1 Simulated Field Distribution .................................................. 103
8.4 Results of Characterization and Simulation ....................................... 104
8.4.1 Measured Potential Field Distribution.................................... 105
8.4.2 Investigation of the Phase Boundary .................................... 106
8.4.3 Simulated Potential Field Distribution.................................... 108
8.4.4 Activation Function................................................................ 110
8.4.5 Comparison of Measurement and Simulation ....................... 113
8.5 Assessment of Results ...................................................................... 115
8.6 Safe Stimulation Parameters ............................................................. 118
8.6.1 Electrical Characterization .................................................... 120
8.6.2 Stimulation Parameters – Cell Environment.......................... 121
8.6.3 Stimulation Parameters......................................................... 123
9 Design and Development of Interfaces 128
9.1 Electrode System Fabrication............................................................ 128
9.2 Amplification and Filtering.................................................................. 134
9.3 Recording, Data Acquisition & Storage.............................................. 137
9.3.1 Analog to Digital Converters ................................................. 138
9.3.2 Integration of Amplifier and Converter .................................. 139
9.4 Neuro-Stimulator................................................................................ 140
9.5 Modular System for Neuro-Technical Interfaces................................ 143
10 Decoding of Natural Sensor Information 144
10.1 Experimental Setup ........................................................................... 144
10.2 Signal Processing Chain.................................................................... 148
10.3 Signal Processing of Neural Signals.................................................. 149
10.4 Feature based processing ................................................................. 150
10.4.1 Digital Filtering of Neural Signals .......................................... 152
10.4.2 Feature Calculation............................................................... 153
10.4.3 Onset Detection in Neural Signals ........................................ 155
10.4.4 Principal Component Analysis of Features ........................... 156
10.4.5 Classification of Neural Activity ............................................. 158

XVI

Un pour Un
Permettre à tous d'accéder à la lecture
Pour chaque accès à la bibliothèque, YouScribe donne un accès à une personne dans le besoin