Brain Energy Metabolism:
Brain Energy Metabolism addresses its challenging subject by presenting diverse technologies allowing for the investigation of brain energy metabolism on different levels of complexity. Model systems are discussed, starting from the reductionist approach like primary cell cultures which allow assess...
Gespeichert in:
| Weitere Verfasser: | , |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer New York
2014
|
| Schriftenreihe: | Neuromethods
90 |
| Schlagworte: | |
| Online-Zugang: | UBR01 TUM01 URL des Erstveröffentlichers Inhaltsverzeichnis |
| Zusammenfassung: | Brain Energy Metabolism addresses its challenging subject by presenting diverse technologies allowing for the investigation of brain energy metabolism on different levels of complexity. Model systems are discussed, starting from the reductionist approach like primary cell cultures which allow assessing of the properties and functions of a single brain cell type with many different types of analysis, however, at the expense of neglecting the interaction between cell types in the brain. On the other end, analysis in animals and humans in vivo is discussed, maintaining the full complexity of the tissue and the organism but making high demands on the methods of analysis. Written for the popular Neuromethods series, chapters include the kind of detailed description and key implementation advice that aims to support reproducible results in the lab. Meticulous and authoritative, Brain Energy Metabolism provides an ideal guide for researchers interested in brain energy metabolism with the hope of stimulating more research in this exciting and very important field |
| Beschreibung: | 1 Online-Ressource (XIV, 368 p. 97 illus., 52 illus. in color) |
| ISBN: | 9781493910595 |
| DOI: | 10.1007/978-1-4939-1059-5 |
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| 520 | |a Brain Energy Metabolism addresses its challenging subject by presenting diverse technologies allowing for the investigation of brain energy metabolism on different levels of complexity. Model systems are discussed, starting from the reductionist approach like primary cell cultures which allow assessing of the properties and functions of a single brain cell type with many different types of analysis, however, at the expense of neglecting the interaction between cell types in the brain. On the other end, analysis in animals and humans in vivo is discussed, maintaining the full complexity of the tissue and the organism but making high demands on the methods of analysis. Written for the popular Neuromethods series, chapters include the kind of detailed description and key implementation advice that aims to support reproducible results in the lab. Meticulous and authoritative, Brain Energy Metabolism provides an ideal guide for researchers interested in brain energy metabolism with the hope of stimulating more research in this exciting and very important field | ||
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Datensatz im Suchindex
| _version_ | 1804178538472931328 |
|---|---|
| adam_text | CONTENTS
ABSTRACT III
ACKNOWLEDGEMENTS VII
LIST OF FIGURES XV
LIST OF TABLES XXI
I. INTRODUCTION AND BACKGROUNDS 1
1. INTRODUCTION 3
1.1. PROBLEM DEFINITION 3
1.1.1. USABILITY EVALUATIONS 4
1.1.2. HUMAN COMPUTER INTERACTIONS 5
1.2. RESEARCH OBJECTIVES 6
1.3. CONTRIBUTIONS 7
1.4. OVERVIEW OF THE DISSERTATION ORGANIZATION 9
2. OPERATING ROOM DOMAIN MODEL 11
2.1. INTRODUCTION 11
2.2. COMPLEX DOMAINS 12
2.3. COMPLEXITY IN THE OPERATING ROOM 14
HTTP://D-NB.INFO/1036388859
CONTENTS
2.4. DOMAIN MODELING APPROACH 16
2.4.1. MAIN COMPONENTS 16
2.4.2. DOMAIN MODEL CONSTRUCTION 18
2.5. MODELING THE OPERATING ROOM 18
2.5.1. SURGICAL WORKFLOW 19
2.5.2. HUMAN ROLES 20
2.5.3. INTRA-OPERATIVE DEVICES 21
2.5.4. MAPPING TABLES 21
2.6. SUMMERY AND CONCLUSION 23
I
*4
II. INTRA-OPERATIVE USABILITY EVALUATIONS 25
3. BACKGROUND AND RELATED WORK 27
3.1. INTRODUCTION 27
3.1.1. USABILITY 28
3.1.2. USABILITY ENGINEERING 29
3.2. EVALUATION METHODS 30
3.2.1. TESTING METHODS 30
3.2.2. INSPECTION METHODS 33
3.2.3. INQUIRY METHODS 33
3.2.4. ANALYTICAL MODELING METHODS 34
3.2.5. SIMULATION METHODS 34
3.3. USABILITY EVALUATIONS IN COMPLEX DOMAINS 34
3.3.1. SPECIFIC CHALLENGES FOR USABILITY TESTING 35
3.4. USABILITY EVALUATIONS OF MEDICAL DEVICES 35
3.4.1. USABILITY FOR
MEDICAL STAFF 36
3.4.2. BEST PRACTICE IN MEDICAL DOMAIN 36
3.4.3. REGULATORY CONSTRAINTS 37
3.5. USABILITY EVALUATIONS SUPPORT TOOLS 37
3.6. SUMMERY AND CONCLUSION 38
4. OR-USE FRAMEWORK 39
4.1. INTRODUCTION 39
4.2. REQUIREMENTS SPECIFICATIONS 40
4.2.1. USABILITY TESTING REQUIREMENTS 40
4.2.2. NON-FUNCTIONAL REQUIREMENTS 42
X
CONTENTS
4.3. ARCHITECTURE OVERVIEW 43
4.4. USABILITY DATA ACQUISITION 43
4.4.1. PERFORMANCE LOG
CONVERSION TOOL 43
4.4.2. ON-SITE ANNOTATION TOOL 44
4.5. CLIENT-SERVER ARCHITECTURE 49
4.5.1. DATA TRANSFER
AND MESSAGING PROTOCOL 49
4.5.2. USABILITY DATA MANAGEMENT
SERVICE 50
4.5.3. SERVER SIDE USABILITY DATA
PROCESSING 51
4.6. USABILITY DATA MANAGEMENT 51
4.6.1. DATA BINDING 51
4.6.2. DESIGN OF DATABASE 53
4.6.3. STRUCTURE OF DATAPOOL 55
4.7. USABILITY DATA RETRIEVAL 55
4.8. TECHNOLOGY 56
4.8.1. ANDROID PLATFORM 56
4.8.2. XML WEB SERVICES 57
4.8.3. RELATIONAL DATABASE 58
4.9. SUMMERY AND CONCLUSION 58
5. USABILITY DATA VISUALIZATION TO SUPPORT ANALYSIS 59
5.1. INTRODUCTION 59
5.1.1. INFORMATION VISUALIZATION 60
5.1.2. USABILITY DATA VISUALIZATION 60
5.2. DOMAIN MODELING 62
5.2.1. USABILITY DATA BINDING 63
5.3. USABILITY DATA VISUALIZATION USING PIVOT 63
5.3.1. PIVOT WEB SERVICE 64
5.3.2. USABILITY DATA FACETS 65
5.3.3. VISUAL REPRESENTATION 67
5.3.4. VIDEO INDEXING 67
5.4. APPLICATION IN ANALYSIS 67
5.5. SUMMERY AND CONCLUSION 67
6. CASE STUDIES AND EVALUATIONS 69
6.1. INTRODUCTION 69
XI
CONTENTS
6.2. DOMAIN MODELING 69
6.2.1. HUMAN ROLES 70
6.2.2. INTRA-OPERATIVE SPECT IMAGING DEVICE 70
6.2.3. SLNB WORKFLOW 71
6.2.4. VIEW MAPPINGS 72
6.3. CASE STUDY 1: SYNTHETIC OPERATING ROOM 73
6.3.1. OBJECTIVES 73
6.3.2. STUDY DESIGN 73
6.3.3. CONDUCTING THE TEST 75
6.3.4. ANALYSIS AND INTERPRETATION . ; 76
6.4. CASE STUDY 2: REAL OPERATING ROOM 80
6.4.1. OBJECTIVES 81
6.4.2. STUDY DESIGN 81
6.4.3. ANALYSIS AND INTERPRETATION 82
6.5. TOOLS EFFECTIVENESS 83
6.6. USABILITY OF ON-SITE ANNOTATION TOOL 84
6.7. PERFORMANCE EVALUATIONS 85
6.7.1. USABILITY DATA GROWTH 85
6.7.2. UPLOAD AND PROCESSING TIME 87
6.8. SUMMERY AND CONCLUSION 89
III. INTRA-OPERATIVE HUMAN COMPUTER INTERACTION DESIGN 91
7. CATEGORICAL AND SPATIO-TEPORAL GESTURING 93
7.1. INTRODUCTION 93
7.1.1. THE USER
INTERFACE 94
7.1.2. CUSTOMIZATION REQUIREMENTS 95
7.2. RELATED WORK 96
7.3. SIMULTANEOUS CATEGORICAL AND SPATIO-TEMPORAL GESTURES 97
7.4. INPUT MODALITIES 98
7.4.1. INERTIAL ORIENTATION SENSORS 99
7.4.2. MICROSOFT KINECT 100
7.5. GESTURE RECOGNITION METHODS 101
7.5.1. MODELING GESTURES 102
7.5.2. PRINCIPLE COMPONENT ANALYSIS 103
XII
CONTENTS
7.5.3. NON-LINEAR MANIFOLD
LEARNING 105
7.6. SENSOR DATA AND FEATURE EXTRACTION ILL
7.6.1. FEATURE REPRESENTATIONS ILL
7.6.2. FEATURE NORMALIZATIONS 113
7.7. SUMMERY AND CONCLUSION 114
8. SIGNAL.NET FRAMEWORK 115
8.1. INTRODUCTION 115
8.2. RELATED WORK 116
8.3. CLINICAL USE-CASE 119
8.4. REQUIREMENTS SPECIFICATIONS 119
8.4.1. CUSTOMIZATION 120
8.4.2. WORKFLOW-AWARENESS 120
8.4.3. MULTIPLE USERS 120
8.4.4. INTEGRATION OF GESTURING 121
8.5. FRAMEWORK ARCHITECTURE 121
8.5.1. HETEROGENEOUS COMPONENTS 121
8.5.2. BINDINGS AND DATA PIPELINE 122
8.5.3. CONFIGURATION MANAGEMENT 123
8.5.4. VISUAL PROGRAMMING INTERFACE 124
8.6. GESTURING COMPONENTS 125
8.6.1. SENSOR COMPONENTS 127
8.6.2. TARGET COMPONENTS 127
8.6.3. RECOGNITION COMPONENTS 128
8.6.4. DEMULTIPLEXER COMPONENTS 128
8.6.5. ACTIVATION CONTROL 128
8.7. COMPONENT DATABASE 129
8.7.1. IMPLEMENTATION 129
8.8. CONTEXT-AWARENESS 130
8.9. METHODOLOGICAL APPROACH 131
8.9.1. PLANING STAGE 132
8.9.2. TRAINING STAGE 132
8.9.3. DESIGNING STAGE 132
8.9.4. INTERACTION STAGE 132
8.10. SUMMERY AND CONCLUSION 133
XIII
CONTENTS
9. CASE STUDIES AND EVALUATIONS 135
9.1. INTRODUCTION 135
9.2. QUANTITATIVE EXPERIMENTS FOR RECOGNITION TECHNIQUES 136
9.2.1. INERTIAL SENSORS WITH MANIFOLD 136
9.2.2. INERTIAL SENSORS WITH PCA 137
9.2.3. KINECT WITH PCA 140
9.3. FRAMEWORK PERFORMANCE EVALUATION 144
9.4. GESTURING USER STUDIES WITH BIOMEDICAL STUDENTS 145
9.4.1. INERTIAL SENSORS WITH MANIFOLD 146
9.4.2. INERTIAL SENSORS WITH PCA 146
I
9.4.3. KINECT WITH PCA 148
9.5. HCI DESIGN USER STUDIES WITH SURGEONS AND UI EXPERTS 150
9.5.1. USER
STUDY WITH UI EXPERTS 151
9.5.2. USER STUDY WITH SURGEONS 152
9.6. DISCUSSION 153
9.7. SUMMERY AND CONCLUSION 156
IV. FINAL CONCLUSIONS 157
10. CONCLUSIONS 159
10.1. SUMMERY 159
10.1.1. USABILITY EVALUATIONS 160
10.1.2. HUMAN COMPUTER INTERACTIONS 162
10.2. FUTURE WORK 163
11.
GLOSSARY AND ACRONYMS 165
APPENDIX 171
12. DOMAIN MODEL OF SLNB USING THE SPECT IMAGING DEVICE 173
BIBLIOGRAPHY 181
XIV
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| series2 | Neuromethods |
| spelling | Brain Energy Metabolism edited by Johannes Hirrlinger, Helle S. Waagepetersen New York, NY Springer New York 2014 1 Online-Ressource (XIV, 368 p. 97 illus., 52 illus. in color) txt rdacontent c rdamedia cr rdacarrier Neuromethods 90 Brain Energy Metabolism addresses its challenging subject by presenting diverse technologies allowing for the investigation of brain energy metabolism on different levels of complexity. Model systems are discussed, starting from the reductionist approach like primary cell cultures which allow assessing of the properties and functions of a single brain cell type with many different types of analysis, however, at the expense of neglecting the interaction between cell types in the brain. On the other end, analysis in animals and humans in vivo is discussed, maintaining the full complexity of the tissue and the organism but making high demands on the methods of analysis. Written for the popular Neuromethods series, chapters include the kind of detailed description and key implementation advice that aims to support reproducible results in the lab. Meticulous and authoritative, Brain Energy Metabolism provides an ideal guide for researchers interested in brain energy metabolism with the hope of stimulating more research in this exciting and very important field Biomedicine Neurosciences Neurobiology Medicine Gehirn (DE-588)4019752-9 gnd rswk-swf Energiestoffwechsel (DE-588)4125217-2 gnd rswk-swf 1\p (DE-588)4143413-4 Aufsatzsammlung gnd-content Gehirn (DE-588)4019752-9 s Energiestoffwechsel (DE-588)4125217-2 s DE-604 Hirrlinger, Johannes edt Waagepetersen, Helle S. edt Erscheint auch als Druck-Ausgabe 9781493910588 https://doi.org/10.1007/978-1-4939-1059-5 Verlag URL des Erstveröffentlichers Volltext DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030343467&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Brain Energy Metabolism Biomedicine Neurosciences Neurobiology Medicine Gehirn (DE-588)4019752-9 gnd Energiestoffwechsel (DE-588)4125217-2 gnd |
| subject_GND | (DE-588)4019752-9 (DE-588)4125217-2 (DE-588)4143413-4 |
| title | Brain Energy Metabolism |
| title_auth | Brain Energy Metabolism |
| title_exact_search | Brain Energy Metabolism |
| title_full | Brain Energy Metabolism edited by Johannes Hirrlinger, Helle S. Waagepetersen |
| title_fullStr | Brain Energy Metabolism edited by Johannes Hirrlinger, Helle S. Waagepetersen |
| title_full_unstemmed | Brain Energy Metabolism edited by Johannes Hirrlinger, Helle S. Waagepetersen |
| title_short | Brain Energy Metabolism |
| title_sort | brain energy metabolism |
| topic | Biomedicine Neurosciences Neurobiology Medicine Gehirn (DE-588)4019752-9 gnd Energiestoffwechsel (DE-588)4125217-2 gnd |
| topic_facet | Biomedicine Neurosciences Neurobiology Medicine Gehirn Energiestoffwechsel Aufsatzsammlung |
| url | https://doi.org/10.1007/978-1-4939-1059-5 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030343467&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT hirrlingerjohannes brainenergymetabolism AT waagepetersenhelles brainenergymetabolism |