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Cyberphysical Systems for Epilepsy and Related Brain Disorders : Multi-Parametric Monitoring and Analysis for Diagnosis and Optimal Disease Management.

By: Contributor(s): Material type: TextTextPublisher: Cham : Springer International Publishing AG, 2015Copyright date: ©2015Edition: 1st edDescription: 1 online resource (286 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319200491
Subject(s): Genre/Form: Additional physical formats: Print version:: Cyberphysical Systems for Epilepsy and Related Brain DisordersDDC classification:
  • 502.85
LOC classification:
  • R856-857
Online resources:
Contents:
Intro -- Foreword -- Acknowledgments -- Contents -- Chapter 1: Introduction to ARMOR Project -- 1.1 Introduction -- 1.2 ARMOR Perspectives -- 1.2.1 Medical Perspective -- 1.2.2 ICT Perspective -- 1.3 What ARMOR Project Offers? -- 1.4 Conclusions -- References -- Chapter 2: Introduction to Epilepsy and Related Brain Disorders -- 2.1 Introduction -- 2.2 Definitions -- 2.3 Classification -- 2.4 Etiology -- 2.4.1 Febrile Seizures -- 2.4.2 Developmental Brain Abnormalities -- 2.4.3 Acquired Lesions -- 2.4.3.1 Brain Injury (Traumatic, Hypoxic/Ischemic) -- 2.4.3.2 Hippocampal Sclerosis (HS) -- 2.4.3.3 Tumor-Associated Epilepsy (TAE) -- 2.4.4 Seizure Precipitants and Modulators -- 2.4.4.1 Sleep Deprivation -- 2.4.4.2 Stress and Epilepsy -- 2.4.4.3 Epilepsy and Reproductive Hormones -- 2.5 Pathophysiology of Seizures and Epilepsy -- 2.5.1 Basic Neurophysiology -- 2.5.2 Hypersynchrony, Hyperexcitation and Epileptogenesis -- 2.5.3 Pathophysiology of Focal Epilepsy -- 2.5.4 Pathophysiology of Generalized Epilepsy -- References -- Chapter 3: Sleep Features and Underlying Mechanisms Related to Epilepsy and Its Long Term Monitoring -- 3.1 Introduction -- 3.2 Sleep Physiology -- 3.3 The Interictal State and Sleep -- 3.4 Epileptic Seizures and Sleep -- 3.5 Mechanisms Underlying the Effect of Sleep on Epilepsy -- 3.5.1 Sleep Mechanisms Altering Brain Synchrony and Excitability -- 3.5.2 Neuromodulation in Sleep and Epilepsy -- 3.5.3 Circadian Rhythms and Epilepsy -- 3.6 Polysomnography in Long Term Monitoring of Epilepsy -- 3.6.1 Open Problems in Polysomnographic Monitoring of Epilepsy -- 3.6.2 The ARMOR Approach -- References -- Chapter 4: Source-Estimation from Non-invasive Recordings of Brain Electrical Activity in Sleep and Epilepsy -- 4.1 Introduction -- 4.1.1 K-Complex and Its Relationship with Epilepsy -- 4.1.1.1 Background -- 4.1.1.2 Description of KC.
4.1.1.3 Neuronal Mechanisms Underlying the KC -- Sensory-Evoked KCs -- 4.1.1.4 Association of KC to Epilepsy -- 4.1.1.5 Mechanisms Underlying the Effect of KC on Seizures -- 4.1.2 EEG, MEG and Electromagnetic Inverse Solvers -- 4.1.2.1 EEG -- 4.1.2.2 MEG -- 4.1.2.3 Main Differences Between MEG and EEG -- 4.1.2.4 Electromagnetic Inverse Problem -- Dipolar Models -- Spatial Filters or Beamformers -- Distributed Source Models -- 4.1.2.5 Magnetic Field Tomography (MFT) and Electric Field Tomography (EFT) -- 4.1.3 Source Analysis of Large Epileptic and Sleep Graphoelements -- 4.1.3.1 Source Analysis of Epileptic Graphoelements -- MEG in Idiopathic Focal Epilepsies (IFE) -- 4.1.3.2 Source Analysis of Sleep Graphoelements -- 4.2 Methods -- 4.2.1 Subjects -- 4.2.2 Data Acquisition and Pre-processing -- 4.2.3 Sensory Stimulation During Sleep -- 4.2.4 Source Analysis -- 4.3 Results and Discussion -- 4.3.1 Localization of Neural Sources of Spontaneous KCs Using Different Methods -- 4.3.2 Sensory Cortical Sources of the Auditory and Somatosensory Evoked KCs -- 4.4 Conclusions -- References -- Chapter 5: Current Practices in Epilepsy Monitoring -- Future Prospects and the ARMOR Challenge -- 5.1 General Introduction -- 5.2 Demand and Prospects of Novel Sensors for Long Term EEG Monitoring of Epilepsy at Home -- 5.2.1 Introduction -- 5.2.2 The Challenges Faced by Conventional Electrodes EEG Recording -- 5.2.2.1 Clinical Demands for EEG Are Increasing and Changing -- 5.2.2.2 New Non Medical EEG Applications Are Emerging -- 5.2.2.3 In Many Ways EEG Acquisition Fails Short of the Demand -- 5.2.3 Development of Dry-Contact Electrodes -- 5.2.4 Development of Non-contact Electrodes -- 5.2.5 Beyond the Electrode/Skin Interface -- 5.2.6 Conclusions and Prospects -- 5.3 EEG Data Analysis for Epilepsy.
5.3.1 Tomographic Analysis of Epileptic Spikes Identified by ARMOR Automatic Spike Detection Methods -- 5.3.2 Tomographic Analysis of Epileptic Spikes Recorded from an ARMOR Test Case Patient -- 5.3.2.1 Spike-Related Brain Activity -- 5.3.2.2 Selection of Optimal Electrode Positions -- 5.3.2.3 Summary -- 5.4 Outlook -- References -- Chapter 6: Data Management Processes -- 6.1 Identifying the Need for Data Management Processes -- 6.2 Highly Critical Data Management Procedures -- 6.2.1 Software Related Procedures -- 6.2.1.1 Password Policy -- 6.2.1.2 Acceptable Encryption Policy -- 6.2.1.3 Anti Virus Policy Guidelines -- 6.2.1.4 Database Credentials Policy -- Overview -- 6.2.1.5 User Encryption Key Protection Policy -- Overview -- 6.2.2 Equipment Related Procedures -- 6.2.2.1 Removable Media Policy -- Policy -- 6.2.2.2 Equipment Disposal Policy -- Policy -- 6.2.2.3 Information Backup Policy -- Overview -- Policy -- Information Back Up -- Information Restore -- 6.2.3 Incident Handling Procedure -- 6.2.3.1 Policy -- Incident Specific Procedures -- Virus and Worm Incidents -- Hacker/Cracker Incidents -- Active Hacker/Cracker Activity -- 6.3 Conclusions -- References -- Chapter 7: System Architecture -- 7.1 State of the Art System Architectures -- 7.2 System Requirements for Multi-parametric Monitoring of Epileptic Patients -- 7.2.1 General Functional and Nonfunctional Requirements -- 7.3 System Architecture and Interface Definition -- 7.3.1 Hardware Components -- 7.3.1.1 Sensor Platform -- 7.3.2 Software Components -- 7.4 Conclusions -- References -- Chapter 8: Mobile Sensors for Multiparametric Monitoring in Epileptic Patients -- 8.1 Introduction -- 8.2 State of the Art in Mobile Epilepsy Monitoring -- 8.2.1 Ambulatory EEG: State of the Art -- 8.2.2 Long Term Monitoring (LTM) in the Patient's Home: State of the Art.
8.3 Sensor Requirements for Multiparametric Monitoring of Epileptic Patients -- 8.3.1 Application of Mobile Sensors in Epilepsy Monitoring -- 8.3.1.1 Application Scenario 1: Distinction Between Epilepsy or Non- epileptic Paroxysmal Events (NEPE) -- 8.3.1.2 Application Scenario 2: Delineation of the Clinical EEG Expression of Different Types of Epilepsy -- 8.3.1.3 Application Scenario 3: Follow Up-Medication Evaluation -- 8.3.1.4 Application Scenario 4: Protection from Seizures -- 8.3.1.5 Application Scenario 5: Research on Local Signs of Idiopathic Generalized Epilepsy (IGE) -- 8.3.1.6 Application Scenario 6: Pre-surgical Evaluation -- 8.3.1.7 Application Scenario 7: Nocturnal Seizures -- 8.3.2 General Functional and Nonfunctional Requirements -- 8.3.3 Sensors Selection -- 8.3.3.1 Application Scenario 1: Distinction Between Epilepsy or Non- epileptic Paroxysmal Events (NEPE) -- 8.3.3.2 Application Scenario 2: Delineation of the Clinical EEG Expression of Different Types of Epilepsy -- 8.3.3.3 Application Scenario 3: Follow Up-Medication Evaluation -- 8.3.3.4 Application Scenario 4: Protection from Seizures -- 8.3.3.5 Application Scenario 5: Research on Local Signs of Idiopathic Generalized Epilepsy (IGE) -- 8.3.3.6 Application Scenario 6: Pre-surgical Evaluation -- 8.3.3.7 Application Scenario 7: Nocturnal Seizures -- 8.4 Mobile Sensor Systems -- 8.4.1 Sensor System Architecture -- 8.4.2 Sensor Systems for Mobile Epilepsy Monitoring -- 8.5 Conclusions -- References -- Chapter 9: Secure and Efficient WSN Communication Infrastructure -- 9.1 Wireless Network Sensors Secure Data Acquisition and Local Storage -- 9.1.1 Requirements -- 9.1.1.1 Availability -- 9.1.1.2 Integrity of Data or Systems -- 9.1.1.3 Confidentiality of Data or Systems -- 9.1.1.4 Accountability -- 9.1.1.5 Assurance -- 9.1.2 Challenges -- 9.1.2.1 Excessive Privileges.
9.1.2.2 Privilege Abuse -- 9.1.2.3 Unauthorized Privilege Elevation -- 9.1.2.4 Platform Vulnerabilities -- 9.1.2.5 SQL Injection -- 9.1.2.6 Weak Audit -- 9.1.2.7 Denial of Service -- 9.1.2.8 Database Protocol Vulnerabilities -- 9.1.2.9 Weak Authentication -- 9.1.3 State of the Art Security Countermeasures -- 9.1.3.1 Attacks on the ARMOR Sensor -- Security of the Bluetooth Interface -- Deactivation of the Debugger Interface -- Attacks over the Power Supply Interface -- 9.1.3.2 Design Alternatives for Mobile Cryptography -- Application Specific Integrated Circuit (ASIC) -- Hardware Based Crypto Accelerator -- Software Based Solution -- 9.1.3.3 Texas Instruments AES Crypto Software for the MSP 430 -- 9.1.3.4 Attacks on Computer and Infrastructure -- 9.1.3.5 Evaluation and Conclusion -- 9.2 Wireless Sensor Network Secure and Efficient Communication -- 9.2.1 Requirements -- 9.2.1.1 Access Control -- 9.2.1.2 Access Rights Administration -- 9.2.1.3 Authentication -- 9.2.1.4 Encryption -- 9.2.1.5 Privacy -- 9.2.1.6 Authentication-Integrity -- 9.2.1.7 Authorization -- 9.2.1.8 Availability -- 9.2.2 Challenges -- 9.2.2.1 Denial of Service -- 9.2.2.2 Sybil Attack -- 9.2.2.3 Traffic Analysis Attack -- 9.2.2.4 Node Replication Attack -- 9.2.2.5 Privacy Attacks -- 9.2.2.6 Limited Resources -- Limited Memory and Storage Space -- Power Limitation -- Limited Bandwidth -- Limited Processing Power -- 9.2.2.7 Unreliable Communication Medium -- Unreliable Data Transfer -- Conflicts -- Latency -- 9.2.2.8 Unattended Operation -- Exposure to Physical Attacks -- Remote Management -- No Central Management Point -- 9.2.2.9 Key Management Approaches -- 9.2.3 State of the Art Measures -- 9.2.3.1 IEEE 802.15.4 Based Solutions -- Encryption Algorithms' Requirements -- 9.2.3.2 Bluetooth Based Solutions -- Bluetooth Security Characteristics and Weaknesses.
Network Performance Overhead Due to Bluetooth Security.
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Intro -- Foreword -- Acknowledgments -- Contents -- Chapter 1: Introduction to ARMOR Project -- 1.1 Introduction -- 1.2 ARMOR Perspectives -- 1.2.1 Medical Perspective -- 1.2.2 ICT Perspective -- 1.3 What ARMOR Project Offers? -- 1.4 Conclusions -- References -- Chapter 2: Introduction to Epilepsy and Related Brain Disorders -- 2.1 Introduction -- 2.2 Definitions -- 2.3 Classification -- 2.4 Etiology -- 2.4.1 Febrile Seizures -- 2.4.2 Developmental Brain Abnormalities -- 2.4.3 Acquired Lesions -- 2.4.3.1 Brain Injury (Traumatic, Hypoxic/Ischemic) -- 2.4.3.2 Hippocampal Sclerosis (HS) -- 2.4.3.3 Tumor-Associated Epilepsy (TAE) -- 2.4.4 Seizure Precipitants and Modulators -- 2.4.4.1 Sleep Deprivation -- 2.4.4.2 Stress and Epilepsy -- 2.4.4.3 Epilepsy and Reproductive Hormones -- 2.5 Pathophysiology of Seizures and Epilepsy -- 2.5.1 Basic Neurophysiology -- 2.5.2 Hypersynchrony, Hyperexcitation and Epileptogenesis -- 2.5.3 Pathophysiology of Focal Epilepsy -- 2.5.4 Pathophysiology of Generalized Epilepsy -- References -- Chapter 3: Sleep Features and Underlying Mechanisms Related to Epilepsy and Its Long Term Monitoring -- 3.1 Introduction -- 3.2 Sleep Physiology -- 3.3 The Interictal State and Sleep -- 3.4 Epileptic Seizures and Sleep -- 3.5 Mechanisms Underlying the Effect of Sleep on Epilepsy -- 3.5.1 Sleep Mechanisms Altering Brain Synchrony and Excitability -- 3.5.2 Neuromodulation in Sleep and Epilepsy -- 3.5.3 Circadian Rhythms and Epilepsy -- 3.6 Polysomnography in Long Term Monitoring of Epilepsy -- 3.6.1 Open Problems in Polysomnographic Monitoring of Epilepsy -- 3.6.2 The ARMOR Approach -- References -- Chapter 4: Source-Estimation from Non-invasive Recordings of Brain Electrical Activity in Sleep and Epilepsy -- 4.1 Introduction -- 4.1.1 K-Complex and Its Relationship with Epilepsy -- 4.1.1.1 Background -- 4.1.1.2 Description of KC.

4.1.1.3 Neuronal Mechanisms Underlying the KC -- Sensory-Evoked KCs -- 4.1.1.4 Association of KC to Epilepsy -- 4.1.1.5 Mechanisms Underlying the Effect of KC on Seizures -- 4.1.2 EEG, MEG and Electromagnetic Inverse Solvers -- 4.1.2.1 EEG -- 4.1.2.2 MEG -- 4.1.2.3 Main Differences Between MEG and EEG -- 4.1.2.4 Electromagnetic Inverse Problem -- Dipolar Models -- Spatial Filters or Beamformers -- Distributed Source Models -- 4.1.2.5 Magnetic Field Tomography (MFT) and Electric Field Tomography (EFT) -- 4.1.3 Source Analysis of Large Epileptic and Sleep Graphoelements -- 4.1.3.1 Source Analysis of Epileptic Graphoelements -- MEG in Idiopathic Focal Epilepsies (IFE) -- 4.1.3.2 Source Analysis of Sleep Graphoelements -- 4.2 Methods -- 4.2.1 Subjects -- 4.2.2 Data Acquisition and Pre-processing -- 4.2.3 Sensory Stimulation During Sleep -- 4.2.4 Source Analysis -- 4.3 Results and Discussion -- 4.3.1 Localization of Neural Sources of Spontaneous KCs Using Different Methods -- 4.3.2 Sensory Cortical Sources of the Auditory and Somatosensory Evoked KCs -- 4.4 Conclusions -- References -- Chapter 5: Current Practices in Epilepsy Monitoring -- Future Prospects and the ARMOR Challenge -- 5.1 General Introduction -- 5.2 Demand and Prospects of Novel Sensors for Long Term EEG Monitoring of Epilepsy at Home -- 5.2.1 Introduction -- 5.2.2 The Challenges Faced by Conventional Electrodes EEG Recording -- 5.2.2.1 Clinical Demands for EEG Are Increasing and Changing -- 5.2.2.2 New Non Medical EEG Applications Are Emerging -- 5.2.2.3 In Many Ways EEG Acquisition Fails Short of the Demand -- 5.2.3 Development of Dry-Contact Electrodes -- 5.2.4 Development of Non-contact Electrodes -- 5.2.5 Beyond the Electrode/Skin Interface -- 5.2.6 Conclusions and Prospects -- 5.3 EEG Data Analysis for Epilepsy.

5.3.1 Tomographic Analysis of Epileptic Spikes Identified by ARMOR Automatic Spike Detection Methods -- 5.3.2 Tomographic Analysis of Epileptic Spikes Recorded from an ARMOR Test Case Patient -- 5.3.2.1 Spike-Related Brain Activity -- 5.3.2.2 Selection of Optimal Electrode Positions -- 5.3.2.3 Summary -- 5.4 Outlook -- References -- Chapter 6: Data Management Processes -- 6.1 Identifying the Need for Data Management Processes -- 6.2 Highly Critical Data Management Procedures -- 6.2.1 Software Related Procedures -- 6.2.1.1 Password Policy -- 6.2.1.2 Acceptable Encryption Policy -- 6.2.1.3 Anti Virus Policy Guidelines -- 6.2.1.4 Database Credentials Policy -- Overview -- 6.2.1.5 User Encryption Key Protection Policy -- Overview -- 6.2.2 Equipment Related Procedures -- 6.2.2.1 Removable Media Policy -- Policy -- 6.2.2.2 Equipment Disposal Policy -- Policy -- 6.2.2.3 Information Backup Policy -- Overview -- Policy -- Information Back Up -- Information Restore -- 6.2.3 Incident Handling Procedure -- 6.2.3.1 Policy -- Incident Specific Procedures -- Virus and Worm Incidents -- Hacker/Cracker Incidents -- Active Hacker/Cracker Activity -- 6.3 Conclusions -- References -- Chapter 7: System Architecture -- 7.1 State of the Art System Architectures -- 7.2 System Requirements for Multi-parametric Monitoring of Epileptic Patients -- 7.2.1 General Functional and Nonfunctional Requirements -- 7.3 System Architecture and Interface Definition -- 7.3.1 Hardware Components -- 7.3.1.1 Sensor Platform -- 7.3.2 Software Components -- 7.4 Conclusions -- References -- Chapter 8: Mobile Sensors for Multiparametric Monitoring in Epileptic Patients -- 8.1 Introduction -- 8.2 State of the Art in Mobile Epilepsy Monitoring -- 8.2.1 Ambulatory EEG: State of the Art -- 8.2.2 Long Term Monitoring (LTM) in the Patient's Home: State of the Art.

8.3 Sensor Requirements for Multiparametric Monitoring of Epileptic Patients -- 8.3.1 Application of Mobile Sensors in Epilepsy Monitoring -- 8.3.1.1 Application Scenario 1: Distinction Between Epilepsy or Non- epileptic Paroxysmal Events (NEPE) -- 8.3.1.2 Application Scenario 2: Delineation of the Clinical EEG Expression of Different Types of Epilepsy -- 8.3.1.3 Application Scenario 3: Follow Up-Medication Evaluation -- 8.3.1.4 Application Scenario 4: Protection from Seizures -- 8.3.1.5 Application Scenario 5: Research on Local Signs of Idiopathic Generalized Epilepsy (IGE) -- 8.3.1.6 Application Scenario 6: Pre-surgical Evaluation -- 8.3.1.7 Application Scenario 7: Nocturnal Seizures -- 8.3.2 General Functional and Nonfunctional Requirements -- 8.3.3 Sensors Selection -- 8.3.3.1 Application Scenario 1: Distinction Between Epilepsy or Non- epileptic Paroxysmal Events (NEPE) -- 8.3.3.2 Application Scenario 2: Delineation of the Clinical EEG Expression of Different Types of Epilepsy -- 8.3.3.3 Application Scenario 3: Follow Up-Medication Evaluation -- 8.3.3.4 Application Scenario 4: Protection from Seizures -- 8.3.3.5 Application Scenario 5: Research on Local Signs of Idiopathic Generalized Epilepsy (IGE) -- 8.3.3.6 Application Scenario 6: Pre-surgical Evaluation -- 8.3.3.7 Application Scenario 7: Nocturnal Seizures -- 8.4 Mobile Sensor Systems -- 8.4.1 Sensor System Architecture -- 8.4.2 Sensor Systems for Mobile Epilepsy Monitoring -- 8.5 Conclusions -- References -- Chapter 9: Secure and Efficient WSN Communication Infrastructure -- 9.1 Wireless Network Sensors Secure Data Acquisition and Local Storage -- 9.1.1 Requirements -- 9.1.1.1 Availability -- 9.1.1.2 Integrity of Data or Systems -- 9.1.1.3 Confidentiality of Data or Systems -- 9.1.1.4 Accountability -- 9.1.1.5 Assurance -- 9.1.2 Challenges -- 9.1.2.1 Excessive Privileges.

9.1.2.2 Privilege Abuse -- 9.1.2.3 Unauthorized Privilege Elevation -- 9.1.2.4 Platform Vulnerabilities -- 9.1.2.5 SQL Injection -- 9.1.2.6 Weak Audit -- 9.1.2.7 Denial of Service -- 9.1.2.8 Database Protocol Vulnerabilities -- 9.1.2.9 Weak Authentication -- 9.1.3 State of the Art Security Countermeasures -- 9.1.3.1 Attacks on the ARMOR Sensor -- Security of the Bluetooth Interface -- Deactivation of the Debugger Interface -- Attacks over the Power Supply Interface -- 9.1.3.2 Design Alternatives for Mobile Cryptography -- Application Specific Integrated Circuit (ASIC) -- Hardware Based Crypto Accelerator -- Software Based Solution -- 9.1.3.3 Texas Instruments AES Crypto Software for the MSP 430 -- 9.1.3.4 Attacks on Computer and Infrastructure -- 9.1.3.5 Evaluation and Conclusion -- 9.2 Wireless Sensor Network Secure and Efficient Communication -- 9.2.1 Requirements -- 9.2.1.1 Access Control -- 9.2.1.2 Access Rights Administration -- 9.2.1.3 Authentication -- 9.2.1.4 Encryption -- 9.2.1.5 Privacy -- 9.2.1.6 Authentication-Integrity -- 9.2.1.7 Authorization -- 9.2.1.8 Availability -- 9.2.2 Challenges -- 9.2.2.1 Denial of Service -- 9.2.2.2 Sybil Attack -- 9.2.2.3 Traffic Analysis Attack -- 9.2.2.4 Node Replication Attack -- 9.2.2.5 Privacy Attacks -- 9.2.2.6 Limited Resources -- Limited Memory and Storage Space -- Power Limitation -- Limited Bandwidth -- Limited Processing Power -- 9.2.2.7 Unreliable Communication Medium -- Unreliable Data Transfer -- Conflicts -- Latency -- 9.2.2.8 Unattended Operation -- Exposure to Physical Attacks -- Remote Management -- No Central Management Point -- 9.2.2.9 Key Management Approaches -- 9.2.3 State of the Art Measures -- 9.2.3.1 IEEE 802.15.4 Based Solutions -- Encryption Algorithms' Requirements -- 9.2.3.2 Bluetooth Based Solutions -- Bluetooth Security Characteristics and Weaknesses.

Network Performance Overhead Due to Bluetooth Security.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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