4 research outputs found
Changes in Physiological Network Connectivity of Body System in Narcolepsy during REM Sleep: λ μλ©΄ μ€ κΈ°λ©΄ νμμ μΈμ²΄ μμ€ν λ΄ μ리νμ λ€νΈμν¬ μ°κ²°μ± λ³ν
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Όλ¬Έ(μμ¬) -- μμΈλνκ΅λνμ : 곡과λν νλκ³Όμ λ°μ΄μ€μμ§λμ΄λ§μ 곡, 2022.2. λ°κ΄μ.μ°κ΅¬ λ°°κ²½: κΈ°λ©΄μ¦μ λ³λ¦¬νμ μ¦μμ μλ°νλ μλ©΄ μ§νμ νλλ‘, μΌκ°μ μΆ©λΆν μλ©΄μ μ·¨νμμλ μ£Όκ°μ κ³Όλν μ‘Έλ¦Όμ¦, 무기λ ₯μ¦μ μ¦μμ λνλΈλ€. κΈ°λ©΄μ¦μ λ κ°μ§μ μ νμ΄ μμΌλ©° μ΄λ€μ νλ ₯λ°μμ λλ°ν 1μ ν κΈ°λ©΄μ¦κ³Ό νλ ₯λ°μμ λλ°νμ§ μλ 2μ ν κΈ°λ©΄μ¦μΌλ‘ ꡬλ³λλ€. 1μ ν κΈ°λ©΄μ¦μ μ§λ¨ μ체 μ§νλ‘μ νν¬ν¬λ ν΄μ΄λΌλ μ κ²½ λ¬Όμ§μ΄ μ‘΄μ¬νμ§λ§, κ·Έμ λ°νμ¬ 2μ ν κΈ°λ©΄μ¦μ μ μ ν μ체 μ§νκ° λΆμ¬νμ¬ 2μ ν κΈ°λ©΄μ¦μ κΈ°λ©΄ μ¦μ λ° μΈκ³Όκ΄κ³μ νμΈμ νκ³λ₯Ό μ§λκ³ μλ€. μ΄μ κΈ°λ°νμ¬, λ³Έ μ°κ΅¬λ 2μ ν κΈ°λ©΄μ¦μ μλ‘μ΄ μ체 μ§νμ νμμ λͺ©νλ‘ νλ©° μ΄λ₯Ό μν΄ μΈμ²΄μ μμ€ν
μ μ°κ²°λ§μ λΆμμ μ§ννμλ€.
μ°κ΅¬ λ°©λ²: λ³Έ μ°κ΅¬λ 30λͺ
μ μ°Έμ¬μ (15λͺ
μ 2μ ν κΈ°λ©΄μ¦ νμ, 15λͺ
μ μ μ λμ‘°κ΅°)λ₯Ό λμμΌλ‘, μκ° μ§μ° μμ μ±μ λ°©λ²μ ν΅ν΄ μκ°μ μ 보μ κΈ°λ°νμ¬ μ¬λ¬ μ체μ νΈλ€μ κ΄κ³μ λν λΆμμ μ§ννμλ€. κ° μ°Έμ¬μμ μΌκ° μλ©΄λ€μ κ²μ¬λ‘λΆν° μ»μ 9κ° μ체μ νΈλ€ (λν, μ¬μ₯, νΈν‘, κ·Όμ‘κ³Ό μꡬμ μμ§μμΌλ‘ λΆν°μ μ νΈ)μ μ°κ²°μ± λ€νΈμν¬μ λν μ λμ λΆμμ μ§ννμμΌλ©°, νΉν μλ©΄ λ¨κ³μ λ°λ₯Έ λ€νΈμν¬ μ°κ²°μ±μ μ°¨μ΄κ° λ κ·Έλ£Ή μ¬μ΄μ μ΄λ ν μν₯λ ₯μ λ―ΈμΉλ©° μ΄λ€μ΄ κΈ°λ©΄μ¦κ³Ό μ μκ΅°μ ꡬλ³νλ μ μ¬μ μ체 μ§νλ‘μ μ¬μ©λ μ μμμ§μ λν λΆμμ μ€μ μ λμλ€. κ·Έλ£Ή κ°μ μ°¨μ΄μ λν μΈκ³Όκ΄κ³μ μ‘°μ¬μ ν¨κ» μ체 μ§νμ λΆλ₯ μ±λ₯μ νμΈμ μν μν¬νΈ λ²‘ν° λ¨Έμ κΈ°λ²μ μ μ©ν μ‘°μ¬λ ν¨κ» μ§ννμλ€.
μ°κ΅¬ κ²°κ³Ό: λ μλ©΄μμ, κΈ°λ©΄ νμκ΅°μ μ μ λμ‘°κ΅°μ λΉκ΅νμ¬ λ λ§μ λ€νΈμν¬μ μ°κ²°μ 보μλ€ (κΈ°λ©΄ νμ μ°κ²° μ: 24.47 Β± 2.87, λμ‘°κ΅° μ°κ²° μ: 21.34 Β± 3.49; p = 0.022). μ΄λ¬ν μ°¨μ΄λ μ¬λ¬ μ°κ²°μ μμλ€ μ€ μμ§μκ³Ό κ΄λ ¨λ κΈ°κ΄κ³Ό μ¬μ₯ νλμμ μ μλ―Ένκ² λνλ κ²μ νμΈν μ μμμΌλ©°, λ€νΈμν¬μ μ°κ²° κ°μμ μ μλ―Έν μ°¨μ΄λ₯Ό 보μ΄λ μ체μ νΈ μμμ μ 보λ₯Ό μ΄μ©ν μν¬νΈ λ²‘ν° λ¨Έμ κΈ°λ° λΆλ₯ μ±λ₯μ 0.93μ λ―Όκ°λ, νΉμ΄λ, μ νλλ₯Ό κ°κ° λνλ΄μλ€.
κ²° λ‘ : λ³Έ μ°κ΅¬λ μκ° μ§μ° μμ μ±μ κΈ°λ°ν λ€νΈμν¬ μ°κ²°μ±μ΄ 2μ ν κΈ°λ©΄μ¦μ λμ‘°κ΅°κ³Ό λΆλ₯νλ λ°μ μμ΄ μ μ©ν μ체μ§νλ‘ μ΄μ©λ μ μμμ 보μ΄λ©°, λμκ° μΈμ²΄μ μμ€ν
μ λ€νΈμν¬μ λν λΆμμ ν΅ν΄ μ°¨μ΄μ λν μΈκ³Όκ΄κ³ λΆμ λ° μ λμ μ κ·Όμ΄ κ°λ₯ν¨μ 보μ¬μ€λ€.Background: Narcolepsy is marked by pathologic symptoms including excessive daytime drowsiness and lethargy, even with sufficient nocturnal sleep. There are two types of narcolepsy: type 1 (with cataplexy) and type 2 (without cataplexy). Unlike type 1, for which hypocretin is a biomarker, type 2 narcolepsy has no adequate biomarker to identify the causality of narcoleptic phenomenon. Therefore, we aimed to establish new biomarkers for narcolepsy using the bodyβs systemic networks.
Method: Thirty participants (15 with type 2 narcolepsy, 15 healthy controls) were included. We used the time delay stability (TDS) method to examine temporal information and determine relationships among multiple signals. We quantified and analyzed the network connectivity of nine biosignals (brainwaves, cardiac and respiratory information, muscle and eye movements) during nocturnal sleep. In particular, we focused on the differences in network connectivity between groups according to sleep stages and investigated whether the differences could be potential biomarkers to classify both groups by using a support vector machine.
Result: In rapid eye movement sleep, the narcolepsy group displayed more connections than the control group (narcolepsy connections: 24.47 Β± 2.87, control connections: 21.34 Β± 3.49; p = 0.022). The differences were observed in movement and cardiac activity. The performance of the classifier based on connectivity differences was a 0.93 for sensitivity, specificity and accuracy, respectively.
Conclusion: Network connectivity with the TDS method may be used as a biomarker to identify differences in the systemic networks of patients with narcolepsy type 2 and healthy controls.Chapter 1. Introduction 1
1.1. Narcolepsy 1
1.2. Physiological interactions in body system 3
1.3. Connectivity with time delay stability 5
1.4. Dissertation Outline 7
Chapter 2. Material and Methods 9
2.1. Participants 9
2.2. PSG recording and data 12
2.3. Data processing 14
2.4. Time delay cross-correleation 17
2.5. TDS methods 20
2.6. Threshold tuning 22
2.7. Test-retest reproducibility 25
2.8. Brain and peripheral connections 26
2.9. Effect of brain-brain connections according to brain areas 27
2.10. Feature significance analysis 28
2.11. Network directionality with correlation 29
2.12. Verifications of network connectivity as classifier 30
2.13. Classification with support vector machine 31
Chater 3. Results and Discussion 32
3.1. Results 32
3.1.1. Network connections between narcolepsy and control groups 32
3.1.2. Test-retest analysis for reproducibility 35
3.1.3. Significant feature identification 36
3.1.4. Effect of brain-brain connections according to brain areas 39
3.1.5. Network directionality with correlation 44
3.1.6. Performance comparison between unimodal biosignal and connectivity 46
3.1.7. Classification performance with SVM 49
3.2. Discussion 51
3.2.1. Differences between patients with narcolepsy and healthy controls 51
3.2.2. Analysis of nervous system with HRV 52
3.2.3. Causalities in network connections 55
3.2.4. Effect of brain-brain connections 58
3.2.5. Network connectivity as a biomarker and prospective utility 59
Limitations 61
References 63
κ΅λ¬Έμ΄λ‘ 72μ
Wearable Wireless Devices
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