基於功能性近紅外光腦光譜與腦電圖發展多模態腦活動無線監測系統

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：180

、訪客IP：3.15.151.94

姓名

林以哲(Yi-Je Lin) 查詢紙本館藏

畢業系所

生物醫學工程研究所

論文名稱

基於功能性近紅外光腦光譜與腦電圖發展多模態腦活動無線監測系統
(Implementation of a portable multimodal Wireless System for brain activity monitoring based on functional Near-Infrared Spectroscopy and Electroencephalogram)

相關論文

★ 麻醉監測技術進步與優化病人安全_應用小波頻譜分析麻醉動態自主神經反應	★ 不同麻醉深度之相位-振幅耦合量測及強度比較
★ 設計及製作可攜式非侵入性心搏輸出量監測系統	★ 開發可攜式十二導程心電圖和聲學雙功能系統於居家分析心臟電生理訊號
★ 應用非侵入性方法來探究透析過程中血流動力學變化及心血管疾病之預後	★ 開發具深度學習應用於自動追蹤耳膜功能之數位耳鏡於中耳炎輔助系統
★ 反覆編曲結構音樂對人體生理訊號之影響	★ 設計具低功耗無線傳輸及結合人工智慧判讀之長時間聽診監測系統
★ 實踐經驗模態分解於高度非穩態生理訊號之訊號特徵擷取	★ Exploring Beat-to-Beat Photoplethysmography Features at the Upper and Lower Extremities as Potential Biomarkers for Early Diagnosis of Peripheral Arterial Occlusive Disease: A Comparative study with Ultrasound Doppler and Ankle-Brachial Index
★ 應用稀疏時頻表現式解析生理系統間非線性耦合機轉	★ 脂質奈米顆粒在mRNA疫苗技術應用發展綜述
★ 自12導程心電圖擷取P波特徵辨識竇性心律下之心房顫動高風險病患	★ 探討以非侵入方式的影像心衝擊圖形態特徵來評估左心室射血分數 : 基於數學模型與臨床驗證的初步研究
★ 發展可用於肺部疾病患者呼吸音監測之高解析加速度陣列感測器	★ 以光體積變化描記儀作為男性勃起功能及陰莖血液動力學及性功能客觀指標之探討

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

至系統瀏覽論文 (2025-9-23以後開放)

摘要(中)

人腦一直是人體中最為重要的器官之一，它掌控著我們的每一個舉動，也關乎我們對於周遭事物的理解。而如此重要的器官，也引發人們想透過各種方式進行觀察與探測。截至目前為止，科學家們已經開發出多種方法能及時監測腦部的活動狀態，各個方法各有其優缺點與適合應用的場景，但對於各方法視為缺點的場域卻難以攻克。
為此本研究設計開發了一套無線監測系統，用以同時量測fNIRS訊號與EEG訊號，使我們可以更有效地利用fNIRS訊號在其空間解析度的優勢與EEG在時間解析度的優勢，並且訊號透過低功耗藍芽(BLE)進行資料的即時傳輸，在本地端即可使用手機進行即時的數據觀察。
在EEG訊號方面，此裝置採用類比前端整合IC (ADS1299)進行訊號的收取，而採用乾式導極的設計避免了導電膠的使用。在fNIRS訊號方面，總共有8個通道的fNIRS訊號接收通道被置於前額處，其中2個被規劃為Short Separation 通道，而透過此設計，可以在面臨表層組織的耗氧量產生劇烈改變而影響到腦內耗氧的監測時進行動態補償，進一步使取得的訊號更為精確。同時，本研究也將閘道器(Gateway)技術應用於此裝置，透過此閘道器的設計，原本只能透過BLE進行資料傳輸的設備，也可以直接與雲端相連並將量測數據即時上傳。
在最後，我們透過進行閉眼放鬆實驗與閉氣實驗確認此儀器的有效性，當受測者在閉眼時可以明顯觀察到α波的增加，並在閉氣實驗中可以看出訊號波動的頻率與受測者進行閉氣時間的關係，而以上實驗皆可透過設計之閘道器即時於伺服器中觀察。

摘要(英)

The brain is one of the most important organs of the human body. It controls every single movement and affects every single thought of us on everything. To date, scientists have developed numerous ways to monitor the brain. While Every method has its advantages and disadvantages, it is difficult to overcome the fields that are regarded as shortcomings.
The study proposes a wireless multimodal monitoring system that records the fNIRS and EEG signals at the same time. The system allows us to effectively make use of the high spatial resolution on fNIRS and the high time resolution on EEG, with the signal being able to transmit to the smartphone for real-time display.
This study uses ADS1299 for EEG measurement. And the implementation of the dry electrodes prevents the use of the gel. As for the fNIRS signal, there are 8 channels in total placed on the forehead, and two of them are designed to be Short Separation channels. The design provides a way of for compensating the change caused by the surface structure. At the same time, a BLE-NET gateway is implemented in this study for making it possible to let the BLE device connect to a web server directly.
An eye-closed resting experiment and a breath-suspending experiment are used for examining the functionality. The rising energy of α-wave while closing eyes and the correlation between the change in signal and the period on breath-suspending time was observed with all the data collected through the BLE-gateway in real-time.

關鍵字(中)

★ fNIRS
★ EEG
★ 低功耗藍芽
★ 即時傳輸
★ 閘道器

關鍵字(英)

★ fNIRS
★ EEG
★ BLE
★ real-time transmission
★ gateway

論文目次

中文摘要 .................................................................................................................................................. i
ABSTRACT ........................................................................................................................................... ii
TABLE OF CONTENTS ..................................................................................................................... iii
LIST OF FIGURES .............................................................................................................................. v
LIST OF TABLES ............................................................................................................................... vi
Chapter 1. Introduction ..................................................................................................................... 1
Chapter 2. Related Work ................................................................................................................... 2
2-1 Anatomy of Brain................................................................................................................. 2
2-2 Record Method ..................................................................................................................... 3
2-2-1 EEG................................................................................................................................... 3
2-2-2 MRI ................................................................................................................................... 4
2-2-3 NIRS ................................................................................................................................. 4
2-3 Data Fusion ........................................................................................................................... 8
2-4 IoT Gateway Introduction ................................................................................................ 10
Chapter 3. Implementation of fNIRS and EEG device ................................................................. 11
3-1 Board Design ...................................................................................................................... 11
3-2 Power Supplies ................................................................................................................... 13
3-3 EEG Measuring Circuit .................................................................................................... 14
3-4 fNIRS Measuring Circuit .................................................................................................. 15
3-5 Mechanical structure ......................................................................................................... 17
Chapter 4. Experiments and Results of the fNIRS device ............................................................ 19
Chapter 5. Implementation of Wireless System ............................................................................. 24
5-1 Wireless Unified Management System............................................................................. 24
5-2 Hardware ............................................................................................................................ 25
5-3 Web Platform ..................................................................................................................... 25
Chapter 6. Result of the Management System ............................................................................... 27
Chapter 7. Discussion ....................................................................................................................... 28
Chapter 8. Conclusion ...................................................................................................................... 29
References ............................................................................................................................................ 30

參考文獻

1. Nair, K.G.S., V. Ramaiyan, and S.K. Sukumaran, Enhancement of drug permeability across blood brain barrier using nanoparticles in meningitis. Inflammopharmacology, 2018. 26(3): p. 675-684.
2. Benarroch, E.E., Neuron-Astrocyte Interactions: Partnership for Normal Function and Disease in the Central Nervous System. Mayo Clinic Proceedings, 2005. 80(10): p. 1326-1338.
3. Attwell, D., et al., Glial and neuronal control of brain blood flow. Nature, 2010. 468(7321): p. 232-243.
4. Kocsis, L., P. Herman, and A. Eke, The modified Beer–Lambert law revisited. Physics in Medicine and Biology, 2006. 51(5): p. N91-N98.
5. Budnev, V.M., et al., The two-photon particle production mechanism. Physical problems. Applications. Equivalent photon approximation. Physics Reports, 1975. 15(4): p. 181-282.
6. Fishkin, J.B. and E. Gratton, Propagation of photon-density waves in strongly scattering media containing an absorbing semi-infinite plane bounded by a straight edge. Journal of the Optical Society of America A, 1993. 10(1): p. 127-140.
7. Myllylä, T., et al. Optical sensing of a pulsating liquid in a brain-mimicking phantom. in Diffuse Optical Imaging IV. 2013. Munich: Optica Publishing Group.
8. Wang, J., et al., Phantom-based evaluation of near-infrared intracranial hematoma detector performance. J Biomed Opt, 2019. 24(4): p. 1-10.
9. Strangman, G.E., Z. Li, and Q. Zhang, Depth Sensitivity and Source-Detector Separations for Near Infrared Spectroscopy Based on the Colin27 Brain Template. PLOS ONE, 2013. 8(8): p. e66319.
10. Al-Shargie, F., et al. Mental stress assessment using simultaneous measurement of EEG and fNIRS. Biomedical optics express, 2016. 7, 3882-3898 DOI: 10.1364/boe.7.003882.
11. Cimenser, A., et al., Tracking brain states under general anesthesia by using global coherence analysis. Proc Natl Acad Sci U S A, 2011. 108(21): p. 8832-7.
12. Tang, C.Y. and R. Ramani, fMRI and Anesthesia. International Anesthesiology Clinics, 2016. 54(1).
13. Hinrichs, H., et al., Comparison between a wireless dry electrode EEG system with a conventional wired wet electrode EEG system for clinical applications. Scientific Reports, 2020. 10(1): p. 5218.
14. Mazzillo, M., et al., Noise Reduction in Silicon Photomultipliers for Use in Functional Near-Infrared Spectroscopy. IEEE Transactions on Radiation and Plasma Medical Sciences, 2017. 1(3): p. 212-220.
15. Eskes, G., et al., Contribution of Physical Fitness, Cerebrovascular Reserve and Cognitive Stimulation to Cognitive Function in Post-Menopausal Women. Frontiers in Aging Neuroscience, 2010. 2.
16. Scarpa, F., et al., A reference-channel based methodology to improve estimation of event-related hemodynamic response from fNIRS measurements. NeuroImage, 2013. 72: p. 106-119.
17. Grant, H., Y. Bhambhani, and A. Singhal, Hemodynamic changes in the prefrontal cortex during working memory in essential hypertension. Journal of the American Society of Hypertension, 2015. 9(8): p. 628-639.
18. Tong, Y., P.R. Bergethon, and B.d. Frederick, An improved method for mapping cerebrovascular reserve using concurrent fMRI and near-infrared spectroscopy with Regressor Interpolation at Progressive Time Delays (RIPTiDe). NeuroImage, 2011. 56(4): p. 2047-2057.
19. Irani, F., et al., Functional Near Infrared Spectroscopy (fNIRS): An Emerging Neuroimaging Technology with Important Applications for the Study of Brain Disorders. The Clinical Neuropsychologist, 2007. 21(1): p. 9-37.
20. Tak, S. and J.C. Ye, Statistical analysis of fNIRS data: A comprehensive review. NeuroImage, 2014. 85: p. 72-91.

指導教授

林澂(Chen Lin)

審核日期

2022-9-23

推文