臺灣博碩士論文加值系統

腦部活動觀測，能夠反應受測者的生理與心理狀況，透過記錄並分析腦部活動訊號，如非侵入式的腦波、腦血氧濃度變化，以及侵入式的腦皮質層電訊號，能夠根據不同的需求與應用，建立大腦地圖，幫助了解腦部功能的分布情形，進一步剖析疾病的成因。
在非侵入腦部活動觀測方面，本研究建立了一套同時記錄腦部活動所造成的血氧濃度變化與腦電訊號反應的系統，並利用同步量測之腦電訊號驗證血氧濃度變化量測之有效性。此系統相具有非侵入式、穿戴方便與操作簡單之優勢。為了縮短訊號傳遞路徑，並減少訊號傳遞損耗，本系統設計了前端類比放大電路，並將其置於感測探頭之中，在訊號傳輸前先進行預處理放大，提高訊號訊雜比，其單一通道功耗僅18.3 µW。接著將前端類比放大晶片與後端血氧濃度與腦電訊號同步量測系統整合，利用閉眼與憋氣、心算和握拳實驗來驗證系統的可靠度，並同步記錄血氧濃度與腦電訊號的變化，在不同實驗狀態下，成功驗證本系統能有效利用腦部血氧變化評估受測者的腦部活動情形。
此外，本研究更提出一套侵入式的高密度256通道之微探針陣列系統。利用矽基材製作微探針陣列，並透過垂直矽穿孔技術，實現超高密度的腦電訊號擷取探針陣列，將腦皮質層電訊號，垂直傳遞至後端神經訊號處理電路，節省額外繞線所造成的雜訊干擾與訊號損失。接著利用垂直矽穿孔封裝整合與無電鍍鎳金(ENIG)覆金封裝技術，可將腦神經電訊號處理晶片、微探針陣列透過中介層(interposer)進行整合，大幅縮小探針陣列系統尺寸，減少腦部手術開孔面積，提高手術成功率，並在有限面積下，實現超高解析度腦神經訊號擷取。在體感誘發電位的實驗中，本研究的矽探針電極，能夠有效分辨來自各部位肢體受到電刺激後的腦皮質層電訊號反應，有助於解析腦部各部位的神經傳遞的異常情形。

Brain activity monitoring can help reflect philological and psychological conditions of a subject through recordings of electroencephalography (EEG) and concentration of hemoglobin, and electrocorticography (ECoG). According to different requirement and applications, these tools of brain activity monitory could be useful to build brain mapping to figure out the relation between each biomarker to different brain diseases. Hence, this study proposed non-invasive and invasive system to monitor brain signal for further analysis.
In non-invasive monitoring, this study proposes a wearable system to simultaneously monitor variations in hemoglobin concentrations and EEG, which will help understand the relationship between these changes. To shorten the signal transmission path and reduce signal loss, we designed a low power consumption analog front-end (AFE) amplifier embedded into sensor devices to amplify and filter signals before processing and increase the signal-to-noise ratio. It can substitute the skin-electrode interface DC offset and avoid AFE amplifier saturation or distortion; it requires only 18.3-µW power consumption. Moreover, the sensor device with the AFE amplifier was integrated into the system for recording blood oxygen and EEG, and its feasibility for the system was proved by experiments involving closing the eyes, holding the breath, mental arithmetic, and grasping the hand. The experimental results proved that the near-infrared spectroscopy and electroencephalography recordings for event-triggered behaviors have different response times. These results help in disease diagnosis, surgery monitoring, neural rehabilitation, and prevention of behavioral disorders.
Moreover, highly integrated neural sensing microsystems are crucial to capture accurate signals for brain function investigations. In this study, a 256-channel neural sensing microsystem is presented based on 2.5D through-silicon-via (TSV) integration to acquire high spatiotemporal neural signals. This microsystem composes of dissolvable µ-needles, TSV-embedded µ-probes, and neural sensing circuits. Through TSV technologies, the neural signals sense from the proposed µ-probe array can be delivered to the neural signal processing circuit to prevent from signal distortion and external noise without redundant wire routing. By using technologies of TSV and ENIG, the size of the proposed micro system can be greatly reduced for implantation and increase the success rate of surgery with a limited surgical area. The feasibility of the proposed microsystem has been also successfully verified through responses of somatosensory evoked potentials according to different intensity of current stimuli at body, and shows the system can distinguish each stimulation came from different positions.

Table of Contents

摘要 III
Abstract V
Table of Contents VII
List of Figures X
List of Tables XVI
Chapter 1. Introduction 1
1.1 Brain Activities 1
1.2 Method of Brain Monitoring 2
1.3 Application of Brain Activity Monitoring 3
1.4 Organization 4
Chapter 2. Sensor Systems for Non-invasive and Invasive Brain Signal Recording 5
2.1 Non-invasive Brain Signal Recording 5
2.2 Application of Non-invasive Brain Signal Recording 7
2.2.1 Neural Rehabilitation 7
2.2.2 Brain Function and Disease Diagnosis 8
2.3 Introduction to EEG Signals 12
2.4 Introduction to NIRS Signals 14
2.5 BCI with EEG and NIRS 18
2.6 Relations between NIRS and EEG Signals 22
2.7 Invasive Brain Signal Recording 24
2.8 Importance of Sensor Design for Brain Signal Recording 31
2.8.1 Improvement of Non-invasive Sensor Design 31
2.8.2 Improvement of Invasive Sensor Design 32
Chapter 3. NIRS and EEG System for Brain Signal Recording 33
3.1 Proposed Cost-effective NIRS and EEG System 33
3.1.1 Design of NIRS and EEG Probe 35
3.1.2 Design of Analog Front-end Amplifier Circuit 37
3.1.3 Design of Proposed Pseudo Resistor 38
3.1.4 Simulation Result of Analog Front-end Amplifier Circuit 40
3.1.5 Chip implementation of the proposed analog front-end amplifier 43
3.1.6 Measurement results of the proposed analog front-end amplifier IC 44
3.1.7 Design of Post Signal Processing Circuit for NIRS and EEG Signals 46
3.1.8 Design of FPGA 48
3.1.9 LED and PD Calibration 49
3.1.10 Design of Software Interface 51
3.1.11 System Implementation and Integration 52
3.2 Experiments for NIRS and EEG System Verification 53
3.2.1 Brain Oxygen Blocking Test for NIRS system 54
3.2.2 Evoked Potential response to Alpha wave 57
3.3 Experiments for Simultaneously Recording with NIRS and EEG 60
3.3.1 Eye-closing and Breath-holding Experiment 61
3.3.2 Mental Arithmetic Experiment 67
3.3.3 Hand-clenching Experiments 70
3.4 Discussion of Simultaneously Recording with NIRS and EEG 73
Chapter 4. TSV-embedded µ-needle Array Neural Sensing Microsystem 75
4.1 Proposed ultra-high density TSV-based µ-needle array for ECoG/LFP Monitoring 75
4.2 Fabrication of TSV-embedded µ-needle Array Neural Sensing Microsystem 80
4.2.1 Fabrication of µ-probe Array 80
4.2.2 Fabrication of Interposer 81
4.2.3 256-Channel Neural Signal Acquisition Circuit 82
4.2.4 Fabrication Process of µ-needles 87
4.2.5 Implementation of TSV-embedded µ-needle Array Neural Sensing Microsystem 88
4.3 EIS and Physical Test of µ-probe array system for feasibility verification 90
4.3.1 EIS Measurement 90
4.3.2 Penetration Test 91
4.4 Somatosensory Cortex SSEP Experiment for Verification 93
4.4.1 Animal Preparation and Electrocorticography (ECoG) Recording 93
4.4.2 Electrical Stimulation and Data Analysis 96
4.4.3 Experimental Results and Discussion 99
4.5 Integration of TSV-embedded µ-needle Array Neural Sensing Microsystem 108
4.6 Discussion and Summarization 110
Chapter 5. Conclusion and Future Work 111
5.1 Conclusion 111
5.2 Future Work 113
Reference 114
Curriculum Vitae 123

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