臺灣博碩士論文加值系統

穿戴式生理監控系統解決了傳統監控系統上的許多限制，而類比前端電路是穿戴式生理監控系統中重要的區塊。本篇論文提出了類比前端感測電路中的低功耗低雜訊生理訊號放大器及小面積高功耗效率的高線性度轉導電容濾波器，並且使用懸浮閘電晶體編程技術調整此兩種電路的所有參數。

此篇論文提出了全差動電路及電流重複使用的低雜訊放大器，其雜訊效率因素的理論極限值等同於一顆電晶體，並用懸浮閘電晶體編程技術調整放大器的增益、高通截止頻率及低通截止頻率。量測到的雜訊效率因素範圍在不同的頻寬下為$1.96$到$2.25$。本論文用此低雜訊放大器量測了肌電圖、心電圖、眼動圖以及腦波。

本研究亦提出了一可重組化高功耗效率以及高面積效率的轉導電容二階濾波器，並使用懸浮閘電晶體編程技術調整所有二階濾波器的參數，如增益、頻寬以及品質因素。本論文提出一個由六組擴散器跟四組差動對組成之高線性度差動對去解決轉導電容二階濾波器操作在次臨界區時線性範圍極小的問題，此差動對亦展現了最佳的線性效率因素，又用互補的高線性度差動對以及懸浮閘電晶體提出一高功耗效率高線性度轉導放大器，而所提出的二階濾波器即是由四個高功耗效率的高線性度轉導放大器所組成。為了考慮製程變異的影響，本論文量測了許多不同晶片中的二階濾波器，量測結果顯示我們提出的架構有$62.3\dB$的動態範圍，與先前的論文做比較，本論文提出之轉導電容二階濾波器有最佳的功率效能、面積效能及最大的頻寬調整，最低及最高的可調整頻寬比例為$10000$倍。

又為了優化線性效率，本論文實現了一以全面學習粒子群演算法為基礎之最佳化演算法，並用此演算法對八組擴散器跟四組差動對進行優化，進而提出一線性度最佳化之差動對。本論文使用此差動對結合懸浮閘電晶體組成一高功耗效率線性度最佳化之轉導放大器，所提出的轉導放大器線性範圍比基本的次臨界區轉導放大器寬$8.25$倍，功耗效率提升$6.2$倍。又使用此轉導放大器提出一個高功耗效率線性度最佳化轉導電容濾波器，所有二階濾波器的參數：增益、頻寬以及品質因素，亦皆可以調整。量測到的動態範圍提升到$66\dB$。最後本論文串接了六個二階濾波器，提出了一可重組化高階高功耗效率以及線性度最佳化的轉導電容濾波器，並在本篇論文中展示了由六個二階濾波器合成出的十二階之巴特沃斯濾波器以及六階之柴比雪夫濾波器。

In a wearable health monitoring system, the analog front-end (AFE) circuit is the key element. This thesis presents two main components of AFE circuit for biomedical sensing applications, a low-power low-noise biopotential sensing amplifier (LNA) and a compact power-efficient linearized operational-transconductance-amplifier-capacitor (OTA-C) filter, with the feature of full reconfigurability. In these works, the floating-gate (FG) transistors are employed for reconfigurable design.

To detect weak biopotential signals, the input referred noise of an LNA must be as low as possible. By using complementary differential pairs along with the current reuse technique, the theoretical limit for the noise efficiency factor (NEF) of the proposed amplifier is approaching to that of a single transistor. In this proposed LNA, the gain, high frequency corner, and low frequency corner are programmable by tuning the charges stored in FG transistors. The measured NEF values in different bandwidth settings, are $1.96$ to $2.25$. The proposed amplifier is also demonstrated by recording electromyography (EMG), electrocardiography (ECG), electrooculography (EOG), and electroencephalography (EEG) signals from human bodies.

A FG-based reconfigurable OTA-C biquadratric filter with excellent power and area efficiencies is presented. According to FG techniques, all filter parameters, including the gains, the natural frequency, and the quality factor, in a biquadratic section are programmable. To widen the linear range of a subthreshold differential pair, we presented a linearized differential pair, hextuple-diffusor-quadruple-differential-pairs (HDQDP) a the excellent linearity efficiency factor (LEF). We also proposed an OTA composed of complementary HDQDPs and a FG common-mode feedback scheme. The reconfigurable biquadratic section is composed of four proposed power-efficient linearized OTAs. In consideration of process variation, multi-chip biquadratic sections are measured. The proposed topology exhibits the dynamic of $62.3\dB$. Compared with the prior works, the proposed power-efficient linearized reconfigurable OTA-C biquadratric section possesses the best power and area efficiencies with the natural frequency tuning range more than four decades.

To optimize linearity efficiency, an optimization algorithm based on the comprehensive learning particle swarm optimizer (CLPSO) is implemented to obtain dimensions of a linearity-optimized differential pair, octuple-diffusor-quadruple-differential-pairs (ODQDP). Based on the ODQDPs and FG transistors, a linearity-optimized OTA is designed to comprise a power-efficient biquadratic section. As measurement result showing, the proposed OTA can be improved to exhibit $8.25$ times wider input linear range and $6.2$ times improvement in power efficiency when compared with a basic subthreshold OTA. All filter parameters, including the gain, the natural frequency, and the quality factor, in this biquadratic section are programmable. The measured dynamic is improved to $66\dB$. A FG-based power-efficient OTA-C filter consisting of a cascade of multiple power-efficient linearity-optimized biquadratic sections are used to implemented a $12^{th}-$order Butterworth lowpass response and a $6^{th}-$order Chebyshev bandpass response.

Recommendation Letter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i
Approval Letter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
Abstract in Chinese . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
Abstract in English . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi
Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x
List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Biomedical Sensing Front-End Circuit . . . . . . . . . . . . . . . . . . . 1
1.3 Floating-Gate Transistor and Reliability . . . . . . . . . . . . . . . . . . 3
2 A Fully Reconfigurable Low-Noise Biopotential Sensing Amplifier with 1.96
Noise Efficiency Factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.2 Biopotential Amplifiers . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.3 Reconfigurable Low-Noise Amplifier Design . . . . . . . . . . . . . . . 12
2.3.1 Floating-Gate Operational Transconductance Amplifier . . . . . . 13
2.3.2 Reconfigurable Feedback Pseudo-Resistor . . . . . . . . . . . . . 17
2.3.3 Input and Output Voltage Swing Analysis . . . . . . . . . . . . . 17
2.3.4 Noise analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.3.5 Design Tradeoff and Comparison . . . . . . . . . . . . . . . . . 21
2.4 Measurement Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.4.1 Test Bench Results . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.4.2 Biological Measurement Results . . . . . . . . . . . . . . . . . . 29
2.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3 A Compact Power-Efficient Reconfigurable OTA-C Filter Achieving 62dB Dynamic
Range in Subthreshold Operation with A Tuning Range More Than Four
Decades . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.2 Differential Pairs, Linearization, and Linearity Efficiency Factor . . . . . 37
3.2.1 Basic Differential Pair . . . . . . . . . . . . . . . . . . . . . . . 37
3.2.2 Commonly-Used Linearization Techniques . . . . . . . . . . . . 38
3.2.3 Nonlinearity Cancellation . . . . . . . . . . . . . . . . . . . . . 40
3.2.4 The Linearity Efficiency Factor . . . . . . . . . . . . . . . . . . 41
3.3 Design of A Low-Power Highly-Linear OTA . . . . . . . . . . . . . . . 42
3.3.1 Hextuple-Diffusor-Quadruple-Differential-Pair (HDQDP) . . . . 42
3.3.2 Power Efficient Linearized OTA . . . . . . . . . . . . . . . . . . 46
3.3.3 OTA Noise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.4 Reconfigurable OTA-C Biquadratic Filter Architecture . . . . . . . . . . 49
3.5 Measurement Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.5.1 Power Efficient Linearized OTA . . . . . . . . . . . . . . . . . . 50
3.5.2 Reconfigurable Biquadratic filter . . . . . . . . . . . . . . . . . 54
3.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
4 An Optimization Algorithm for the Linearity-Optimized OTA-C Filter in Subthreshold
Operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
4.2 Review on Differential Pair Linearization . . . . . . . . . . . . . . . . . 66
4.2.1 Common Linearization Techniques . . . . . . . . . . . . . . . . 66
4.2.2 Linearity Efficiency Factor . . . . . . . . . . . . . . . . . . . . . 67
4.2.3 Multiple-Diffusor-Multiple-Differential-Pair(MDMDP) . . . . . 69
4.3 The Design of A Power-Efficient Linearity-Optimized OTA in Subthreshold
Operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
4.3.1 Transistor and Differential Pair Modelling . . . . . . . . . . . . . 72
4.3.2 Optimization Algorithm . . . . . . . . . . . . . . . . . . . . . . 74
4.3.3 The Complete Design of Current-reuse OTA . . . . . . . . . . . 77
4.4 Reconfigurable OTA-C Filter . . . . . . . . . . . . . . . . . . . . . . . . 80
4.5 Measurement Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
4.5.1 Power Efficient Linearity-Optimized OTA . . . . . . . . . . . . . 83
4.5.2 Reconfigurable Biquadratic Section . . . . . . . . . . . . . . . . 86
4.5.3 Programmable High-Order Filter . . . . . . . . . . . . . . . . . . 89
4.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
5 Conclusion and Future Works . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
5.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
5.2 Future Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
Letter of Authority . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104

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