抑鬱或焦慮是最常見的心理健康問題之一，目前抑鬱症缺乏有效的治療方法，主要是由於對其遺傳基礎和潛在分子機制的不完全了解。越來越多的證據表明，空氣中的懸浮微粒(PM2.5)有機會越過血腦屏障(BBB)進入大腦，並且對大腦產生影響。這些影響包括抑鬱症這類型的心理疾病。懸浮微粒對抑鬱症是否具有潛在的影響仍然是個缺乏了解的問題。
本研究旨在探討二氧化矽微粒與斑馬魚焦慮和抑鬱行為關係。二氧化矽微粒為工業中常見的空氣污染源之一，在本研究中二氧化矽微粒被用來當作實驗的特定空氣汙染物。斑馬魚是研究抑鬱和焦慮症的優秀模型系統，因為斑馬魚的神經內分泌系統和焦慮反應都與人類相似。並且斑馬魚對人類的焦慮和抑鬱藥物具有高度的敏感性。
在這裡報告了一種使用物聯網技術研究抑鬱和焦慮的實驗方法。二氧化矽微粒透過自製的IoT空氣汙染箱輸入到斑馬魚的行為測試水箱裡面，並且在水箱中模擬出對人體有害的空氣污染濃度場景(55.5 ug/m3 ~ 500.4 ug/m3)。二氧化矽顆粒濃度對斑馬魚的影響的定量分析是通過使用開源軟件idTracker.ai來進行。
研究結果表明，二氧化矽顆粒可以誘導斑馬魚在高濃度實驗中表現出抑鬱行為，並可以為未來空氣污染對人類抑鬱症的研究提供一種新的行為檢測模型。這些發現意味著特定物質的類似行為和抑鬱誘導作用可能具有共同的生理機制。

Depression or anxiety is one of the most common mental health problems. The current lack of effective treatments for depression is mainly due to incomplete understanding of its genetic basis and underlying molecular mechanisms. More and more evidence shows that particulate matter (PM2.5) in the air has the opportunity to cross the blood-brain barrier (BBB), enter the brain, and impact the brain. These effects include mental illnesses such as depression. Whether aerosols have a potential impact on depression is still a question of lack of understanding.
This study aims to explore the relationship between silica particles and zebrafish anxiety and depression behavior. Silica particles are one of the common air pollution sources in the industry. In this study, silica particles were used as specific air pollutants in the experiment. Zebrafish is an excellent model for studying depression and anxiety because zebrafish's neuroendocrine system and anxiety response are similar to humans. Moreover, zebrafish are highly sensitive to human anxiety and depression drugs.
An experimental method using IoT technology to study depression and anxiety is reported here. Silica particles are input into the zebrafish test tank through the self-made IoT air pollution box. The air pollution concentration scene harmful to the human body is simulated in the test tank (55.5 g/m3 ~ 500.4 g/m3). Quantitative analysis of the effect of silica particle concentration on zebrafish was carried out using the open-source software idTracker.ai.
The research results show that silica particles can induce zebrafish to show depressive behavior in high-concentration experiments and provide a new behavior detection model for future research on human depression caused by air pollution. These findings imply that similar behaviors and depression-inducing effects of certain substances may have a common physiological mechanism.

誌謝 i
摘要 ii
Abstract iii
Contents v
List of figures vii
List of tables xvii
Chapter 1 Introduction 1
1-1 Background and motivation 1
1-2 Challenge and solution 15
1-2-1 Simulate human anxiety and depression behavior 16
1-2-2 3D video recording of zebrafish 34
1-2-3 3D video tracking of zebrafish 38
1-2-4 3D trajectory analysis of zebrafish 46
1-2-5 Quantitative control of air pollutions 49
1-3 Thesis layout 53
Chapter 2 Deep learning-based video tracking 54
2-1 AI、ML and DL 56
2-2 idtracker.ai 63
Chapter 3 Method 74
3-1 Technology of IoT system development 74
3-2 Experiment conceptual design 87
3-3 3D video recording system 94
3-3-1 Novel test tank 97
3-3-2 Stage 102
3-3-3 Combination of Novel Tank and stage 107
3-3-4 IoT camera system 113
3-4 IoT Air pollution box system 125
3-4-1 Assemble the IoT air pollution box 133
3-4-2 Generate the air pollution in box 136
3-4-3 PM2.5 sensor 144
3-4-4 SiO2 air pollutant test 149
3-4-5 Pump out air pollution 152
3-4-6 Control time limit test of air pump 160
3-4-7 Full setup of IoT Air pollution box 163
3-5 Real device 169
3-6 Pharmacological manipulation 171
3-7 Video tracking 175
Chapter 4 idtracker.ai tracking video analysis 179
4-1 Introduction to idtracker.ai neural network architecture 185
4-2 Deep Crossing detector (DCD) 190
4-3 Identification convolutional neural network (idCNN) 199
4-4 idtracker.ai automated tracking results of 3D zebrafish videos 209
Chapter 5 Zebrafish behavior analysis 226
5-1 3D behavior trajectory analysis of zebrafish 229
5-2 Geotaxis behavior analysis of zebrafish 234
5-3 Thigmotaxic behavior analysis of zebrafish 239
5-4 Analysis of the movement behavior of zebrafish 244
5-5 Comparison of the geotaxis, thigmotaxic and movement behavior of zebrafish 249
5-6 Fractal dimension analysis of zebrafish 252
Chapter 6 Conclusion and future work 253
6-1 Conclusion 253
6-2 Future work 256

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