隨著智慧型手機的普及，市面上開始有著許多的智慧型穿戴裝置，與手機連線後，透過感測的數據來監控使用者的生理狀況。本研究主要目的在於，設計一個方便攜帶的肌肉電流檢測裝置，將檢測的數值傳送至手機，經由分析輸入的肌電訊號，及時量測個人肌肉狀況，並偵測使用者的動作，下達一些簡單指令。
在通訊介面上運用USB OTG介面來達到智慧型手機與8051單晶片之間的通訊，手機端使用Android提供的API來處理USB的訊息，8051端則是自行撰寫相關的中斷及描述元，並透過8051單晶片的ADC(Analog-to-digital converter)來取樣感測器的數值並回傳給手機端。因為是經由USB OTG來做傳輸，所以不論是8051還是感測器都不需要額外供電，由手機端提供即可。感測器的部份我們是選用三組肌肉電流感測器，藉著人體動作時肌肉釋放出的微弱電壓(Electromyogram, EMG)，來偵測使用者的肌電訊號。由於任何使用市電的家電或3C產品，通電後均會產生60Hz的電磁干擾，這會對感測器造成不可預期干擾，我們提出了幾個方法來減低市電干擾的影響，最後測試的結果，準確度高達95.1%。

With the popularity of smartphones, there are more and more smart wearable devices appear on the market, after connection with smartphones, it can be used to monitor the physiological condition of user through the sensed data. The main purpose of this paper is to design a portable muscle current detecting device which can send detected data to the smartphones, measure individual muscle state, and detect user’s action to order some simple command.
We select USB OTG as the communication interface to achieve the data transmission between smartphone and microcontroller. In the part of smartphone we use the API (Application programming interface) provided by Android to handle USB message, and in the part of microcontroller we design the associated interrupt and descriptor, then through the ADC (Analog-to-digital converter) to sample the sensor value and send the sampling data back to the smartphone. Because the transmission is via USB OTG, all power can be provided by the smartphone. In the part of sensor, we use 3 sets of EMG (Electromyogram) sensor to detect EMG signal from the weak voltage generated by muscle action. Since the environment exist the electromagnetic interference caused by AC power, EMG sensor will be affected, so we propose several methods to minimize the impact of this interference. After the last test, the accuracy is up to 95.1%.

致謝 I
中文摘要 II
ABSTRACT III
LIST OF TABLES VIII
LIST OF FIGURES IX
CHAPTER 1 INTRODUCTION 1
1.1. Motivation 1
1.2. Goals 2
1.2.1. Goals of Communication Interface 2
1.2.2. Goals of Android Application 3
1.3. Thesis Structure 3
CHAPTER 2 RELATED WORK 5
2.1. USB (Universal Serial Bus) 5
2.1.1. USB Descriptor 5
2.1.2. Transmission Mode 9
2.1.3. USB OTG (On-The-Go) 10
2.2. MCU (Microcontroller Unit) 11
2.3. Android 11
2.4. EMG 12
2.4.1. EMG Signal 12
2.4.2. EMG Sensor 13
CHAPTER 3 SYSTEM DESIGN 14
3.1. System Model 14
3.2. C8051 F342 15
3.3. Android program design 19
3.3.1. USB Host & Android Version 19
3.3.2. USB OTG Debug Mode 20
3.3.3. Program of Connection 22
3.3.4. Transmission Mode 24
3.4. Fast Mode & Slow Mode 26
3.4.1. Fast Mode 26
3.4.2. Slow Mode 33
CHAPTER 4 SIGNAL ANALYSIS & GESTURE DETECTION 36
4.1. EMG Signal 36
4.1.1. Time Domain(Electrical Activity) 36
4.1.2. IEMG (Integral of EMG) 36
4.1.3. RMS (Root Mean Square) 37
4.1.4. Frequency Domain 37
4.1.5. Grove – EMG Detector 38
4.2. Mapping System 39
4.2.1. Real-Time Signal(Electrical Activity) 42
4.2.2. Differential 42
4.2.3. Diff-IEMG 43
4.2.4. Diff-RMS 45
4.2.5. FFT (Fast Fourier Transform) 46
4.3. Electromagnetic Interference 49
4.3.1. Moving Average Filter 50
4.4. Action Recognition 55
4.4.1. Activity Time Constraint 55
4.4.2. Single Threshold 55
4.4.3. Double Threshold 56
4.4.4. Dynamic Threshold 58
4.4.5. Adaptive Threshold 58
4.4.6. Action Detection 60
CHAPTER 5 TESTING & DISCUSSION 62
5.1. Implementation Environment 62
5.2. Testing Process 62
5.3. Test Result 65
CHAPTER 6 CONCLUSION AND FUTURE WORK 67
REFERENCES 68

[1] USB 2.0 Specification
http://www.usb.org/developers/docs/usb20_docs/
[2] 林錫寬, USB 標準描述元之技巧, e科技雜誌, vol.24, Dec.2002
http://web.it.nctu.edu.tw/~sklin/etech/describe1.pdf
[3] 林錫寬, USB 之人性化界面裝置的報告描述元, e科技雜誌, vol.30, Jue.2003
http://web.it.nctu.edu.tw/~sklin/etech/report1.pdf
[4] C8051F340/1/2/3/4/5/6/7/8/9/A/B/C/D Full Speed USB Flash MCU Family
http://www.silabs.com/Support%20Documents/TechnicalDocs/C8051F34x.pdf
[5] Android developers - USB host
https://developer.android.com/guide/topics/connectivity/usb/host.html
[6] Android versions dashboards. Android Developers Site. (Viewed July, 2016)
https://developer.android.com/about/dashboards/index.html
[7] SDK versions. Android Developers Site. (Viewed July, 2016)
http://developer.android.com/guide/topics/manifest/uses-sdk-element.html
[8] Grove - EMG Detector
http://www.seeedstudio.com/wiki/Grove_-_EMG_Detector
[9] FFT.java Source File – Columbia University
https://www.ee.columbia.edu/~ronw/code/MEAPsoft/doc/html/FFT_8java-source.html
[10] Steven W. Smith (1999), The Scientist and Engineer’s Guide to Digital Signal Processing (2nd ed.), pp. 274-284. San Diego, California: California Technical.
[11] 蔡政龍, “Analyzing Human EMG Signal and Movement Velocity for Robot Control”, National Chiao Tung University, Master Thesis, Jul.2006.
[12] SMALLCOLLATION – Muscular System
https://smallcollation.blogspot.tw/p/muscular-system.html#gsc.tab=0