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High Six The Sign Language Glove

High Six The Sign Language Glove. Group 6. Group Members. Kirk Chan – CpE Brian Troili – EE Ali Mizan – CpE Laura Rubio-Perez – EE & CpE. Project Introduction. Motivation. Fresh idea to the UCF community This project has the potential to help the speech impaired

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High Six The Sign Language Glove

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  1. High SixThe Sign Language Glove Group 6

  2. Group Members • Kirk Chan – CpE • Brian Troili – EE • Ali Mizan – CpE • Laura Rubio-Perez – EE & CpE

  3. Project Introduction

  4. Motivation • Fresh idea to the UCF community • This project has the potential to help the speech impaired • Based on the research, technologies necessary were interesting • Android development • Bluetooth communication • Personal taste

  5. Goals We want the following key factors:

  6. Specifications

  7. Design Approach

  8. Design Overview

  9. Hardware Components

  10. Hardware Components • Flex Sensors • Able to detect changes in bend/flex • Changes its resistance at several points along the device • When a current is applied, it creates a voltage divider

  11. Hardware Components • Pressure Sensors • Acts as a force sensing resistor • When the sensor is unloaded, its resistance is very high • When pressure is applied, its resistance decreases

  12. Hardware Components Analog/Digital Converter (ADC) • Serial communication preferred. • Large number of input channels. • Avoid serial address conflict. - ADS7828 • I2C compatible • 8 Channel ADC • variable I2C address

  13. Hardware Components Analog/Digital Converter (ADC) • Serial communication preferred. • Large number of input channels. • Avoid serial address conflict. - ADS7828 • I2C compatible • 8 Channel ADC • variable I2C address

  14. Hardware Components Accelerometer and Gyroscope • Inertial Measurement Unit (IMU) • Speed demand allow for serial buses. - ITG3200/ADXL345 combo board • 3.3V input • I2C compatible • 3 axis each • calibrate to 2, 4, 8, and 16g

  15. Hardware Components • ADXL345 • 3-axis accelerometer • Low power • Low current use: 40μA in measuring mode and 0.1μA in stand by • Suited for mobile device applications

  16. Hardware Components • ITG3200 • 3-axis digital gyroscope • Low-cost motion sensor • Features 16-bit analog-to-digital converters • Supply voltage range: 2.1V - 3.6V • Current consumption of 6.5mA

  17. Hardware Components Wireless Communication

  18. Hardware Components Wireless Communication

  19. Hardware Components HC-06 Bluetooth Module • Bluetooth v3.0 • Operating voltage: 3.6V – 6V • Working current of 40mA • Approximately $6 • Range: 30ft

  20. Hardware Components • Microcontroller

  21. Hardware Components • Microcontroller

  22. Hardware Components • Development Environment

  23. Hardware Components • Development Environment

  24. Hardware components • Battery

  25. Hardware components • Battery

  26. Hardware components • LP-063048 Polymer Lithium Ion Battery • Extremely light weight • Outputs a 3.7V at 1000 mAh. • Features 2C continuous discharge • Robust power source under extreme conditions • Long-term self-discharge rates • Approximately $9 • Bought from: Sparkfun

  27. Hardware components • Power Cell-LiPo Charger/Booster • Single cell boost converter to 3.3V and 5V and Micro-USB charger all in one • Boost converter is based on the TPS61200 from Texas Instrument • Low input voltage synchronous boost converter • Operating input voltage range from 0.3V to 5.5V • Fixed and adjustable output voltage from 1.8V to 5.5V

  28. Hardware components • Power Cell-LiPo Charger/Booster • micro-USB charger uses the MCP73831 • It charges 3.7V LiPo cells at 100mA. • Limits the charge current based on the die temperature during high power • It utilizes a constant- current/ constant-voltage configuration • The constant-voltage regulation has four options: 4.20V, 4.35V, 4.40V, and 4.50V

  29. Hardware components • LP2985 Regulator • Low-dropout: • 280 mV at 150-mA load current • 7 mV at 1-mA load • Low-noise operation with a typical output noise of 30 μVRMS • Consumption of only 0.01 μA when the ON/OFF pin is pulled low. • Overcurrent and thermal protection

  30. PCB

  31. PCB

  32. PCB

  33. PCB

  34. Software Components

  35. Android vs iPhone • Android • Cross platform capable integrated development environment • Familiarity with the Java language • The most popular mobile platform • iPhone • Can only be developed in Mac • Apps written in objective C • Apple development software only works with other apple development software

  36. Eclipse Advantages: More plug-ins available More commonly used Disadvantages: Has bugs and crashes a lot Android IDEs IntelliJ (free version) • Advantages: • Less buggy • More intuitive • Faster • Better GUI • Disadvantages: • Java, Groovy, or Scala are only 3 languages supported in free version

  37. Software Components • Two main components: • Android Application • Is the interface between the user and the classification algorithm • Takes in raw data from glove • Displays letter on screen • Translator • Translates letters just by checking flex sensors and accelerometer to see if they fit certain boundaries • The application has some default boundaries set, but can be customized by user

  38. Traditional Bluetooth Setup

  39. Our Bluetooth Setup

  40. Our Android Setup

  41. Threshold – Based Algorithm • How to recognize gestures? • Compare sensor input from glove to high and low thresholds. • Boundaries can be adjusted • Default boundaries we created come with application • New boundaries stored in local memory and can be reset back to defaults

  42. Threshold – Based Algorithm • How to segment data? • Recognition algorithm only called when hand is still for about .5 seconds • Which sensors need to be read? • The flex and pressure sensors alone can differentiate between 32 of the 36 character • For the 4 hand gestures that have same shape, orientation is used to differentiate them

  43. Final Financing

  44. Progress

  45. Issues • No such thing as universal boundaries • Boundaries differ from user to user • Hard to define boundaries • Even with just one user, it may be difficult to define boundaries that work well most of the time • BLE and Hidden Markov Model • TPS61200 reference errors

  46. Approaching the issues • No Universal Boundaries • allow the user to train boundaries for their hand • Boundaries hard to define • To make letters easier to classify, add a tolerance on top of the boundaries • Ie: if tolerance = 5%, high and low boundaries both multiplied by 1.05 • BLE and Hidden Markov Model • Switched to classic Bluetooth (3.0) • Switched to deterministic algorithm

  47. Questions?

  48. DEMO

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