1. High Six The 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
Glove diagram contrast. Re-do please.

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: HARDWARE SOFTWARE Low-power
Android
Lightweight
Accurate & fast translations
Wireless
Support text & audio translations
Low power relative to Bluetooth Classic

6. American 26 letters, 10 numbers
Specifications
Component
Design Specification
Hand gesture translation
Less than 1s
Glove weight
Less than 1.5lbs
Battery life (from one charge)
Approximately 20hr
Application startup
Within 5s
Bluetooth connection range
Up to 50m
Default gesture library
American 26 letters, 10 numbers

7. Design Approach
Draw squares in final copy

8. Design Overview

9. Hardware Components
Our hardware block diagram is divided into 4 subsystems:
Analog sensors
IMU
Power supply
Communication

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
Due to the very little variety of flex sensor available in the market .. long-short
We selected the 2.2” flex sensor. This decision was made because sensors get ruin when bend more than 90 degree.
This was important to consider since most of the hand gestures in the American sign language blend the fingers at a degree greater than 90.
There is a total of 11 flex sensors in our glove, there are 2 sensors in each finger and one across the palm

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
For the hand gestures ,such as the letter S, that have specific points of contact we decided to use pressure sensors in order to identify them easily.
We also selected the pressure sensors because there are cheaper and reliable than the case of adding flex sensors in between fingers

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 Wifi Bluetooth NFC
Secure connection
Portable connection
Low power
Approx. 100m range
Approx. 7-8in

18. Hardware Components Wireless Communication Wifi Bluetooth NFC
Secure connection
Portable connection
Low power
Approx. 100m range
Approx. 7-8in

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 MSP430g2553 ATmega328p ATmega32u4
Operating Voltage
3.3V 5V
5.5V
Digital I/O Pins 12 14
Analog Input Pins 6
Clock Speed
16MHz
Architecture
RISC
Flash Memory
16KB
32KB

21. Hardware Components Microcontroller MSP430g2553 ATmega328p ATmega32u4
Operating Voltage
3.3V 5V
5.5V
Digital I/O Pins 12 14
Analog Input Pins 6
Clock Speed
16MHz
Architecture
RISC
Flash Memory
16KB
32KB

22. Hardware Components Development Environment Arduino IDE Code Composer
Free
Open source (Unlimited support )
Limited support
Extensive libraries
Direct access to control registers
avr-gcc compiler
C/C++ compilers and assembly

23. Hardware Components Development Environment Arduino IDE Code Composer
Free
Open source (Unlimited support )
Limited support
Extensive libraries
Direct access to control registers
avr-gcc compiler
C/C++ compilers and assembly

24. Hardware components Battery Nickel Cadmium Nickel Metal Hydride
Polymer Lithium Ion
Rechargeable
Low energy density
High energy density
Highest energy density
Good performance in low temperature
Can operate in low temperature
Resistant to overcharge
Not environmental friendly
Limited service life
Require circuit protection
High-self discharge
Degradation in performance
Age quickly

25. Hardware components Battery Nickel Cadmium Nickel Metal Hydride
Polymer Lithium Ion
Rechargeable
Low energy density
High energy density
Highest energy density
Good performance in low temperature
Can operate in low temperature
Resistant to overcharge
Not environmental friendly
Limited service life
Require circuit protection
High-self discharge
Degradation in performance
Age quickly

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
As charge/discharge cycles are repeated, the battery capacity gradually declines

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
lm2576

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
lm2576

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

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. Successful Recognition of a letter
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
Successful Recognition of a letter
Sensor
High Threshold
Sensor data
Low Threshold
Within boundaries? S1 18 15 13
yes S2 11 9 S3 25 21 17
From mobile development environment to deeper look into the layout of Android app

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
From mobile development environment to deeper look into the layout of Android app

43. Final Financing DESCRIPTION QTY PRICE Flex sensors 2.2” 11 $79.50
IMU Digital Combo Board (3-Axis Gyro/Accelerometer) 1
$51.96
Flexiforce Pressure Sensors 4
$79.80
Bluetooth module (Free)
$0.00
Microcontroller (Atmega 328P)
$37.97
PCB 2
$584.78
Miscellaneous Surface Mounting -
$85.00
TOTAL
$919.00
Boeing sponsorship
- $518.00
Total Available from Sponsorship
Over budget
$401.00
Total per person
$100.25
here is what we have so far
thank you boeing
early stages of our development
half way done through our budget
underbudget-pcb

44. Progress

45. Issues No such thing as universal boundaries Hard to define 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
May lack libraries for Arduino IDE.
BLE lacks online support since it’s new.
We’ve determined that the hidden markov model is the appropriate algorithm that we need for our project, but the exact implementation is still under research. It’s a complex algorithm and it’s going to take time to implement it as a software module and test it against various hand sizes and gestures.

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