Saron Paz Zvika Markfeld Tomer Daniel Oleg Imanilov

An open source software & hardwareopen source Combining:  Arduino Arduino  Sensors  Android ADK Android ADK  Android

 A glove that translates a predefined vocabulary of the deaf and mute sign language into text

 Develop a humane, easy-to-use interface allowing hearing impaired people to communicate more freely with their physical surrounding  Allow for new interaction models between (non- disabled) people and machines  For example, we can all probably think of reasonable ways to express concepts such as "Send", "Undo", "Okay" etc. in hand gestures.  Incorporating these into everyday interactions between people and computers may help people get into more intuitive touch with technology  This, in turn, may enable elderly people and/or people coming from non-technological background to tap into today's technological world

Lily-Pad Arduino samples sensors attached to glove ADK board relays data from the Lily-Pad to Android Android uses a back propagation Neural Network to analyze data

Arduino compatible microcontroller board designed for wearables and e-textiles

Flex Sensors measure finger bending Wii Nunchuck = Accelerometer + Gyros Conductive tape detects fingers touching

 Flex Sensor changes resistance when bent  Using a voltage divider the voltage is read by Arduino ADC (10 bits)

2 Buttons Joystick Accelerometer (X,Y,Z) Gyros (Roll, Pitch) I2C & Power

 Interconnected group of artificial neurons  Good at pattern recognitionpattern recognition

 Each connection has weight, which can be modified so as to model synaptic learning  Each neuron computes a threshold function of the weighted sum of its inputs  In a back propagation network weights are modified proportionally to the error

Artificial Neural Network GUI Relay ADK library Sensor Control Serial

 How to position flex sensors?  Fix tip to top and pass through sewn loops  How to distinguish between R,U,V,S,E,T,N?  Conductive tape detects fingers touching  How to distinguish between each letter?  Time based  How to record movement?  Freeze in the middle

 The user is required to calibrate the glove once the application starts  Calibration is needed to compensate for different wearers and even for re-wearing  All sensors are flexed to find working minima and maxima  After calibration all sensors are normalized

 The user is required to train the neural network to the vocabulary  Training involves recording of every gesture as well as training the neural network

Saron Paz is an experience designer & a hopeless idealist Zvika Markfeld is a design freshman and an aspiring inventor Tomer Daniel is a software architect by day & a maker by night Oleg Imanilov is a software engineer & a brilliant ideas generator

 Show & Tell Google code project  translator-glove/ translator-glove/  Sensors  Flex Sensors  Nunchuck controller-for-wii  Arduino  Wiichuck class  Android ADK