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USING GOOGLE’S ANDROID TO CREATE A HEALTH GAME

USING GOOGLE’S ANDROID TO CREATE A HEALTH GAME. By: Elie ElChartouni , Diami Goudiaby , Brice Sorrells. Motivation. Childhood Obesity According to the American Academy of Child & Adolescent Psychiatry:. Between 16 and 33 percent of children and adolescents are obese.

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USING GOOGLE’S ANDROID TO CREATE A HEALTH GAME

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  1. USING GOOGLE’S ANDROID TO CREATE A HEALTH GAME By: Elie ElChartouni, DiamiGoudiaby, Brice Sorrells

  2. Motivation • Childhood Obesity • According to the American Academy of Child & Adolescent Psychiatry: • Between 16 and 33 percent of children and adolescents are obese • An obese child between 10 and 13 has an 80% chance of being an obese adult • Annual cost to society for obesity is nearly $100 billion

  3. Background Info Current state of Health games This represents a first step in developing a health game for DexterNet

  4. DexterNet • Wearable body sensor network • Multiple wireless sensor nodes and one wearable base station • Action recognition • Automatic communication with doctors

  5. G1 Features • Android-based Mobile Phone • Built-in receiver and digital compass • Built-in Accelerometer & GPS • 3.2’’ Touchscreen 7/29/2009

  6. What is ANDROID? A complete set of software for mobile devices(an operating system, middleware and key mobile application). Is the first free, open source, and fully customizable mobile platform.

  7. Our Game • Multi-purpose: • Played for fun by children on their own • Will be tested at children’s obesity clinics to promote exercise • Uses single accelerometer on G1 Mobile Phone • Targeting children (6 - 10 yrs old)

  8. Original Goal • A “Simon Says” game • Use audio to prompt player to do an action • Requires reorientation of the sensor’s x,y,z-axis • Requires a classification algorithm to determine the actions done

  9. Data Collection • Actions to Recognize: • Jump, Squat, Shake, Slide, Spin left, Spin right.. • Collected accelerometer data from 10 different individuals doing each action four times

  10. Data Collection • Two different people jumping: • Huge variety in how the action looks

  11. Classification • Allen's algorithm • vector representation of data • Filtration and compression of vectors • sample action is compared to a sets of training data • best match is used • KNN algorithm

  12. New Game “GO CRAZY” • Altered game to measure general activity level • As a fun children’s game: • shake & “go crazy” level of activity • As a medical tool in an obesity clinic: • A way of measuring the level of effort put into doing a specified activity

  13. Future Development • Best classification algorithm • More data for the “Go Crazy” game • Testing on children needed

  14. Questions? 7/29/2009

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