Alexander Amini : Tennis Sensor Data Analysis

The Official Website of Alexander Amini: Tennis Sensor Data Analysis
EU Young Scientist and BT Young Scientist of 2011

Tennis Sensor Data Analysis: An Automated System for Macro Motion Refinement

About Me:

My name is Alexander Amini. I was named European Union Young Scientist of 2011 with my project entitled Tennis Sensor Data Analysis: An Automated System for Macro Motion Refinement. I qualified for this competition by winning the top award at my national competition, the BT Young Scientist Exhibition, as did 87 other competitors from 37 different countries from all around the world.  I live in Dublin, Ireland and attend Castleknock College.

 The Young Scientist competitions have allowed me to meet so many incredible people all around the world. During the 2012 BT Young Scientist and Technology Exhibition I was able to meet the current President of Ireland, Michael D. Higgins, the U.S. Ambassador of Ireland, Daniel M. Rooney, and U.S. NASA Astronaut, Dr. Daniel Tani. In February 2011 I was also invited to meet the Eighth President of Ireland, Mary Patricia McAleese, in the Aras an Uachtarian


Project Abstract:

Sensors capable of capturing audio, video, and inertial data (such as accelerometers, gyroscopes, and magnetometers) have become so inexpensive, they are often found in smart phones and even remote control toys. Sports scientists also seek to use data from these devices to give insights to coaches, players, and fans. However, it is not easy to correlate the performance of an athlete to the huge volumes of raw data captured by such sensors. In this study, I collected and analyzed gigabytes of tennis sensor data. I discovered a technique for automatically distinguishing between 15 different tennis stroke types using only inertial data, with accuracy averaging over 98%. I tested my algorithms after collecting data at the elite Sanchez-Casal Tennis Academy, and created a real-time computer software system that employs the algorithms I discovered. My algorithms analyse sports performance data as it is generated and provide unbiased and precise motion refinement feedback to the athlete or coach. My findings are relevant to a wide variety of motion assessment scenarios in sports, physical therapy, and emergency response.

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