Robust and Large-scale Human Motion Estimation with Low-cost Sensors

Speaker: Hua-I Chang
Affiliation: Ph.D. Candidate - UCLA

Abstract: Enabling large-scale monitoring and classification of a range of motion activities is of primary importance due to the need by healthcare and fitness professionals to monitor exercises for quality and compliance. Video based motion capturing systems (e.g., Vicon-460 camera) provide a partial solution. However, these expensive and fixed systems cannot be used for patients’ at-home daily motion monitoring. Wireless motion sensors, including accelerometers, gyroscopes and magnetometers, can potentially provide a low-cost, small-size, and highly-mobile option. However, acquiring robust inference of human motion trajectory via low-cost inertial sensors remains challenging. Sensor noise and drift, sensor placement errors and variation of activity over the population all lead to the necessity of a large amount of data collection. Unfortunately, such a large amount of data collection is prohibitively costly.

In observance of these issues, a series of solutions for robust human motion monitoring and activity classification will be presented. The implementation of a real-time context-guided activity classification system will be discussed. To facilitate ground truth data acquisition, we proposed a virtual inertial measurements platform to convert the currently available camera motion database into a noiseless and error-free inertial measurements database. An opportunistic calibration system which deals with sensor orientation and position will be discussed. In addition, a sensor fusion approach for robust upper limb motion tracking will also be presented.

Biography: Hua-I Chang is currently a Ph.D. candidate in the Department of Electrical Engineering under the mentorship of Professor Gregory J. Pottie. He received his B.S. degree in Electrical Engineering from National Chiao Tung University, Hsinchu, Taiwan in 2008. After that, he served as an IT officer in Taiwan Coast Guard during his mandatory military service. In 2012, he received a M.S. degree in Electrical Engineering at UCLA. Hua-I’s research interests include activity monitoring, motion reconstruction, machine learning and algorithm development.

For more information, contact Prof. Gregory J. Pottie ()

Date(s) - May 09, 2016
2:00 pm - 4:00 pm

E-IV Faraday Room #67-124
420 Westwood Plaza - 6th Flr., Los Angeles CA 90095