Human Motion Analysis using Inertial Sensors
|Title||Human Motion Analysis using Inertial Sensors|
|Summary||Compare and evaluate accelerometer and gyroscopes for analyzing human motion in real-world applications.|
|Keywords||inertial sensors, gait|
|References|| J. Rueterbories, E. G. Spaich, B. Larsen, and O. K. Andersen, “Methods for gait event detection and analysis in ambulatory systems,” Med. Eng. & Phys., vol. 32, no. 6, pp. 545–552, 2010.
J. J. Kavanagh and H. B. Menz, “Accelerometry: A technique for quantifying movement patterns during walking,” Gait & Posture, vol. 28, no. 1, pp. 1–15, 2008.
D. Lai, R. Begg, and M. Palaniswami, “Computational intelligence in gait research: A perspective on current app. And future challenges,” Info. Tech. in Biomed., IEEE Trans. on, vol. 13, no. 5, pp. 687–702, 2009.
|Prerequisites||Background in signal analysis and programming are required. Interest in inertial sensors is a bonus.|
|Supervisor||Siddhartha Khandelwal, Nicholas Wickström|
In recent years, technological advancements in inertial sensors have made them miniature, low-powered, durable, inexpensive and highly mobile leading to the development of ambulatory and wearable systems. These systems are either being used as stand-alone devices or are integrated into smart phones and smart watches in order to collect humans’ motion data from their daily life. While many algorithms that assess this motion data have been developed from accelerometers, others have been developed using gyroscopes. However, it remains to be investigated which of the two is more appropriate for real-world applications.
The goal of this project is to collect accelerometer and gyroscope data from real-world experiments and implement state of the art algorithms on the collected signals. The results shall be compared and evaluated to present which is the better sensor for real-world applications. As this is a highly active research area right now, there is a high probability of this project leading to a research publication in a reputed conference or journal.
The suggested project could be specified in the following work packages:
WP1 Collecting human motion data in indoor and outdoor environments.
WP2 Implementing state of the art algorithms on the collected data.
WP3 Comparing, evaluating and presenting the results.