Difference between revisions of "Human Motion Analysis using Inertial Sensors"

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{{StudentProjectTemplate
|Summary=Compare and evaluate accelerometer and gyroscopes for analyzing human motion in real-world applications.
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|Summary=Compare and evaluate accelerometer and gyroscopes for analyzing human motion in real-world applications.
 
|Keywords=inertial sensors, gait
 
|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.
 
|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.
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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.
 
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.
 
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|Prerequisites=Background in signal analysis and programming are required. Interest in inertial sensors is a bonus.
|Prerequisites=Background in signal analysis and programming are required. Interest in inertial sensors is a bonus.  
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|Supervisor=Siddhartha Khandelwal, Nicholas Wickström,
|Supervisor=Siddhartha Khandelwal, Nicholas Wickström,  
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|Level=Master
 
|Level=Master
 
|Status=Open
 
|Status=Open

Latest revision as of 13:19, 14 October 2015

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
TimeFrame
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.
Author
Supervisor Siddhartha Khandelwal, Nicholas Wickström
Level Master
Status Open


Background:

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.

Project Description:

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.

Activity Plan:

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.