Evaluation of KINECT and SHIMMER Sensors for Detection of Gait Parameters

Katja Orlowski, Harald Loose

2013

Abstract

Detecting gait parameters is possible using various sensors based on different physical principles. In our investigation a visual system, the Microsoft KINECT, and an inertial sensor system with SHIMMER 9DoFsensors, are used for capturing the gait of various persons. Both systems have a small form factor and are affordable regarding cost. Hence these are well-suited for mobile applications in the health care environment. Using these low-cost sensor systems, motion capture and analysis can be done in hospitals, physiotherapy units or nursing homes. This paper focusses on the comparison of detected gait parameters by analyzing statistical parameters. The examination of accuracy of both systems is carried out in two steps; first by initially measuring the gait of a small group of volunteers and second of a larger group. The noise is also examined which has to be filtered out in the preprocessing procedure. The choice of filter impacts the detection of gait parameters. As a result the noise is characterized rather nonspecifically in both systems. As expected, the gait parameters determined by the systems are not identical, but similar. The deviations vary in the specific gait parameters; some are less error-prone than other.

References

  1. Fernandez, D. (2011). Skeletal tracking fundamentals (beta 2 sdk). http://channel9.msdn.com/Series/KinectSDK Quickstarts/Skeletal-Tracking-Fundamentals. Online: 16.02.2012.
  2. Greene, B. e. a. (2010). An adaptive gyroscope-based algorithm for temporal gait analysis. Med Biol Eng Comput, 48:1251-1260.
  3. Khoshelham, K. and Elberink, O. (2012). Accuracy and resolution of kinect depth data for indoor mapping applications. Sensors : journal on the science and technology of sensors and biosensors : open access, 12:1437-1454.
  4. Murray, M.P.; Drought, A. and Kory, R. (1964). Walking patterns of normal men. J Bone Joint Surg Am, 46A:335 - 360.
  5. Oeberg, T.; Karsznia, A. and Oeberg, K. (1993). Basic gait parameters : Reference data for normal subjects, 10- 79 years of age. Journal of Rehabilitation Research and Development, 30(2):210-223.
  6. Orlowski, K. and Loose, H. (2012). Low-cost locomotion sensors. Proceedings of the 13. Nachwuchswissenschaftlerkonferenz 2012, 13.
  7. Orlowski, K., Loose, H., Otte, K., Mansow-Model, S., and Thiers, A. (2012). Kinect and shimmer sensors in motion analysis in health applications. Proceedings of BIOSIGNALS 2012, Int. Conference on Bio-Inspired Systems and Signal Processing, Vilamoura, Algarve, Portugal, 1-4 Feb. 2012, pages 226-231.
  8. Perry, J. (2010). Gait Analysis - Normal and Pathological Function. Slack Inc.
  9. Taylor, T. (2011). Kinect for robotics. http://blogs. msdn.com/b/msroboticsstudio/archive/2011/11/29/ kinect-for-robotics.aspx. Online: 24.01.2012.
Download


Paper Citation


in Harvard Style

Orlowski K. and Loose H. (2013). Evaluation of KINECT and SHIMMER Sensors for Detection of Gait Parameters . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013) ISBN 978-989-8565-36-5, pages 157-162. DOI: 10.5220/0004227901570162


in Bibtex Style

@conference{biosignals13,
author={Katja Orlowski and Harald Loose},
title={Evaluation of KINECT and SHIMMER Sensors for Detection of Gait Parameters},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013)},
year={2013},
pages={157-162},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004227901570162},
isbn={978-989-8565-36-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013)
TI - Evaluation of KINECT and SHIMMER Sensors for Detection of Gait Parameters
SN - 978-989-8565-36-5
AU - Orlowski K.
AU - Loose H.
PY - 2013
SP - 157
EP - 162
DO - 10.5220/0004227901570162