BIOSIGNALS EVENTS DETECTION - A Morphological Signal-independent Approach

Rui Santos, Joana Sousa, Borja Sañudo, Carlos J. Marques, Hugo Gamboa

2012

Abstract

This study presents a signal-independent algorithm, which detects significant events in a biosignal, without previous knowledge or specific pre-processing steps. From a morphological analysis, the algorithm computes the instants when the most significant standard deviation discontinuities occur. An iterative optimization step is then applied. This assures that a minimal error is achieved when modeling the signal segments (between the detected instants) with a polynomial regression. The detection scale can be modified by an optional input scale factor. An objective algorithm performance evaluation procedure was designed, and applied on two types of synthetic signals, for which the events instants were previously known. An overall mean error of 20.32 (+/-16.01) samples between the detected and the real events show the high accuracy of the proposed algorithm. The algorithm was also applied on accelerometry and electromyography raw signals collected in different experimental scenarios. The fact that this approach does not require any previous knowledge and the good level of accuracy represents a relevant contribution in events detection and biosignal analysis.

References

  1. Bonato, P., D'Alessio, T., and Knaflitz, M. (1998). A statistical method for the measurement of muscle activation intervals from surface myoelectric signal during gait. Biomedical Engineering, IEEE Transactions on, 45(3):287-299.
  2. Ciaccio, E., Dunn, S., and Akay, M. (1993). Biosignal pattern recognition and interpretation systems. Engineering in Medicine and Biology Magazine, IEEE, 12(3):89-95.
  3. Clifford, G. (2006). A novel framework for signal representation and source separation: Applications to filtering and segmentation of biosignals. Journal of Biological Systems, 14(2):169-184.
  4. Hodges, P. and Bui, B. (1996). A comparison of computer-based methods for the determination of onset of muscle contraction using electromyography. Electroencephalography and Clinical Neurophysiology/Electromyography and Motor Control, 101(6):511-519.
  5. Marques, C. J., Gamboa, H., Lampe, F., Barreiros, J., and Cabri, J. (2011). Muscle activation thresholds before and after total knee arthoplasty - protocol of a randomized comparison of minimally invasive vs. standard approach. In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing.
  6. PLUX (2007). PLUX - Wireless Biosignals, S.A. [online] Available at: http://plux.info/ [Accessed 5 September 2011].
  7. Sankur, B., Gü ler, E. C., and Kahya, Y. (1996). Multiresolution biological transient extraction applied to respiratory crackles. Computers in biology and medicine, 26(1):25-39.
  8. Staude, G., Flachenecker, C., Daumer, M., and Wolf, W. (2001). Onset detection in surface electromyographic signals: a systematic comparison of methods. EURASIP Journal on Applied Signal Processing, 2001(1):67-81.
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Paper Citation


in Harvard Style

Santos R., Sousa J., Sañudo B., J. Marques C. and Gamboa H. (2012). BIOSIGNALS EVENTS DETECTION - A Morphological Signal-independent Approach . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2012) ISBN 978-989-8425-89-8, pages 385-388. DOI: 10.5220/0003772403850388


in Bibtex Style

@conference{biosignals12,
author={Rui Santos and Joana Sousa and Borja Sañudo and Carlos J. Marques and Hugo Gamboa},
title={BIOSIGNALS EVENTS DETECTION - A Morphological Signal-independent Approach},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2012)},
year={2012},
pages={385-388},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003772403850388},
isbn={978-989-8425-89-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2012)
TI - BIOSIGNALS EVENTS DETECTION - A Morphological Signal-independent Approach
SN - 978-989-8425-89-8
AU - Santos R.
AU - Sousa J.
AU - Sañudo B.
AU - J. Marques C.
AU - Gamboa H.
PY - 2012
SP - 385
EP - 388
DO - 10.5220/0003772403850388