Kawala-Janik, Aleksandra, Podpora, Michal, Baranowski, Jerzy, Bauer, Waldemar and Pelc, Mariusz (2014) Innovative approach in analysis of EEG and EMG signals — Comparision of the two novel methods. In: 2014 19th International Conference on Methods and Models in Automation and Robotics (MMAR). Institute of Electrical and Electronics Engineers Inc., Piscataway, NJ, USA, pp. 804-807. ISBN 9781479950812 (doi:https://doi.org/10.1109/MMAR.2014.6957459)

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Abstract

In this paper comparison of the two innovative signal processing methods for analysis of both EEG and EMG biomedical signals is in short presented. The reason for that is caused by the fact, that nowadays the broad analysis of various biomedical signals is extremely popular. The first method presented in this paper relies on kernel density estimators application. Implementation of such method enables construction of densitograms for the examined bio-signals. One of the biggest advantages of this method is that it allows to obtain statistically filtered signals, which results in making the whole signal processing task significantly quicker. The second method described in this paper is based on basic mathematical operations only. Despite its simplicity the whole process can be implemented on almost any hardware platform, including those with very limited computational capabilities. Also it makes the task quick. In accordance with the conducted experiments - the method is also efficient and as it can also be implemented on embedded platform and the algorithm can be rewritten in any programming language, the potential application of this method is wide.

Item Type:	Conference Proceedings
Title of Proceedings:	2014 19th International Conference on Methods and Models in Automation and Robotics (MMAR)
Additional Information:	[1] This paper appears in: 2014 19th International Conference On Methods and Models in Automation and Robotics (MMAR). Conference Location : Miedzyzdroje, Poland. Issue Date: 2-5 Sept. 2014. Written by: Kawala-Janik, A.; Podpora, M.; Baranowski, J.; Bauer, W.; Pelc, M.
Uncontrolled Keywords:	EEG biomedical signal, EMG biomedical signal, densitogram, kernel density estimator, signal processing method
Subjects:	Q Science > QA Mathematics
Faculty / School / Research Centre / Research Group:	Faculty of Liberal Arts & Sciences
Related URLs:	Publisher
Last Modified:	14 Oct 2016 09:30
URI:	http://gala.gre.ac.uk/id/eprint/12809

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