Tytuł artykułu

Noise Detection for Biosignals Using an Orthogonal Wavelet Packet Tree Denoising Algorithm

Tytuł czasopisma

International Journal of Electronics and Telecommunications

Rocznik

2016

Wolumin

vol. 62

Numer

No 1

Autorzy

Schimmack, Manuel ; Mercorelli, Paolo

Wydział PAN

Nauki Techniczne

Wydawca

Polish Academy of Sciences Committee of Electronics and Telecommunications

Data

2016

Identyfikator

DOI: 10.1515/eletel-2016-0002 ; eISSN 2300-1933 (since 2013) ; ISSN 2081-8491 (until 2012)

Źródło

International Journal of Electronics and Telecommunications; 2016; vol. 62; No 1

Referencje

Neville (2006), Wavelet denoising of coarsely quantized signals Transactions on Instrumentation and Measurement, IEEE, 55, 892. ; Unser (1996), A review of wavelets in biomedical applications of the, Proceedings IEEE, 84, 626, doi.org/10.1109/5.488704 ; Luca (1979), Physiology and mathematics of myoelectrical signals on, IEEE Transactions Biomedical Engineering, 26, 313, doi.org/10.1109/TBME.1979.326534 ; Jiang (2013), Multi - scale surface lectromyography modeling to identify changes in neuromuscular activation with myofascial pain Transactions on Neural Systems and, IEEE Rehabilitation Engineering, 21, 89. ; Kumar (2003), Wavelet analysis of surface electromyography to determine muscle fatigue Transactions on Neural Systems and, IEEE Rehabilitation Engineering, 11, 400. ; Phinyomark (2012), Feature extraction and reduction of wavelet transform coefficients for emg pattern classification and, Electronics Electrical Engineering, 122, 27. ; Shahid (2005), Application of higher order statistics techniques to EMG signals to characterize the motor unit action potential on, IEEE Transactions Biomedical Engineering, 52, 1195, doi.org/10.1109/TBME.2005.847525 ; Mercorelli (2006), Noise Level Estimation Using Haar Wavelet Packet Trees for Sensor Robust Outlier Detection Series : Lecture Note in Computer Springer - Verlag publishers, Sciences.