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Multistate Lempel-Ziv (MLZ) index interpretation as a measure of amplitude and complexity changes
Sarlabous Uranga, Leonardo; Torres Cebrián, Abel; Fiz Fernández, José Antonio; Gea, Joaquim; Galdiz, Juan B.; Jané Campos, Raimon
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial; Universitat Politècnica de Catalunya. SISBIO - Senyals i Sistemes Biomèdics
The Lempel-Ziv complexity (LZ) has been widely used to evaluate the randomness of finite sequences. In general, the LZ complexity has been used to determine the complexity grade present in biomedical signals. The LZ complexity is not able to discern between signals with different amplitude variations and similar random components. On the other hand, amplitude parameters, as the root mean square (RMS), are not able to discern between signals with similar power distributions and different random components. In this work, we present a novel method to quantify amplitude and complexity variations in biomedical signals by means of the computation of the LZ coefficient using more than two quantification states, and with thresholds fixed and independent of the dynamic range or standard deviation of the analyzed signal: the Multistate Lempel-Ziv (MLZ) index. Our results indicate that MLZ index with few quantification levels only evaluate the complexity changes of the signal, with high number of levels, the amplitude variations, and with an intermediate number of levels informs about both amplitude and complexity variations. The study performed in diaphragmatic mechanomyographic signals shows that the amplitude variations of this signal are more correlated with the respiratory effort than the complexity variations. Furthermore, it has been observed that the MLZ index with high number of levels practically is not affected by the existence of impulsive, sinusoidal, constant and Gaussian noises compared with the RMS amplitude parameter.
Peer Reviewed
Àrees temàtiques de la UPC::Enginyeria biomèdica::Electrònica biomèdica
Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
Medical signal processing
Lempel-Ziv complexity
Respiratory system
Respiració -- Mesurament
Processament digital -- Biomedicina
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Sarlabous Uranga, Leonardo; Torres Cebrián, Abel; Fiz Fernández, José Antonio; Gea Guiral, Joaquim; Martínez Llorens, Juana María; Morera Prat, Josep Maria; Jané Campos, Raimon
 

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