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1

Effects of sampling rate on multiscale entropy of electroencephalogram time series

Zheng Jinlin, Li Yan, Zhai Yawen, Zhang Nan, Yu Haoyang, Tang Chi, Yan Zheng, Luo Erping, Xie Kangning

Biocybernetics and Biomedical Engineering

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2023

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Vol. 43, no. 1

233--245

EN

A physiological system encompasses numerous components that function at various time scales. To characterize the scale-dependent feature, the multiscale entropy (MSE) analysis has been proposed to describe the complex processes on multiple time scales. However, MSE analysis uses the relative scale factors to reveal the time-related dynamics, which may cause in-comparability of results from diverse studies with inconsistent sampling rates. In this study, in addition to the conventional MSE with relative scale factors, we also expressed MSE with absolute time scales (MaSE). We compared the effects of sampling rates on MSE and MaSE of simulated and real EEG time series. The results show that the previously found phenomenon (down-sampling can increase sample entropy) is just the projection of the compressing effect of down-sampling on MSE. And we have also shown the compressing effect of down-sampling on MSE does not change MaSE’s profile, despite some minor right-sliding. In addition, by analyzing a public EEG dataset of emotional states, we have demonstrated improved classification rate after choosing appropriate sampling rate. We have finally proposed a working strategy to choose an appropriate sampling rate, and suggested using MaSE to avoid confusion caused by sampling rate inconsistency. This novel study may apply to a broad range of studies that would traditionally utilize sample entropy and MSE to analyze the complexity of an underlying dynamic process.

2

Complexity analyses of Godavari and Krishna river streamflow using the concept of entropy

Singh Rahul Kumar, Jain Manoj Kumar

Acta Geophysica

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2021

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Vol. 69, no. 6

2325--2338

EN

The hydrological regime in both the Godavari and Krishna River has been altered due to both human-induced and environmental changes. The present study utilizes the sample entropy and its more generalized approach known as multiscale entropy to investigate the temporal and spatial distribution of complexity and quantify them using SampEn values. Daily streamflow for five stations, three from Godavari River (Dhalegaon, Nowrangpur, and Polavaram), and two from Krishna River (Yadgir and K. Agraharam), was analysed for the complexity analyses. Trends in the streamflow for the selected gauging stations and their annual entropy values have also been evaluated using the Mann–Kendall test. The trend results revealed that three (Dhalegaon and Nowrangpur in Godavari basin and Yadgir in Krishna basin) out of five stations showed significant decreasing trends for both monthly and annual streamflow series. The declining trend in streamflow could be attributed to both anthropogenic (reservoir operation, increased water abstraction, etc.) and climatic (change in monsoon rainfall, temperature, etc.) factors. The most significant reduction in annual streamflow during the post-impact period was observed at Dhalegaon station in Godavari Basin (from 53,573 to 19,555 m3/s) signifying maximum alteration in annual flow regime. The entropy analysis results of streamflow showed that there was obvious spatial and temporal variation in the complexity, as indicated by the annual SampEn values. Although not profound, a negative correlation exists between the annual runoff and SampEn values (highest −0.42 at K. Agraharam) and hence a reverse correspondence exists between them. In MSE analysis, the original streamflow series increased with time scale (up to 30 days was chosen for this study), whereas entropy decreased with an increased time scale. Due to the fully operational state of the dams upstream of the gauging stations, the entropy values during the post-impact period were less the pre-impact period. The present study can be used as a scientific reference to use information science to detect hydrologic alterations in the river basins. Future studies should focus on considering both climatic and land-use changes in conjunction with the human-induced changes for more comprehensive river system disorder analysis.

3

Analiza kompleksowości sygnału pulsu rogówki u osób zdrowych, chorych na jaskrę i z podejrzeniem jaskry

Ząbkiewicz P. M., Placek M. M., Danielewska M. E.

Acta Bio-Optica et Informatica Medica. Inżynieria Biomedyczna

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2018

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Vol. 24, nr 2

65--73

PL

Puls rogówki, jako jeden z przejawów dynamiki oka, ma duży potencjał w diagnostyce jaskry. Sygnał pulsu rogówki, podobnie jak wiele innych sygnałów biologicznych, charakteryzuje się pewnym stopniem kompleksowości odzwierciedlającym zmiany w organizmie związane z wiekiem, a także występowaniem różnych zjawisk chorobowych. Metodą, która umożliwia pomiar złożoności sygnału, jest badanie entropii. W niniejszej pracy po raz pierwszy podjęto próbę sprawdzenia, czy analiza kompleksowości sygnału pulsu rogówki z zastosowaniem algorytmu Refined Composite Multiscale Fuzzy Entropy, pozwoli dokonać klasyfikacji badanych osób i określenie przynależności do grupy osób zdrowych, chorych na jaskrę albo z podejrzeniem jaskry. Analiza statystyczna klasyfikatorów uzyskanych na podstawie wyników entropii wykazała istotną różnicę w przypadku dwu par grup: z podejrzeniem jaskry vs z jaskrą oraz w przypadku zdrowych vs chorych na jaskrę. Uzyskane wyniki pokazują, że entropia wieloskalowa z sygnału pulsu rogówki może być w przyszłości nowym parametrem wspomagającym okulistów w diagnostyce jaskry.

EN

The corneal pulse, as one of the manifestations of eye dynamics, shows great potential in the glaucoma diagnosis. The corneal pulse signal, like many other biological signals, is characterized by a certain degree of complexity reflecting changes in the body and it is related to age, as well as the occurrence of various diseases. The method that allows the measurement of the signal complexity is entropy. In this study, for the first time, an attempt was made to assess, whether the complexity analysis of corneal pulse signal using Refined Composite Multiscale Fuzzy Entropy algorithm allows to classify the subjects as healthy, glaucomatous or glaucoma suspects. Statistical analysis of classifiers obtained from the results of entropy showed a significant difference in the case of two pairs of groups: with glaucoma suspects vs glaucoma patients, and healthy subjects vs glaucoma patients. The results show that multiscale entropy of the corneal pulse signal may become a new parameter supporting ophthalmologists in the diagnosis of glaucoma.

4

A hierarchical classification method for automatic sleep scoring using multiscale entropy features and proportion information of sleep architecture

Tian P., Hu J., Qi J., Ye X., Che D., Ding Y., Peng Y.

Biocybernetics and Biomedical Engineering

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2017

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Vol. 37, no. 2

263--271

EN

Background: Sleep scoring is a critical step in medical researches and clinical applications. Traditional visual scoring method is based on the processing of physiological signals, such as electroencephalogram (EEG), electrooculogram (EOG) and electromyogram (EMG), which is a time consuming and subjective procedure. It is an urgent task to develop an effective method for automatic sleep scoring. Method: This paper presents a hierarchical classification method for automatic sleep scoring by combining multiscale entropy features with the proportion information of the sleep architecture. Based on a three-layer classification scheme, sleep is categorized into five stages (Awake, S1, S2, SWS and REM). Specifically, the first layer is a standard SVM which performs classification between Awake and Sleep, while the second and third layers are implemented by combining probabilistic output SVM with proportion-based clustering. Multiscale entropy (MSE) from electroencephalogram (EEG) is extracted to represent signal characteristics in multiple temporal scales. Results: The proposed method is evaluated with 20 sleep recordings, including 10 subjects with mild difficulty falling asleep and 10 healthy subjects. The overall accuracy of the proposed method is 91.4%. Compared with traditional methods, the classification accuracy of the proposed method is more balanced and the global performance is much better. The dataset includes both healthy subjects and subjects with sleep disorders, which means the presented method has good generalization capacity. Experimental results demonstrate the feasibility of the attempt to introduce proportion information into automatic sleep scoring.

5

Analiza wpływu wybranych czynników na entropię wieloskalową rytmu pracy serca w populacji badanych pochodzącej z laboratorium snu

Radliński J., Baran Z., Tomalak W.

Pomiary Automatyka Kontrola

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2012

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R. 58, nr 4

365-368

PL

Celem pracy jest wstępna analiza wpływu czynników: fizjologicznego - wieku oraz chorobowych - zaburzeń oddychania, na entropię wieloskalową (Multiscale Entropy) rytmu pracy serca. W pracy dokonano analizy wpływu wieku na dwóch szerokich grupach badanych: osobach zdrowych (wiek od 1,5 do 63 lat) oraz grupie w wąskim przedziale wiekowym (40-50 lat) o różnym zakresie występowania zaburzeń oddychania w czasie snu (wskaźnik liczby zaburzeń oddychania RDI - Respiratory Disturbance Index 0,5 - 111 1/h). Wykazano wpływ wieku na wartość entropii (zmniejszanie), szczególnie w grupie osób dorosłych, oraz wpływ zaburzeń oddychania i zjawisk im towarzyszących (wybudzenia).

EN

High costs and complication of standard polysomnography (PSG) lead to attempts to develop cheaper and less complicated methods. The analysis of heart rate complexity using non-linear dynamics methods seems to be promising, however the dynamics of heart rate is biased by several physiological factors. The aim of that study was to check the influence of a physiological factor - age and of respiratory disorders during sleep on heart rate variability analysed by multiscale entropy (MSE). The two groups were selected from archived measurements from the Sleep Laboratory of Institute for TBC and Lung Diseases Rabka Branch: a healthy group and a group of semi-constant age but without limitations to those disorders (Table 1). In both groups the full night diagnostics PSG according to the American Academy of Sleep Medicine (AASM) rules was performed. The R-R intervals were detected in the recorded ECG signal (250Hz), and the multiscale entropy (Goldberg's MSE) was calculated. We found high correlation between the entropy and age (Figs. 1, 2, 3) in adults, however in the children group (age<15) there was no such relation. Similar results were found in analysis of the influence of respiratory disorders on the RR time series entropy (Figs. 4, 5, 6, 7). The results lead to a conclusion that heart rate complexity described with use of the MSE analysis is strongly biased by age. MSE could also detect changes in RR time series associated with respiratory disorders during sleep. The further investigations should be performed to