The Review of the Major Entropy Methods and Applications in Biomedical Signal Research

Liu, Guangdi; Yuan, Xin; Yang, Chuanwei; Zhang, Le

doi:10.1007/978-3-319-94968-0_8

Cited by 9 publications

(6 citation statements)

References 84 publications

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“…This trend for the temperature to vary at different shooting distances was consistent with the findings observed in previously published studies where an acceptable temperature difference of 0.2 • C was seen when the measurements were performed at 0.2 m and 2.5 m distances from the ROI [64][65][66]. However, the magnitude of the measured differences in this study, in comparison to the previously published studies, varied.…”

Section: Discussionsupporting

confidence: 92%

Optimization of Image Capture Distance for Facial Thermograms in Dentistry

Schöffauer,

Angst,

Stillhart

et al. 2023

Applied Sciences

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Thermography has not yet been validated for the screening of oral disorders and no clear guidelines or methodology for this purpose have been defined in the literature. The current pilot study was aimed as an initial step to evaluate the influence of shooting distances on the detection of the temperature asymmetries on the face for the purpose of dental thermography. Facial thermograms were taken in three views at three shooting distances for each participant. The mean temperature of the overall image and at the region of interest (ROI) were measured from the analysis software. Thirty adult volunteers participated in this study [n = 30, mean age: 25.8 ± 6.0]. The differences between the mean temperature values at the ROI for all different shooting distances within each profile view were statistically significant [Front: H(2) = 80.176, p < 0.001; Left: H(2) = 21.399, p < 0.001; Right: H(2) = 49.451, p < 0.001]. The mean ROI temperature was influenced by personal effects (p < 0.001), medications (p < 0.001), undergoing dental treatments (p < 0.001) as well as the consumption of food (p < 0.001). This study concludes that the detection of temperature asymmetries on the face in adult volunteers are affected by the capture distance as well as factors such as medication, oral-care, and alimentation. Therefore, it is advised that personal as well as medical histories are obtained in detail prior to making the facial thermograms.

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Section: Discussionsupporting

confidence: 92%

Optimization of Image Capture Distance for Facial Thermograms in Dentistry

Schöffauer,

Angst,

Stillhart

et al. 2023

Applied Sciences

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“…Entropy is essentially a measure of irregularity/unpredictability, assigning lower entropy values to periodic, predictable data, and higher entropy values to irregular, unpredictable data. Multiple different implementations of entropy have been proposed for the analysis of time-varying physiological signals, including approximate entropy (ApEn), sample entropy (SampEn), multi-scale entropy, and cross entropy [ 17 , 18 , 19 , 20 ]. In the present work, we investigated two of the most widely used entropy measures for investigating physiological time series data, namely, ApEn and SampEn.…”

Section: Introductionmentioning

confidence: 99%

“…In the present work, we investigated two of the most widely used entropy measures for investigating physiological time series data, namely, ApEn and SampEn. Having been initially developed for physiological applications, both ApEn and SampEn have been demonstrated to provide reliable estimates of signal complexity in cardiovascular data [ 14 , 17 , 18 , 19 , 21 , 22 , 23 , 24 ]. ApEn was first proposed in 1991 by Pincus et al [ 25 ].…”

Section: Introductionmentioning

confidence: 99%

Associations between Neurocardiovascular Signal Entropy and Physical Frailty

Knight

Newman

O’Connor

et al. 2020

Entropy

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In this cross-sectional study, the relationship between noninvasively measured neurocardiovascular signal entropy and physical frailty was explored in a sample of community-dwelling older adults from The Irish Longitudinal Study on Ageing (TILDA). The hypothesis under investigation was that dysfunction in the neurovascular and cardiovascular systems, as quantified by short-length signal complexity during a lying-to-stand test (active stand), could provide a marker for frailty. Frailty status (i.e., “non-frail”, “pre-frail”, and “frail”) was based on Fried’s criteria (i.e., exhaustion, unexplained weight loss, weakness, slowness, and low physical activity). Approximate entropy (ApEn) and sample entropy (SampEn) were calculated during resting (lying down), active standing, and recovery phases. There was continuously measured blood pressure/heart rate data from 2645 individuals (53.0% female) and frontal lobe tissue oxygenation data from 2225 participants (52.3% female); both samples had a mean (SD) age of 64.3 (7.7) years. Results revealed statistically significant associations between neurocardiovascular signal entropy and frailty status. Entropy differences between non-frail and pre-frail/frail were greater during resting state compared with standing and recovery phases. Compared with ApEn, SampEn seemed to have better discriminating power between non-frail and pre-frail/frail individuals. The quantification of entropy in short length neurocardiovascular signals could provide a clinically useful marker of the multiple physiological dysregulations that underlie physical frailty.

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“…Richman and Moorman [ 38 ] developed sample entropy. Sample entropy, compared with approximate entropy, shows better relative consistency and less dependence on data length [ 38 , 39 , 40 ].…”

Section: Methodsmentioning

confidence: 99%

Multiscale Entropy as a New Feature for EEG and fNIRS Analysis

Angsuwatanakul

O’Reilly

Ounjai

et al. 2020

Entropy

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The present study aims to apply multiscale entropy (MSE) to analyse brain activity in terms of brain complexity levels and to use simultaneous electroencephalogram and functional near-infrared spectroscopy (EEG/fNIRS) recordings for brain functional analysis. A memory task was selected to demonstrate the potential of this multimodality approach since memory is a highly complex neurocognitive process, and the mechanisms governing selective retention of memories are not fully understood by other approaches. In this study, 15 healthy participants with normal colour vision participated in the visual memory task, which involved the making the executive decision of remembering or forgetting the visual stimuli based on his/her own will. In a continuous stimulus set, 250 indoor/outdoor scenes were presented at random, between periods of fixation on a black background. The participants were instructed to make a binary choice indicating whether they wished to remember or forget the image; both stimulus and response times were stored for analysis. The participants then performed a scene recognition test to confirm whether or not they remembered the images. The results revealed that the participants intentionally memorising a visual scene demonstrate significantly greater brain complexity levels in the prefrontal and frontal lobe than when purposefully forgetting a scene; p < 0.05 (two-tailed). This suggests that simultaneous EEG and fNIRS can be used for brain functional analysis, and MSE might be the potential indicator for this multimodality approach.

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The Review of the Major Entropy Methods and Applications in Biomedical Signal Research

Cited by 9 publications

References 84 publications

Optimization of Image Capture Distance for Facial Thermograms in Dentistry

Optimization of Image Capture Distance for Facial Thermograms in Dentistry

Associations between Neurocardiovascular Signal Entropy and Physical Frailty

Multiscale Entropy as a New Feature for EEG and fNIRS Analysis

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