Wavelet principal component analysis of fetal movement counting data preceding hospital examinations due to decreased fetal movement: a prospective cohort study

Winje, Brita Askeland; Røislien, Jo; Saastad, Eli; Eide, Jorid; Riley, Christopher Finne; Stray‐Pedersen, Babill; Frøen, J. Frederik

doi:10.1186/1471-2393-13-172

Cited by 5 publications

(7 citation statements)

References 40 publications

(66 reference statements)

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“…Wavelets have a long tradition in time series analysis, and allows for statistical modelling of less smooth temporal changes. Wavelet based PCA has recently been applied successfully to among others fetal movement data [ 38 , 39 ] and a similar approach might be worthwhile exploring also for WWA data.…”

Section: Discussionmentioning

confidence: 99%

Wastewater-Based Epidemiology of Stimulant Drugs: Functional Data Analysis Compared to Traditional Statistical Methods

et al. 2015

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BackgroundWastewater-based epidemiology (WBE) is a new methodology for estimating the drug load in a population. Simple summary statistics and specification tests have typically been used to analyze WBE data, comparing differences between weekday and weekend loads. Such standard statistical methods may, however, overlook important nuanced information in the data. In this study, we apply functional data analysis (FDA) to WBE data and compare the results to those obtained from more traditional summary measures.MethodsWe analysed temporal WBE data from 42 European cities, using sewage samples collected daily for one week in March 2013. For each city, the main temporal features of two selected drugs were extracted using functional principal component (FPC) analysis, along with simpler measures such as the area under the curve (AUC). The individual cities’ scores on each of the temporal FPCs were then used as outcome variables in multiple linear regression analysis with various city and country characteristics as predictors. The results were compared to those of functional analysis of variance (FANOVA).ResultsThe three first FPCs explained more than 99% of the temporal variation. The first component (FPC1) represented the level of the drug load, while the second and third temporal components represented the level and the timing of a weekend peak. AUC was highly correlated with FPC1, but other temporal characteristic were not captured by the simple summary measures. FANOVA was less flexible than the FPCA-based regression, and even showed concordance results. Geographical location was the main predictor for the general level of the drug load.ConclusionFDA of WBE data extracts more detailed information about drug load patterns during the week which are not identified by more traditional statistical methods. Results also suggest that regression based on FPC results is a valuable addition to FANOVA for estimating associations between temporal patterns and covariate information.

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Section: Discussionmentioning

confidence: 99%

Wastewater-Based Epidemiology of Stimulant Drugs: Functional Data Analysis Compared to Traditional Statistical Methods

et al. 2015

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“…In this work, we have investigated FDA for WBE further. First comparing various FPCA using both Fourier and B-spline basis functions [ 25 , 26 ] to crude PCA [ 24 ] and the more temporally flexible WPCA [ 22 , 23 ]. We further explored the stability of the FPCA results through bootstrapping, and sensitivity to missing data by randomly deleting 5, 10, 15 and 20 % of the original data.…”

Section: Discussionmentioning

confidence: 99%

“…Wavelet basis functions are localized in both frequency and time domains simultaneously, allowing for the extraction of features that are less smooth from temporal data [ 20 , 21 ]. Wavelet-based principal component analysis (WPCA) has recently been applied successfully to analysis of foetal movement monitoring data [ 22 , 23 ]. The temporally more flexible WPCA could be able to detect rapid temporal changes in wastewater data.…”

Section: Introductionmentioning

confidence: 99%

“…The aim of this study was to explore whether the well-established FDA framework is sufficiently flexible to model temporal changes properly in wastewater data. We compared the stability of results, applying traditional principal component analysis (PCA) [ 24 ], FPCA [ 25 , 26 ], and WPCA [ 22 , 23 ] using various basis functions and smoothing approaches, and investigated the sensitivity to missing data.…”

Section: Introductionmentioning

confidence: 99%

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Exploring functional data analysis and wavelet principal component analysis on ecstasy (MDMA) wastewater data

Salvatore¹,

Bramness²,

Røislien³

2016

BMC Med Res Methodol

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BackgroundWastewater-based epidemiology (WBE) is a novel approach in drug use epidemiology which aims to monitor the extent of use of various drugs in a community. In this study, we investigate functional principal component analysis (FPCA) as a tool for analysing WBE data and compare it to traditional principal component analysis (PCA) and to wavelet principal component analysis (WPCA) which is more flexible temporally.MethodsWe analysed temporal wastewater data from 42 European cities collected daily over one week in March 2013. The main temporal features of ecstasy (MDMA) were extracted using FPCA using both Fourier and B-spline basis functions with three different smoothing parameters, along with PCA and WPCA with different mother wavelets and shrinkage rules. The stability of FPCA was explored through bootstrapping and analysis of sensitivity to missing data.ResultsThe first three principal components (PCs), functional principal components (FPCs) and wavelet principal components (WPCs) explained 87.5-99.6 % of the temporal variation between cities, depending on the choice of basis and smoothing. The extracted temporal features from PCA, FPCA and WPCA were consistent. FPCA using Fourier basis and common-optimal smoothing was the most stable and least sensitive to missing data.ConclusionFPCA is a flexible and analytically tractable method for analysing temporal changes in wastewater data, and is robust to missing data. WPCA did not reveal any rapid temporal changes in the data not captured by FPCA. Overall the results suggest FPCA with Fourier basis functions and common-optimal smoothing parameter as the most accurate approach when analysing WBE data.Electronic supplementary materialThe online version of this article (doi:10.1186/s12874-016-0179-2) contains supplementary material, which is available to authorized users.

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“…First, results appeared to be independent of counting method and DFM limit used, indicating that increased vigilance is important in stillbirth prevention. This observation has been corroborated by studies designed specifically to validate FMC data . Given the prominent role of awareness, the value of other interventions in raising maternal awareness warrants further study.…”

Section: Discussionmentioning

confidence: 59%

Interventions to enhance maternal awareness of decreased fetal movement: a systematic review

Winje

Wojcieszek

Gonzalez-Angulo

et al. 2015

BJOG

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Background Decreased fetal movement is associated with adverse pregnancy and birth outcomes; timely reporting and appropriate management may prevent stillbirth.Objectives Determine effects of interventions to enhance maternal awareness of decreased fetal movement.Search strategy Cinahl, The Cochrane Library, EMBASE, MEDLINE, PsycINFO and SCOPUS databases; without limitation on language or publication year.Selection criteria Randomised or non-randomised studies evaluating interventions to enhance maternal awareness of decreased fetal movement.Data collection and analysis Two authors independently extracted data and assessed quality.Main results We included 23 publications from 16 studies of fair to poor quality. We were unable to pool results due to substantial heterogeneity between studies. Three randomised controlled trials (RCTs) and five non-randomised studies (NRSs), involving 72 888 and 115 435 pregnancies, respectively, assessed effects of interventions on stillbirth and perinatal death. One large cluster RCT (n = 68 654) reported no stillbirth reduction, one RCT (n = 3111) reported significant stillbirth reduction, and one RCT (n = 1123) was small with no deaths. All NRSs favoured intervention over standard care; three studies (n = 31 131) reported significant reduction, whereas two studies (n = 84 304) reported non-significant reductions in stillbirth or perinatal deaths. Promising results from NRSs warrant further research. We found no evidence of increased maternal concern following interventions. No cost-effectiveness data were available.Conclusions We found no clear evidence of benefit or harm; indirect evidence suggests improved pregnancy and birth outcomes. The optimal approach to support women in monitoring their pregnancies needs to be established. Meanwhile, women need to be informed about the importance of fetal movement for fetal health.Keywords Awareness, decreased fetal movement, fetal movement counting, maternal concern, maternal-fetal attachment, stillbirth.Tweetable abstract The benefits and risks of interventions to increase pregnant women's awareness of fetal movement are unclear.

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Wavelet principal component analysis of fetal movement counting data preceding hospital examinations due to decreased fetal movement: a prospective cohort study

Cited by 5 publications

References 40 publications

Wastewater-Based Epidemiology of Stimulant Drugs: Functional Data Analysis Compared to Traditional Statistical Methods

Wastewater-Based Epidemiology of Stimulant Drugs: Functional Data Analysis Compared to Traditional Statistical Methods

Exploring functional data analysis and wavelet principal component analysis on ecstasy (MDMA) wastewater data

Interventions to enhance maternal awareness of decreased fetal movement: a systematic review

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