scholarly journals Use of Functional Linear Models to Detect Associations between Characteristics of Walking and Continuous Responses Using Accelerometry Data

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6394
Author(s):  
William F. Fadel ◽  
Jacek K. Urbanek ◽  
Nancy W. Glynn ◽  
Jaroslaw Harezlak
Keyword(s):  
Physical Activity ◽  
Linear Models ◽  
Laboratory Data ◽  
Objective Measure ◽  
Functional Linear Model ◽  
Additional Information ◽  
Non Invasive ◽  
Continuous Responses ◽  
Wearable Accelerometers ◽  
Important Activity

Various methods exist to measure physical activity. Subjective methods, such as diaries and surveys, are relatively inexpensive ways of measuring one’s physical activity; however, they are prone to measurement error and bias due to self-reporting. Wearable accelerometers offer a non-invasive and objective measure of one’s physical activity and are now widely used in observational studies. Accelerometers record high frequency data and each produce an unlabeled time series at the sub-second level. An important activity to identify from the data collected is walking, since it is often the only form of activity for certain populations. Currently, most methods use an activity summary which ignores the nuances of walking data. We propose methodology to model specific continuous responses with a functional linear model utilizing spectra obtained from the local fast Fourier transform (FFT) of walking as a predictor. Utilizing prior knowledge of the mechanics of walking, we incorporate this as additional information for the structure of our transformed walking spectra. The methods were applied to the in-the-laboratory data obtained from the Developmental Epidemiologic Cohort Study (DECOS).

Markers of arterial stiffness in peripheral arterial disease

VASA ◽  
2015 ◽  
Vol 44 (5) ◽  
pp. 341-348 ◽  
Author(s):  
Marc Husmann ◽  
Vincenzo Jacomella ◽  
Christoph Thalhammer ◽  
Beatrice R. Amann-Vesti
Keyword(s):  
Arterial Stiffness ◽  
Peripheral Arterial Disease ◽  
Pulse Wave ◽  
Augmentation Index ◽  
Arterial Disease ◽  
Care Physician ◽  
Additional Information ◽  
Non Invasive ◽  
Assessment Techniques ◽  
Peripheral Arterial

Abstract. Increased arterial stiffness results from reduced elasticity of the arterial wall and is an independent predictor for cardiovascular risk. The gold standard for assessment of arterial stiffness is the carotid-femoral pulse wave velocity. Other parameters such as central aortic pulse pressure and aortic augmentation index are indirect, surrogate markers of arterial stiffness, but provide additional information on the characteristics of wave reflection. Peripheral arterial disease (PAD) is characterised by its association with systolic hypertension, increased arterial stiffness, disturbed wave reflexion and prognosis depending on ankle-brachial pressure index. This review summarises the physiology of pulse wave propagation and reflection and its changes due to aging and atherosclerosis. We discuss different non-invasive assessment techniques and highlight the importance of the understanding of arterial pulse wave analysis for each vascular specialist and primary care physician alike in the context of PAD.

scholarly journals Forensic analysis of beverage stains using hyperspectral imaging

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Binu Melit Devassy ◽  
Sony George
Keyword(s):  
Hyperspectral Imaging ◽  
Crime Scene ◽  
Forensic Analysis ◽  
Classification Model ◽  
Support Vector ◽  
Additional Information ◽  
Non Invasive ◽  
Spectral Bands ◽  
Data Dimensionality Reduction ◽  
Gradient Based

AbstractDocumentation and analysis of crime scene evidences are of great importance in any forensic investigation. In this paper, we present the potential of hyperspectral imaging (HSI) to detect and analyze the beverage stains on a paper towel. To detect the presence and predict the age of the commonly used drinks in a crime scene, we leveraged the additional information present in the HSI data. We used 12 different beverages and four types of paper hand towel to create the sample stains in the current study. A support vector machine (SVM) is used to achieve the classification, and a convolutional auto-encoder is used to achieve HSI data dimensionality reduction, which helps in easy perception, process, and visualization of the data. The SVM classification model was re-established for a lighter and quicker classification model on the basis of the reduced dimension. We employed volume-gradient-based band selection for the identification of relevant spectral bands in the HSI data. Spectral data recorded at different time intervals up to 72 h is analyzed to trace the spectral changes. The results show the efficacy of the HSI techniques for rapid, non-contact, and non-invasive analysis of beverage stains.

scholarly journals General Relative Rate Models for the Analysis of Studies Using Case-Cohort Designs

2018 ◽  
Vol 188 (2) ◽  
pp. 444-450
Author(s):  
David B Richardson ◽  
Bryan Langholz ◽  
Kaitlin Kelly-Reif
Keyword(s):  
Information Needs ◽  
Linear Models ◽  
Broad Class ◽  
Relative Rate ◽  
Model Misspecification ◽  
Model Fitting ◽  
Simple Random Sampling ◽  
Additional Information ◽  
Cohort Design ◽  
Cohort Data

Abstract A standard approach to analysis of case-cohort data involves fitting log-linear models. In this paper, we describe how standard statistical software can be used to fit a broad class of general relative rate models to case-cohort data and derive confidence intervals. We focus on a case-cohort design in which a roster has been assembled and events ascertained but additional information needs to be collected on explanatory variables. The additional information is ascertained just for persons who experience the event of interest and for a sample of the cohort members enumerated at study entry. One appeal of such a case-cohort design is that this sample of the cohort may be used to support analyses of several outcomes. The ability to fit general relative rate models to case-cohort data may allow an investigator to reduce model misspecification in exposure-response analyses, fit models in which some factors have effects that are additive and others multiplicative, and facilitate estimation of relative excess risk due to interaction. We address model fitting for simple random sampling study designs as well as stratified designs. Data on lung cancer among radon-exposed men (Colorado Plateau uranium miners, 1950–1990) are used to illustrate these methods.

scholarly journals Getting Moving Together; a field experiment on workplace physical activity

2021 ◽  
Author(s):  
Michael Sanders ◽  
Karen Tindall ◽  
Alex Gyani ◽  
Susannah Hume ◽  
Min-Taec Kim ◽  
...  
Keyword(s):  
Physical Activity ◽  
Social Comparison ◽  
Comparison Group ◽  
Controlled Trial ◽  
Wearable Devices ◽  
Control Group ◽  
Activity Levels ◽  
Additional Information ◽  
Baseline Activity ◽  
The Social

Importance: Wearable devices are widely used in an effort to increase physical activity and consequently to improve health. The evidence for this is patchy, and it does not appear that wearables alone are sufficient to achieve this end.Objective: To determine whether social comparisons in a workplace setting can increase the effectiveness of wearables at promoting physical activity.Design: A four week randomized controlled trial conducted in November 2015 with employees of a large firm. Participants were randomised to one of two treatment conditions (control vs social comparison) at team level, and teams are formed into ‘leagues’ based on their activity levels before the study. Impact is measured through wearable devices issued to all participants throughout the study duration.Setting: Offices of a large Australian employer.Participants: 646 employees of an Australian employer, issued with wearable activity trackers prior to the beginning of the study. Intervention(s) (for clinical trials) or Exposure(s) (for observational studies). Participants used a wearable device to track steps. Participants had been wearing these for at least four weeks at the outset of the trial, establishing a baseline level of activity. Teams (n=646, k=49), were randomly assigned to either control (k=24), or a social comparison (k=25) treatment. All participants took part in a step-count competition between their team and others at their employer, in which their team’s ranking within a mini-league of five teams, as well as their own activity was communicated each week. The control group had access to the usual features of the wearable, while the social comparison group received additional information about the performance of the other teams in their league, including how far behind and ahead their nearest rival teams were.Main Outcome(s) and Measure(s): Number of steps taken per day on average, measured by the wearable devices issued to all participants. Results: A total of 646 participants were included in the study. Compared to the control, participants in the social comparison group took significantly more steps per day during the trial period (an additional 620 steps, 8.2%, p<0.001). These effects are largest in both relative and absolute terms for people whose prior steps were in the bottom quartile of steps (an additional 948 steps, 40%, p<0.001), while the effect on people with highest levels of activity was a precisely estimated null (an additional 6 steps, 0.01%, p=0.98).Conclusions and Relevance: Social comparison increased the effectiveness of wearables at improving physical activity, particularly for those with the lowest baseline activity.

scholarly journals Identification of Plasmatic Biomarkers of Foie Gras Qualities in Duck by Metabolomics

2021 ◽  
Vol 12 ◽  
Author(s):  
Zohre Mozduri ◽  
Nathalie Marty-Gasset ◽  
Bara Lo ◽  
Ali Akbar Masoudi ◽  
Mireille Morisson ◽  
...  
Keyword(s):  
Amino Acids ◽  
Linear Models ◽  
Glucuronic Acid ◽  
Liver Weight ◽  
Quality Parameters ◽  
Strongly Correlated ◽  
H Nmr ◽  
Non Invasive ◽  
Technological Quality ◽  
Foie Gras

The foie gras is an emblematic product of French gastronomy composed of waterfowl fatty liver. The organoleptic qualities of this product depend on the liver characteristics such as liver weight (LW) and technological yield (TY) at cooking. One of the main issues for producers is to classify the foie gras with high or low technological quality before cooking them. Thus the study aims at identifying biomarkers of these characteristics with non-invasive biomarkers in duck. 1H-NMR (nuclear magnetic resonance of the proton) analyses were performed on plasma of male mule ducks at different time points during the overfeeding period to obtain a large range of liver characteristics so as to identify plasmatic biomarkers of foie gras. We used two methods, one based on bucket data from the 1H-NMR spectra and another one based on the fingerprints of several metabolites. PLS analyses and Linear models were performed to identify biomarkers. We identified 18 biomarkers of liver weight and 15 biomarkers of technological yield. As these two quality parameters were strongly correlated (−0.82), 13 biomarkers were common. The lactate was the most important biomarker, the other were mainly amino acids. Contrary to the amino acids, the lactate increased with the liver weight and decreased with the technological yield. We also identified 5 biomarkers specific to LW (3 carbohydrates: glucuronic acid, mannose, sorbitol and 2 amino acids: glutamic acid and methionine) that were negatively correlated to liver weight. It was of main interest to identify 2 biomarkers specific to the technological yield. Contrary to the isovaleric acid, the valine was negatively correlated to the technological yield.

scholarly journals Day Length and Weather Effects on Children’s Physical Activity and Participation in Play, Sports, and Active Travel

2012 ◽  
Vol 9 (8) ◽  
pp. 1105-1116 ◽  
Author(s):  
Anna Goodman ◽  
James Paskins ◽  
Roger Mackett
Keyword(s):  
Physical Activity ◽  
Cloud Cover ◽  
Objective Measure ◽  
Active Travel ◽  
Day Length ◽  
Physically Active ◽  
The Public ◽  
Daylight Saving ◽  
Long Day ◽  
Children’S Physical Activity

Background:Children in primary school are more physically active in the spring/summer. Little is known about the relative contributions of day length and weather, however, or about the underlying behavioral mediators.Methods:325 British children aged 8 to 11 wore accelerometers as an objective measure of physical activity, measured in terms of mean activity counts. Children simultaneously completed diaries in which we identified episodes of out-of-home play, structured sports, and active travel. Our main exposure measures were day length, temperature, rainfall, cloud cover, and wind speed.Results:Overall physical activity was higher on long days (≥ 14 hours daylight), but there was no difference between short (< 9.5 hours) and medium days (10.2–12.6 hours). The effect of long day length was largest between 5 PM and 8 PM, and persisted after adjusting for rainfall, cloud cover, and wind. Up to half this effect was explained by a greater duration and intensity of out-of-home play on long days; structured sports and active travel were less affected by day length.Conclusions:At least above a certain threshold, longer afternoon/evening daylight may have a causal role in increasing child physical activity. This strengthens the public health arguments for daylight saving measures such as those recently under consideration in Britain.

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