scholarly journals Examination of food reward and energy intake under laboratory and free-living conditions in a trait binge eating subtype of obesity

2013 ◽  
Vol 4 ◽  
Author(s):  
Michelle Dalton ◽  
John Blundell ◽  
Graham S. Finlayson
Keyword(s):  
Binge Eating ◽  
Energy Intake ◽  
Food Reward ◽  
Living Conditions ◽  
Free Living ◽  
Free Living Conditions

Association of number of bites and eating speed with energy intake: Wearable technology results under free-living conditions

Appetite ◽  
2021 ◽  
pp. 105653
Author(s):  
Nabil Alshurafa ◽  
Shibo Zhang ◽  
Christopher Romano ◽  
Hui Zhang ◽  
Angela Fidler Pfammatter ◽  
...  
Keyword(s):  
Energy Intake ◽  
Wearable Technology ◽  
Living Conditions ◽  
Free Living ◽  
Free Living Conditions

Safety and Performance of the Omnipod®Hybrid Closed-Loop System in Adolescents with Type 1 Diabetes over Five Days Under Free-Living Conditions

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1376-P
Author(s):  
GREGORY P. FORLENZA ◽  
BRUCE BUCKINGHAM ◽  
JENNIFER SHERR ◽  
THOMAS A. PEYSER ◽  
JOON BOK LEE ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Closed Loop ◽  
Living Conditions ◽  
Loop System ◽  
Closed Loop System ◽  
Free Living ◽  
And Performance ◽  
Free Living Conditions

Safety and Performance of the Omnipod® Hybrid Closed-Loop System in Adults with Type 1 Diabetes over Five Days Under Free-Living Conditions

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 207-OR
Author(s):  
BRUCE A. BUCKINGHAM ◽  
JENNIFER SHERR ◽  
GREGORY P. FORLENZA ◽  
THOMAS A. PEYSER ◽  
JOON BOK LEE ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Closed Loop ◽  
Living Conditions ◽  
Loop System ◽  
Closed Loop System ◽  
Free Living ◽  
And Performance ◽  
Free Living Conditions

scholarly journals Data-driven modelling approach to circadian temperature rhythm profiles in free-living conditions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jari Lipsanen ◽  
Liisa Kuula ◽  
Marko Elovainio ◽  
Timo Partonen ◽  
Anu-Katriina Pesonen
Keyword(s):  
Skin Surface ◽  
Living Conditions ◽  
Data Driven ◽  
Physiological Data ◽  
Free Living ◽  
Physiological Level ◽  
Temperature Rhythm ◽  
Time Series Modelling ◽  
Circadian Preference ◽  
Free Living Conditions

AbstractThe individual variation in the circadian rhythms at the physiological level is not well understood. Albeit self-reported circadian preference profiles have been consolidated, their premises are grounded on human experience, not on physiology. We used data-driven, unsupervised time series modelling to characterize distinct profiles of the circadian rhythm measured from skin surface temperature in free-living conditions. We demonstrate the existence of three distinct clusters of individuals which differed in their circadian temperature profiles. The cluster with the highest temperature amplitude and the lowest midline estimating statistic of rhythm, or rhythm-adjusted mean, had the most regular and early-timed sleep–wake rhythm, and was the least probable for those with a concurrent delayed sleep phase, or eveningness chronotype. While the clusters associated with the observed sleep and circadian preference patterns, the entirely unsupervised modelling of physiological data provides a novel basis for modelling and understanding the human circadian functions in free-living conditions.

Invariance of Wearing Location of Omron-BI Pedometers: A Validation Study

2010 ◽  
Vol 7 (6) ◽  
pp. 706-717 ◽  
Author(s):  
Weimo Zhu ◽  
Miyoung Lee
Keyword(s):  
Validation Study ◽  
Absolute Error ◽  
Activity Monitor ◽  
Error Rates ◽  
Living Conditions ◽  
The Body ◽  
Validity And Reliability ◽  
Free Living ◽  
Climbing Stairs ◽  
Free Living Conditions

Background:The purpose of this study was to investigate the validity and reliability evidences of the Omron BI pedometer, which could count steps taken even when worn at different locations on the body.Methods:Forty (20 males and 20 females) adults were recruited to walk wearing 5 sets, 1 set at a time, of 10 BI pedometers during testing, 1 each at 10 different locations. For comparison, they also wore 2 Yamax Digi-Walker SW-200 pedometers and a Dynastream AMP 331 activity monitor. The subjects walked in 3 free-living conditions: a fat sidewalk, stairs, and mixed conditions.Results:Except for a slight decrease in accuracy in the pant pocket locations, Omron BI pedometers counted steps accurately across other locations when subjects walked on the fat sidewalk, and the performance was consistent across devices and trials. When the subjects climbed up stairs, however, the absolute error % of the pant pocket locations increased significantly (P < .05) and similar or higher error rates were found in the AMP 331 and SW-200s.Conclusions:The Omron BI pedometer can accurately count steps when worn at various locations on the body in free-living conditions except for front pant pocket locations, especially when climbing stairs.

scholarly journals Substantial Intra-Individual Variability in Post-Prandial Time to Peak in Controlled and Free-Living Conditions in Children with Type 1 Diabetes

Nutrients ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 4154
Author(s):  
Emily Bell ◽  
Sabrina Binkowski ◽  
Elaine Sanderson ◽  
Barbara Keating ◽  
Grant Smith ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Individual Variability ◽  
Living Conditions ◽  
Optimal Time ◽  
Daily Routine ◽  
Free Living ◽  
Continuous Glucose Monitor ◽  
Time To Peak ◽  
Free Living Conditions

The optimal time to bolus insulin for meals is challenging for children and adolescents with type 1 diabetes (T1D). Current guidelines to control glucose excursions do not account for individual differences in glycaemic responses to meals. This study aimed to examine the within- and between-person variability in time to peak (TTP) glycaemic responses after consuming meals under controlled and free-living conditions. Participants aged 8–15 years with T1D ≥ 1 year and using a continuous glucose monitor (CGM) were recruited. Participants consumed a standardised breakfast for six controlled days and maintained their usual daily routine for 14 free-living days. CGM traces were collected after eating. Linear mixed models were used to identify within- and between-person variability in the TTP after each of the controlled breakfasts, free-living breakfasts (FLB), and free-living dinners (FLD) conditions. Thirty participants completed the study (16 females; mean age and standard deviation (SD) 10.5 (1.9)). The TTP variability was greater within a person than the variability between people for all three meal types (between-person vs within-person SD; controlled breakfast 18.5 vs 38.9 minutes; FLB 14.1 vs 49.6 minutes; FLD 5.7 vs 64.5 minutes). For the first time, the study showed that within-person variability in TTP glycaemic responses is even greater than between-person variability.

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