Assessing Activity and Recovery Following Benign Gynecologic Surgery Using an Activity Monitor and Validated Tool Sets: A Pilot Study

2021 ◽  
Vol 28 (11) ◽  
pp. S70-S71
Author(s):  
JHJ Kim ◽  
CA Young ◽  
R Walters ◽  
T Ryntz ◽  
L Yurteri-Kaplan ◽  
...  
2020 ◽  
Vol 222 (3) ◽  
pp. S827-S828
Author(s):  
J.J. Kim ◽  
C. Young ◽  
R. Walters ◽  
T. Ryntz ◽  
L.A. Yurteri-Kaplan ◽  
...  

2019 ◽  
Vol 99 (12) ◽  
pp. 1656-1666
Author(s):  
Jean A M Ribeiro ◽  
Simone G Oliveira ◽  
Luciana Di Thommazo-Luporini ◽  
Clara I Monteiro ◽  
Shane A Phillips ◽  
...  

Abstract Background After experiencing stroke, individuals expend more energy walking than people who are healthy. However, among individuals who have experienced stroke, the correlation between the energy cost of walking, as measured by validated tests (such as the 6-minute walk test), and participation in walking, as measured by more sensitive tools (such as an ambulatory activity monitor), remains unknown. Objective The main objective of this study was to determine whether the energy cost of walking is correlated with participation in walking. Design This study was a correlational, cross-sectional pilot study. Methods Data from 23 participants who had experienced chronic stroke were analyzed. On the first day, data on oxygen uptake were collected using a portable metabolic system while participants walked during the 6-minute walk test. Then, the ambulatory activity monitor was placed on the participants’ nonparetic ankle and removed 9 days later. The energy cost of walking was calculated by dividing the mean oxygen uptake recorded during the steady state by the walking speed. Results The energy cost of walking was correlated with the following: the number of steps (Spearman rank correlation coefficient [rs] = −0.59); the percentage of time spent in inactivity (rs = 0.48), low cadence (rs = 0.67), medium cadence (rs = −0.56), high cadence (rs = −0.65), and the percentages of steps taken at low cadence (rs = 0.65) and high cadence (rs = −0.64). Limitations Individuals who were physically inactive, convenience sampling, and a small sample size were used in this study. Conclusions Higher energy costs of walking were associated with fewer steps per day and lower cadence in real-world walking in individuals who had experienced stroke.


2020 ◽  
Vol 159 (1) ◽  
pp. 187-194
Author(s):  
Oliver Zivanovic ◽  
Ling Y. Chen ◽  
Andrew Vickers ◽  
Alli Straubhar ◽  
Raymond Baser ◽  
...  

Author(s):  
Leandro Mantoani ◽  
Rita Priori ◽  
Chevone Barretto ◽  
Privender Saini ◽  
Mareike Klee ◽  
...  

e-Pedagogium ◽  
2011 ◽  
Vol 11 (3) ◽  
pp. 147-162
Author(s):  
Erik Sigmund ◽  
Romana Šnoblová ◽  
Petra Nováková Lokvencová ◽  
František Chmelík ◽  
Dagmar Sigmundová ◽  
...  

2012 ◽  
Vol 19 (5) ◽  
pp. 606-614 ◽  
Author(s):  
Katherine G. Kratz ◽  
Stephanie H. Spytek ◽  
Aileen Caceres ◽  
Roy Lukman ◽  
Steven D. McCarus

2017 ◽  
Vol 5 (1) ◽  
pp. e2 ◽  
Author(s):  
Justin David Schrager ◽  
Philip Shayne ◽  
Sarah Wolf ◽  
Shamie Das ◽  
Rachel Elizabeth Patzer ◽  
...  

2020 ◽  
Author(s):  
Aditya Ponnada ◽  
Binod Thapa Chhetry ◽  
Justin Manjourides ◽  
Stephen Intille

BACKGROUND Ecological momentary assessment (EMA) is an in-situ method of gathering self-report on behaviors using mobile devices. Microinteraction-EMA (Micro-EMA or μEMA) is a type of EMA where all the self-report prompts are single-question surveys that can be answered using a one-tap glanceable microinteraction, conveniently on a smartwatch. Prior work suggests that μEMA may permit a substantially higher prompting rate than EMA with higher response rates. However, the validity of μEMA self-report has not yet been assessed. OBJECTIVE In this pilot study, we evaluated the criterion validity of μEMA on a smartwatch, using physical activity (PA) assessment as an example behavior of interest. METHODS Seventeen participants answered 72 μEMA prompts each day for one-week, self-reporting whether they were doing sedentary, light/standing, moderate/walking, or vigorous activities at each prompt. Responses were then compared with a research-grade activity monitor worn on the dominant ankle continuously measuring PA. RESULTS We observed significantly higher (P <.001) momentary PA levels on the activity monitor when participants self-reported (using μEMA) engaging in moderate/walking or vigorous activities as compared to sedentary or light/standing activities. CONCLUSIONS For PA measurement, high-frequency μEMA self-report could be used to capture the information comparable to that of a research-grade continuous sensor – suggesting criterion validity.


Sign in / Sign up

Export Citation Format

Share Document