Monitoring Physical Activity Intensity During Pregnancy

2021 ◽  
pp. 155982762110522
Author(s):  
Kelly R. Evenson ◽  
Kathryn R. Hesketh
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Pregnant Women ◽  
Scientific Literature ◽  
Healthcare Providers ◽  
Physical Activity Intensity ◽  
Activity Intensity ◽  
Relative Exercise Intensity ◽  
Exercise During Pregnancy ◽  
Apparently Healthy

For apparently healthy pregnant women, regular physical activity is recommended. The American College of Obstetricians and Gynecologists (ACOG) created recommendations for physical activity and exercise during pregnancy in 1985. At that time, pregnant women were advised to not exceed a heart rate of 140 beats per minute with physical activity. The heart rate recommendation was subsequently removed with the recommendations published in 1994, 2002, and 2015. In 2020, the ACOG updated its recommendations on physical activity for pregnant and postpartum women. The recommendation included exercising at a “fairly light to somewhat hard” perceived intensity and at less than 60–80% of age-predicted maximum heart rate, usually not exceeding a heart rate of 140 beats per minute. Women often seek advice from healthcare providers on physical activity during pregnancy, yet providers report concern about giving appropriate physical activity guidance. This paper summarizes the key scientific literature on monitoring absolute and relative exercise intensity in relation to the current ACOG recommendations, providing background on intensity-related concepts used in the recommendation. This paper also provides practical guidance to assist healthcare providers in relaying this information to pregnant women.

scholarly journals Application and Validation of Activity Monitors’ Epoch Lengths and Placement Sites for Physical Activity Assessment in Exergaming

2018 ◽  
Vol 7 (9) ◽  
pp. 268 ◽  
Author(s):  
Jungyun Hwang ◽  
Austin Fernandez ◽  
Amy Lu
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Intraclass Correlation ◽  
Activity Levels ◽  
Physical Activity Intensity ◽  
Activity Monitors ◽  
Epoch Length ◽  
Activity Intensity ◽  
Physical Activity Levels ◽  
Rate Sensor

We assessed the agreement of two ActiGraph activity monitors (wGT3X vs. GT9X) placed at the hip and the wrist and determined an appropriate epoch length for physical activity levels in an exergaming setting. Forty-seven young adults played a 30-min exergame while wearing wGT3X and GT9X on both hip and wrist placement sites and a heart rate sensor below the chest. Intraclass correlation coefficient indicated that intermonitor agreement in steps and activity counts was excellent on the hip and good on the wrist. Bland-Altman plots indicated good intermonitor agreement in the steps and activity counts on both placement sites but a significant intermonitor difference was detected in steps on the wrist. Time spent in sedentary and physical activity intensity levels varied across six epoch lengths and depended on the placement sites, whereas time spent from a 1-s epoch of the hip-worn monitors most accurately matched the relative exercise intensity by heart rate. Hip placement site was associated with better step-counting accuracy for both activity monitors and more valid estimation of physical activity levels. A 1-s epoch was the most appropriate epoch length to detect short bursts of intense physical activity and may be the best choice for data processing and analysis in exergaming studies examining intermittent physical activities.

HEART RATE AS AN INDICATOR OF PHYSICAL ACTIVITY INTENSITY IN ADOLESCENTS

2001 ◽  
Vol 33 (5) ◽  
pp. S250 ◽  
Author(s):  
U Ekelund ◽  
E Poortvliet ◽  
A Yngve ◽  
A Nilsson ◽  
A Hurtig-Wennl??f ◽  
...  
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Physical Activity Intensity ◽  
Activity Intensity

scholarly journals Physical activity and exercise during pregnancy in Africa: a review of the literature

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Uchenna Benedine Okafor ◽  
Daniel Ter Goon
Keyword(s):  
Physical Activity ◽  
Pregnant Women ◽  
Healthcare Providers ◽  
Western World ◽  
Published Data ◽  
Factors Affecting ◽  
Exercise Participation ◽  
Beneficial Effects ◽  
Inadequate Information ◽  
Exercise During Pregnancy

Abstract Background Pregnancy is an important phase in a woman’s life, with health status at this stage affecting both the woman and her child’s life. Global evidence suggests that many women engage in low levels of physical activity (PA) and exercise during pregnancy despite its beneficial effects. This is particularly the case in Africa. Methods This article reviews the literature on levels of PA and exercise among pregnant women in Africa, highlighting the level of PA or exercise participation during pregnancy in Africa, including types of PA, factors affecting PA, beliefs about and benefits of prenatal activity, advice or counselling on PA during pregnancy in Africa, and PA interventions proposed to promote the uptake of prenatal PA. Electronic search databases used were Google Scholar, Science Direct, Scopus, EMBASE, ERIC, Medline, Web of Science, EBSCOhost, PubMed, BIOMED Central, and African Journal Online. The basic search terms were: ‘Physical activity’, ‘Exercise’, ‘Pregnancy’, ‘Pregnant women’ and ‘Africa’. A total of 40 references were found. On the basis of an analysis of titles, abstracts and the language of publication (other than English), 11 articles were rejected, and 29 articles were fully read, although two had to be rejected due to a lack of access to the full version. Finally, 27 references were included in the review. Results Few studies exist on PA during pregnancy in Africa. The limited data available suggests that, compared to the Western world, pregnant women in Africa do not adhere to the recommendations for PA during pregnancy. Levels of participation in PA during pregnancy are low and decline as the pregnancy progresses. The majority of the studies used direct, objective measures to assess PA during pregnancy. Personal and environmental factors such as lack of time, lack of knowledge, inadequate information from healthcare providers, feelings of tiredness and an absence of social support constituted the main barriers to PA during pregnancy. The types of PA participation among pregnant women varied across studies and geographical settings. Conclusions While published data is limited, it seems clear that the participation of pregnant women in PA during pregnancy in Africa is low and declines with advancing pregnancy. There is a need for more studies to examine the dynamics of PA during pregnancy in Africa to guide contextual interventions to improve and promote maternal health on the continent.

Abstract P497: Association Between Accelerometer-estimated Physical Activity Intensity and Heart Rate Variability: Mediation by Glycemic Measures and Triglycerides (from The Cardia Study)

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Zachary C Pope ◽  
Kelley P Gabriel ◽  
Kara M Whitaker ◽  
Lin Y Chen ◽  
Pamela J Schreiner ◽  
...  
Keyword(s):  
Physical Activity ◽  
Blood Pressure ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Fasting Glucose ◽  
Oral Glucose ◽  
Physical Activity Intensity ◽  
Cross Sectional ◽  
Rr Intervals ◽  
Activity Intensity

Introduction: We estimated cross-sectional associations between accelerometer-estimated light (LPA), moderate (MPA), and vigorous (VPA) intensity physical activity (PA) and heart rate variability (HRV), and tested mediation of these associations by glycemic control indices, blood lipids, and blood pressure. Hypothesis: PA is positively and independently associated with higher (improved) HRV. Glycemic measures are partial physiological mediators of these associations. Methods: Data were from 1,668 participants (X -age = 46 ± 4 yrs, 58% F, 40% black) in Year 20 (2005-06) of the Coronary Artery Risk Development in Young Adults (CARDIA) Fitness Study. The ActiGraph 7164 estimated participants’ mean min/d of LPA, MPA, and VPA over 7d. Three sequential 10-sec 12-lead ECG strips provided standard deviation of all normal RR intervals (SDNN) and root mean square of all successive RR intervals (rMSSD) HRV. Physiological mediators included fasting glucose and insulin as well as 2-hr oral glucose tolerance (OGTT), fasting triglycerides (TG), HDL-C, and systolic blood pressure (BP). Multiple linear regression, controlling for demographic and lifestyle confounders, assessed independent associations of PA with SDNN and rMSSD HRV per 1-SD. Mediation analyses computed the proportion of the PA-HRV associations attributable to physiological mediators. Results: Participants averaged 360.2 ± 83.8, 33.0 ± 22.0, and 2.7 ± 6.2 min/d of LPA, MPA, and VPA, respectively, with mean values for SDNN (32.6 ± 22.4 ms) and rMSSD (34.0 ± 24.8 ms) similar. VPA was associated with both HRV metrics (SDNN: std = .06 [.03, .10]; rMSSD: std = .08, [.05, .12]) and LPA with rMSSD only (std = .05, [.01, .08]). Fasting glucose and insulin mediated between 11.6%-20.7% of the association of VPA and LPA with HRV (Table). Triglycerides also mediated these associations (range: 9.6%-13.4%; Table). Conclusions: Accelerometer-estimated VPA and LPA were positively associated with higher HRV. These associations may be due most to glycemia and insulinemia.

scholarly journals Automatic Identification of Physical Activity Intensity and Modality from the Fusion of Accelerometry and Heart Rate Data

2016 ◽  
Vol 55 (06) ◽  
pp. 533-544 ◽  
Author(s):  
Pedro Benito ◽  
María Hernando ◽  
Fernando García-García
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Dimensionality Reduction ◽  
Automatic Classification ◽  
Automatic Identification ◽  
Physical Activity Intensity ◽  
Vigorous Exercise ◽  
Temporal Filtering ◽  
Linear Discriminant ◽  
Activity Intensity

SummaryBackground: Physical activity (PA) is essential to prevent and to treat a variety of chronic diseases. The automated detection and quantification of PA over time empowers lifestyle interventions, facilitating reliable exercise tracking and data-driven counseling.Methods: We propose and compare various combinations of machine learning (ML) schemes for the automatic classification of PA from multi-modal data, simultaneously captured by a biaxial accelerometer and a heart rate (HR) monitor. Intensity levels (low / moderate / vigorous) were recognized, as well as for vigorous exercise, its modality (sustained aerobic / resistance / mixed). In to -tal, 178.63 h of data about PA intensity (65.55 % low / 18.96 % moderate / 15.49 % vigorous) and 17.00 h about modality were collected in two experiments: one in free- living conditions, another in a fitness center under controlled protocols. The structure used for automatic classification comprised: a) definition of 42 time-domain signal features, b) dimensionality reduction, c) data clustering, and d) temporal filtering to exploit time redundancy by means of a Hidden Markov Model (HMM). Four dimensionality reduction techniques and four clustering algorithms were studied. In order to cope with class imbalance in the dataset, a custom performance metric was defined to aggregate recognition accuracy, precision and recall.Results: The best scheme, which comprised a projection through Linear Discriminant Ana -lysis (LDA) and k-means clustering, was evaluated in leave-one-subject-out cross-validation; notably outperforming the standard industry procedures for PA intensity classification: score 84.65 %, versus up to 63.60 %. Errors tended to be brief and to appear around transients.Conclusions: The application of ML techniques for pattern identification and temporal filtering allowed to merge accelerometry and HR data in a solid manner, and achieved markedly better recognition performances than the standard methods for PA intensity estimation.

Use of Heart Rate Cutpoints to Assess Physical Activity Intensity in Sixth-Grade Girls

2000 ◽  
Vol 12 (3) ◽  
pp. 284-292 ◽  
Author(s):  
Karin M. Allor ◽  
James M. Pivarnik
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Adolescent Girls ◽  
Sixth Grade ◽  
Maximal Heart Rate ◽  
Treadmill Test ◽  
Physical Activity Intensity ◽  
Heart Rates ◽  
Activity Intensity ◽  
The Relationship

We calculated individual heart rate–oxygen consumption (HR–V̇O2) regression lines for 49 sixth-grade girls based on a treadmill test. From these data, we determined V̇O2 at HRs of 140 and 160 b · min−1 and 50%, 60%, and 75% of maximal heart rate reserve (MHRR), and the relationship between V̇O2 and %fat at given heart rates. Results indicated traditional 140 and 160 b · min−1 HR cutpoints were at the low end of exercise intensity (46 and 63% V̇O2max) and were negatively correlated with %fat. Heart rates at 50%, 60%, and 75% MHRR corresponded to 52%, 62%, and 76% of V̇O2max. Although the best method for analyzing HR data to describe physical activity intensity is unknown, use of 140 and 160 cutpoints may not describe vigorous or very hard exercise in adolescent girls as well as 75% MHRR. Researchers should also consider the effects of adiposity when using specific heart rate cutpoints.

scholarly journals Cardiovascular Responses, Physical Activity Intensity, and Enjoyment Level of Nintendo Switch™ Exergaming, Comparing Different Tempos and Playing Modes: A Pilot Study

2021 ◽  
Vol 3 (2) ◽  
pp. 44
Author(s):  
Bayu Aji Mayogya Putra ◽  
Reni Hendrarati Masduchi ◽  
Martha Kurnia Kusumawardani
Keyword(s):  
Physical Activity ◽  
Blood Pressure ◽  
Heart Rate ◽  
Perceived Exertion ◽  
Cardiovascular Responses ◽  
Rating Of Perceived Exertion ◽  
Physical Activity Intensity ◽  
Activity Intensity ◽  
Before And After ◽  
Rate Sensor

Background: Physical activity (PA) has been associated with multiple health benefits. However, the global population does not meet the PA recommendations. Virtual reality exergaming (VR EXG) can become an option to increase PA because it is fun, relatively easy to access and affordable through popular commercial devices.Aim: To investigate the immediate cardiovascular responses(blood pressure, heart rate), quantification of PA intensity(percentage of maximum heart rate (%HRmax), Borg’s rating of perceived exertion (RPE), and the level of enjoyment using visual analog scale (VAS) while playing VR EXG.Material and Methods: Fifteen healthy men (aged 31.87±3.14 years old, body mass index 23.77±2.47 kg/m2) undergone three“Fitness Boxing” Nintendo Switch™ playing modes in the same order: (1) single player-normal tempo, (2) single player-fast tempo and (3) versus. During playing, participant’s HR was monitored using Polar H10 heart rate sensor. Blood pressure was measured before and after playing. Borg’s RPE and VAS were collected after playing.Results: Our results showed significant heart rate and systolic blood pressure increase (p = 0.001) in all three playing conditions, whereas diastolic blood pressure was relatively constant (p > 0.05). The Borg’s RPE were in 12-13 range (moderate) and %HRmax range between 72- 81% (vigorous). The enjoyment level was found greatest in versus mode compared to other playing modes.Conclusion: VR EXG Nintendo Switch™ “Fitness Boxing” can elicit immediate cardiovascular responses and provides an enjoyable moderate to vigorous PA intensity in healthy male adults, and can be used to meet the weekly PA recommendations. 

Relationships of Heart Rate and Movement with Physical Activity Intensity

2006 ◽  
Vol 38 (Supplement) ◽  
pp. S556
Author(s):  
Soren Brage ◽  
Niels Brage ◽  
Ulf Ekelund ◽  
Paul Franks ◽  
Karsten Froberg ◽  
...  
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Physical Activity Intensity ◽  
Activity Intensity

Hierarchy of individual calibration levels for heart rate and accelerometry to measure physical activity

2007 ◽  
Vol 103 (2) ◽  
pp. 682-692 ◽  
Author(s):  
Søren Brage ◽  
Ulf Ekelund ◽  
Niels Brage ◽  
Mark A. Hennings ◽  
Karsten Froberg ◽  
...  
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Longitudinal Axis ◽  
Calibration Procedure ◽  
Epidemiological Studies ◽  
Step Test ◽  
Activity Measurement ◽  
Physical Activity Intensity ◽  
Activity Intensity ◽  
Individual Calibration

Combining accelerometry with heart rate (HR) monitoring may improve precision of physical activity measurement. Considerable variation exists in the relationships between physical activity intensity (PAI) and HR and accelerometry, which may be reduced by individual calibration. However, individual calibration limits feasibility of these techniques in population studies, and less burdensome, yet valid, methods of calibration are required. We aimed to evaluate the precision of different individual calibration procedures against a reference calibration procedure: a ramped treadmill walking-running test with continuous measurement of PAI by indirect calorimetry in 26 women and 25 men [mean (SD): 35 ( 9 ) yr, 1.69 (0.10) m, 70 ( 14 ) kg]. Acceleration (along the longitudinal axis of the trunk) and HR were measured simultaneously. Alternative calibration procedures included treadmill testing without calorimetry, submaximal step and walk tests with and without calorimetry, and nonexercise calibration using sleeping HR and gender. Reference accelerometry and HR models explained >95% of the between-individual variance in PAI ( P < 0.001). This fraction dropped to 73 and 81%, respectively, for accelerometry and HR models calibrated with treadmill tests without calorimetry. Step-test calibration captured 62–64% (accelerometry) and 68% (HR) of the variance between individuals. Corresponding values were 63–76% and 59–61% for walk-test calibration. There was only little benefit of including calorimetry during step and walk calibration for HR models. Nonexercise calibration procedures explained 54% (accelerometry) and 30% (HR) of the between-individual variance. In conclusion, a substantial proportion of the between-individual variance in relationships between PAI, accelerometry, and HR is captured with simple calibration procedures, feasible for use in epidemiological studies.

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