Using consumer-grade physical activity trackers to measure frailty progression in critical care survivors: An exploratory observational study (Preprint)

2020 ◽  
Author(s):  
Ben Kim ◽  
Miranda Hunt ◽  
John Muscedere ◽  
David M Maslove ◽  
Joon Lee
Keyword(s):  
Physical Activity ◽  
Critical Illness ◽  
Observational Study ◽  
Wearable Devices ◽  
Step Count ◽  
Wearable Device ◽  
Strongly Correlated ◽  
Daily Step ◽  
Daily Step Count

BACKGROUND Critical illness has been suggested as a sentinel event for frailty development for at-risk older adults. Frail critical illness survivors suffer increased adverse health outcomes but monitoring the recovery post-Intensive Care Unit (ICU) is challenging. Clinicians and funders of healthcare system envision an increased role of wearable devices in monitoring clinically relevant measures as the sensor technology is advancing rapidly. Use of wearable devices also generated great interest among older patients and they are the fastest growing group of consumer-grade wearable device users. Recent research studies indicate that consumer-grade wearable devices offer a possibility of measuring frailty. OBJECTIVE To examine the data collected from wearable devices for the progression of frailty among the critical illness survivors. METHODS An observational study was conducted with 12 critical illness survivors from Kingston General Hospital in Canada. Frailty was measured by Clinical Frailty Scale (CFS) at ICU admission (AD), hospital discharge (DC), and 4-week follow-up (FU). Wearable device was worn between DC and FU. The wearable device collected data on steps, physical activity, sleep and heart rate (HR). Patient assessments were reviewed including the severity of illness, cognition level, delirium, activities of daily living, and comorbidity. RESULTS The CFS increased significantly following critical illness compared pre-ICU frailty level (P=.02, d=-0.53). Frail survivors over the 4-week follow-up period had significantly lower daily step counts than non-frail survivors (P=.02, d=1.81). There was no difference in sleep and HR measures. Daily step count was strongly correlated with the CFS at FU (r=-0.72, P=.04). Average HR was strongly correlated with the CFS at DC (r=-0.72, P=.046). HR standard deviation was strongly correlated (r=0.78, P<0.05) with the CFS change from AD to FU. No assocation was found between the CFS and sleep measures. The pattern of increasing step count over the FU period was correlated with the worsening of frailty (r=.62, P=.03). CONCLUSIONS This study demonstrated association between frailty and data generated from a consumer-grade wearable device. Daily step count and HR showed strong association with the frailty progression of the critical illness survivors over time. Understanding this assocation could unlock a new avenue for clinicians to monitor and identify a vulnerable subset of the population that might benefit from an early intervention. CLINICALTRIAL

Comparison of Pedometer and Accelerometer Measures of Physical Activity in Preschool Children

2007 ◽  
Vol 19 (2) ◽  
pp. 205-214 ◽  
Author(s):  
Greet Cardon ◽  
Ilse De Bourdeaudhuij
Keyword(s):  
Physical Activity ◽  
Preschool Children ◽  
Vigorous Physical Activity ◽  
Step Count ◽  
Activity Levels ◽  
Accelerometer Data ◽  
Strongly Correlated ◽  
Daily Step ◽  
Step Counts ◽  
Daily Step Count

In this study, daily step counts were recorded for 4 consecutive days in 129 four- and five-year-old children. To compare daily Yamax Digiwalker step counts with minutes of engagement in moderate to vigorous physical activity (MVPA), concurrent accelerometer data were collected in a random subsample (n = 76). The average daily step count was 9,980 (± 2,605). Step counts and MVPA minutes were strongly correlated (r = .73, p < .001). The daily step count of 13,874, equating to 1-hr MVPA engagement, was reached by 8% of the children. Daily step counts in preschool children give valid information on physical activity levels—daily step counts in preschoolers are low.

scholarly journals Monitoring of Physical Activity of Soldiers of the Army of the Czech Republic

2020 ◽  
Vol 13 (2) ◽  
pp. 72-83
Author(s):  
Jan Zemánek
Keyword(s):  
Physical Activity ◽  
Czech Republic ◽  
Physical Inactivity ◽  
Step Count ◽  
Daily Step ◽  
The Czech Republic ◽  
Daily Step Count ◽  
Weekly Physical Activity ◽  
Age Range

Aim: This research is aimed at the possibilities of physical training of Army of the Czech Republic personnel (soldiers of the 7th mechanised brigade) during a routine week spent in garrison and the follow-up analysis of the amount of their physical activity.Methodology: The observed group was made up of 52 professional soldier volunteers in the age range of 29.9 ± 4.5 years. The measurement has been performed continuously during the time span of one week. Physical activity has been measured with the utilization of the ActiGraph GT1M accelerometers supplemented with the use of a weekly physical activity protocol.Results: Based on the results it is possible to infer that the average daily physical activity (7.66 hours) has been greater than the average daily physical inactivity (5.89 hours). No difference in the amount of weekly physical activity of professional soldiers in relation to age (≤ 30 years and  30 years) has been found, nor in relation to being a smoker/non-smoker, nor in relation to BMI ( 24.9 kg/m2 and ≥ 24.9 kg/m2).Conclusion: With an average daily step count of 10169.84 the amount of physical activity of the soldiers is sufficient and meets the health recommendation for the daily step count (Aoyagi & Shephard, 2009).

The translation of preschoolers’ physical activity guidelines into a daily step count target

2014 ◽  
Vol 33 (10) ◽  
pp. 1051-1057 ◽  
Author(s):  
Marieke De Craemer ◽  
Ellen De Decker ◽  
Ilse De Bourdeaudhuij ◽  
Maïté Verloigne ◽  
Yannis Manios ◽  
...  
Keyword(s):  
Physical Activity ◽  
Step Count ◽  
Daily Step ◽  
Physical Activity Guidelines ◽  
Daily Step Count

Abstract 11: mActive: A Blinded, Randomized mHealth Trial Supporting Digital Tracking and Smart Texting for Promotion of Physical Activity

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
Seth S Martin ◽  
David I Feldman ◽  
Roger S Blumenthal ◽  
Steven R Jones ◽  
Wendy S Post ◽  
...  
Keyword(s):  
Physical Activity ◽  
Phase I ◽  
Real Time ◽  
Phase Ii ◽  
The United States ◽  
Step Count ◽  
Daily Step ◽  
Baseline Activity ◽  
Daily Step Count ◽  
Digital Tracking

Introduction: The recent advent of smartphone-linked wearable pedometers offers a novel opportunity to promote physical activity using mobile health (mHealth) technology. Hypothesis: We hypothesized that digital activity tracking and smart (automated, real-time, personalized) texting would increase physical activity. Methods: mActive (NCT01917812) was a 5-week, blinded, sequentially-randomized, parallel group trial that enrolled patients at an academic preventive cardiovascular center in Baltimore, MD, USA from January 17 th to May 20 th , 2014. Eligible patients were 18-69 year old smartphone users who reported low leisure-time physical activity by a standardized survey. After establishing baseline activity during a 1-week blinded run-in, we randomized 2:1 to unblinded or blinded tracking in phase I (2 weeks), then randomized unblinded participants 1:1 to receive or not receive smart texts in phase II (2 weeks). Smart texts provided automated, personalized, real-time coaching 3 times/day towards a daily goal of 10,000 steps. The primary outcome was change in daily step count. Results: Forty-eight patients (22 women, 26 men) enrolled with a mean (SD) age of 58 (8) years, body mass index of 31 (6), and baseline daily step count of 9670 (4350). The phase I change in activity was non-significantly higher in unblinded participants versus blinded controls by 1024 steps/day (95% CI -580-2628, p=0.21). In phase II, smart text receiving participants increased their daily steps over those not receiving texts by 2534 (1318-3750, p<0.001) and over blinded controls by 3376 (1951-4801, p<0.001). The unblinded-texts group had the highest proportion attaining the 10,000 steps/day goal (p=0.02) (Figure). Conclusions: In present-day adult smartphone users receiving preventive cardiovascular care in the United States, a technologically-integrated mHealth strategy combining digital tracking with automated, personalized, real-time text message coaching resulted in a large short-term increase in physical activity.

scholarly journals Neural Network–Based Algorithm for Adjusting Activity Targets to Sustain Exercise Engagement Among People Using Activity Trackers: Retrospective Observation and Algorithm Development Study

10.2196/18142 ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. e18142
Author(s):  
Ramin Mohammadi ◽  
Mursal Atif ◽  
Amanda Jayne Centi ◽  
Stephen Agboola ◽  
Kamal Jethwani ◽  
...  
Keyword(s):  
Neural Network ◽  
Physical Activity ◽  
Machine Learning ◽  
Learning Model ◽  
Step Count ◽  
Daily Step ◽  
Activity Tracker ◽  
Activity Trackers ◽  
Machine Learning Model ◽  
Daily Step Count

Background It is well established that lack of physical activity is detrimental to the overall health of an individual. Modern-day activity trackers enable individuals to monitor their daily activities to meet and maintain targets. This is expected to promote activity encouraging behavior, but the benefits of activity trackers attenuate over time due to waning adherence. One of the key approaches to improving adherence to goals is to motivate individuals to improve on their historic performance metrics. Objective The aim of this work was to build a machine learning model to predict an achievable weekly activity target by considering (1) patterns in the user’s activity tracker data in the previous week and (2) behavior and environment characteristics. By setting realistic goals, ones that are neither too easy nor too difficult to achieve, activity tracker users can be encouraged to continue to meet these goals, and at the same time, to find utility in their activity tracker. Methods We built a neural network model that prescribes a weekly activity target for an individual that can be realistically achieved. The inputs to the model were user-specific personal, social, and environmental factors, daily step count from the previous 7 days, and an entropy measure that characterized the pattern of daily step count. Data for training and evaluating the machine learning model were collected over a duration of 9 weeks. Results Of 30 individuals who were enrolled, data from 20 participants were used. The model predicted target daily count with a mean absolute error of 1545 (95% CI 1383-1706) steps for an 8-week period. Conclusions Artificial intelligence applied to physical activity data combined with behavioral data can be used to set personalized goals in accordance with the individual’s level of activity and thereby improve adherence to a fitness tracker; this could be used to increase engagement with activity trackers. A follow-up prospective study is ongoing to determine the performance of the engagement algorithm.

scholarly journals Adding team-based financial incentives to the Carrot Rewards physical activity app increases daily step count on a population scale: a 24-week matched case control study

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Emma Pearson ◽  
Harry Prapavessis ◽  
Christopher Higgins ◽  
Robert Petrella ◽  
Lauren White ◽  
...  
Keyword(s):  
Physical Activity ◽  
Financial Incentives ◽  
Step Count ◽  
Daily Step ◽  
Individual Level ◽  
Significant Difference ◽  
Daily Step Count ◽  
Steps Per Day ◽  
The Impact ◽  
Experimental Group

Abstract Background Mobile health applications (mHealth apps) targeting physical inactivity have increased in popularity yet are usually limited by low engagement. This study examined the impact of adding team-based incentives (Step Together Challenges, STCs) to an existing mHealth app (Carrot Rewards) that rewarded individual physical activity achievements. Methods A 24-week quasi-experimental study (retrospective matched pairs design) was conducted in three Canadian provinces (pre-intervention: weeks 1–12; intervention: weeks 13–24). Participants who used Carrot Rewards and STCs (experimental group) were matched with those who used Carrot Rewards only (controls) on age, gender, province and baseline mean daily step count (±500 steps/d). Carrot Rewards users earned individual-level incentives (worth $0.04 CAD) each day they reached a personalized daily step goal. With a single partner, STC users could earn team incentives ($0.40 CAD) for collaboratively reaching individual daily step goals 10 times in seven days (e.g., Partner A completes four goals and Partner B completes six goals in a week). Results The main analysis included 61,170 users (mean age = 32 yrs.; % female = 64). Controlling for pre-intervention mean daily step count, a significant difference in intervention mean daily step count favoured the experimental group (p < 0.0001; ηp2 = 0.024). The estimated marginal mean group difference was 537 steps per day, or 3759 steps per week (about 40 walking min/wk). Linear regression suggested a dose-response relationship between the number of STCs completed (app engagement) and intervention mean daily step count (adjusted R2 = 0.699) with each new STC corresponding to approximately 200 more steps per day. Conclusion Despite an explosion of physical activity app interest, low engagement leading to small or no effects remains an industry hallmark. In this paper, we found that adding modest team-based incentives to the Carrot Rewards app increased mean daily step count, and importantly, app engagement moderated this effect. Others should consider novel small-teams based approaches to boost engagement and effects.

A Pilot Study Comparing Pedometer Counts with Reported Physical Activity in Elementary Schoolchildren

2004 ◽  
Vol 16 (4) ◽  
pp. 355-367 ◽  
Author(s):  
Greet Cardon ◽  
Ilse De Bourdeaudhuij
Keyword(s):  
Physical Activity ◽  
Pilot Study ◽  
Vigorous Physical Activity ◽  
Step Count ◽  
Regression Equations ◽  
Moderate Correlation ◽  
Daily Step ◽  
Step Counts ◽  
Daily Step Count

In this study pedometer counts were recorded for 6 consecutive days for 92 children (mean age = 9.6 years; range 6.5–12.7) and were compared with the number of minutes per day in which the participants engaged in moderate-to-vigorous physical activity (MVPA). Diaries filled out with the assistance of one of the children’s parents were used to determine minutes of MVPA. The average daily step count was significantly higher in boys than in girls, although the average daily MVPA engagement in minutes did not vary significantly between genders. Based on the regression equations, 60 min of MVPA was equivalent to 15,340 step counts in boys, 11,317 step counts in girls, and 13,130 step counts when results for both genders were combined. A moderate correlation (r = .39, p < .001) was found between pedometer step counts and reported minutes of MVPA. According to the present study findings, however, predictions and promotion of daily MVPA engagement in children based on pedometer counts per day should be made with caution.

scholarly journals Self-reported task-oriented physical activity: A comparison with objective daily step count in COPD

2018 ◽  
Vol 140 ◽  
pp. 63-70 ◽  
Author(s):  
Emily S. Wan ◽  
Ana Kantorowski ◽  
Diana Homsy ◽  
Reema Kadri ◽  
Caroline R. Richardson ◽  
...  
Keyword(s):  
Physical Activity ◽  
Step Count ◽  
Daily Step ◽  
Daily Step Count ◽  
Task Oriented

scholarly journals Association of Habitual Physical Activity With Home Blood Pressure in the Electronic Framingham Heart Study (eFHS): Cross-sectional Study

10.2196/25591 ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. e25591
Author(s):  
Mayank Sardana ◽  
Honghuang Lin ◽  
Yuankai Zhang ◽  
Chunyu Liu ◽  
Ludovic Trinquart ◽  
...  
Keyword(s):  
Physical Activity ◽  
Blood Pressure ◽  
Habitual Physical Activity ◽  
Step Count ◽  
Daily Step ◽  
Community Based ◽  
Cross Sectional ◽  
Heart Study ◽  
Daily Step Count ◽  
The Mean

Background When studied in community-based samples, the association of physical activity with blood pressure (BP) remains controversial and is perhaps dependent on the intensity of physical activity. Prior studies have not explored the association of smartwatch-measured physical activity with home BP. Objective We aimed to study the association of habitual physical activity with home BP. Methods Consenting electronic Framingham Heart Study (eFHS) participants were provided with a study smartwatch (Apple Watch Series 0) and Bluetooth-enabled home BP cuff. Participants were instructed to wear the watch daily and transmit BP values weekly. We measured habitual physical activity as the average daily step count determined by the smartwatch. We estimated the cross-sectional association between physical activity and average home BP using linear mixed effects models adjusting for age, sex, wear time, antihypertensive drug use, and familial structure. Results We studied 660 eFHS participants (mean age 53 years, SD 9 years; 387 [58.6%] women; 602 [91.2%] White) who wore the smartwatch 5 or more hours per day for 30 or more days and transmitted three or more BP readings. The mean daily step count was 7595 (SD 2718). The mean home systolic and diastolic BP (mmHg) were 122 (SD 12) and 76 (SD 8). Every 1000 increase in the step count was associated with a 0.49 mmHg lower home systolic BP (P=.004) and 0.36 mmHg lower home diastolic BP (P=.003). The association, however, was attenuated and became statistically nonsignificant with further adjustment for BMI. Conclusions In this community-based sample of adults, higher daily habitual physical activity measured by a smartwatch was associated with a moderate, but statistically significant, reduction in home BP. Differences in BMI among study participants accounted for the majority of the observed association.

scholarly journals Physical Activity Levels of Adolescents and Adults With Cerebral Palsy in Urban South Africa

2021 ◽  
Vol 12 ◽  
Author(s):  
Roshaan Salie ◽  
Maaike M. Eken ◽  
Kirsten A. Donald ◽  
A. Graham Fieggen ◽  
Nelleke G. Langerak
Keyword(s):  
Physical Activity ◽  
South Africa ◽  
Step Count ◽  
Daily Step ◽  
Physically Active ◽  
Urban South ◽  
Daily Step Count ◽  
Adolescents And Adults ◽  
Level I ◽  
Gmfcs Level

Background: Research in high income countries shows that people with cerebral palsy (CP) are less physically active than typically developing (TD) peers, but less is known regarding physical activity (PA) in those with CP in low-to-middle income countries. The aim of this study was to determine daily step count and levels of PA in adolescents and adults with CP living in urban South Africa, compared to TD peers, and to determine associations with sex, Gross Motor Function Classification System (GMFCS) level, body mass index and socio-economic status.Materials and Methods: This case–control study included 26 adolescents and 22 adults with CP (GMFCS Level I-V) and matched TD peers (25 and 30, respectively). Participants wore an ActiGraph GT3X for 7 consecutive days to determine step count and time (minutes per hour) spent in PA levels, including sedentary (SED), low physical activity (LPA) and moderate to vigorous physical activity (MVPA).Results: The daily step count and PA levels for ambulant adolescents with CP (GMFCS level I-III) were similar to TD peers, while this was less for adolescents classified in GMFCS level IV-V. Daily step count, SED and MVPA were similar for adults classified in GMFCS level I-II compared to TD adults, while all parameters were lower for adults using assistive devices (GMFCS level III) and non-ambulant adults (GMFCS level IV-V) compared to TD peers. Daily step count and PA levels were inversely associated with GMFCS, while no other associations were found.Conclusion: People with CP who were more mobile dependent (higher GMFCS level) were less active. However, adolescents and adults with CP classified as GMFCS levels I-II living in urban South Africa recorded similar step count and PA levels as their TD peers. This was also the case for adolescents using assistive devices, though not for those in the adult group (GMFCS level III). Furthermore, it was apparent that even the ambulant individuals with CP and TD cohorts were relatively inactive. Intervention programs for CP and TD adolescents should be aimed at finding strategies to keep adolescents physically active well into adulthood, in order to promote physical health, social and emotional well-being and independence.

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