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The aims of this paper were to provide an overview of available activity monitors used in research in patients with heart failure and to identify the key criteria in the selection of the most appropriate activity monitor for collecting, reporting, and analysing physical activity in heart failure research. This study was conducted in three parts. First, the literature was systematically reviewed to identify physical activity concepts and activity monitors used in heart failure research. Second, an additional scoping literature search for validation of these activity monitors was conducted. Third, the most appropriate criteria in the selection of activity monitors were identified. Nine activity monitors were evaluated in terms of size, weight, placement, costs, data storage, water resistance, outcomes and validation, and cut-off points for physical activity intensity levels were discussed. The choice of a monitor should depend on the research aims, study population and design regarding physical activity. If the aim is to motivate patients to be active or set goals, a less rigorously tested tool can be considered. On the other hand, if the aim is to measure physical activity and its changes over time or following treatment adjustment, it is important to choose a valid activity monitor with a storage and battery longevity of at least one week. The device should provide raw data and valid cut-off points should be chosen for analysing physical activity intensity levels. Other considerations in choosing an activity monitor should include data storage location and ownership and the upfront costs of the device. Funding Agencies|European Society of Cardiology Funding Source: Medline

Background The COVID-19 pandemic has impacted multiple aspects of daily living, including behaviors associated with occupation, transportation, and health. It is unclear how these changes to daily living have impacted physical activity and sedentary behavior. Objective In this study, we add to the growing body of research on the health impact of the COVID-19 pandemic by examining longitudinal changes in objectively measured daily physical activity and sedentary behavior among overweight or obese young adults participating in an ongoing weight loss trial in San Diego, California. Methods Data were collected from 315 overweight or obese (BMI: range 25.0-39.9 kg/m2) participants aged from 18 to 35 years between November 1, 2019, and October 30, 2020, by using the Fitbit Charge 3 (Fitbit LLC). After conducting strict filtering to find valid data on consistent wear (>10 hours per day for ≥250 days), data from 97 participants were analyzed to detect multiple structural changes in time series of physical activity and sedentary behavior. An algorithm was designed to detect multiple structural changes. This allowed for the automatic identification and dating of these changes in linear regression models with CIs. The number of breakpoints in regression models was estimated by using the Bayesian information criterion and residual sum of squares; the optimal segmentation corresponded to the lowest Bayesian information criterion and residual sum of squares. To quantify the changes in each outcome during the periods identified, linear mixed effects analyses were conducted. In terms of key demographic characteristics, the 97 participants included in our analyses did not differ from the 210 participants who were excluded. Results After the initiation of the shelter-in-place order in California on March 19, 2021, there were significant decreases in step counts (−2872 steps per day; 95% CI −2734 to −3010), light physical activity times (−41.9 minutes; 95% CI −39.5 to −44.3), and moderate-to-vigorous physical activity times (−12.2 minutes; 95% CI −10.6 to −13.8), as well as significant increases in sedentary behavior times (+52.8 minutes; 95% CI 47.0-58.5). The decreases were greater than the expected declines observed during winter holidays, and as of October 30, 2020, they have not returned to the levels observed prior to the initiation of shelter-in-place orders. Conclusions Among overweight or obese young adults, physical activity times decreased and sedentary behavior times increased concurrently with the implementation of COVID-19 mitigation strategies. The health conditions associated with a sedentary lifestyle may be additional, unintended results of the COVID-19 pandemic.

Background Older cancer survivors are at risk of the development or worsening of both age- and treatment-related morbidity. Sedentary behavior increases the risk of or exacerbates these chronic conditions. Light-intensity physical activity (LPA) is more common in older adults and is associated with better health and well-being. Thus, replacing sedentary time with LPA may provide a more successful strategy to reduce sedentary time and increase physical activity. Objective This study primarily aims to evaluate the feasibility, acceptability, and preliminary efficacy of a home-based mobile health (mHealth) intervention to interrupt and replace sedentary time with LPA (standing and stepping). The secondary objective of this study is to examine changes in objective measures of physical activity, physical performance, and self-reported quality of life. Methods Overall, 54 cancer survivors (aged 60-84 years) were randomized in a 1:1:1 allocation to the tech support intervention group, tech support plus health coaching intervention group, or waitlist control group. Intervention participants received a Jawbone UP2 activity monitor for use with their smartphone app for 13 weeks. Tech support and health coaching were provided via 5 telephone calls during the 13-week intervention. Sedentary behavior and physical activity were objectively measured using an activPAL monitor for 7 days before and after the intervention. Results Participants included survivors of breast cancer (21/54, 39%), prostate cancer (16/54, 30%), and a variety of other cancer types; a mean of 4.4 years (SD 1.6) had passed since their cancer diagnosis. Participants, on average, were 70 years old (SD 4.8), 55% (30/54) female, 24% (13/54) Hispanic, and 81% (44/54) overweight or obese. Malfunction of the Jawbone trackers occurred in one-third of the intervention group, resulting in enrollment stopping at 54 rather than the initial goal of 60 participants. Despite these technical issues, the retention in the intervention was high (47/54, 87%). Adherence was high for wearing the tracker (29/29, 100%) and checking the app daily (28/29, 96%) but low for specific aspects related to the sedentary features of the tracker and app (21%-25%). The acceptability of the intervention was moderately high (81%). There were no significant between-group differences in total sedentary time, number of breaks, or number of prolonged sedentary bouts. There were no significant between-group differences in physical activity. The only significant within-group change occurred within the health coaching group, which increased by 1675 daily steps (95% CI 444-2906; P=.009). This increase was caused by moderate-intensity stepping rather than light-intensity stepping (+15.2 minutes per day; 95% CI 4.1-26.2; P=.008). Conclusions A home-based mHealth program to disrupt and replace sedentary time with stepping was feasible among and acceptable to older cancer survivors. Future studies are needed to evaluate the optimal approach for replacing sedentary behavior with standing and/or physical activity in this population. Trial Registration ClinicalTrials.gov NCT03632694; https://clinicaltrials.gov/ct2/show/NCT03632694

Background Low back pain (LBP) is a highly prevalent condition affecting individuals of all ages. To manage the symptoms and prevent recurrences and flare-ups, physical activity in conjunction with self-management education is recommended. Tools such as diaries and questionnaires have been the gold standard for tracking physical activity in clinical studies. However, there are issues with consistency, accuracy, and recall with the use of these outcome measures. Given the growth of technology in today’s society, consumer-grade activity monitors have become a common and convenient method of recording physical activity data. Objective The aim of this study is to test the feasibility and convergent validity of a Garmin Vivofit 3 activity tracker in evaluating physical activity levels in a clinical trial of patients with LBP. Methods We recruited 17 individuals with nonspecific LBP referred from health care professionals or self-referred through advertisements in the community. The participants entered into a 12-week physical activity and self-management program. Physical activity was assessed using a self-reported questionnaire and the Garmin activity tracker. Activity tracker data (eg, steps taken, distance walked, and intensity minutes) were extracted weekly from the Garmin Connect online platform. Outcomes of pain and activity limitation were assessed weekly using a mobile app. A linear regression was conducted to evaluate if demographic factors (ie, age, gender, pain level) affected the adherence rates to the activity monitor. We also used Pearson correlations to evaluate the convergent validity of the Garmin activity tracker with the physical activity questionnaire. Results The mean daily adherence rate for activity monitors was 70% (SD 31%) over the 26 weeks of study. The mean response rate for the weekly physical activity measures using REDCap for the first 12 weeks of the study was 91% (SD 17%). None of the hypothesized variables or questionnaires were predictors of response rate. Conclusions The majority of participants were compliant with wearing the tracker, and demographic factors were not found to be predictors of adherence to wearing the device. However, there were poor correlations between the modified International Physical Activity Questionnaire Short Form (IPAQ-SF) and the activity monitor, demonstrating problems with convergent validity.

Background:Technological advancements of remote-monitoring used in clinical-care and research require validation of model updates. Objectives:To compare the output of a newer consumer-grade accelerometer to a previous model in people with multiple sclerosis (MS) and to the ActiGraph, a waist-worn device widely used in MS research. Methods:Thirty-one individuals with MS participated in a 7-day validation by the Fitbit Flex (Flex), Fitbit Flex-2 (Flex2) and ActiGraph GT3X. Primary outcome was step count. Valid epochs of 5-min block increments, where there was overlap of ≥1 step/min for both devices were compared and summed to give a daily total for analysis. Results:Bland-Altman plots showed no systematic difference between the Flex and Flex2; mean step-count difference of 25 more steps-per-day more recorded by Flex2 (95% confidence intervals (CI) = 2, 48; p = 0.04),interclass correlation coefficient (ICC) = 1.00. Compared to the ActiGraph, Flex2 (and Flex) tended to record more steps (808 steps-per-day more than the ActiGraph (95% CI= -2380, 765; p

Background Commercially available activity monitors are a promising approach for tracking and changing physical activity in multiple sclerosis. Objective This study reports on the rate and pattern of activity monitor use in persons with multiple sclerosis, and compares self-reported physical activity levels between persons who do wear and those who do not wear activity monitors. Methods Participants completed a cross-sectional survey that included a demographic and clinical characteristics scale, activity monitor use questionnaire, and Godin Leisure-Time Exercise Questionnaire (GLTEQ) for measuring total and health-promoting physical activity. Results Of the 629 participants who completed the full survey, 249 (40%) reported using an activity monitor. The most common activity monitors were Fitbit, Apple watch, iPhone, and Garmin. There was a significant (p

Background: It is well documented that meeting the guideline levels (150 minutes per week) of moderate-to-vigorous physical activity (PA) is protective against chronic disease. Conversely, emerging evidence indicates the deleterious effects of prolonged sitting. Therefore, there is a need to change both behaviors. Self-monitoring of behavior is one of the most robust behavior-change techniques available. The growing number of technologies in the consumer electronics sector provides a unique opportunity for individuals to self-monitor their behavior. Objective: The aim of this study is to review the characteristics and measurement properties of currently available self-monitoring devices for sedentary time and/or PA. Methods: To identify technologies, four scientific databases were systematically searched using key terms related to behavior, measurement, and population. Articles published through October 2015 were identified. To identify technologies from the consumer electronic sector, systematic searches of three Internet search engines were also performed through to October 1, 2015. Results: The initial database searches identified 46 devices and the Internet search engines identified 100 devices yielding a total of 146 technologies. Of these, 64 were further removed because they were currently unavailable for purchase or there was no evidence that they were designed for, had been used in, or could readily be modified for self-monitoring purposes. The remaining 82 technologies were included in this review (73 devices self-monitored PA, 9 devices self-monitored sedentary time). Of the 82 devices included, this review identified no published articles in which these devices were used for the purpose of self-monitoring PA and/or sedentary behavior; however, a number of technologies were found via Internet searches that matched the criteria for self-monitoring and provided immediate feedback on PA (ActiGraph Link, Microsoft Band, and Garmin Vivofit) and sedentary time (activPAL VT, the Lumo Back, and Darma). Conclusions: There are a large number of devices that self-monitor PA; however, there is a greater need for the development of tools to self-monitor sedentary time. The novelty of these devices means they have yet to be used in behavior change interventions, although the growing field of wearable technology may facilitate this to change. [J Med Internet Res 2016;18(5):e90]

Background: The office workplace is a key setting in which to address excessive sitting time and inadequate physical activity. One major influence on workplace sitting is the organizational environment. However, the impact of organizational-level strategies on individual level activity change is unknown. Further, the emergence of sophisticated, consumer-targeted wearable activity trackers that facilitate real-time self-monitoring of activity, may be a useful adjunct to support organizational-level strategies, but to date have received little evaluation in this workplace setting. Objective: The aim of this study is to evaluate the feasibility, acceptability, and effectiveness of organizational-level strategies with or without an activity tracker on sitting, standing, and stepping in office workers in the short (3 months, primary aim) and long-term (12 months, secondary aim). Methods: This study is a pilot, cluster-randomized trial (with work teams as the unit of clustering) of two interventions in office workers: organizational-level support strategies (eg, visible management support, emails) or organizational-level strategies plus the use of a waist-worn activity tracker (the LUMOback) that enables self-monitoring of sitting, standing, and stepping time and enables users to set sitting and posture alerts. The key intervention message is to ‘Stand Up, Sit Less, and Move More.’ Intervention elements will be implemented from within the organization by the Head of Workplace Wellbeing. Participants will be recruited via email and enrolled face-to-face. Assessments will occur at baseline, 3, and 12 months. Time spent sitting, sitting in prolonged (≥30 minute) bouts, standing, and stepping during work hours and across the day will be measured with activPAL3 activity monitors (7 days, 24 hours/day protocol), with total sitting time and sitting time during work hours the primary outcomes. Web-based questionnaires, LUMOback recorded data, telephone interviews, and focus groups will measure the feasibility and acceptability of both interventions and potential predictors of behavior change. Results: Baseline and follow-up data collection has finished. Results are expected in 2016. Conclusions: This pilot, cluster-randomized trial will evaluate the feasibility, acceptability, and effectiveness of two interventions targeting reductions in sitting and increases in standing and stepping in office workers. Few studies have evaluated these intervention strategies and this study has the potential to contribute both short and long-term findings.

This research was funded by the Plan Nacional de Investigacion Cientifica, Desarrollo e Innovacion Tecnologica (I + D + I), Instituto de Salud Carlos III-HealthResearchFunding (FONDOS FEDER) (PI11/02042, PI11/02059, PI11/01425; PI16/00871, PI16/01301, PI16/01205) and RETIC (Redes tematicas de investigacion cooperativa) (Red SAMID RD12/0026/0015). Angel Gil is funded by the Plan Propio de la Universidad de Granada with a Sabatical Program 2020-21. This paper will be included in Jose Manuel Jurado-Castro's doctorate, under the "Social and Legal Sciences Program" at the University of Cordoba, Spain., Background: Physical activity (PA) has acquired a significant relevance due to the health benefits associated with its practice. Accelerometers are an effective tool to assess PA; however, the diversity of cut-off points used to define different PA intensities through accelerometry could interfere in the interpretation of the findings among studies. Objectives: The present study aimed to examine the sedentary behavior (SB) and physical activity (PA) levels in children using six selected accelerometry protocols based on diverse cut-off points. Methods: Clinical examination, anthropometric measurements, and PA evaluation by accelerometry were assessed in 543 selected children (10 ± 2.4 years old) from the Spanish GENOBOX study. The ActiLife data scoring program was used to determine daily min spent in SB, and light, moderate, vigorous and moderate-vigorous PA using six validated accelerometry protocols differing in their cut-off points. Results: Very different estimations for SB and PA intensity levels were found in children, independently of the nonwear- time algorithm selected, and considering puberty stages, age and body mass index. The time spent in daily SB varied from 471 to 663.7 min, PA ranged from 141 to 301.6 min, and the moderate-vigorous PA was reported between 20.7 and 180.2 min. Conclusion: The choice of a particular accelerometry protocol considering these factors is important to evaluate SB or PA intensities to suit the characteristics of the sample researched. It seems necessary to establish future lines of research that include different analytical approaches to measure SB and PA by accelerometry based on standardized and validated methodology., Plan Nacional de Investigacion Cientifica, Desarrollo e Innovacion Tecnologica (I + D + I), Instituto de Salud Carlos III-HealthResearchFunding (FONDOS FEDER) PI11/02042 PI11/02059 PI11/01425 PI16/00871 PI16/01301 PI16/01205, RETIC (Redes tematicas de investigacion cooperativa) RD12/0026/0015, Plan Propio de la Universidad de Granada

This paper evaluates the use of a sensor mounted on a finger to detect bites during food consumption. Previous works have demonstrated the capability to detect bites by tracking wrist motion. The key motion is the roll of the wrist that occurs between picking up food and delivering it to the mouth. We hypothesize that the roll axes of the wrist, hand, and finger are congruent, and that therefore the roll motion measured at the wrist can be similarly measured at the finger. We collected data for 10 meals of subjects wearing sensors on both the wrist and finger. Results indicate that the bite counting algorithm obtains similar accuracy at both locations. The practical implication is that an eating activity monitor could be embedded in the form of a ring worn on the finger, and that this form factor could work as well as a watch-like device.

WHAT THIS PAPER ADDS The aim of the study was to validate a tri-axial activity monitor to measure daily activities and walking steps (physical activity) in patients with intermittent claudication. A clear call in vascular research for alternative tests to determine walking capacity or walking behaviour in patients with peripheral arterial disease (PAD) has been made. This study validated an activity monitor to measure these types of outcome variables, which may offer a valuable contribution to the research armamentarium of PAD and could therefore support future PAD research. Objectives: The daily life physical activity (PA) of patients with peripheral arterial disease (PAD) may be severely hampered by intermittent claudication (IC). From a therapeutic, as well as research, point of view, it may be more relevant to determine improvement in PA as an outcome measure in IC. The aim of this study was to validate daily activities using a novel type of tri-axial accelerometer (Dynaport MoveMonitor) in patients with IC. Methods: Patients with IC were studied during a hospital visit. Standard activities (locomotion, lying, sitting, standing, shuffling, number of steps and “not worn” detection) were video recorded and compared with activities scored by the MoveMonitor. Inter-rater reliability (expressed in intraclass correlation coefficients [ICC]), sensitivity, specificity, and positive predictive values (PPV) were calculated for each activity. Results: Twenty-eight hours of video observation were analysed (n ¼ 21). Our video annotation method (the gold standard method) appeared to be accurate for most postures (ICC > 0.97), except for shuffling (ICC ¼ 0.38). The MoveMonitor showed a high sensitivity (>86%), specificity (>91%), and PPV (>88%) for locomotion, lying, sitting, and “not worn” detection. Moderate accuracy was found for standing (46%), while shuffling appeared to be undetectable (18%). A strong correlation was found between video recordings and the MoveMonitor with regard to the calculation of the “number of steps” (ICC ¼ 0.90). Conclusions: The MoveMonitor provides accurate information on a diverse set of postures, daily activities, and number of steps in IC patients. However, the detection of low amplitude movements, such as shuffling and “sitting to standing” transfers, is a matter of concern. This tool is useful in assessing the role of PA as a novel, clinically relevant outcome parameter in IC.

This paper explores changes in musculoskeletal pain among desk-based workers over three months of a workplace-delivered, sitting-reduction intervention. Participants (n = 153, 46% female, mean &plusmn, SD aged 38.9 &plusmn, 8.0 years) were cluster-randomized (n = 18 work teams) to receive an organizational change intervention, with or without an activity tracker. A modified Nordic Musculoskeletal Questionnaire assessed pain intensity (0&ndash, 9, none&ndash, worst possible) in the neck, upper and lower back, upper and lower extremities, and in total. The activPAL3 (7 days, 24 h/day protocol) measured sitting and prolonged sitting in &ge, 30 min bouts at work. Mixed models adjusting for cluster and intervention arm examined changes in pain (n = 104), and their associations with reductions in sitting and prolonged sitting (h/10 h at work) (n = 90). Changes in pain were nonsignificant (p &ge, 0.05) and small for total pain (&minus, 0.06 [95% CI: &minus, 0.27, 0.16]) and for each body area (&minus, 0.26 [&minus, 0.66, 0.15] for upper back to 0.09 [&minus, 0.39, 0.56] for lower back). Sitting reduction was associated with reduced lower back pain (&minus, 0.84 [&minus, 1.44, &minus, 0.25] per hour, p = 0.005), other effects were small and non-significant. No substantial average changes in pain were seen, some improvement in lower back pain might be expected with larger sitting reductions. Larger samples and diverse interventions are required for more definitive evidence.

The metabolic activity of organisms can be measured by recording the heat output using microcalorimetry. In this paper, the total alkaloids in the traditional Chinese medicine Radix Aconiti Lateralis were extracted and applied to Escherichia coli and Staphylococcus aureus. The effect of alkaloids on bacteria growth was studied by microcalorimetry. The power-time curves were plotted with a thermal activity monitor (TAM) air isothermal microcalorimeter and parameters such as growth rate constant (μ), peak-time (Tm), inhibitory ratio (I), and enhancement ratio (E) were calculated. The relationships between the concentration of Aconitum alkaloids and μ of E. coli or S. aureus were discussed. The results showed that Aconitum alkaloids had little effect on E. coli and had a potentially inhibitory effect on the growth of S. aureus.