Despite their enhanced marketplace visibility, validity of wearable photoplethysmographic heart rate monitoring is scarce. Forty-seven healthy participants performed seven, 6-min exercise bouts and completed a valid skin type scale. Participants wore an Omron HR500U (OHR) and a Mio Alpha (MA), two commercial wearable photoplethysmographic heart rate monitors. Data were compared to a Polar RS800CX (PRS). Means and error were calculated between devices using minutes 2-5. Compared to PRS, MA data was significantly different in walking, biking (2.41 ± 3.99 bpm and 3.26 ± 11.38 bpm, p < 0.05) and weight lifting (23.30 ± 31.94 bpm, p < 0.01). OHR differed from PRS in walking (4.95 ± 7.53 bpm, p < 0.05) and weight lifting (4.67 ± 8.95 bpm, p < 0.05). MA during elliptical, stair climbing and biking conditions demonstrated a strong correlation between jogging speed and error (r = 0.55, p < 0.0001), and showed differences in participants with less photosensitive skin.

Epidemic levels of inactivity are associated with chronic diseases and rising healthcare costs. To address this, accelerometers have been used to track levels of activity. The Fitbit and Fitbit Ultra are some of the newest commercially available accelerometers. The purpose of this study was to determine the reliability and validity of the Fitbit and Fitbit Ultra. Twenty-three subjects were fitted with two Fitbit and Fitbit Ultra accelerometers, two industry-standard accelerometers and an indirect calorimetry device. Subjects participated in 6-min bouts of treadmill walking, jogging and stair stepping. Results indicate the Fitbit and Fitbit Ultra are reliable and valid for activity monitoring (step counts) and determining energy expenditure while walking and jogging without an incline. The Fitbit and standard accelerometers under-estimated energy expenditure compared to indirect calorimetry for inclined activities. These data suggest the Fitbit and Fitbit Ultra are reliable and valid for monitoring over-ground energy expenditure.

BackgroundThere are currently over 1000 exercise apps for mobile devices on the market. These apps employ a range of features, from tracking exercise activity to providing motivational messages. However, virtually nothing is known about whether exercise apps improve exercise levels and health outcomes and, if so, the mechanisms of these effects.ObjectiveOur aim was to examine whether the use of exercise apps is associated with increased levels of exercise and improved health outcomes. We also develop a framework within which to understand how exercise apps may affect health and test multiple models of possible mechanisms of action and boundary conditions of these relationships. Within this framework, app use may increase physical activity by influencing variables such as self-efficacy and may help to overcome exercise barriers, leading to improved health outcomes such as lower body mass index (BMI).MethodsIn this study, 726 participants with one of three backgrounds were surveyed about their use of exercise apps and health: (1) those who never used exercise apps, (2) those who used exercise apps but discontinued use, and (3) those who are currently using exercise apps. Participants were asked about their long-term levels of exercise and about their levels of exercise during the previous week with the International Physical Activity Questionnaire (IPAQ).ResultsNearly three-quarters of current app users reported being more active compared to under half of non-users and past users. The IPAQ showed that current users had higher total leisure time metabolic equivalent of task (MET) expenditures (1169 METs), including walking and vigorous exercise, compared to those who stopped using their apps (612 METs) or who never used apps (577 METs). Importantly, physical activity levels in domains other than leisure time activity were similar across the groups. The results also showed that current users had lower BMI (25.16) than past users (26.8) and non-users (26.9) and that this association was mediated by exercise levels and self-efficacy. That relationship was also moderated by perceived barriers to exercise. Multiple serial mediation models were tested, which revealed that the association between app use and BMI is mediated by increased self-efficacy and increased exercise.ConclusionsExercise app users are more likely to exercise during their leisure time, compared to those who do not use exercise apps, essentially fulfilling the role that many of these apps were designed to accomplish. Data also suggest that one way that exercise apps may increase exercise levels and health outcomes such as BMI is by making it easier for users to overcome barriers to exercise, leading to increased self-efficacy. We discuss ways of improving the effectiveness of apps by incorporating theory-driven approaches. We conclude that exercise apps can be viewed as intervention delivery systems consisting of features that help users overcome specific barriers.

Combining accelerometry with heart rate monitoring has been suggested to improve energy estimates, however, it remains unclear whether the single, currently existing commercially available device combining these data streams (Actiheart) provides improved energy estimates compared to simpler and less expensive accelerometry-only devices. The purpose of this study was to compare the validity of the heart rate (HR), accelerometry (ACC), and combined ACC/HR estimates of the Actiheart to the ACC estimates of the Actical during low and moderate intensity activities. Twenty-seven participants (mean age 26.3 ± 7.3) wore an Actical, Actiheart and indirect calorimeter (K4b(2)) while performing card playing, sweeping, lifting weights, walking and jogging activities. All estimates tended to underestimate energy, sometimes by substantial amounts. Viewed across all activities studied, there was no significant difference in the ability of the waist-mounted Actical and torso-mounted Actiheart (ACC, HR, ACC/HR) estimates to predict energy expenditure. However, the Actiheart provided significantly better estimates than the Actical for the activities in which acceleration of the pelvis is not closely related to energy expenditure (card playing, sweeping, lifting weights) and the Actical provided significantly better estimates for level walking and level jogging. Similar to a previous study, the ACC component of the Actiheart was found to be the weakest predictor of energy suggesting it may be responsible for the failure of the combined ACC/HR estimate to equal or better the estimates derived solely from a waist mounted ACC device.

The objective of this study is to describe energy drink consumption and health behaviors among college students attending a predominantly minority university. Undergraduate and graduate students attending a private, minority-serving university were invited to participate in an online survey between September 2009 and August 2010. Out of 2,500 students, 407 participated yielding a response of 16 %. Analysis assessed energy drink consumption as well as participation in sport activities and high-risk behaviors. Energy drink consumption is significantly related with drinking alcohol to inebriation and driving (r = .14, p < .05) and to riding with a drunk driver (r = .15, p < .05). Athletes were more likely to engage in drinking alcohol to inebriation and driving F (1, 186) = 6.12, p < .02. Energy drink consumption is a common practice among racial minority university students. Tailored health promotion strategies and interventions are needed to address misconceptions of energy drink and alcohol mixing.