Accelerometer Output and MET Values of Common Physical Activities

Abstract

Purpose This paper 1) provides the calibration procedures and methods for metabolic and activity monitor data collection, 2) compares measured MET values to the MET values from the Compendium of Physical Activities, and 3) examines the relationship between accelerometer output and METs for a range of physical activities Methods Participants (n=277) completed 11 activities for seven minutes each from a menu of 23 physical activities. Oxygen consumption (VO2) was measured using a portable metabolic system and an accelerometer was worn. MET values were defined as follows; measuredMETs (VO2/measured RMR) and standardMETs (VO2/3.5ml·kg·min−1). For the total sample and by sub-group (age [young <40y], sex and BMI [normal-weight <25 kg·m2]), measuredMETs and standardMETs were compared to the Compendium, using 95% confidence intervals to determine statistical significance (α=0.05). Average count·min−1 for each activity and the linear association between count·min−1 and METs are presented. Results Compendium METs were different than measured METs for 17/21 activities (81%). The number of activities different than the Compendium were similar between sub-groups or when standard METs were used. The average counts for the activities ranged from 11 counts·min−1(dishes) to 7490 counts·min−1 (2.23m·s−1, 3%) The r2 between counts and METs was 0.65. Conclusions This study provides valuable information about data collection, metabolic responses, and accelerometer output for common physical activities in a diverse participant sample. The Compendium should be updated with additional empirical data and linear regression models are inappropriate for accurately predicting METs from accelerometer output.

Accelerometer-determined moderate intensity lifestyle activity and cardiometabolic health

“…We utilized 30 min of LA, and 1000 steps of LA as units for analysis, and although the odds ratios are similar in magnitude, these values may not be equivalent. Activities such as gardening, vacuuming and raking do generate counts within the LA interval (Crouter et al, 2006;Kozey et al, 2010;Matthews, 2005); however, it is likely that other activities may also be detected. Despite this limitation, utilizing this interval as a surrogate for LA provides objective evidence that accelerometer-detected activities below traditional MVPA cut points can be beneficial for cardiometabolic health.…”

Body metabolic rate and electromyographic activities of antigravitational muscles in supine and standing postures

“…Sometimes Statistical significance of the observed differences are also reported (n = 12) HR, heart rate; SAP, systolic arterial pressure; DAP, diastolic arterial pressure; RP, rate-systolic arterial pressure product; V 0 E, pulmonary ventilation, V 0 O 2 , oxygen uptake; V 0 CO 2 , carbon dioxide production; MR, metabolic rate; RER, respiratory exchange ratio; EMGS and EMGG integrated electromyographic activity of soleus and gastrocnemius muscles, respectively resting metabolic rate (RMR) is measured. RMR can be measured after 4 h without any exercise, eating or drinking caffeinated drinks while the subject stays in a supine position (Kozey et al 2010). In our experiment, we used a quasi-RMR model.…”

“…Because of the short timeframe separating the measurements taken in the two tested positions, the observed changes were considered to be caused by the posture, regardless of the factors possibly influencing the absolute RMR values. Our aim was in fact to detect postural relative metabolic effects and not the measurement of the absolute RMR value; notwithstanding the RMR has been standardized to 3.5 ml/kg/min (Liu et al 2010;Kozey et al 2010), other researchers have demonstrated that this value may not be appropriate across the general population (Bader et al 2005), because the RMR is influenced by age, muscle mass and environmental temperature. Our subjects may have shown a greater mean oxygen uptake with respect to standard values due to their high level of muscle mass (Gravante et al 2001;Zurlo et al 1990), high temperature in the laboratory (27°C), feeding state, muscular activity prior to the test and time of the day (Ziogas and Thomas 1998;Sjödin et al 1996).…”

Cloud based activity monitoring system for health and sport

“…Inertial sensors are very useful for the determination of activity of the user [1] [2] and are very low power and thus are suitable for long term monitoring. Inertial sensors are very good at determining events and have been used for performance analysis in many different sports such as cricket [4], soccer [5], and tennis [6][7][8].…”