A calibration study was conducted to determine the threshold counts for two commonly used accelerometers, the ActiGraph and the Actical, to classify activities by intensity in children 5 to 8 years of age. Thirty-three children wore both accelerometers and a COSMED portable metabolic system during 15 min of rest and then performed up to nine different activities for 7 min each, on two separate days in the laboratory. Oxygen consumption was measured on a breath-by-breath basis, and accelerometer data were collected in 15-s epochs. Using receiver operating characteristic curve (ROC) analysis, cutpoints that maximised both sensitivity and specificity were determined for sedentary, moderate and vigorous activities. For both accelerometers, discrimination of sedentary behaviour was almost perfect, with the area under the ROC curve at or exceeding 0.98. For both the ActiGraph and Actical, the discrimination of moderate (0.85 and 0.86, respectively) and vigorous activity (0.83 and 0.86, respectively) was acceptable, but not as precise as for sedentary behaviour. This calibration study, using indirect calorimetry, suggests that the two accelerometers can be used to distinguish differing levels of physical activity intensity as well as inactivity among children 5 to 8 years of age.

Calibration of two objective measures of physical activity for children

Purpose: The purpose of this review is to address important methodological issues related to conducting accelerometer-based assessments of physical activity in free-living individuals. Methods: We review the extant scientific literature for empirical information related to the following issues: product selection, number of accelerometers needed, placement of accelerometers, epoch length, and days of monitoring required to estimate habitual physical activity. We also discuss the various options related to distributing and collecting monitors and strategies to enhance compliance with the monitoring protocol. Results: No definitive evidence exists currently to indicate that one make and model of accelerometer is more valid and reliable than another. Selection of accelerometer therefore remains primarily an issue of practicality, technical support, and comparability with other studies. Studies employing multiple accelerometers to estimate energy expenditure report only marginal improvements in explanatory power. Accelerometers are best placed on hip or the lower back. Although the issue of epoch length has not been studied in adults, the use of count cut points based on 1-min time intervals maybe inappropriate in children and may result in underestimation of physical activity. Among adults, 3-5 d of monitoring is required to reliably estimate habitual physical activity. Among children and adolescents, the number of monitoring days required ranges from 4 to 9 d, making it difficult to draw a definitive conclusion for this population. Face-to-face distribution and collection of accelerometers is probably the best option in field-based research, but delivery and return by express carrier or registered mail is a viable option. Conclusion: Accelerometer-based activity assessments requires careful planning and the use of appropriate strategies to increase compliance.

Conducting accelerometer-based activity assessments in field-based research.

An increase in world population along with a significant aging portion is forcing rapid rises in healthcare costs. The healthcare system is going through a transformation in which continuous monitoring of inhabitants is possible even without hospitalization. The advancement of sensing technologies, embedded systems, wireless communication technologies, nano technologies, and miniaturization makes it possible to develop smart systems to monitor activities of human beings continuously. Wearable sensors detect abnormal and/or unforeseen situations by monitoring physiological parameters along with other symptoms. Therefore, necessary help can be provided in times of dire need. This paper reviews the latest reported systems on activity monitoring of humans based on wearable sensors and issues to be addressed to tackle the challenges.

Wearable Sensors for Human Activity Monitoring: A Review

Purpose:This paper reviews accelerometry-based activity monitors, including single-site first-generation devices, emerging technologies, and analytical approaches to predict energy expenditure, with suggestions for further research and development.Methods:The physics and measurement principl

The Technology of Accelerometry-Based Activity Monitors: Current and Future

The deleterious health consequences of physical inactivity are vast, and they are of paramount clinical and research importance. Risk identification, benchmarks, efficacy, and evaluation of physical activity behavior change initiatives for clinicians and researchers all require a clear understanding of how to assess physical activity. In the present report, we have provided a clear rationale for the importance of assessing physical activity levels, and we have documented key concepts in understanding the different dimensions, domains, and terminology associated with physical activity measurement. The assessment methods presented allow for a greater understanding of the vast number of options available to clinicians and researchers when trying to assess physical activity levels in their patients or participants. The primary outcome desired is the main determining factor in the choice of physical activity assessment method. In combination with issues of feasibility/practicality, the availability of resources, and administration considerations, the desired outcome guides the choice of an appropriate assessment tool. The decision matrix, along with the accompanying tables, provides a mechanism for this selection that takes all of these factors into account. Clearly, the assessment method adopted and implemented will vary depending on circumstances, because there is no single best instrument appropriate for every situation. In summary, physical activity assessment should be considered a vital health measure that is tracked regularly over time. All other major modifiable cardiovascular risk factors (diabetes mellitus, hypertension, hypercholesterolemia, obesity, and smoking) are assessed routinely. Physical activity status should also be assessed regularly. Multiple physical activity assessment methods provide reasonably accurate outcome measures, with choices dependent on setting-specific resources and constraints. The present scientific statement provides a guide to allow professionals to make a goal-specific selection of a meaningful physical activity assessment method.

Guide to the Assessment of Physical Activity: Clinical and Research Applications A Scientific Statement From the American Heart Association

Accurate quantification of physical activity energy expenditure is a key part of the effort to understand disorders of energy metabolism. The Actiheart, a combined heart rate (HR) and movement sensor, is designed to assess physical activity in populations. To examine aspects of Actiheart reliability and validity in mechanical settings and during walking and running. In eight Actiheart units, technical reliability (coefficients of variation, CV) and validity for movement were assessed with sinusoid accelerations (0.1–20 m/s2) and for HR by simulated R-wave impulses (25–250 bpm). Agreement between Actiheart and ECG was determined during rest and treadmill locomotion (3.2–12.1 km/h). Walking and running intensity (in J/min/kg) was assessed with indirect calorimetry in 11 men and nine women (26–50 y, 20–29 kg/m2) and modelled from movement, HR, and movement+HR by multiple linear regression, adjusting for sex. Median intrainstrument CV was 0.5 and 0.03% for movement and HR, respectively. Corresponding interinstrument CV values were 5.7 and 0.03% with some evidence of heteroscedasticity for movement. The linear relationship between movement and acceleration was strong (R2=0.99, P 0.84, P<0.001) but significantly highest when combining HR and movement (SEE<1 MET). The Actiheart is technically reliable and valid. Walking and running intensity may be estimated accurately but further studies are needed to assess validity in other activities and during free-living. The study received financial support from the Wellcome Trust and SB was supported by a scholarship from Unilever, UK.

Reliability and validity of the combined heart rate and movement sensor actiheart

Accurate quantification of physical activity energy expenditure is a key part of the effort to understand disorders of energy metabolism. The Actiheart, a combined heart rate (HR) and movement sensor, is designed to assess physical activity in populations. Objective: To examine aspects of Actiheart reliability and validity in mechanical settings and during walking and running. Methods: In eight Actiheart units, technical reliability (coefficients of variation, CV) and validity for movement were assessed with sinusoid accelerations (0.1–20 m/s 2 ) and for HR by simulated R-wave impulses (25–250 bpm). Agreement between Actiheart and ECG was determined during rest and treadmill locomotion (3.2–12.1 km/h). Walking and running intensity (in J/ min/kg) was assessed with indirect calorimetry in 11 men and nine women (26–50 y, 20–29 kg/m 2 ) and modelled from movement, HR, and movement þ HR by multiple linear regression, adjusting for sex. Results: Median intrainstrument CV was 0.5 and 0.03% for movement and HR, respectively. Corresponding interinstrument CV values were 5.7 and 0.03% with some evidence of heteroscedasticity for movement. The linear relationship between movement and acceleration was strong (R 2 ¼ 0.99, Po0.001). Simulated R-waves were detected within 1 bpm from 30 to 250 bpm. The 95% limits of agreement between Actiheart and ECG were � 4.2 to 4.3 bpm. Correlations with intensity were generally high (R 2 40.84, Po0.001) but significantly highest when combining HR and movement (SEEo1 MET). Conclusions: The Actiheart is technically reliable and valid. Walking and running intensity may be estimated accurately but further studies are needed to assess validity in other activities and during free-living. Sponsorship: The study received financial support from the Wellcome Trust and SB was supported by a scholarship from

ORIGINAL COMMUNICATION Reliability and validity of the combined heart rate and movement sensor Actiheart

The combination of heart rate (HR) monitoring and movement registration may improve measurement precision of physical activity energy expenditure (PAEE). Previous attempts have used either regressi...

https://www.physiology.org/doi/pdf/10.1152/japplphysiol.00703.2003

Branched equation modeling of simultaneous accelerometry and heart rate monitoring improves estimate of directly measured physical activity energy expenditure

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.

https://www.physiology.org/doi/pdf/10.1152/japplphysiol.00092.2006

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

A placement effect on activity measures from movement sensors has been reported during treadmill and free-living activity. Positioning of electrodes may impact on movement artifact susceptibility as well as surface ECG waveform amplitudes and thus potentially on the precision by which heart rate (HR) is ascertained from such ECG traces. The purpose of this study was to examine the extent to which placement of the combined HR and movement sensor, Actiheart, influences measurement of HR and movement, and estimates of energy expenditure. A total of 24 participants (20–39 years, 45–109 kg, 1.54–2.05 m, 19–29 kg m−2) were recruited. Whilst wearing two monitors, one placed at the level of the third intercostal space (upper position) and one just below the apex of the sternum (lower position), study participants performed level walking, incline walking, and level running on treadmill, and completed at least one day of free-living monitoring. Placement differences in HR data quality, movement counts, and energy expenditure (estimated from combined HR and movement) were analyzed with regression techniques. Quality of HR data was generally higher when monitors were placed in the lower position. This effect was more pronounced in men during both treadmill activity (relative risk, RR [95% CI] of noisy HR data in upper vs. lower position, RR=1.3[0.3; 5.6] in women, RR=174[14; 2,156] in men) and during free-living (RR=1.2[0.4; 3.3] in women, RR=25[9.6; 67] in men). There were minor placement differences (≤8%) in movement counts only in women during incline walking and running. During free-living, no placement effect on counts was observed. In all test scenarios, estimates of energy expenditure from the two positions were not significantly different. Positioning the Actiheart at the level below the sternum may yield cleaner HR data. Regardless of which position is used, this has little or no effect on movement counts and energy expenditure estimates, which is encouraging for studies where research participants may have to position the monitors themselves.

Niels Brage

Papers

Reliability and validity of the combined heart rate and movement sensor actiheart

ORIGINAL COMMUNICATION Reliability and validity of the combined heart rate and movement sensor Actiheart

Branched equation modeling of simultaneous accelerometry and heart rate monitoring improves estimate of directly measured physical activity energy expenditure

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

Effect of combined movement and heart rate monitor placement on physical activity estimates during treadmill locomotion and free-living.