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Detection of Physical Activity Types Using Triaxial Accelerometers

Jørgen Skotte, Mette Korshøj, Jesper Kristiansen, Christiana Hanisch, and Andreas Holtermann

Background:

The aim of this study was to validate a triaxial accelerometer setup for identifying everyday physical activity types (ie, sitting, standing, walking, walking stairs, running, and cycling).

Methods:

Seventeen subjects equipped with triaxial accelerometers (ActiGraph GT3X+) at the thigh and hip carried out a standardized test procedure including walking, running, cycling, walking stairs, sitting, and standing still. A method was developed (Acti4) to discriminate between these physical activity types based on threshold values of standard deviation of acceleration and the derived inclination. Moreover, the ability of the accelerometer placed at the thigh to detect sitting posture was separately validated during free living by comparison with recordings of pressure sensors in the hip pockets.

Results:

Sensitivity for discriminating between the physical activity types sitting, standing, walking, running, and cycling in the standardized trials were 99%–100% and 95% for walking stairs. Specificity was higher than 99% for all activities. During free living (140 hours of measurements), sensitivity and specificity for detection of sitting posture were 98% and 93%, respectively.

Conclusion:

The developed method for detecting physical activity types showed a high sensitivity and specificity for sitting, standing, walking, running, walking stairs, and cycling in a standardized setting and for sitting posture during free living.

Cover Journal of Physical Activity and Health

In Journal of Physical Activity and Health Volume 11 (2014): Issue 1 (Jan 2014)

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How Does Definition of Minimum Break Length Affect Objective Measures of Sitting Outcomes Among Office Workers?

Stine Kloster, Ida Høgstedt Danquah, Andreas Holtermann, Mette Aadahl, and Janne Schurmann Tolstrup

Background:

Harmful health effects associated with sedentary behavior may be attenuated by breaking up long periods of sitting by standing or walking. However, studies assess interruptions in sitting time differently, making comparisons between studies difficult. It has not previously been described how the definition of minimum break duration affects sitting outcomes. Therefore, the aim was to address how definitions of break length affect total sitting time, number of sit-to-stand transitions, prolonged sitting periods and time accumulated in prolonged sitting periods among office workers.

Methods:

Data were collected from 317 office workers. Thigh position was assessed with an ActiGraph GT3X+ fixed on the right thigh. Data were exported with varying bout length of breaks. Afterward, sitting outcomes were calculated for the respective break lengths.

Results:

Absolute numbers of sit-to-stand transitions decreased, and number of prolonged sitting periods and total time accumulated in prolonged sitting periods increased, with increasing minimum break length. Total sitting time was not influenced by varying break length.

Conclusions:

The definition of minimum break length influenced the sitting outcomes with the exception of total sitting time. A standard definition of break length is needed for comparison and interpretation of studies in the evolving research field of sedentary behavior.

Cover Journal of Physical Activity and Health

In Journal of Physical Activity and Health Volume 14 (2017): Issue 1 (Jan 2017)

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Sedentary and Physical Activity Behavior in “Blue-Collar” Workers: A Systematic Review of Accelerometer Studies

Nicholas D. Gilson, Caitlin Hall, Andreas Holtermann, Allard J. van der Beek, Maaike A. Huysmans, Svend Erik Mathiassen, and Leon Straker

Background: This systematic review assessed evidence on the accelerometer-measured sedentary and physical activity (PA) behavior of nonoffice workers in “blue-collar” industries. Methods: The databases CINAHL, Embase, MEDLINE, PubMed, and Scopus were searched up to April 6, 2018. Eligibility criteria were accelerometer-measured sedentary, sitting, and/or PA behaviors in “blue-collar” workers (≥10 participants; agricultural, construction, cleaning, manufacturing, mining, postal, or transport industries). Data on participants’ characteristics, study protocols, and measured behaviors during work and/or nonwork time were extracted. Methodologic quality was assessed using a 12-item checklist. Results: Twenty studies (representing 11 data sets), all from developed world economies, met inclusion criteria. The mean quality score for selected studies was 9.5 (SD 0.8) out of a maximum of 12. Data were analyzed using a range of analytical techniques (eg, accelerometer counts or pattern recognition algorithms). “Blue-collar” workers were more sedentary and less active during nonwork compared with work time (eg, sitting 5.7 vs 3.2 h/d; moderate to vigorous PA 0.5 vs 0.7 h/d). Drivers were the most sedentary (work time 5.1 h/d; nonwork time 8.2 h/d). Conclusions: High levels of sedentary time and insufficient PA to offset risk are health issues for “blue-collar” workers. To better inform interventions, research groups need to adopt common measurement and reporting methodologies.

Cover Journal of Physical Activity and Health

In Journal of Physical Activity and Health Volume 16 (2019): Issue 11 (Nov 2019)

Open access

Comparison of Sedentary Time Between Thigh-Worn and Wrist-Worn Accelerometers

Kristin Suorsa, Anna Pulakka, Tuija Leskinen, Jaana Pentti, Andreas Holtermann, Olli J. Heinonen, Juha Sunikka, Jussi Vahtera, and Sari Stenholm

Background: The accuracy of wrist-worn accelerometers in identifying sedentary time has been scarcely studied in free-living conditions. The aim of this study was to compare daily sedentary time estimates between a thigh-worn accelerometer, which measured sitting and lying postures, and a wrist-worn accelerometer, which measured low levels of movement. Methods: The study population consisted of 259 participants (M age = 62.8 years, SD = 0.9) from the Finnish Retirement and Aging Study (FIREA). Participants wore an Axivity AX3 accelerometer on their mid-thigh and an Actigraph wActiSleep-BT accelerometer on their non-dominant wrist simultaneously for a minimum of 4 days in free-living conditions. Two definitions to estimate daily sedentary time were used for data from the wrist-worn accelerometer: 1) the count cutpoint, ≤1853 counts per minute; and 2) the Euclidean Norm Minus One (ENMO) cutpoint, <30 mg. Results: Compared to the thigh-worn accelerometer, daily sedentary time estimate was 63 min (95% confidence interval [CI] = −53 to −73) lower by the count cutpoint and 50 min (95% CI = 34 to 67) lower by the ENMO cutpoint. The limits of agreement in daily sedentary time estimates between the thigh- and cutpoint methods for wrist-worn accelerometers were wide (the count cutpoint: −117 to 243, the ENMO cutpoint: −212 to 313 min). Conclusions: Currently established cutpoint-based methods to estimate sedentary time from wrist-worn accelerometers result in underestimation of daily sedentary time compared to posture-based estimates of thigh-worn accelerometers. Thus, sedentary time estimates obtained from wrist-worn accelerometers using currently available cutpoint-based methods should be interpreted with caution and future work is needed to improve their accuracy.

Cover Journal for the Measurement of Physical Behaviour

In Journal for the Measurement of Physical Behaviour Volume 3 (2020): Issue 3 (Sep 2020)