Accuracy of Actigraph inclinometer to classify free-living postures and motion in adults with overweight and obesity

Júdice, Pedro B.; Teixeira, Luís; Silva, Analiza M.; Sardinha, Luís B.

doi:10.1080/02640414.2019.1586281

Cited by 12 publications

(7 citation statements)

References 36 publications

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“…Second, while the AX3 placed on the lower back has been shown to produce reasonably similar day-level estimates compared with the GT3X+ on the hip (Brønd et al, 2015), it is possible that any differences in posture and intensity observed in this study could be confounded by sensor placement. Third, we did not consider the participants' weight status, which has been shown to have an influence on posture prediction via inclinometer (Júdice, Teixeira, Silva, & Sardinha, 2019). In addition, MET values from the Compendium of Physical Activities were used as the criterion measurement of activity intensity, which are absolute values that do not take into account individual characteristics such as weight, sex, and physical fitness (Garber et al, 2011).…”

Section: Discussionmentioning

confidence: 99%

Concurrent Validity of ActiGraph GT3X+ and Axivity AX3 Accelerometers for Estimating Physical Activity and Sedentary Behavior

Hedayatrad¹,

Duncan²

2021

Journal for the Measurement of Physical Behaviour

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Introduction: Accelerometers are commonly used to assess time-use behaviors related to physical activity, sedentary behavior, and sleep; however, as new accelerometer technologies emerge, it is important to ensure consistency with previous devices. This study aimed to evaluate the concurrent validity of the commonly used accelerometer, ActiGraph GT3X+, and the relatively new Axivity AX3 (fastened to the lower back) for detecting physical activity intensity and body postures when using direct observation as the criterion measure. Methods: A total of 41 children (aged 6–16 years) and 33 adults (aged 28–59 years) wore both monitors concurrently while performing 10 prescribed activities under laboratory conditions. The GT3X+ data were categorized into different physical activity intensity and posture categories using intensity-based cut points and ActiGraph proprietary inclinometer algorithms, respectively. The AX3 data were first converted to ActiGraph counts before being categorized into different physical activity intensity categories, while activity recognition models were used to detect the target postures. Sensitivity, specificity, and the balanced accuracy for intensity and posture category classification were calculated for each accelerometer. Differences in balanced accuracy between the devices and between children and adults were also calculated. Results: Both accelerometers obtained 74–96% balanced accuracy, with the AX3 performing slightly better (∼4% higher, p < .01) for detecting postures and physical activity intensity. Error in both devices was greatest when contrasting sitting/standing, sedentary/light intensity, and moderate/light intensity. Conclusion: In comparison with the GT3X+ accelerometer, AX3 was able to detect various postures and activity intensities with slightly higher balanced accuracy in children and adults.

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Section: Discussionmentioning

confidence: 99%

Concurrent Validity of ActiGraph GT3X+ and Axivity AX3 Accelerometers for Estimating Physical Activity and Sedentary Behavior

Hedayatrad¹,

Duncan²

2021

Journal for the Measurement of Physical Behaviour

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“…The ActiGraph GT9X Link triaxial accelerometer is a small square device (14 grams; 3.5×3.5×1 cm) (Actigraph 2019) that measures intensity and duration of movements and allows researchers to classify time spent in various intensities of activity. The ActiGraph also has an inclinometer function, but this function has not been established as valid and will not be used in this analysis (Judice et al 2019). Evidence suggests the ActiGraph is reliable for measuring SB in older adults (Hart et al 2011), but validity of the ActiGraph for measuring sedentary time compared to direct observation has been low (Kozey-Keadle et al 2011), in part because it is highly influenced by the choice of processing techniques (Aguilar-Farias et al 2014).…”

Section: Methodsmentioning

confidence: 99%

Comparative assessment of ActiGraph data processing techniques for measuring sedentary behavior in adults with COPD

Webster¹,

Colabianchi²,

Ploutz‐Snyder³

et al. 2021

Physiol. Meas.

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Objective. The ActiGraph is commonly used for measuring sedentary behavior (SB), but the best data processing technique is not established for sedentary adults with chronic illness. The purpose of this study was to process ActiGraph vertical axis and vector magnitude data with multiple combinations of filters, non-wear algorithm lengths, and cut-points and to compare ActiGraph estimates to activPAL-measured sedentary time in sedentary adults with chronic obstructive pulmonary disease (COPD). Approach. This study was a secondary analysis of adults ≥50 years (N = 59; mean age: 69.4 years; N = 31 males) with COPD. Participants wore ActiGraph GT9X and activPAL3 for 7 d. ActiGraph vertical axis and vector magnitude data were processed using combinations of filters (normal, low frequency extension (LFE)), non-wear algorithm lengths (60, 90, 120 min), and cut-points for SB previously validated in older adults (two for vertical axis and three for vector magnitude data). The Bland–Altman method was used to assess concordance between sedentary time measured with 30 ActiGraph techniques and activPAL-measured sedentary time. Main results. Agreement between the two devices was moderate to strong for all techniques; concordance correlations ranged from 0.614 to 0.838. Limits of agreement were wide. The best overall technique was vector magnitude data with LFE filter, 120 min non-wear algorithm, and <40 counts/15 s SB cut-point (concordance correlation 0.838; mean difference −11.7 min d−1). Significance. This analysis supports the use of ActiGraph vector magnitude data and LFE filter in adults with COPD, but also demonstrates that other techniques may be acceptable with appropriate cut-points. These results can guide ActiGraph data processing decisions.

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“…There are important considerations regarding the agreement and comparability of SB measurements from accelerometers and inclinometers. Different studies tested the agreement between SB measured through accelerometers and inclinometers and found that accelerometer-based measures of SB can be overestimated, especially in short bouts [30][31][32][33][34]. The overestimation of SB by accelerometers is, in general, low, but this bias can influence the findings of interventions [30].…”

Section: Research-based 2221 Accelerometers and Inclinometersmentioning

confidence: 99%

Methods of Assessing Sedentary Behaviour

Marconcin¹,

Júdice²,

Ferrari³

et al. 2021

Sedentary Behaviour - A Contemporary View

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Increasing amounts of time spent in sedentary behaviour (SB), during occupation or recreation activities, is considered a global health problem. SB has been associated with several non-communicable diseases and all-cause mortality. Thus, it is essential to assess SB through the most accurate and suitable measurement tools. This chapter presents an overview of different methods for assessing SB and highlights the importance of determining the best measurement tool. In choosing an appropriate and accurate method, it is relevant to consider multiple factors, such as population characteristics, context, validity and reliability of measurement tools, and potential research and participant burdens. Subjective measurements, such as self-reported questionnaires, are widely used in epidemiologic studies because they are easy to administer at low cost. However, there is a large variety of questionnaires, which makes it difficult to select a single questionnaire to assess SB. Device-based measurements are more accurate for assessing SB as well as determining bouts and breaks. Both methods present strengths and limitations, and when possible, researchers should use a combination of device-based and subjective methods to improve SB assessment.

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Accuracy of Actigraph inclinometer to classify free-living postures and motion in adults with overweight and obesity

Cited by 12 publications

References 36 publications

Concurrent Validity of ActiGraph GT3X+ and Axivity AX3 Accelerometers for Estimating Physical Activity and Sedentary Behavior

Concurrent Validity of ActiGraph GT3X+ and Axivity AX3 Accelerometers for Estimating Physical Activity and Sedentary Behavior

Comparative assessment of ActiGraph data processing techniques for measuring sedentary behavior in adults with COPD

Methods of Assessing Sedentary Behaviour

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