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Miguel Ángel de la Cámara, Sara Higueras-Fresnillo, David Martinez-Gomez and Óscar L. Veiga

therefore affect the number of days of monitoring needed to estimate movement and nonmovement behaviors. The Intelligent Device for Energy Expenditure and Activity (IDEEA monitor) is a high-tech pattern-recognizing monitor. This monitor, in addition to the total movement behavior and the total nonmovement

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Miguel A. de la Cámara, Sara Higueras-Fresnillo, Verónica Cabanas-Sánchez, Kabir P. Sadarangani, David Martinez-Gomez and Óscar L. Veiga

influence healthy aging. 29 , 30 New monitoring systems for determining postural allocation (ie, sitting, reclining, lying, and standing) as the ActivPAL or the Intelligent Device for Energy Expenditure and Activity (IDEEA) could provide more precise estimates of SB, and they can be useful for validating

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Daniel Arvidsson, Mark Fitch, Mark L. Hudes and Sharon E. Fleming

Background:

Overweight children show different movement patterns during walking than normal-weight children, suggesting the accuracy of multisensory activity monitors may differ in these groups.

Methods:

Eleven normal and 15 high BMI African American children walked at 2, 4, 5, and 6 km/h on a treadmill wearing the Intelligent Device for Energy Expenditure and Activity (IDEEA) and SenseWear (SW). Accuracy was determined using indirect calorimetry and manually counted steps as references.

Results:

For IDEEA, no significant differences in accuracy were observed between BMI groups for energy expenditure (EE), but differences were significant by speed (+15% at 2 km/h to −10% at 6 km/h). For SW, EE accuracy was significantly different for high (+21%) versus normal BMI girls (−13%) at 2 km/h. For high BMI girls, EE was overestimated at low speed and underestimated at higher speeds. Underestimations in steps did not differ by BMI group at 4 to 6 km/h, but were significantly larger at 2 km/h than at the other speeds for all groups with IDEEA, and for normal BMI children with SW.

Conclusions:

Similar accuracies during walking may be expected in normal and overweight children using IDEEA and SW. Both monitors showed small errors for steps provided speed exceeded 2 km/h.

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Teresa L. Hart, James J. McClain and Catrine Tudor-Locke

Background:

Emerging interest in the health impacts of sedentary behaviors has driven the exploration of objective instrumentation capable of capturing these behaviors. The purpose was to compare (under laboratory conditions) outputs from ActiGraph (AG), Intelligent Device for Energy Expenditure and Physical Activity (IDEEA), and activPAL Professional (AP) against direct observation (DO) in sedentary, standing, and active behaviors; and assess convergent validity of instrument outputs under free-living conditions.

Methods:

Participants (13 males/16 females; 28.9 ± 6.2 years) wore instruments concurrently during laboratory and free-living studies. AG cutpoints of ≤50, <100, and ≤259 counts/minute were used to determine time in sedentary behaviors. Laboratory data were evaluated using mean percent error. Free-living data were analyzed using dependent t tests and RM ANOVA.

Results:

AP precisely measured all identified DO behaviors under laboratory conditions; IDEEA precisely identified sitting and standing. For the free-living study, there was no difference in sedentary time detected by AP and IDEEA but a significant difference was observed in standing time. No difference was apparent between AP and AG259 in sit/lie/stand or ambulatory activity time.

Conclusions:

In a laboratory setting, the utility of all instruments to classify activities into behavioral categories was confirmed. This may enhance research on sedentary behaviors and health-related outcomes.

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Miguel A. Calabro, Gregory J. Welk, Alicia L. Carriquiry, Sarah M. Nusser, Nicholas K. Beyler and Charles E. Matthews

Purpose:

The purpose of this study was to examine the validity of a computerized 24-hour physical activity recall instrument (24PAR).

Methods:

Participants (n = 20) wore 2 pattern-recognition activity monitors (an IDEEA and a SenseWear Pro Armband) for a 24-hour period and then completed the 24PAR the following morning. Participants completed 2 trials, 1 while maintaining a prospective diary of their activities and 1 without a diary. The trials were counterbalanced and completed within a week from each other. Estimates of energy expenditure (EE) and minutes of moderate-to-vigorous physical activity (MVPA) were compared with the criterion measures using 3-way (method by gender by trial) mixed-model ANOVA analyses.

Results:

For EE, pairwise correlations were high (r > .88), and there were no differences in estimates across methods. Estimates of MVPA were more variable, but correlations were still in the moderate to high range (r > .57). Average activity levels were significantly higher on the logging trial, but there was no significant difference in the accuracy of self-report on days with and without logging.

Conclusions:

The results of this study support the overall utility of the 24PAR for group-level estimates of daily EE and MVPA.

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Alexander H.K. Montoye, Kimberly A. Clevenger, Kelly A. Mackintosh, Melitta A. McNarry and Karin A. Pfeiffer

the IDEEA monitor, a five-accelerometer system (left and right upper leg, left and right foot, sternum), generally show better EE prediction than some, but not all, single-accelerometer prediction models in adults ( Dannecker, Sazonova, Melanson, Sazonov, & Browning, 2013 ; Lof, Henriksson, & Forsum

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Anantha Narayanan, Farzanah Desai, Tom Stewart, Scott Duncan and Lisa Mackay

and 10 females); Healthy population, aged 22–51 y Tracmor (Philips Research, Eindhoven, The Netherlands) 1; 3-axis accelerometer, 20 Hz; Waist; IDEEA monitor (MiniSun, Fresno, CA); 5; N/M, 32 Hz; Soles of the feet, thighs, and upper sternum Data set 1: Considered to be direct observation as this is a