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Ricardo A. Tanhoffer, Aldre I.P. Tanhoffer, Jacqueline Raymond, Nathan A. Johnson, Andrew P. Hills and Glen M. Davis

Background:

The objective of this study was to determine whether doubly labeled water (DLW) and a multi-sensor armband (SWA) could detect the variation in energy expenditure incurred by a period of increased exercise (EXE) versus a period of high sedentary activity (SED), in individuals with spinal cord injury (SCI).

Methods:

Eight participants with SCI were submitted to 2 testing periods of energy expenditure assessment: 1) a 14-day phase during which sedentary living conditions were imposed and 2) a 14-day phase during which an exercise training intervention was employed. For each phase, total daily energy expenditure (TDEE) and physical activity energy expenditure (PAEE) were measured by DLW and SWA.

Results:

Mean TDEE assessed by DLW, was significantly higher during EXE versus SED (11,605 ± 2151 kJ·day-1 and 10,069 ± 2310 kJ·day-1). PAEE predicted by DLW was also significantly higher during EXE versus SED (5422 ± 2240 kJ·day-1 and 3855 ± 2496 kJ·day-1). SWA-predicted PAEE significantly underestimated PAEE measured by the DLW during SED and EXE.

Conclusion:

DLW is sensitive to detect variation in within-individual energy expenditure during voluntary increase in physical activity in individuals with SCI. SWA failed to detect statistically significant variations in energy expenditure between periods of high versus low activity in SCI.

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Gianluca Vernillo, Aldo Savoldelli, Barbara Pellegrini and Federico Schena

Background:

Accurate assessments of physical activity and energy expenditure (EE) are needed to advance research on positive and negative graded walking.

Purpose:

To evaluate the validity of 2 SenseWear Armband monitors (Pro3 and the recently released Mini) during graded walking.

Methods:

Twenty healthy adults wore both monitors during randomized walking activities on a motorized treadmill at 7 grades (0%, ±5%, ±15%, and ±25%). Estimates of total EE from the monitors were computed using different algorithms and compared with values derived from indirect calorimetry methodology using a 2-way mixed model ANOVA (Device × Condition), correlation analyses and Bland-Altman plots.

Results:

There was no significant difference in EE between the 2 armbands in any of the conditions examined. Significant main effects for device and condition, as well as a consistent bias, were observed during positive and negative graded walking with a greater over- and under-estimation at higher slope.

Conclusions:

Both the armbands produced similar EE values and seem to be not accurate in estimation of EE during activities involving uphill and downhill walking. Additional work is needed to understand factors contributing to this discrepancy and to improve the ability of these monitors to accurately measure EE during graded walking.

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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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Lisa S. Jutte, Kenneth L. Knight and Blaine C. Long

Objective:

Examine thermocouple model uncertainty (reliability + validity).

Design:

First, a 3 × 3 repeated measures design with independent variables electrothermometers and thermocouple model. Second, a 1 × 3 repeated measures design with independent variable subprobe.

Intervention:

Three electrothermometers, 3 thermocouple models, a multi-sensor probe and a mercury thermometer measured a stable water bath.

Main Outcome Measures:

Temperature and absolute temperature differences between thermocouples and a mercury thermometer.

Results:

Thermocouple uncertainty was greater than manufactures’ claims. For all thermocouple models, validity and reliability were better in the Iso-Themex than the Datalogger, but there were no practical differences between models within an electrothermometers. Validity of multi-sensor probes and thermocouples within a probe were not different but were greater than manufacturers’ claims. Reliability of multiprobes and thermocouples within a probe were within manufacturers claims.

Conclusion:

Thermocouple models vary in reliability and validity. Scientists should test and report the uncertainty of their equipment rather than depending on manufactures’ claims.

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Sofie Martien, Christophe Delecluse, Jan Seghers and Filip Boen

The primary purpose of this study was to assess the validity of two motion sensors in measuring steps in institutionalized older adults during daily life activities. Sixty-eight nursing home residents (85.8 ± 5.6 years) were equipped with a hip-worn and ankle-worn piezoelectric pedometer (New Lifestyles 2000) and with an arm-mounted multisensor (SenseWear Mini). An investigator with a hand counter tallied the actual steps. The results revealed that the multisensor and hip- and ankle-worn pedometer significantly underestimated step counts (89.6 ± 17.2%, 72.9 ± 25.8%, and 20.8 ± 24.6%, respectively). Walking speed accounted for 41.6% of the variance in percent error of the ankle-worn pedometer. The threshold value for accurate step counting was set at 2.35 km/hr, providing percent error scores within ± 5%. The ankle-worn piezoelectric pedometer can be useful for accurate quantification of walking steps in the old and old-old (> 85 years) walking faster than 2.35 km/hr.

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Enough? Refining the Administration of SOPARC Deborah A. Cohen * Claude Setodji * Kelly R. Evenson * Phillip Ward * Sandra Lapham * Amy Hillier * Thomas L. McKenzie * 11 2011 8 8 1117 1123 10.1123/jpah.8.8.1117 Accuracy of Multisensor Activity Monitors in Normal Versus High BMI African

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With Spinal Cord Injury Quantified by Doubly Labeled Water and a Multi-Sensor Armband Ricardo A. Tanhoffer * Aldre I.P. Tanhoffer * Jacqueline Raymond * Nathan A. Johnson * Andrew P. Hills * Glen M. Davis * 2 2015 12 12 2 2 163 163 170 170 10.1123/jpah.2013-0190 The Physical Activity Energy

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Kathryn J. DeShaw, Laura Ellingson, Yang Bai, Jeni Lansing, Maria Perez and Greg Welk

-based epochs ( Lyden, Keadle, Staudenmayer, & Freedson, 2014 ). Our research team further refined the Sojourn method by incorporating data from the activPal to better differentiate postural changes and discrimination of sedentary behavior ( Ellingson, Schwabacher, Kim, Welk, & Cook, 2016 ). As such, the multi-sensor

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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

groups ( P  < .05). a Statistically significant differences in relation to sedentary time from GPAQ-SB. Asterisk denotes that the correlation is statistically significant: * P  < .05; ** P  < .01; *** P  < .001. Discussion As far as we know, this is the first study to use a multisensor pattern

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Giovanni Mario Pes, Maria Pina Dore, Alessandra Errigo and Michel Poulain

.1093/sleep/33.5.601 Heiermann , S. , Khalaj Hedayati , K. , Müller , M.J. , & Dittmar , M. ( 2011 ). Accuracy of a portable multisensor body monitor for predicting resting energy expenditure in older people: A comparison with indirect calorimetry . Gerontology, 57 , 473 – 479 . PubMed doi:10