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Items: 1 to 20 of 83


Identifying sedentary time using automated estimates of accelerometer wear time.

Winkler EA, Gardiner PA, Clark BK, Matthews CE, Owen N, Healy GN.

Br J Sports Med. 2012 May;46(6):436-42. doi: 10.1136/bjsm.2010.079699.


Validation of accelerometer wear and nonwear time classification algorithm.

Choi L, Liu Z, Matthews CE, Buchowski MS.

Med Sci Sports Exerc. 2011 Feb;43(2):357-64. doi: 10.1249/MSS.0b013e3181ed61a3.


Classification of accelerometer wear and non-wear events in seconds for monitoring free-living physical activity.

Zhou SM, Hill RA, Morgan K, Stratton G, Gravenor MB, Bijlsma G, Brophy S.

BMJ Open. 2015 May 11;5(5):e007447. doi: 10.1136/bmjopen-2014-007447.


Impact of accelerometer data processing decisions on the sample size, wear time and physical activity level of a large cohort study.

Keadle SK, Shiroma EJ, Freedson PS, Lee IM.

BMC Public Health. 2014 Nov 24;14:1210. doi: 10.1186/1471-2458-14-1210.


Development and application of an automated algorithm to identify a window of consecutive days of accelerometer wear for large-scale studies.

Rillamas-Sun E, Buchner DM, Di C, Evenson KR, LaCroix AZ.

BMC Res Notes. 2015 Jun 26;8:270. doi: 10.1186/s13104-015-1229-2.


Reliability of RT3 accelerometers among overweight and obese adults.

Jerome GJ, Young DR, Laferriere D, Chen C, Vollmer WM.

Med Sci Sports Exerc. 2009 Jan;41(1):110-4. doi: 10.1249/MSS.0b013e3181846cd8.


Reliability of Objectively Measured Sedentary Time and Physical Activity in Adults.

Aadland E, Ylvisåker E.

PLoS One. 2015 Jul 20;10(7):e0133296. doi: 10.1371/journal.pone.0133296.


Agreement between accelerometer-assessed and self-reported physical activity and sedentary time in colon cancer survivors.

Boyle T, Lynch BM, Courneya KS, Vallance JK.

Support Care Cancer. 2015 Apr;23(4):1121-6. doi: 10.1007/s00520-014-2453-3.


Study protocol of physical activity and sedentary behaviour measurement among schoolchildren by accelerometry--cross-sectional survey as part of the ENERGY-project.

Yıldırım M, Verloigne M, de Bourdeaudhuij I, Androutsos O, Manios Y, Felso R, Kovács É, Doessegger A, Bringolf-Isler B, te Velde SJ, Brug J, Chinapaw MJ.

BMC Public Health. 2011 Mar 25;11:182. doi: 10.1186/1471-2458-11-182.


How many days of monitoring predict physical activity and sedentary behaviour in older adults?

Hart TL, Swartz AM, Cashin SE, Strath SJ.

Int J Behav Nutr Phys Act. 2011 Jun 16;8:62. doi: 10.1186/1479-5868-8-62.


Comparison of two objective monitors for assessing physical activity and sedentary behaviors in bariatric surgery patients.

Unick JL, Bond DS, Jakicic JM, Vithiananthan S, Ryder BA, Roye GD, Pohl D, Trautvetter J, Wing RR.

Obes Surg. 2012 Mar;22(3):347-52. doi: 10.1007/s11695-011-0491-1.


Effects of Varying Epoch Lengths, Wear Time Algorithms, and Activity Cut-Points on Estimates of Child Sedentary Behavior and Physical Activity from Accelerometer Data.

Banda JA, Haydel KF, Davila T, Desai M, Bryson S, Haskell WL, Matheson D, Robinson TN.

PLoS One. 2016 Mar 3;11(3):e0150534. doi: 10.1371/journal.pone.0150534.


Is the pain of activity log-books worth the gain in precision when distinguishing wear and non-wear time for tri-axial accelerometers?

Peeters G, van Gellecum Y, Ryde G, Farías NA, Brown WJ.

J Sci Med Sport. 2013 Nov;16(6):515-9. doi: 10.1016/j.jsams.2012.12.002.


Assessment of wear/nonwear time classification algorithms for triaxial accelerometer.

Choi L, Ward SC, Schnelle JF, Buchowski MS.

Med Sci Sports Exerc. 2012 Oct;44(10):2009-16. doi: 10.1249/MSS.0b013e318258cb36.


Accelerometer-derived sedentary and physical activity time in overweight/obese adults with type 2 diabetes: cross-sectional associations with cardiometabolic biomarkers.

Healy GN, Winkler EA, Brakenridge CL, Reeves MM, Eakin EG.

PLoS One. 2015 Mar 16;10(3):e0119140. doi: 10.1371/journal.pone.0119140.


Identifying accelerometer nonwear and wear time in older adults.

Hutto B, Howard VJ, Blair SN, Colabianchi N, Vena JE, Rhodes D, Hooker SP.

Int J Behav Nutr Phys Act. 2013 Oct 25;10:120. doi: 10.1186/1479-5868-10-120.


Validity of an automated algorithm to identify waking and in-bed wear time in hip-worn accelerometer data collected with a 24 h wear protocol in young adults.

McVeigh JA, Winkler EA, Healy GN, Slater J, Eastwood PR, Straker LM.

Physiol Meas. 2016 Sep 21;37(10):1636-1652. [Epub ahead of print]


Parent-child relationship of directly measured physical activity.

Fuemmeler BF, Anderson CB, Mâsse LC.

Int J Behav Nutr Phys Act. 2011 Mar 8;8:17. doi: 10.1186/1479-5868-8-17.

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