title: Autocalibration of accelerometer data for free-living physical activity assessment using local gravity and temperature: an evaluation on four continents.
abstract: Wearable acceleration sensors are increasingly used for the assessment of free-living physical activity. Acceleration sensor calibration is a potential source of error. This study aims to describe and evaluate an autocalibration method to minimize calibration error using segments within the free-living records (no extra experiments needed). The autocalibration method entailed the extraction of nonmovement periods in the data, for which the measured vector magnitude should ideally be the gravitational acceleration (1 g); this property was used to derive calibration correction factors using an iterative closest-point fitting process. The reduction in calibration error was evaluated in data from four cohorts: UK (n = 921), Kuwait (n = 120), Cameroon (n = 311), and Brazil (n = 200). Our method significantly reduced calibration error in all cohorts (P < 0.01), ranging from 16.6 to 3.0 mg in the Kuwaiti cohort to 76.7 to 8.0 mg error in the Brazil cohort. Utilizing temperature sensor data resulted in a small nonsignificant additional improvement (P > 0.05). Temperature correction coefficients were highest for the z-axis, e.g., 19.6-mg offset per 5°C. Further, application of the autocalibration method had a significant impact on typical metrics used for describing human physical activity, e.g., in Brazil average wrist acceleration was 0.2 to 51% lower than uncalibrated values depending on metric selection (P < 0.01). The autocalibration method as presented helps reduce the calibration error in wearable acceleration sensor data and improves comparability of physical activity measures across study locations. Temperature ultization seems essential when temperature deviates substantially from the average temperature in the record but not for multiday summary measures.
authors.affiliation: MoveLab, Institute of Cellular Medicine, Newcastle University, Newcastle, United Kingdom; Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
authors.forename: Vincent T
authors.initials: VT
authors.lastname: van Hees
authors.affiliation: Department of Statistics, University of Oxford, Oxford, United Kingdom; Activinsight, Limited, Kimbolton, United Kingdom;
authors.forename: Zhou
authors.initials: Z
authors.lastname: Fang
authors.affiliation: Activinsight, Limited, Kimbolton, United Kingdom;
authors.forename: Joss
authors.initials: J
authors.lastname: Langford
authors.affiliation: University of Yaoundé, Yaoundé, Cameroon;
authors.forename: Felix
authors.initials: F
authors.lastname: Assah
authors.affiliation: Dasman Diabetes Institute, Kuwait City, Kuwait;
authors.forename: Anwar
authors.initials: A
authors.lastname: Mohammad
authors.affiliation: Federal University of Pelotas-Postgraduate Program in Epidemiology, Pelotas, Brazil; and Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
authors.forename: Inacio C M
authors.initials: IC
authors.lastname: da Silva
authors.affiliation: MoveLab, Institute of Cellular Medicine, Newcastle University, Newcastle, United Kingdom;
authors.forename: Michael I
authors.initials: MI
authors.lastname: Trenell
authors.affiliation: Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
authors.forename: Tom
authors.initials: T
authors.lastname: White
authors.affiliation: Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
authors.forename: Nicholas J
authors.initials: NJ
authors.lastname: Wareham
authors.affiliation: Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom soren.brage@mrc-epid.cam.ac.uk.
authors.forename: Søren
authors.initials: S
authors.lastname: Brage
mesh_terms: D061725:Accelerometry / Q000379:methods*; D000293:Adolescent; D000328:Adult; D002138:Calibration; D005260:Female; D006112:Gravitation; D006801:Humans; D008297:Male; D008875:Middle Aged; D009043:Motor Activity / Q000502:physiology*; D013696:Temperature; D055815:Young Adult
keywords: GENEActiv; accelerometry; calibration; epidemiology; physical activity
references.citation: Med Sci Sports Exerc. 2009 Apr;41(4):810-7
references.pmid: 19276852
references.citation: J Biomech. 2012 Feb 2;45(3):448-54
references.pmid: 22218284
references.citation: PLoS One. 2013 Apr 23;8(4):e61691
references.pmid: 23626718
references.citation: Med Sci Sports Exerc. 2011 Jun;43(6):1085-93
references.pmid: 21088628
references.citation: Comput Methods Programs Biomed. 2013 Jul;111(1):62-71
references.pmid: 23566707
references.citation: Am J Epidemiol. 2014 Mar 15;179(6):781-90
references.pmid: 24500862
references.citation: Med Sci Sports Exerc. 2013 Oct;45(10):2012-9
references.pmid: 23584403
references.citation: Obesity (Silver Spring). 2009 Aug;17(8):1588-95
references.pmid: 19247268
references.citation: Med Sci Sports Exerc. 2014 Apr;46(4):826-33
references.pmid: 24121241
references.citation: Sensors (Basel). 2013 Sep 12;13(9):12192-217
references.pmid: 24036581
references.citation: IEEE Trans Biomed Eng. 1997 Mar;44(3):136-47
references.pmid: 9216127
references.citation: Am J Hum Biol. 2012 Jul-Aug;24(4):558-61
references.pmid: 22308165
references.citation: IEEE Trans Inf Technol Biomed. 2010 Jul;14(4):1098-105
references.pmid: 20483689
references.citation: Diabetes Care. 2011 Feb;34(2):491-6
references.pmid: 21270205
references.citation: Biom J. 2008 Jun;50(3):346-63
references.pmid: 18481363
references.citation: Med Sci Sports Exerc. 2014 Jun;46(6):1235-47
references.pmid: 24263980
references.citation: Am J Clin Nutr. 2010 Aug;92(2):347-52
references.pmid: 20519560
references.citation: Med Sci Sports Exerc. 2013 Jun;45(6):1097-104
references.pmid: 23274612
references.citation: Med Sci Sports Exerc. 2014 Sep;46(9):1816-24
references.pmid: 24887173
references.citation: Int J Epidemiol. 2008 Aug;37(4):704-9
references.pmid: 17846051