2,254
Views
11
CrossRef citations to date
0
Altmetric
Assessment Procedure

Analyzing walking speeds with ankle and wrist worn accelerometers in a cohort with myotonic dystrophy

ORCID Icon, , , , , , & show all
Pages 2972-2978 | Received 23 Jan 2018, Accepted 25 May 2018, Published online: 10 Jul 2018

References

  • Westerterp KR. Physical activity assessment with accelerometers. Int J Obes. 1999;23:S45.
  • van Hees VT, Sabia S, Anderson KN, et al. A novel, open access method to assess sleep duration using a wrist-worn accelerometer. Plos One. 2015;10:e0142533.
  • Strath SJ, Kaminsky LA, Ainsworth BE, et al. Guide to the assessment of physical activity: clinical and research applications. Circulation. 2013;128:2259–2279.
  • Jimenez-Moreno AC, Newman J, Charman SJ, et al. Measuring habitual physical activity in neuromuscular disorders: a systematic review. Jnd. 2017;4:25–52.
  • Fini NA, Holland AE, Keating J, et al. How is physical activity monitored in people following stroke? Disabil Rehabil. 2015;37:1717–1731.
  • Del Din S, DGodfrey A, Mazza C, et al. Free-living monitoring of Parkinson’s disease: lessons from the field. Mov Disord. 2016;31:1293–1313.
  • Steins D, Dawes H, Esser P, et al. Wearable accelerometry-based technology capable of assessing functional activities in neurological populations in community settings: a systematic review. J Neuroengineering Rehabil. 2014;11:36.
  • Motl RW, Snook EM, Agiovlasitis S. Does an accelerometer accurately measure steps taken under controlled conditions in adults with mild multiple sclerosis? Disability Health J. 2011;4:52–57.
  • Thornton CA. Myotonic dystrophy. Neurol Clin. 2014;32:705–719, viii.
  • Turner C, Hilton-Jones D. Myotonic dystrophy: diagnosis, management and new therapies. Curr Opin Neurol. 2014;27:599–606.
  • Norwood FLM, Harling C, Chinnery PF, et al. Prevalence of genetic muscle disease in Northern England: in-depth analysis of a muscle clinic population. Brain. 2009;132(Pt 11):3175–3186.
  • Galli M, Cimolin V, Crugnola V, et al. Gait pattern in myotonic dystrophy (Steinert disease): a kinematic, kinetic and EMG evaluation using 3D gait analysis. J Neurol Sci. 2012;314:83–87.
  • Hammaren E, Kjellby-Wendt G, Kowalski J, et al. Factors of importance for dynamic balance impairment and frequency of falls in individuals with myotonic dystrophy type 1 – a cross-sectional study – including reference values of Timed Up & Go, 10m walk and step test. Neuromuscular Disorders: NMD. 2014;24:207–215.
  • Kierkegaard M, Harms-Ringdahl K, Widen Holmqvist L, et al. Perceived functioning and disability in adults with myotonic dystrophy type 1: a survey according to the International Classification Of Functioning, Disability and Health. J Rehabil Med. 2009;41:512–520.
  • Gagnon C, Mathieu J, Jean S, et al. Predictors of disrupted social participation in myotonic dystrophy type 1. Arch Phys Med Rehabil. 2008;89:1246–1255.
  • Gagnon C, Chouinard MC, Laberge L, et al. Health supervision and anticipatory guidance in adult myotonic dystrophy type 1. Neuromuscular Disorders. 2010;20:847–851.
  • Schillings M, Kalkman J, Janssen H, et al. Experienced and physiological fatigue in neuromuscular disorders. Clin Neurophysiol. 2007;118:292–300.
  • van Engelen B. Cognitive behaviour therapy plus aerobic exercise training to increase activity in patients with myotonic dystrophy type 1 (DM1) compared to usual care (OPTIMISTIC): study protocol for randomised controlled trial. Trials. 2015;16:224.
  • Berlin JES, Storti JES, Brach JS Using activity monitors to measure physical activity in free-living conditions. Physical Therapy. 2006;86:1137–1145.
  • Trost SG, O'Neil M. Clinical use of objective measures of physical activity. Br J Sports Med. 2014;48:178–181.
  • Byrom B, Rowe DA. Measuring free-living physical activity in COPD patients: Deriving methodology standards for clinical trials through a review of research studies. Contemp Clin Trials. 2016;47:172–184.
  • Mathieu J, Boivin H, Meunier D, et al. Assessment of a disease-specific muscular impairment rating scale in myotonic dystrophy. Neurology. 2001;56:336–340.
  • Jean S, Richer L, Laberge L, et al. Comparisons of intellectual capacities between mild and classic adult-onset phenotypes of myotonic dystrophy type 1 (DM1). Orphanet J Rare Dis. 2014;9:186.
  • McDonald CM, Henricson EK, Han JJ, et al. The 6‐minute walk test as a new outcome measure in Duchenne muscular dystrophy. Muscle Nerve. 2010;41:500–510.
  • Bohannon RW. Comfortable and maximum walking speed of adults aged 20–79 years: reference values and determinants. Age Ageing. 1997;26:15–19.
  • Rowlands AV, Olds TS, Hillsdon M, et al. Assessing sedentary behavior with the GENEActiv: introducing the sedentary sphere. New York: Lippincott Williams & Wilkins; 2014.
  • Esliger DW, Rowlands AV, Hurst TL, et al. Validation of the GENEA Accelerometer. Med Sci Sports Exerc. 2011;43:1085–1093.
  • RCoreTeam. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2013.
  • van Hees VT, Fang Z, Langford J, et al. Autocalibration of accelerometer data for free-living physical activity assessment using local gravity and temperature: an evaluation on four continents. J Appl Physiol. 2014;117:738–744.
  • Hildebrand M, Van Hees VT, Hansen BH, et al. Age group comparability of raw accelerometer output from wrist-and hip-worn monitors. Med Sci Sports Exercise. 2014;46:1816–1824.
  • Van Hees VT, Gorzelniak L, Leon ECD, et al. Separating movement and gravity components in an acceleration signal and implications for the assessment of human daily physical activity. PloS One. 2013;8:e61691.
  • Kayes NM, Schluter PJ, McPherson KM, et al. Exploring actical accelerometers as an objective measure of physical activity in people with multiple sclerosis. Arch Phys Med Rehabil. 2009;90:594–601.
  • Bland JM, Altman D. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;327:307–310.
  • Bland JM, Altman DG. Measuring agreement in method comparison studies. Stat Methods Med Res. 1999;8:135–160.
  • Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropractic Med. 2016;15:155–163.
  • John D, Tyo B, Bassett DR. Comparison of four ActiGraph accelerometers during walking and running. Med Sci Sports Exerc. 2010;42:368.
  • Park J, Ishikawa-Takata K, Tanaka S, et al. Effects of walking speed and step frequency on estimation of physical activity using accelerometers. J Physiol Anthropol. 2011;30:119–127.
  • Rowlands AV, Stone MR, Eston RG. Influence of speed and step frequency during walking and running on motion sensor output. Med Sci Sports Exerc. 2007;39:716–727.
  • Finch E, Brooks D, Stratford PW, et al. Physical rehabilitation outcome measures: a guide to enhanced clinical decision making. Physiother Can. 2003;55:053–054.
  • Severinsen K, Jakobsen JK, Overgaard K, et al. Normalized muscle strength, aerobic capacity, and walking performance in chronic stroke: a population-based study on the potential for endurance and resistance training. Arch Phys Med Rehabil. 2011;92:1663–1668.
  • Middleton A, Braun CH, Lewek MD, et al. Balance impairment limits ability to increase walking speed in individuals with chronic stroke. Disabil Rehabil. 2017;39:497–502.
  • Byrom B, Rowe DA. Measuring free-living physical activity in COPD patients: deriving methodology standards for clinical trials through a review of research studies. Contemporary Clin Trials. 2016;47:172–184.
  • Kuo TBJ, Li JY, Chen CY, et al. Influence of accelerometer placement and/or heart rate on energy expenditure prediction during uphill exercise. J Motor Behav. 2018;50:127–133.
  • Mannini A, Intille SS, Rosenberger M, et al. Activity recognition using a single accelerometer placed at the wrist or ankle. Med Sci Sports Exerc. 2013;45:2193–2203.
  • Kim DY, Jung YS, Park RW, et al. Different location of triaxial accelerometer and different energy expenditures. Yonsei Med J. 2014;55:1145–1151.
  • Mannini A, Rosenberger M, Haskell WL, et al. Activity recognition in youth using single accelerometer placed at wrist or ankle. Med Sci Sports Exerc. 2017;49:801–812.
  • Montoye AH, Mudd LM, Biswas S, et al. Energy expenditure prediction using raw accelerometer data in simulated free living. Med Sci Sports Exerc. 2015;47:1735–1746.
  • Ozemek C, Kirschner MM, Wilkerson BS, et al. Intermonitor reliability of the GT3X + accelerometer at hip, wrist and ankle sites during activities of daily living. Physiol Meas. 2014;35:129–138.
  • Afaq S, Tan S-T, Afzal U, et al. 117 Validation of accelerometers for measurement of physical activity energy expenditure in South Asians and Europeans. Heart. 2014;100:A66.2. A7.
  • Thaler-Kall K, Tusker F, Hermsdörfer J, Gorzelniak L, Horsch A. Where to wear accelerometers to measure physical activity in people? Studies in health technology and informatics. Studies Health Technol Informatics. 2012;192:1045.
  • Cleland I, Kikhia B, Nugent C, et al. Optimal placement of accelerometers for the detection of everyday activities. Sensors (Basel). 2013;13:9183–9200.
  • Felez-Nobrega M, Hillman CH, Dowd KP, et al. ActivPAL™ determined sedentary behaviour, physical activity and academic achievement in college students. J Sports Sci. 2018;1–6. DOI:10.1080/02640414.2018.1451212
  • Matthews CE, Hagströmer M, Pober DM, et al. Best practices for using physical activity monitors in population-based research. Med Sci Sports Exercise. 2012;44:S68.