Literature DB >> 23247702

Estimating activity and sedentary behavior from an accelerometer on the hip or wrist.

Mary E Rosenberger1, William L Haskell, Fahd Albinali, Selene Mota, Jason Nawyn, Stephen Intille.   

Abstract

PURPOSE: Previously, the National Health and Examination Survey measured physical activity with an accelerometer worn on the hip for 7 d but recently changed the location of the monitor to the wrist. This study compared estimates of physical activity intensity and type with an accelerometer on the hip versus the wrist.
METHODS: Healthy adults (n = 37) wore triaxial accelerometers (Wockets) on the hip and dominant wrist along with a portable metabolic unit to measure energy expenditure during 20 activities. Motion summary counts were created, and receiver operating characteristic (ROC) curves were then used to determine sedentary and activity intensity thresholds. Ambulatory activities were separated from other activities using the coefficient of variation of the counts. Mixed-model predictions were used to estimate activity intensity.
RESULTS: The ROC for determining sedentary behavior had greater sensitivity and specificity (71% and 96%) at the hip than at the wrist (53% and 76%), as did the ROC for moderate- to vigorous-intensity physical activity on the hip (70% and 83%) versus the wrist (30% and 69%). The ROC for the coefficient of variation associated with ambulation had a larger AUC at the hip compared to the wrist (0.83 and 0.74). The prediction model for activity energy expenditure resulted in an average difference of 0.55 ± 0.55 METs on the hip and 0.82 ± 0.93 METs on the wrist.
CONCLUSIONS: Methods frequently used for estimating activity energy expenditure and identifying activity intensity thresholds from an accelerometer on the hip generally do better than similar data from an accelerometer on the wrist. Accurately identifying sedentary behavior from a lack of wrist motion presents significant challenges.

Entities:  

Mesh:

Year:  2013        PMID: 23247702      PMCID: PMC3631449          DOI: 10.1249/MSS.0b013e31827f0d9c

Source DB:  PubMed          Journal:  Med Sci Sports Exerc        ISSN: 0195-9131            Impact factor:   5.411


  43 in total

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2.  Predicting energy expenditure of physical activity using hip- and wrist-worn accelerometers.

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4.  Development of novel techniques to classify physical activity mode using accelerometers.

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Journal:  Med Sci Sports Exerc       Date:  2006-09       Impact factor: 5.411

5.  An artificial neural network model of energy expenditure using nonintegrated acceleration signals.

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6.  Physical activity in the United States measured by accelerometer.

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9.  Sensor positioning for activity recognition using wearable accelerometers.

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  76 in total

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2.  Wrist Accelerometry in the Health, Functional, and Social Assessment of Older Adults.

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Review 3.  The 24-Hour Activity Cycle: A New Paradigm for Physical Activity.

Authors:  Mary E Rosenberger; Janet E Fulton; Matthew P Buman; Richard P Troiano; Michael A Grandner; David M Buchner; William L Haskell
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4.  Subjective and Objective Measures of Daytime Activity and Sleep Disturbance in Retinitis Pigmentosa.

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5.  Measuring Physical Activity in Spinal Cord Injury Using Wrist-Worn Accelerometers.

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6.  Activity Recognition in Youth Using Single Accelerometer Placed at Wrist or Ankle.

Authors:  Andrea Mannini; Mary Rosenberger; William L Haskell; Angelo M Sabatini; Stephen S Intille
Journal:  Med Sci Sports Exerc       Date:  2017-04       Impact factor: 5.411

7.  Characterizing Pain Flares From the Perspective of Individuals With Symptomatic Knee Osteoarthritis.

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Journal:  Eur J Appl Physiol       Date:  2017-12-06       Impact factor: 3.078

9.  Validation of a physical activity accelerometer device worn on the hip and wrist against polysomnography.

Authors:  Kelsie M Full; Jacqueline Kerr; Michael A Grandner; Atul Malhotra; Kevin Moran; Suneeta Godoble; Loki Natarajan; Xavier Soler
Journal:  Sleep Health       Date:  2018-01-17

10.  Comparison of Accelerometry Methods for Estimating Physical Activity.

Authors:  Jacqueline Kerr; Catherine R Marinac; Katherine Ellis; Suneeta Godbole; Aaron Hipp; Karen Glanz; Jonathan Mitchell; Francine Laden; Peter James; David Berrigan
Journal:  Med Sci Sports Exerc       Date:  2017-03       Impact factor: 5.411

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